diff --git a/Diabetes__Dataset_2_.ipynb b/Diabetes__Dataset_2_.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e3ec1e264e8b2013ff8ee5a585d0a51dac645039
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+++ b/Diabetes__Dataset_2_.ipynb
@@ -0,0 +1,10487 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "id": "E0-5CFbv5jps"
+ },
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import matplotlib.pyplot as plt\n",
+ "import seaborn as sns\n",
+ "import numpy as np\n",
+ "from sklearn.model_selection import train_test_split, cross_val_score, KFold\n",
+ "from sklearn.linear_model import LogisticRegression, Ridge\n",
+ "from sklearn.metrics import classification_report, confusion_matrix, accuracy_score, f1_score, roc_curve, roc_auc_score, auc\n",
+ "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
+ "from sklearn.decomposition import PCA\n",
+ "from imblearn.over_sampling import SMOTE, RandomOverSampler\n",
+ "from imblearn.under_sampling import RandomUnderSampler\n",
+ "import gymnasium as gym\n",
+ "from gym import spaces\n",
+ "import os\n",
+ "from sklearn.tree import DecisionTreeClassifier, plot_tree\n",
+ "from sklearn import datasets, svm, metrics\n",
+ "from sklearn.svm import SVC\n",
+ "from sklearn.model_selection import StratifiedKFold\n",
+ "\n",
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import seaborn as sns\n",
+ "import matplotlib.pyplot as plt\n",
+ "import warnings\n",
+ "import plotly.express as px\n",
+ "px_template = \"simple_white\""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "https://www.kaggle.com/datasets/alexteboul/diabetes-health-indicators-dataset"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#Read dataset, check for null and duplicates\n",
+ "def read_dataset(dataset):\n",
+ " \n",
+ " data = pd.read_csv(dataset)\n",
+ " nrow = len(data.index)\n",
+ " ncol = len(data.columns)\n",
+ "\n",
+ " print(\"The dataset contains\", format(nrow, \",d\"), \"rows and\", ncol, \"columns.\")\n",
+ " \n",
+ " #Check for null values\n",
+ " if ((data.isna().sum()).sum()) > 0:\n",
+ " print(\"There are null items in the dataset\")\n",
+ " else:\n",
+ " print(\"There are no null items in the dataset\")\n",
+ " \n",
+ " #Check for duplicates\n",
+ " \n",
+ " #col_names = [\"Country\", \"Year\", \"Status\"]\n",
+ " #(data.duplicated(subset=col_names)).sum()\n",
+ "\n",
+ " if (data.duplicated().sum()) > 0:\n",
+ " print(\"There are duplicates in the dataset\")\n",
+ " else:\n",
+ " print(\"There are no duplicates in the dataset\")\n",
+ " \n",
+ " return data\n",
+ "\n",
+ "\n",
+ "\n",
+ "#Function to categorize data into numeric and categorical\n",
+ "def categorize_data(data):\n",
+ " \n",
+ " numeric=[]\n",
+ " categorical=[]\n",
+ " numeric_dtypes = [\"int64\", \"int32\", \"float64\", \"float32\"]\n",
+ "\n",
+ " for i in range (len(data.columns)):\n",
+ " if data[data.columns[i]].dtype in numeric_dtypes:\n",
+ " numeric.append(data.columns[i])\n",
+ " else:\n",
+ " categorical.append(data.columns[i])\n",
+ " \n",
+ " return numeric, categorical\n",
+ "\n",
+ " \n",
+ "#Function to check for outliers\n",
+ "def outliers_check(data, numeric):\n",
+ " outliers_sum =[]\n",
+ "\n",
+ " for col in (numeric):\n",
+ " Q1 = data[col].quantile(0.25)\n",
+ " Q3 = data[col].quantile(0.75)\n",
+ " IQR = Q3 - Q1\n",
+ " outliers = (data[col] < (Q1 - 1.5 * IQR)) | (data[col] > (Q3 + 1.5 * IQR))\n",
+ " print(col, \"\", outliers.sum())\n",
+ " outliers_sum.append(outliers.sum())\n",
+ "\n",
+ " return outliers.sum()\n",
+ "\n",
+ "\n",
+ "def remove_duplicates(data):\n",
+ " duplicated_sum = data.duplicated().sum()\n",
+ " if duplicated_sum == 0:\n",
+ " print(\"Number of duplicated rows in dataset =\", duplicated_sum)\n",
+ " return data\n",
+ " else:\n",
+ " print(\"Number of duplicated rows in dataset =\", duplicated_sum)\n",
+ " data = data[~data.duplicated()]\n",
+ " print(\"Duplicated rows have been removed\")\n",
+ " return data\n",
+ "\n",
+ " \n",
+ "def remove_outliers(data, numeric):\n",
+ " \n",
+ " for col in (numeric):\n",
+ " median_value = np.median(data[col])\n",
+ " Q1 = data[col].quantile(0.25)\n",
+ " Q3 = data[col].quantile(0.75)\n",
+ " IQR = Q3 - Q1\n",
+ " outliers = (data[col] < (Q1 - 1.5 * IQR)) | (data[col] > (Q3 + 1.5 * IQR))\n",
+ " #print(col, \"\", outliers.sum())\n",
+ " data.loc[outliers, col] = median_value\n",
+ " return data\n",
+ "\n",
+ "\n",
+ "# remove special characters from columns\n",
+ "def remove_spec_chars(data, categorical_cols):\n",
+ " for col in categorical_cols:\n",
+ " data[col] = data[col].str.replace(r'\\W+', '').str.strip() #replaces special characters with white sapaces and removes the white spaces\n",
+ " return data\n",
+ "\n",
+ "\n",
+ "def replace_unknown(data, categorical_cols):\n",
+ " for col in categorical_cols:\n",
+ " if \"unknown\" in data[col].values:\n",
+ " #source: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.mode.html\n",
+ " mode = data[col].mode()[0]\n",
+ " data[col] = data[col].replace(\"unknown\", mode)\n",
+ " return data\n",
+ "\n",
+ " \n",
+ "def oneHotEncoding(data, categorical, drop_first):\n",
+ "\n",
+ " data_final = pd.get_dummies(data, columns=categorical, drop_first=drop_first)\n",
+ "\n",
+ " return data_final"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "id": "ZJ49VZ_xB0tn"
+ },
+ "outputs": [],
+ "source": [
+ "file_name = \"diabetes_binary_5050split_health_indicators_BRFSS2015.csv\"\n",
+ "file_name1 = \"diabetes_binary_health_indicators_BRFSS2015.csv\"\n",
+ "file_name2 = \"diabetes_012_health_indicators_BRFSS2015.csv\"\n",
+ "# Load the dataset\n",
+ "#df = pd.read_csv(file_name)\n",
+ "#df1 = pd.read_csv(file_name1)\n",
+ "#df2 = pd.read_csv(file_name2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "The dataset contains 253,680 rows and 22 columns.\n",
+ "There are no null items in the dataset\n",
+ "There are duplicates in the dataset\n"
+ ]
+ }
+ ],
+ "source": [
+ "df1 = read_dataset(\"diabetes_binary_health_indicators_BRFSS2015.csv\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 255
+ },
+ "id": "MCzlQqdf7Xzo",
+ "outputId": "8b0e35bd-914b-43a2-f2e7-7e61842ca46a"
+ },
+ "outputs": [
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+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Diabetes_binary</th>\n",
+ " <th>HighBP</th>\n",
+ " <th>HighChol</th>\n",
+ " <th>CholCheck</th>\n",
+ " <th>BMI</th>\n",
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+ " <th>Age</th>\n",
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+ ],
+ "text/plain": [
+ " Diabetes_binary HighBP HighChol CholCheck BMI Smoker Stroke \\\n",
+ "0 0.0 1.0 1.0 1.0 40.0 1.0 0.0 \n",
+ "1 0.0 0.0 0.0 0.0 25.0 1.0 0.0 \n",
+ "2 0.0 1.0 1.0 1.0 28.0 0.0 0.0 \n",
+ "3 0.0 1.0 0.0 1.0 27.0 0.0 0.0 \n",
+ "4 0.0 1.0 1.0 1.0 24.0 0.0 0.0 \n",
+ "\n",
+ " HeartDiseaseorAttack PhysActivity Fruits Veggies HvyAlcoholConsump \\\n",
+ "0 0.0 0.0 0.0 1.0 0.0 \n",
+ "1 0.0 1.0 0.0 0.0 0.0 \n",
+ "2 0.0 0.0 1.0 0.0 0.0 \n",
+ "3 0.0 1.0 1.0 1.0 0.0 \n",
+ "4 0.0 1.0 1.0 1.0 0.0 \n",
+ "\n",
+ " AnyHealthcare NoDocbcCost GenHlth MentHlth PhysHlth DiffWalk Sex \\\n",
+ "0 1.0 0.0 5.0 18.0 15.0 1.0 0.0 \n",
+ "1 0.0 1.0 3.0 0.0 0.0 0.0 0.0 \n",
+ "2 1.0 1.0 5.0 30.0 30.0 1.0 0.0 \n",
+ "3 1.0 0.0 2.0 0.0 0.0 0.0 0.0 \n",
+ "4 1.0 0.0 2.0 3.0 0.0 0.0 0.0 \n",
+ "\n",
+ " Age Education Income \n",
+ "0 9.0 4.0 3.0 \n",
+ "1 7.0 6.0 1.0 \n",
+ "2 9.0 4.0 8.0 \n",
+ "3 11.0 3.0 6.0 \n",
+ "4 11.0 5.0 4.0 "
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pd.set_option('display.max_columns', None)\n",
+ "\n",
+ "df1.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "mlqb7sod7dS0",
+ "outputId": "aa50569f-7267-4352-9dc7-13149287e410"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(253680, 22)"
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+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df1.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "W8qsng6tEAZH",
+ "outputId": "35f6192c-fb98-4792-b9d6-41a74262ce43"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Index(['Diabetes_binary', 'HighBP', 'HighChol', 'CholCheck', 'BMI', 'Smoker',\n",
+ " 'Stroke', 'HeartDiseaseorAttack', 'PhysActivity', 'Fruits', 'Veggies',\n",
+ " 'HvyAlcoholConsump', 'AnyHealthcare', 'NoDocbcCost', 'GenHlth',\n",
+ " 'MentHlth', 'PhysHlth', 'DiffWalk', 'Sex', 'Age', 'Education',\n",
+ " 'Income'],\n",
+ " dtype='object')"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df1.columns"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "x8AtzNHbECzI",
+ "outputId": "4f5fd5c7-44fd-46fa-b32b-bb318f332dde"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<class 'pandas.core.frame.DataFrame'>\n",
+ "RangeIndex: 253680 entries, 0 to 253679\n",
+ "Data columns (total 22 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 Diabetes_binary 253680 non-null float64\n",
+ " 1 HighBP 253680 non-null float64\n",
+ " 2 HighChol 253680 non-null float64\n",
+ " 3 CholCheck 253680 non-null float64\n",
+ " 4 BMI 253680 non-null float64\n",
+ " 5 Smoker 253680 non-null float64\n",
+ " 6 Stroke 253680 non-null float64\n",
+ " 7 HeartDiseaseorAttack 253680 non-null float64\n",
+ " 8 PhysActivity 253680 non-null float64\n",
+ " 9 Fruits 253680 non-null float64\n",
+ " 10 Veggies 253680 non-null float64\n",
+ " 11 HvyAlcoholConsump 253680 non-null float64\n",
+ " 12 AnyHealthcare 253680 non-null float64\n",
+ " 13 NoDocbcCost 253680 non-null float64\n",
+ " 14 GenHlth 253680 non-null float64\n",
+ " 15 MentHlth 253680 non-null float64\n",
+ " 16 PhysHlth 253680 non-null float64\n",
+ " 17 DiffWalk 253680 non-null float64\n",
+ " 18 Sex 253680 non-null float64\n",
+ " 19 Age 253680 non-null float64\n",
+ " 20 Education 253680 non-null float64\n",
+ " 21 Income 253680 non-null float64\n",
+ "dtypes: float64(22)\n",
+ "memory usage: 42.6 MB\n"
+ ]
+ }
+ ],
+ "source": [
+ "#Checking information of dataframe df1\n",
+ "\n",
+ "df1.info()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 739
+ },
+ "id": "SVurPn4JEFCP",
+ "outputId": "9518cdbb-94cb-4881-8bee-d063c34cbb65"
+ },
+ "outputs": [
+ {
+ "data": {
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+ " <th></th>\n",
+ " <th>Diabetes_binary</th>\n",
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+ " <th>HighChol</th>\n",
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+ " <th>Smoker</th>\n",
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+ " <th>GenHlth</th>\n",
+ " <th>MentHlth</th>\n",
+ " <th>PhysHlth</th>\n",
+ " <th>DiffWalk</th>\n",
+ " <th>Sex</th>\n",
+ " <th>Age</th>\n",
+ " <th>Education</th>\n",
+ " <th>Income</th>\n",
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+ " <td>253680.000000</td>\n",
+ " <td>253680.000000</td>\n",
+ " <td>253680.000000</td>\n",
+ " <td>253680.000000</td>\n",
+ " <td>253680.000000</td>\n",
+ " <td>253680.000000</td>\n",
+ " <td>253680.000000</td>\n",
+ " <td>253680.000000</td>\n",
+ " <td>253680.000000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>mean</th>\n",
+ " <td>0.139333</td>\n",
+ " <td>0.429001</td>\n",
+ " <td>0.424121</td>\n",
+ " <td>0.962670</td>\n",
+ " <td>28.382364</td>\n",
+ " <td>0.443169</td>\n",
+ " <td>0.040571</td>\n",
+ " <td>0.094186</td>\n",
+ " <td>0.756544</td>\n",
+ " <td>0.634256</td>\n",
+ " <td>0.811420</td>\n",
+ " <td>0.056197</td>\n",
+ " <td>0.951053</td>\n",
+ " <td>0.084177</td>\n",
+ " <td>2.511392</td>\n",
+ " <td>3.184772</td>\n",
+ " <td>4.242081</td>\n",
+ " <td>0.168224</td>\n",
+ " <td>0.440342</td>\n",
+ " <td>8.032119</td>\n",
+ " <td>5.050434</td>\n",
+ " <td>6.053875</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>std</th>\n",
+ " <td>0.346294</td>\n",
+ " <td>0.494934</td>\n",
+ " <td>0.494210</td>\n",
+ " <td>0.189571</td>\n",
+ " <td>6.608694</td>\n",
+ " <td>0.496761</td>\n",
+ " <td>0.197294</td>\n",
+ " <td>0.292087</td>\n",
+ " <td>0.429169</td>\n",
+ " <td>0.481639</td>\n",
+ " <td>0.391175</td>\n",
+ " <td>0.230302</td>\n",
+ " <td>0.215759</td>\n",
+ " <td>0.277654</td>\n",
+ " <td>1.068477</td>\n",
+ " <td>7.412847</td>\n",
+ " <td>8.717951</td>\n",
+ " <td>0.374066</td>\n",
+ " <td>0.496429</td>\n",
+ " <td>3.054220</td>\n",
+ " <td>0.985774</td>\n",
+ " <td>2.071148</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>min</th>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>12.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>25%</th>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>24.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>6.000000</td>\n",
+ " <td>4.000000</td>\n",
+ " <td>5.000000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>50%</th>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>27.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>8.000000</td>\n",
+ " <td>5.000000</td>\n",
+ " <td>7.000000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>75%</th>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>31.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>3.000000</td>\n",
+ " <td>2.000000</td>\n",
+ " <td>3.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>10.000000</td>\n",
+ " <td>6.000000</td>\n",
+ " <td>8.000000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>max</th>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>98.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>5.000000</td>\n",
+ " <td>30.000000</td>\n",
+ " <td>30.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>13.000000</td>\n",
+ " <td>6.000000</td>\n",
+ " <td>8.000000</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Diabetes_binary HighBP HighChol CholCheck \\\n",
+ "count 253680.000000 253680.000000 253680.000000 253680.000000 \n",
+ "mean 0.139333 0.429001 0.424121 0.962670 \n",
+ "std 0.346294 0.494934 0.494210 0.189571 \n",
+ "min 0.000000 0.000000 0.000000 0.000000 \n",
+ "25% 0.000000 0.000000 0.000000 1.000000 \n",
+ "50% 0.000000 0.000000 0.000000 1.000000 \n",
+ "75% 0.000000 1.000000 1.000000 1.000000 \n",
+ "max 1.000000 1.000000 1.000000 1.000000 \n",
+ "\n",
+ " BMI Smoker Stroke HeartDiseaseorAttack \\\n",
+ "count 253680.000000 253680.000000 253680.000000 253680.000000 \n",
+ "mean 28.382364 0.443169 0.040571 0.094186 \n",
+ "std 6.608694 0.496761 0.197294 0.292087 \n",
+ "min 12.000000 0.000000 0.000000 0.000000 \n",
+ "25% 24.000000 0.000000 0.000000 0.000000 \n",
+ "50% 27.000000 0.000000 0.000000 0.000000 \n",
+ "75% 31.000000 1.000000 0.000000 0.000000 \n",
+ "max 98.000000 1.000000 1.000000 1.000000 \n",
+ "\n",
+ " PhysActivity Fruits Veggies HvyAlcoholConsump \\\n",
+ "count 253680.000000 253680.000000 253680.000000 253680.000000 \n",
+ "mean 0.756544 0.634256 0.811420 0.056197 \n",
+ "std 0.429169 0.481639 0.391175 0.230302 \n",
+ "min 0.000000 0.000000 0.000000 0.000000 \n",
+ "25% 1.000000 0.000000 1.000000 0.000000 \n",
+ "50% 1.000000 1.000000 1.000000 0.000000 \n",
+ "75% 1.000000 1.000000 1.000000 0.000000 \n",
+ "max 1.000000 1.000000 1.000000 1.000000 \n",
+ "\n",
+ " AnyHealthcare NoDocbcCost GenHlth MentHlth \\\n",
+ "count 253680.000000 253680.000000 253680.000000 253680.000000 \n",
+ "mean 0.951053 0.084177 2.511392 3.184772 \n",
+ "std 0.215759 0.277654 1.068477 7.412847 \n",
+ "min 0.000000 0.000000 1.000000 0.000000 \n",
+ "25% 1.000000 0.000000 2.000000 0.000000 \n",
+ "50% 1.000000 0.000000 2.000000 0.000000 \n",
+ "75% 1.000000 0.000000 3.000000 2.000000 \n",
+ "max 1.000000 1.000000 5.000000 30.000000 \n",
+ "\n",
+ " PhysHlth DiffWalk Sex Age \\\n",
+ "count 253680.000000 253680.000000 253680.000000 253680.000000 \n",
+ "mean 4.242081 0.168224 0.440342 8.032119 \n",
+ "std 8.717951 0.374066 0.496429 3.054220 \n",
+ "min 0.000000 0.000000 0.000000 1.000000 \n",
+ "25% 0.000000 0.000000 0.000000 6.000000 \n",
+ "50% 0.000000 0.000000 0.000000 8.000000 \n",
+ "75% 3.000000 0.000000 1.000000 10.000000 \n",
+ "max 30.000000 1.000000 1.000000 13.000000 \n",
+ "\n",
+ " Education Income \n",
+ "count 253680.000000 253680.000000 \n",
+ "mean 5.050434 6.053875 \n",
+ "std 0.985774 2.071148 \n",
+ "min 1.000000 1.000000 \n",
+ "25% 4.000000 5.000000 \n",
+ "50% 5.000000 7.000000 \n",
+ "75% 6.000000 8.000000 \n",
+ "max 6.000000 8.000000 "
+ ]
+ },
+ "execution_count": 9,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pd.set_option('display.max_columns', None)\n",
+ "\n",
+ "df1.describe()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 739
+ },
+ "id": "4LUsGjcSEHWF",
+ "outputId": "cb5c0fc4-9a06-480b-f720-6629c5cad55d"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>unique value count</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>Diabetes_binary</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HighBP</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HighChol</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>CholCheck</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>BMI</th>\n",
+ " <td>84</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Smoker</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Stroke</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HeartDiseaseorAttack</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>PhysActivity</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Fruits</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Veggies</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HvyAlcoholConsump</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>AnyHealthcare</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>NoDocbcCost</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>GenHlth</th>\n",
+ " <td>5</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>MentHlth</th>\n",
+ " <td>31</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>PhysHlth</th>\n",
+ " <td>31</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>DiffWalk</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Sex</th>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Age</th>\n",
+ " <td>13</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Education</th>\n",
+ " <td>6</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Income</th>\n",
+ " <td>8</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " unique value count\n",
+ "Diabetes_binary 2\n",
+ "HighBP 2\n",
+ "HighChol 2\n",
+ "CholCheck 2\n",
+ "BMI 84\n",
+ "Smoker 2\n",
+ "Stroke 2\n",
+ "HeartDiseaseorAttack 2\n",
+ "PhysActivity 2\n",
+ "Fruits 2\n",
+ "Veggies 2\n",
+ "HvyAlcoholConsump 2\n",
+ "AnyHealthcare 2\n",
+ "NoDocbcCost 2\n",
+ "GenHlth 5\n",
+ "MentHlth 31\n",
+ "PhysHlth 31\n",
+ "DiffWalk 2\n",
+ "Sex 2\n",
+ "Age 13\n",
+ "Education 6\n",
+ "Income 8"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#checking unique val\n",
+ "\n",
+ "unique_values = {}\n",
+ "for col in df1.columns:\n",
+ " unique_values[col] = df1[col].value_counts().shape[0]\n",
+ "\n",
+ "pd.DataFrame(unique_values, index=['unique value count']).transpose()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "YQ4xV0gmEXYN",
+ "outputId": "47e76ea9-ed21-4665-b417-e05f0ac549d3"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Diabetes_binary 0\n",
+ "HighBP 0\n",
+ "HighChol 0\n",
+ "CholCheck 0\n",
+ "BMI 0\n",
+ "Smoker 0\n",
+ "Stroke 0\n",
+ "HeartDiseaseorAttack 0\n",
+ "PhysActivity 0\n",
+ "Fruits 0\n",
+ "Veggies 0\n",
+ "HvyAlcoholConsump 0\n",
+ "AnyHealthcare 0\n",
+ "NoDocbcCost 0\n",
+ "GenHlth 0\n",
+ "MentHlth 0\n",
+ "PhysHlth 0\n",
+ "DiffWalk 0\n",
+ "Sex 0\n",
+ "Age 0\n",
+ "Education 0\n",
+ "Income 0\n",
+ "dtype: int64"
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#checking missing values of columns in Dataframe df1\n",
+ "\n",
+ "df1.isnull().sum()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Number of duplicated rows in dataset = 24206\n",
+ "Duplicated rows have been removed\n"
+ ]
+ }
+ ],
+ "source": [
+ "df1 = remove_duplicates(df1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "qJywYeFTEiZj",
+ "outputId": "7d848a6a-73c6-4f54-f216-39a8e1199f39"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(229474, 22)"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#checking shape after eliminating duplicate rows\n",
+ "\n",
+ "df1.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 656
+ },
+ "id": "kz9N65OMEk36",
+ "outputId": "5683f8bc-8d65-4a40-937c-2a336c1730ce"
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<Figure size 2000x1500 with 25 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#using histogram to understand dataset df1 better\n",
+ "\n",
+ "df1.hist(figsize=(20,15));"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 788
+ },
+ "id": "z0-b0R_iEnN5",
+ "outputId": "780d77b7-1d54-42d7-afcb-dd090eae348f"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Diabetes_binary</th>\n",
+ " <th>HighBP</th>\n",
+ " <th>HighChol</th>\n",
+ " <th>CholCheck</th>\n",
+ " <th>BMI</th>\n",
+ " <th>Smoker</th>\n",
+ " <th>Stroke</th>\n",
+ " <th>HeartDiseaseorAttack</th>\n",
+ " <th>PhysActivity</th>\n",
+ " <th>Fruits</th>\n",
+ " <th>Veggies</th>\n",
+ " <th>HvyAlcoholConsump</th>\n",
+ " <th>AnyHealthcare</th>\n",
+ " <th>NoDocbcCost</th>\n",
+ " <th>GenHlth</th>\n",
+ " <th>MentHlth</th>\n",
+ " <th>PhysHlth</th>\n",
+ " <th>DiffWalk</th>\n",
+ " <th>Sex</th>\n",
+ " <th>Age</th>\n",
+ " <th>Education</th>\n",
+ " <th>Income</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>Diabetes_binary</th>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.254318</td>\n",
+ " <td>0.194944</td>\n",
+ " <td>0.072523</td>\n",
+ " <td>0.205086</td>\n",
+ " <td>0.045504</td>\n",
+ " <td>0.099193</td>\n",
+ " <td>0.168213</td>\n",
+ " <td>-0.100404</td>\n",
+ " <td>-0.024805</td>\n",
+ " <td>-0.041734</td>\n",
+ " <td>-0.065950</td>\n",
+ " <td>0.025331</td>\n",
+ " <td>0.020048</td>\n",
+ " <td>0.276940</td>\n",
+ " <td>0.054153</td>\n",
+ " <td>0.156211</td>\n",
+ " <td>0.205302</td>\n",
+ " <td>0.032724</td>\n",
+ " <td>0.177263</td>\n",
+ " <td>-0.102686</td>\n",
+ " <td>-0.140659</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HighBP</th>\n",
+ " <td>0.254318</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.283963</td>\n",
+ " <td>0.111259</td>\n",
+ " <td>0.194218</td>\n",
+ " <td>0.074264</td>\n",
+ " <td>0.124558</td>\n",
+ " <td>0.201443</td>\n",
+ " <td>-0.104382</td>\n",
+ " <td>-0.019467</td>\n",
+ " <td>-0.042994</td>\n",
+ " <td>-0.014178</td>\n",
+ " <td>0.052044</td>\n",
+ " <td>0.002292</td>\n",
+ " <td>0.272784</td>\n",
+ " <td>0.037482</td>\n",
+ " <td>0.144656</td>\n",
+ " <td>0.211759</td>\n",
+ " <td>0.047119</td>\n",
+ " <td>0.339802</td>\n",
+ " <td>-0.112887</td>\n",
+ " <td>-0.140030</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HighChol</th>\n",
+ " <td>0.194944</td>\n",
+ " <td>0.283963</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.094772</td>\n",
+ " <td>0.089734</td>\n",
+ " <td>0.074583</td>\n",
+ " <td>0.089375</td>\n",
+ " <td>0.176446</td>\n",
+ " <td>-0.063443</td>\n",
+ " <td>-0.026257</td>\n",
+ " <td>-0.027399</td>\n",
+ " <td>-0.019057</td>\n",
+ " <td>0.052363</td>\n",
+ " <td>0.003020</td>\n",
+ " <td>0.188139</td>\n",
+ " <td>0.050346</td>\n",
+ " <td>0.111008</td>\n",
+ " <td>0.136045</td>\n",
+ " <td>0.022859</td>\n",
+ " <td>0.263841</td>\n",
+ " <td>-0.050045</td>\n",
+ " <td>-0.062089</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>CholCheck</th>\n",
+ " <td>0.072523</td>\n",
+ " <td>0.111259</td>\n",
+ " <td>0.094772</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.042487</td>\n",
+ " <td>-0.003721</td>\n",
+ " <td>0.027955</td>\n",
+ " <td>0.050086</td>\n",
+ " <td>-0.004555</td>\n",
+ " <td>0.017860</td>\n",
+ " <td>-0.000653</td>\n",
+ " <td>-0.020975</td>\n",
+ " <td>0.115498</td>\n",
+ " <td>-0.054128</td>\n",
+ " <td>0.062939</td>\n",
+ " <td>-0.001430</td>\n",
+ " <td>0.040758</td>\n",
+ " <td>0.049107</td>\n",
+ " <td>-0.024332</td>\n",
+ " <td>0.095942</td>\n",
+ " <td>-0.009935</td>\n",
+ " <td>0.001989</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>BMI</th>\n",
+ " <td>0.205086</td>\n",
+ " <td>0.194218</td>\n",
+ " <td>0.089734</td>\n",
+ " <td>0.042487</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>-0.009294</td>\n",
+ " <td>0.011006</td>\n",
+ " <td>0.039820</td>\n",
+ " <td>-0.127780</td>\n",
+ " <td>-0.067424</td>\n",
+ " <td>-0.044054</td>\n",
+ " <td>-0.058420</td>\n",
+ " <td>-0.008519</td>\n",
+ " <td>0.045795</td>\n",
+ " <td>0.208351</td>\n",
+ " <td>0.068569</td>\n",
+ " <td>0.102768</td>\n",
+ " <td>0.182556</td>\n",
+ " <td>0.030902</td>\n",
+ " <td>-0.049223</td>\n",
+ " <td>-0.074433</td>\n",
+ " <td>-0.069097</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Smoker</th>\n",
+ " <td>0.045504</td>\n",
+ " <td>0.074264</td>\n",
+ " <td>0.074583</td>\n",
+ " <td>-0.003721</td>\n",
+ " <td>-0.009294</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.054414</td>\n",
+ " <td>0.105169</td>\n",
+ " <td>-0.066869</td>\n",
+ " <td>-0.061731</td>\n",
+ " <td>-0.013744</td>\n",
+ " <td>0.096048</td>\n",
+ " <td>-0.013963</td>\n",
+ " <td>0.037335</td>\n",
+ " <td>0.134894</td>\n",
+ " <td>0.077641</td>\n",
+ " <td>0.100447</td>\n",
+ " <td>0.108144</td>\n",
+ " <td>0.096650</td>\n",
+ " <td>0.107695</td>\n",
+ " <td>-0.135657</td>\n",
+ " <td>-0.095314</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Stroke</th>\n",
+ " <td>0.099193</td>\n",
+ " <td>0.124558</td>\n",
+ " <td>0.089375</td>\n",
+ " <td>0.027955</td>\n",
+ " <td>0.011006</td>\n",
+ " <td>0.054414</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.198814</td>\n",
+ " <td>-0.059306</td>\n",
+ " <td>-0.004486</td>\n",
+ " <td>-0.033029</td>\n",
+ " <td>-0.021347</td>\n",
+ " <td>0.013627</td>\n",
+ " <td>0.028613</td>\n",
+ " <td>0.169809</td>\n",
+ " <td>0.061996</td>\n",
+ " <td>0.140806</td>\n",
+ " <td>0.169339</td>\n",
+ " <td>0.003626</td>\n",
+ " <td>0.128209</td>\n",
+ " <td>-0.064178</td>\n",
+ " <td>-0.117108</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HeartDiseaseorAttack</th>\n",
+ " <td>0.168213</td>\n",
+ " <td>0.201443</td>\n",
+ " <td>0.176446</td>\n",
+ " <td>0.050086</td>\n",
+ " <td>0.039820</td>\n",
+ " <td>0.105169</td>\n",
+ " <td>0.198814</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>-0.073094</td>\n",
+ " <td>-0.006946</td>\n",
+ " <td>-0.027180</td>\n",
+ " <td>-0.035561</td>\n",
+ " <td>0.025987</td>\n",
+ " <td>0.021971</td>\n",
+ " <td>0.246328</td>\n",
+ " <td>0.052601</td>\n",
+ " <td>0.170335</td>\n",
+ " <td>0.202657</td>\n",
+ " <td>0.089828</td>\n",
+ " <td>0.223912</td>\n",
+ " <td>-0.082288</td>\n",
+ " <td>-0.122728</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>PhysActivity</th>\n",
+ " <td>-0.100404</td>\n",
+ " <td>-0.104382</td>\n",
+ " <td>-0.063443</td>\n",
+ " <td>-0.004555</td>\n",
+ " <td>-0.127780</td>\n",
+ " <td>-0.066869</td>\n",
+ " <td>-0.059306</td>\n",
+ " <td>-0.073094</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.125023</td>\n",
+ " <td>0.135240</td>\n",
+ " <td>0.023378</td>\n",
+ " <td>0.023959</td>\n",
+ " <td>-0.046440</td>\n",
+ " <td>-0.237511</td>\n",
+ " <td>-0.105914</td>\n",
+ " <td>-0.199307</td>\n",
+ " <td>-0.235719</td>\n",
+ " <td>0.033516</td>\n",
+ " <td>-0.087881</td>\n",
+ " <td>0.170931</td>\n",
+ " <td>0.165869</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Fruits</th>\n",
+ " <td>-0.024805</td>\n",
+ " <td>-0.019467</td>\n",
+ " <td>-0.026257</td>\n",
+ " <td>0.017860</td>\n",
+ " <td>-0.067424</td>\n",
+ " <td>-0.061731</td>\n",
+ " <td>-0.004486</td>\n",
+ " <td>-0.006946</td>\n",
+ " <td>0.125023</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.242941</td>\n",
+ " <td>-0.028221</td>\n",
+ " <td>0.022659</td>\n",
+ " <td>-0.032387</td>\n",
+ " <td>-0.071221</td>\n",
+ " <td>-0.052191</td>\n",
+ " <td>-0.024441</td>\n",
+ " <td>-0.029932</td>\n",
+ " <td>-0.088768</td>\n",
+ " <td>0.073515</td>\n",
+ " <td>0.084857</td>\n",
+ " <td>0.050907</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Veggies</th>\n",
+ " <td>-0.041734</td>\n",
+ " <td>-0.042994</td>\n",
+ " <td>-0.027399</td>\n",
+ " <td>-0.000653</td>\n",
+ " <td>-0.044054</td>\n",
+ " <td>-0.013744</td>\n",
+ " <td>-0.033029</td>\n",
+ " <td>-0.027180</td>\n",
+ " <td>0.135240</td>\n",
+ " <td>0.242941</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.029772</td>\n",
+ " <td>0.020530</td>\n",
+ " <td>-0.019876</td>\n",
+ " <td>-0.094115</td>\n",
+ " <td>-0.042215</td>\n",
+ " <td>-0.045130</td>\n",
+ " <td>-0.063189</td>\n",
+ " <td>-0.066113</td>\n",
+ " <td>-0.003856</td>\n",
+ " <td>0.131624</td>\n",
+ " <td>0.125068</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HvyAlcoholConsump</th>\n",
+ " <td>-0.065950</td>\n",
+ " <td>-0.014178</td>\n",
+ " <td>-0.019057</td>\n",
+ " <td>-0.020975</td>\n",
+ " <td>-0.058420</td>\n",
+ " <td>0.096048</td>\n",
+ " <td>-0.021347</td>\n",
+ " <td>-0.035561</td>\n",
+ " <td>0.023378</td>\n",
+ " <td>-0.028221</td>\n",
+ " <td>0.029772</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>-0.006202</td>\n",
+ " <td>-0.001272</td>\n",
+ " <td>-0.055783</td>\n",
+ " <td>0.016852</td>\n",
+ " <td>-0.036860</td>\n",
+ " <td>-0.047655</td>\n",
+ " <td>0.009435</td>\n",
+ " <td>-0.041018</td>\n",
+ " <td>0.039132</td>\n",
+ " <td>0.071863</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>AnyHealthcare</th>\n",
+ " <td>0.025331</td>\n",
+ " <td>0.052044</td>\n",
+ " <td>0.052363</td>\n",
+ " <td>0.115498</td>\n",
+ " <td>-0.008519</td>\n",
+ " <td>-0.013963</td>\n",
+ " <td>0.013627</td>\n",
+ " <td>0.025987</td>\n",
+ " <td>0.023959</td>\n",
+ " <td>0.022659</td>\n",
+ " <td>0.020530</td>\n",
+ " <td>-0.006202</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>-0.227469</td>\n",
+ " <td>-0.023286</td>\n",
+ " <td>-0.043582</td>\n",
+ " <td>0.002924</td>\n",
+ " <td>0.017714</td>\n",
+ " <td>-0.021221</td>\n",
+ " <td>0.147465</td>\n",
+ " <td>0.111367</td>\n",
+ " <td>0.146144</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>NoDocbcCost</th>\n",
+ " <td>0.020048</td>\n",
+ " <td>0.002292</td>\n",
+ " <td>0.003020</td>\n",
+ " <td>-0.054128</td>\n",
+ " <td>0.045795</td>\n",
+ " <td>0.037335</td>\n",
+ " <td>0.028613</td>\n",
+ " <td>0.021971</td>\n",
+ " <td>-0.046440</td>\n",
+ " <td>-0.032387</td>\n",
+ " <td>-0.019876</td>\n",
+ " <td>-0.001272</td>\n",
+ " <td>-0.227469</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.149690</td>\n",
+ " <td>0.181769</td>\n",
+ " <td>0.136421</td>\n",
+ " <td>0.106225</td>\n",
+ " <td>-0.046507</td>\n",
+ " <td>-0.130115</td>\n",
+ " <td>-0.083260</td>\n",
+ " <td>-0.187577</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>GenHlth</th>\n",
+ " <td>0.276940</td>\n",
+ " <td>0.272784</td>\n",
+ " <td>0.188139</td>\n",
+ " <td>0.062939</td>\n",
+ " <td>0.208351</td>\n",
+ " <td>0.134894</td>\n",
+ " <td>0.169809</td>\n",
+ " <td>0.246328</td>\n",
+ " <td>-0.237511</td>\n",
+ " <td>-0.071221</td>\n",
+ " <td>-0.094115</td>\n",
+ " <td>-0.055783</td>\n",
+ " <td>-0.023286</td>\n",
+ " <td>0.149690</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.283822</td>\n",
+ " <td>0.516476</td>\n",
+ " <td>0.446696</td>\n",
+ " <td>-0.010519</td>\n",
+ " <td>0.145769</td>\n",
+ " <td>-0.244752</td>\n",
+ " <td>-0.331782</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>MentHlth</th>\n",
+ " <td>0.054153</td>\n",
+ " <td>0.037482</td>\n",
+ " <td>0.050346</td>\n",
+ " <td>-0.001430</td>\n",
+ " <td>0.068569</td>\n",
+ " <td>0.077641</td>\n",
+ " <td>0.061996</td>\n",
+ " <td>0.052601</td>\n",
+ " <td>-0.105914</td>\n",
+ " <td>-0.052191</td>\n",
+ " <td>-0.042215</td>\n",
+ " <td>0.016852</td>\n",
+ " <td>-0.043582</td>\n",
+ " <td>0.181769</td>\n",
+ " <td>0.283822</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.340191</td>\n",
+ " <td>0.218733</td>\n",
+ " <td>-0.083836</td>\n",
+ " <td>-0.103355</td>\n",
+ " <td>-0.076122</td>\n",
+ " <td>-0.185689</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>PhysHlth</th>\n",
+ " <td>0.156211</td>\n",
+ " <td>0.144656</td>\n",
+ " <td>0.111008</td>\n",
+ " <td>0.040758</td>\n",
+ " <td>0.102768</td>\n",
+ " <td>0.100447</td>\n",
+ " <td>0.140806</td>\n",
+ " <td>0.170335</td>\n",
+ " <td>-0.199307</td>\n",
+ " <td>-0.024441</td>\n",
+ " <td>-0.045130</td>\n",
+ " <td>-0.036860</td>\n",
+ " <td>0.002924</td>\n",
+ " <td>0.136421</td>\n",
+ " <td>0.516476</td>\n",
+ " <td>0.340191</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.466852</td>\n",
+ " <td>-0.044433</td>\n",
+ " <td>0.095483</td>\n",
+ " <td>-0.127687</td>\n",
+ " <td>-0.240929</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>DiffWalk</th>\n",
+ " <td>0.205302</td>\n",
+ " <td>0.211759</td>\n",
+ " <td>0.136045</td>\n",
+ " <td>0.049107</td>\n",
+ " <td>0.182556</td>\n",
+ " <td>0.108144</td>\n",
+ " <td>0.169339</td>\n",
+ " <td>0.202657</td>\n",
+ " <td>-0.235719</td>\n",
+ " <td>-0.029932</td>\n",
+ " <td>-0.063189</td>\n",
+ " <td>-0.047655</td>\n",
+ " <td>0.017714</td>\n",
+ " <td>0.106225</td>\n",
+ " <td>0.446696</td>\n",
+ " <td>0.218733</td>\n",
+ " <td>0.466852</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>-0.073405</td>\n",
+ " <td>0.205754</td>\n",
+ " <td>-0.169350</td>\n",
+ " <td>-0.299064</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Sex</th>\n",
+ " <td>0.032724</td>\n",
+ " <td>0.047119</td>\n",
+ " <td>0.022859</td>\n",
+ " <td>-0.024332</td>\n",
+ " <td>0.030902</td>\n",
+ " <td>0.096650</td>\n",
+ " <td>0.003626</td>\n",
+ " <td>0.089828</td>\n",
+ " <td>0.033516</td>\n",
+ " <td>-0.088768</td>\n",
+ " <td>-0.066113</td>\n",
+ " <td>0.009435</td>\n",
+ " <td>-0.021221</td>\n",
+ " <td>-0.046507</td>\n",
+ " <td>-0.010519</td>\n",
+ " <td>-0.083836</td>\n",
+ " <td>-0.044433</td>\n",
+ " <td>-0.073405</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>-0.031862</td>\n",
+ " <td>0.015956</td>\n",
+ " <td>0.130997</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Age</th>\n",
+ " <td>0.177263</td>\n",
+ " <td>0.339802</td>\n",
+ " <td>0.263841</td>\n",
+ " <td>0.095942</td>\n",
+ " <td>-0.049223</td>\n",
+ " <td>0.107695</td>\n",
+ " <td>0.128209</td>\n",
+ " <td>0.223912</td>\n",
+ " <td>-0.087881</td>\n",
+ " <td>0.073515</td>\n",
+ " <td>-0.003856</td>\n",
+ " <td>-0.041018</td>\n",
+ " <td>0.147465</td>\n",
+ " <td>-0.130115</td>\n",
+ " <td>0.145769</td>\n",
+ " <td>-0.103355</td>\n",
+ " <td>0.095483</td>\n",
+ " <td>0.205754</td>\n",
+ " <td>-0.031862</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>-0.092747</td>\n",
+ " <td>-0.116361</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Education</th>\n",
+ " <td>-0.102686</td>\n",
+ " <td>-0.112887</td>\n",
+ " <td>-0.050045</td>\n",
+ " <td>-0.009935</td>\n",
+ " <td>-0.074433</td>\n",
+ " <td>-0.135657</td>\n",
+ " <td>-0.064178</td>\n",
+ " <td>-0.082288</td>\n",
+ " <td>0.170931</td>\n",
+ " <td>0.084857</td>\n",
+ " <td>0.131624</td>\n",
+ " <td>0.039132</td>\n",
+ " <td>0.111367</td>\n",
+ " <td>-0.083260</td>\n",
+ " <td>-0.244752</td>\n",
+ " <td>-0.076122</td>\n",
+ " <td>-0.127687</td>\n",
+ " <td>-0.169350</td>\n",
+ " <td>0.015956</td>\n",
+ " <td>-0.092747</td>\n",
+ " <td>1.000000</td>\n",
+ " <td>0.419045</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Income</th>\n",
+ " <td>-0.140659</td>\n",
+ " <td>-0.140030</td>\n",
+ " <td>-0.062089</td>\n",
+ " <td>0.001989</td>\n",
+ " <td>-0.069097</td>\n",
+ " <td>-0.095314</td>\n",
+ " <td>-0.117108</td>\n",
+ " <td>-0.122728</td>\n",
+ " <td>0.165869</td>\n",
+ " <td>0.050907</td>\n",
+ " <td>0.125068</td>\n",
+ " <td>0.071863</td>\n",
+ " <td>0.146144</td>\n",
+ " <td>-0.187577</td>\n",
+ " <td>-0.331782</td>\n",
+ " <td>-0.185689</td>\n",
+ " <td>-0.240929</td>\n",
+ " <td>-0.299064</td>\n",
+ " <td>0.130997</td>\n",
+ " <td>-0.116361</td>\n",
+ " <td>0.419045</td>\n",
+ " <td>1.000000</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Diabetes_binary HighBP HighChol CholCheck \\\n",
+ "Diabetes_binary 1.000000 0.254318 0.194944 0.072523 \n",
+ "HighBP 0.254318 1.000000 0.283963 0.111259 \n",
+ "HighChol 0.194944 0.283963 1.000000 0.094772 \n",
+ "CholCheck 0.072523 0.111259 0.094772 1.000000 \n",
+ "BMI 0.205086 0.194218 0.089734 0.042487 \n",
+ "Smoker 0.045504 0.074264 0.074583 -0.003721 \n",
+ "Stroke 0.099193 0.124558 0.089375 0.027955 \n",
+ "HeartDiseaseorAttack 0.168213 0.201443 0.176446 0.050086 \n",
+ "PhysActivity -0.100404 -0.104382 -0.063443 -0.004555 \n",
+ "Fruits -0.024805 -0.019467 -0.026257 0.017860 \n",
+ "Veggies -0.041734 -0.042994 -0.027399 -0.000653 \n",
+ "HvyAlcoholConsump -0.065950 -0.014178 -0.019057 -0.020975 \n",
+ "AnyHealthcare 0.025331 0.052044 0.052363 0.115498 \n",
+ "NoDocbcCost 0.020048 0.002292 0.003020 -0.054128 \n",
+ "GenHlth 0.276940 0.272784 0.188139 0.062939 \n",
+ "MentHlth 0.054153 0.037482 0.050346 -0.001430 \n",
+ "PhysHlth 0.156211 0.144656 0.111008 0.040758 \n",
+ "DiffWalk 0.205302 0.211759 0.136045 0.049107 \n",
+ "Sex 0.032724 0.047119 0.022859 -0.024332 \n",
+ "Age 0.177263 0.339802 0.263841 0.095942 \n",
+ "Education -0.102686 -0.112887 -0.050045 -0.009935 \n",
+ "Income -0.140659 -0.140030 -0.062089 0.001989 \n",
+ "\n",
+ " BMI Smoker Stroke HeartDiseaseorAttack \\\n",
+ "Diabetes_binary 0.205086 0.045504 0.099193 0.168213 \n",
+ "HighBP 0.194218 0.074264 0.124558 0.201443 \n",
+ "HighChol 0.089734 0.074583 0.089375 0.176446 \n",
+ "CholCheck 0.042487 -0.003721 0.027955 0.050086 \n",
+ "BMI 1.000000 -0.009294 0.011006 0.039820 \n",
+ "Smoker -0.009294 1.000000 0.054414 0.105169 \n",
+ "Stroke 0.011006 0.054414 1.000000 0.198814 \n",
+ "HeartDiseaseorAttack 0.039820 0.105169 0.198814 1.000000 \n",
+ "PhysActivity -0.127780 -0.066869 -0.059306 -0.073094 \n",
+ "Fruits -0.067424 -0.061731 -0.004486 -0.006946 \n",
+ "Veggies -0.044054 -0.013744 -0.033029 -0.027180 \n",
+ "HvyAlcoholConsump -0.058420 0.096048 -0.021347 -0.035561 \n",
+ "AnyHealthcare -0.008519 -0.013963 0.013627 0.025987 \n",
+ "NoDocbcCost 0.045795 0.037335 0.028613 0.021971 \n",
+ "GenHlth 0.208351 0.134894 0.169809 0.246328 \n",
+ "MentHlth 0.068569 0.077641 0.061996 0.052601 \n",
+ "PhysHlth 0.102768 0.100447 0.140806 0.170335 \n",
+ "DiffWalk 0.182556 0.108144 0.169339 0.202657 \n",
+ "Sex 0.030902 0.096650 0.003626 0.089828 \n",
+ "Age -0.049223 0.107695 0.128209 0.223912 \n",
+ "Education -0.074433 -0.135657 -0.064178 -0.082288 \n",
+ "Income -0.069097 -0.095314 -0.117108 -0.122728 \n",
+ "\n",
+ " PhysActivity Fruits Veggies HvyAlcoholConsump \\\n",
+ "Diabetes_binary -0.100404 -0.024805 -0.041734 -0.065950 \n",
+ "HighBP -0.104382 -0.019467 -0.042994 -0.014178 \n",
+ "HighChol -0.063443 -0.026257 -0.027399 -0.019057 \n",
+ "CholCheck -0.004555 0.017860 -0.000653 -0.020975 \n",
+ "BMI -0.127780 -0.067424 -0.044054 -0.058420 \n",
+ "Smoker -0.066869 -0.061731 -0.013744 0.096048 \n",
+ "Stroke -0.059306 -0.004486 -0.033029 -0.021347 \n",
+ "HeartDiseaseorAttack -0.073094 -0.006946 -0.027180 -0.035561 \n",
+ "PhysActivity 1.000000 0.125023 0.135240 0.023378 \n",
+ "Fruits 0.125023 1.000000 0.242941 -0.028221 \n",
+ "Veggies 0.135240 0.242941 1.000000 0.029772 \n",
+ "HvyAlcoholConsump 0.023378 -0.028221 0.029772 1.000000 \n",
+ "AnyHealthcare 0.023959 0.022659 0.020530 -0.006202 \n",
+ "NoDocbcCost -0.046440 -0.032387 -0.019876 -0.001272 \n",
+ "GenHlth -0.237511 -0.071221 -0.094115 -0.055783 \n",
+ "MentHlth -0.105914 -0.052191 -0.042215 0.016852 \n",
+ "PhysHlth -0.199307 -0.024441 -0.045130 -0.036860 \n",
+ "DiffWalk -0.235719 -0.029932 -0.063189 -0.047655 \n",
+ "Sex 0.033516 -0.088768 -0.066113 0.009435 \n",
+ "Age -0.087881 0.073515 -0.003856 -0.041018 \n",
+ "Education 0.170931 0.084857 0.131624 0.039132 \n",
+ "Income 0.165869 0.050907 0.125068 0.071863 \n",
+ "\n",
+ " AnyHealthcare NoDocbcCost GenHlth MentHlth \\\n",
+ "Diabetes_binary 0.025331 0.020048 0.276940 0.054153 \n",
+ "HighBP 0.052044 0.002292 0.272784 0.037482 \n",
+ "HighChol 0.052363 0.003020 0.188139 0.050346 \n",
+ "CholCheck 0.115498 -0.054128 0.062939 -0.001430 \n",
+ "BMI -0.008519 0.045795 0.208351 0.068569 \n",
+ "Smoker -0.013963 0.037335 0.134894 0.077641 \n",
+ "Stroke 0.013627 0.028613 0.169809 0.061996 \n",
+ "HeartDiseaseorAttack 0.025987 0.021971 0.246328 0.052601 \n",
+ "PhysActivity 0.023959 -0.046440 -0.237511 -0.105914 \n",
+ "Fruits 0.022659 -0.032387 -0.071221 -0.052191 \n",
+ "Veggies 0.020530 -0.019876 -0.094115 -0.042215 \n",
+ "HvyAlcoholConsump -0.006202 -0.001272 -0.055783 0.016852 \n",
+ "AnyHealthcare 1.000000 -0.227469 -0.023286 -0.043582 \n",
+ "NoDocbcCost -0.227469 1.000000 0.149690 0.181769 \n",
+ "GenHlth -0.023286 0.149690 1.000000 0.283822 \n",
+ "MentHlth -0.043582 0.181769 0.283822 1.000000 \n",
+ "PhysHlth 0.002924 0.136421 0.516476 0.340191 \n",
+ "DiffWalk 0.017714 0.106225 0.446696 0.218733 \n",
+ "Sex -0.021221 -0.046507 -0.010519 -0.083836 \n",
+ "Age 0.147465 -0.130115 0.145769 -0.103355 \n",
+ "Education 0.111367 -0.083260 -0.244752 -0.076122 \n",
+ "Income 0.146144 -0.187577 -0.331782 -0.185689 \n",
+ "\n",
+ " PhysHlth DiffWalk Sex Age Education \\\n",
+ "Diabetes_binary 0.156211 0.205302 0.032724 0.177263 -0.102686 \n",
+ "HighBP 0.144656 0.211759 0.047119 0.339802 -0.112887 \n",
+ "HighChol 0.111008 0.136045 0.022859 0.263841 -0.050045 \n",
+ "CholCheck 0.040758 0.049107 -0.024332 0.095942 -0.009935 \n",
+ "BMI 0.102768 0.182556 0.030902 -0.049223 -0.074433 \n",
+ "Smoker 0.100447 0.108144 0.096650 0.107695 -0.135657 \n",
+ "Stroke 0.140806 0.169339 0.003626 0.128209 -0.064178 \n",
+ "HeartDiseaseorAttack 0.170335 0.202657 0.089828 0.223912 -0.082288 \n",
+ "PhysActivity -0.199307 -0.235719 0.033516 -0.087881 0.170931 \n",
+ "Fruits -0.024441 -0.029932 -0.088768 0.073515 0.084857 \n",
+ "Veggies -0.045130 -0.063189 -0.066113 -0.003856 0.131624 \n",
+ "HvyAlcoholConsump -0.036860 -0.047655 0.009435 -0.041018 0.039132 \n",
+ "AnyHealthcare 0.002924 0.017714 -0.021221 0.147465 0.111367 \n",
+ "NoDocbcCost 0.136421 0.106225 -0.046507 -0.130115 -0.083260 \n",
+ "GenHlth 0.516476 0.446696 -0.010519 0.145769 -0.244752 \n",
+ "MentHlth 0.340191 0.218733 -0.083836 -0.103355 -0.076122 \n",
+ "PhysHlth 1.000000 0.466852 -0.044433 0.095483 -0.127687 \n",
+ "DiffWalk 0.466852 1.000000 -0.073405 0.205754 -0.169350 \n",
+ "Sex -0.044433 -0.073405 1.000000 -0.031862 0.015956 \n",
+ "Age 0.095483 0.205754 -0.031862 1.000000 -0.092747 \n",
+ "Education -0.127687 -0.169350 0.015956 -0.092747 1.000000 \n",
+ "Income -0.240929 -0.299064 0.130997 -0.116361 0.419045 \n",
+ "\n",
+ " Income \n",
+ "Diabetes_binary -0.140659 \n",
+ "HighBP -0.140030 \n",
+ "HighChol -0.062089 \n",
+ "CholCheck 0.001989 \n",
+ "BMI -0.069097 \n",
+ "Smoker -0.095314 \n",
+ "Stroke -0.117108 \n",
+ "HeartDiseaseorAttack -0.122728 \n",
+ "PhysActivity 0.165869 \n",
+ "Fruits 0.050907 \n",
+ "Veggies 0.125068 \n",
+ "HvyAlcoholConsump 0.071863 \n",
+ "AnyHealthcare 0.146144 \n",
+ "NoDocbcCost -0.187577 \n",
+ "GenHlth -0.331782 \n",
+ "MentHlth -0.185689 \n",
+ "PhysHlth -0.240929 \n",
+ "DiffWalk -0.299064 \n",
+ "Sex 0.130997 \n",
+ "Age -0.116361 \n",
+ "Education 0.419045 \n",
+ "Income 1.000000 "
+ ]
+ },
+ "execution_count": 15,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#checking correlation between columns of dataset df1\n",
+ "\n",
+ "df1.corr()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 586
+ },
+ "id": "WAPfX8y8Eqzz",
+ "outputId": "f57248e7-85c8-412f-db18-676ebf16ebbc"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Text(0.5, 1.0, 'correlation of feature')"
+ ]
+ },
+ "execution_count": 16,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1900x1000 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#using heatmap to understand correlation better in dataset df1\n",
+ "#Heatmap of correlation\n",
+ "\n",
+ "\n",
+ "plt.figure(figsize = (19,10))\n",
+ "sns.heatmap(df1.corr(),annot=True , cmap ='YlOrRd' )\n",
+ "plt.title(\"correlation of feature\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {
+ "id": "cPL1ZAqJEwXJ"
+ },
+ "outputs": [],
+ "source": [
+ "#Replacing 0 into Non-Diabetic and 1 into Diabetic\n",
+ "#adding new column Diabetes_binary_str\n",
+ "\n",
+ "df1[\"Diabetes_binary_str\"]= df1[\"Diabetes_binary\"].replace({0:\"NOn-Diabetic\",1:\"Diabetic\"})"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "uRPJ3O6WFH3q",
+ "outputId": "7c5fd9f8-0a89-429c-a23b-d2d0fa4659e0"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "NOn-Diabetic 194377\n",
+ "Diabetic 35097\n",
+ "Name: Diabetes_binary_str, dtype: int64"
+ ]
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#average of column Daibetes_binary\n",
+ "# 0 for non-Diabetic person and 1 for Diabetic person\n",
+ "\n",
+ "df1[\"Diabetes_binary_str\"].value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 448
+ },
+ "id": "RmexqoMGFJ7b",
+ "outputId": "73173f0a-b370-4a3d-fde4-a0d5967f23e9"
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<Figure size 1600x800 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Suppress warnings\n",
+ "warnings.filterwarnings('ignore')\n",
+ "\n",
+ "# Create a figure with subplots\n",
+ "figure1, plot1 = plt.subplots(1, 2, figsize=(16, 8))\n",
+ "\n",
+ "# Customize color palette\n",
+ "colors = sns.color_palette('pastel')\n",
+ "\n",
+ "# Count plot for Diabetes_binary_str\n",
+ "sns.countplot(x='Diabetes_binary_str', data=df1, ax=plot1[0], palette=colors)\n",
+ "plot1[0].set_title('Count of Diabetic vs Non-Diabetic', fontsize=16)\n",
+ "plot1[0].set_xlabel('Diabetes Status', fontsize=14)\n",
+ "plot1[0].set_ylabel('Count', fontsize=14)\n",
+ "plot1[0].tick_params(axis='x', labelsize=12)\n",
+ "plot1[0].tick_params(axis='y', labelsize=12)\n",
+ "\n",
+ "# Pie chart for the average of diabetic and non-diabetic people\n",
+ "labels = [\"Non-Diabetic\", \"Diabetic\"]\n",
+ "plot1[1].pie(df1[\"Diabetes_binary\"].value_counts(), labels=labels, autopct='%.2f%%', startangle=90, colors=colors)\n",
+ "plot1[1].set_title('Proportion of Diabetic vs Non-Diabetic', fontsize=16)\n",
+ "\n",
+ "# Improve layout\n",
+ "plt.tight_layout()\n",
+ "\n",
+ "# Display the plots\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 406
+ },
+ "id": "XO97cDH-FOLX",
+ "outputId": "4c2333ef-6d83-46e2-819f-4b7544a6c948"
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#checking HighBP and non HighBP pepoles average by pie\n",
+ "\n",
+ "labels=[\"non HighBP\",\"HighBP\"]\n",
+ "\n",
+ "plt.pie(df1[\"HighBP\"].value_counts() , labels =labels ,autopct='%.02f' );"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 143
+ },
+ "id": "KLPglBOoFTmL",
+ "outputId": "d881e305-50ff-4206-9d9a-68caf962c67d"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th>Diabetes_binary_str</th>\n",
+ " <th>Diabetic</th>\n",
+ " <th>NOn-Diabetic</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>HighBP</th>\n",
+ " <th></th>\n",
+ " <th></th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0.0</th>\n",
+ " <td>8692</td>\n",
+ " <td>116522</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1.0</th>\n",
+ " <td>26405</td>\n",
+ " <td>77855</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ "Diabetes_binary_str Diabetic NOn-Diabetic\n",
+ "HighBP \n",
+ "0.0 8692 116522\n",
+ "1.0 26405 77855"
+ ]
+ },
+ "execution_count": 21,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#number of Diabetic patient with HighBP\n",
+ "\n",
+ "pd.crosstab(df1.HighBP,df1.Diabetes_binary_str)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "yTO9emjhFzSN",
+ "outputId": "fa9ce61a-367d-425b-e1ee-5f12edbcd7ec"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Diabetes_binary_str HighBP\n",
+ "Diabetic 1.0 75.234351\n",
+ " 0.0 24.765649\n",
+ "NOn-Diabetic 0.0 59.946393\n",
+ " 1.0 40.053607\n",
+ "Name: HighBP, dtype: float64"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# checking average of diabetic persons with HighBP and NO HighBP\n",
+ "\n",
+ "\n",
+ "(df1.groupby(\"Diabetes_binary_str\")[\"HighBP\"].value_counts()/df1.groupby(\"Diabetes_binary_str\")[\"HighBP\"].count())*100"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 542
+ },
+ "id": "m_lqYXm3F2_d",
+ "outputId": "77f826d3-b67f-485c-f58d-56b245862f7e"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
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r=L(8/(3*y)),i=e/r;return[t/(r*(1-n(i)/y)),i]},mt.invert=function(t,e){var r=2-n(e)/L(2*y/3);return[t*L(6*y)/(2*r),d(e)*S((4-r*r)/3)]},gt.invert=function(t,e){var r=L(y*(4+y))/2;return[t*r/(1+L(1-e*e*(4+y)/(4*y))),e*r/2]},vt.invert=function(t,e){var r=e*L((4+y)/y)/2,n=S(r),i=o(n);return[t/(2/L(y*(4+y))*(1+i)),S((n+r*(i+2))/(2+x))]},yt.invert=function(t,e){var r=L(2+y),n=e*r/2;return[r*t/(1+o(n)),n]},xt.invert=function(t,e){var r=1+x,n=L(r/2);return[2*t*n/(1+o(e*=n)),S((e+m(e))/r)]};var bt=3+2*w;function _t(t,e){var r=m(t/=2),n=o(t),a=L(o(e)),s=o(e/=2),l=m(e)/(s+w*n*a),u=L(2/(1+l*l)),f=L((w*s+(n+r)*a)/(w*s+(n-r)*a));return[bt*(u*(f-1/f)-2*c(f)),bt*(u*l*(f+1/f)-2*i(l))]}_t.invert=function(t,e){if(!(r=D.invert(t/1.2,1.065*e)))return null;var r,a=r[0],s=r[1],l=20;t/=bt,e/=bt;do{var 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a=V(s,i);return[r/n*(t+e/o(a)),a]},a}function Mt(t){return[t[0]/2,S(g(t[1]/2*M))*A]}function St(t){return[2*t[0],2*i(m(t[1]*M))*A]}function Et(t,r){var i=2*y/r,s=t*t;function l(r,l){var c=e.geoAzimuthalEquidistantRaw(r,l),u=c[0],f=c[1],h=u*u+f*f;if(h>s){var d=L(h),g=a(f,u),b=i*p(g/i),_=g-b,w=t*o(_),T=(t*m(_)-_*m(w))/(x-w),k=Lt(_,T),A=(y-t)/Ct(k,w,y);u=d;var M,S=50;do{u-=M=(t+Ct(k,w,u)*A-d)/(k(u)*A)}while(n(M)>v&&--S>0);f=_*m(u),u<x&&(f-=T*(u-x));var E=m(b),C=o(b);c[0]=u*C-f*E,c[1]=u*E+f*C}return c}return l.invert=function(r,l){var c=r*r+l*l;if(c>s){var u=L(c),f=a(l,r),h=i*p(f/i),d=f-h;r=u*o(d),l=u*m(d);for(var g=r-x,v=m(r),b=l/v,_=r<x?1/0:0,w=10;;){var T=t*m(b),k=t*o(b),A=m(k),M=x-k,S=(T-b*A)/M,E=Lt(b,S);if(n(_)<1e-12||!--w)break;b-=_=(b*v-S*g-l)/(v-2*g*(M*(k+b*T*o(k)-A)-T*(T-b*A))/(M*M))}r=(u=t+Ct(E,k,r)*(y-t)/Ct(E,k,y))*o(f=h+b),l=u*m(f)}return e.geoAzimuthalEquidistantRaw.invert(r,l)},l}function Lt(t,e){return function(r){var n=t*o(r);return r<x&&(n-=e),L(1+n*n)}}function 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float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ vec2(positionOffset.x, -positionOffset.y)))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:i,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:v(c,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:u.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);g(t.kerning,m(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=u.mallocFloat(2*this.count),A=0,M=0;A<this.counts.length;A++){var S=this.counts[A];if(w)for(var E=0;E<S;E++)k[M++]=t.position[2*A],k[M++]=t.position[2*A+1];else for(var L=0;L<S;L++)k[M++]=t.position[A][0],k[M++]=t.position[A][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),u.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var C=u.mallocUint8(this.count),P=u.mallocFloat(2*this.count);this.textWidth=[];for(var I=0,O=0;I<this.counts.length;I++){for(var z=this.counts[I],D=this.font[I]||this.font[0],R=this.fontAtlas[I]||this.fontAtlas[0],F=0;F<z;F++){var B=this.text.charAt(O),N=this.text.charAt(O-1);if(C[O]=R.ids[B],P[2*O]=D.width[B],F){var j=P[2*O-2],U=P[2*O],V=P[2*O-1]+.5*j+.5*U;if(this.kerning){var H=D.kerning[N+B];H&&(V+=.001*H)}P[2*O+1]=V}else P[2*O+1]=.5*P[2*O];O++}this.textWidth.push(P.length?.5*P[2*O-2]+P[2*O-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:C,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:P,type:\"float\",usage:\"stream\"}),u.freeUint8(C),u.freeFloat(P),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),u=x(s*i);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,i+=\"number\"==typeof t?t-n.baseline:-n[t],i*=-1}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var q;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;q=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)q.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;q=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)q.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=q}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},e.exports=T},{\"bit-twiddle\":81,\"color-normalize\":89,\"css-font\":99,\"detect-kerning\":125,\"es6-weak-map\":183,\"flatten-vertex-data\":191,\"font-atlas\":192,\"font-measure\":193,\"gl-util/context\":226,\"is-plain-obj\":236,\"object-assign\":247,\"parse-rect\":249,\"parse-unit\":251,\"pick-by-alias\":253,regl:283,\"to-px\":314,\"typedarray-pool\":327}],226:[function(t,e,r){(function(r){(function(){\"use strict\";var n=t(\"pick-by-alias\");function i(t){if(t.container)if(t.container==document.body)document.body.style.width||(t.canvas.width=t.width||t.pixelRatio*r.innerWidth),document.body.style.height||(t.canvas.height=t.height||t.pixelRatio*r.innerHeight);else{var 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r=e.parse(t[1],1,Bt);if(!r)return null;var n=[],i=null;e.expectedType&&\"value\"!==e.expectedType.kind&&(i=e.expectedType);for(var a=1;a<t.length;a+=2){var o=1===a?-1/0:t[a],s=t[a+1],l=a,c=a+1;if(\"number\"!=typeof o)return e.error('Input/output pairs for \"step\" expressions must be defined using literal numeric values (not computed expressions) for the input values.',l);if(n.length&&n[n.length-1][0]>=o)return e.error('Input/output pairs for \"step\" expressions must be arranged with input values in strictly ascending order.',l);var u=e.parse(s,c,i);if(!u)return null;i=i||u.type,n.push([o,u])}return new He(i,r,n)},He.prototype.evaluate=function(t){var e=this.labels,r=this.outputs;if(1===e.length)return r[0].evaluate(t);var n=this.input.evaluate(t);if(n<=e[0])return r[0].evaluate(t);var i=e.length;return n>=e[i-1]?r[i-1].evaluate(t):r[Ve(e,n)].evaluate(t)},He.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},He.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},He.prototype.serialize=function(){for(var t=[\"step\",this.input.serialize()],e=0;e<this.labels.length;e++)e>0&&t.push(this.labels[e]),t.push(this.outputs[e].serialize());return t};var Ge=Object.freeze({__proto__:null,number:qe,color:function(t,e,r){return new te(qe(t.r,e.r,r),qe(t.g,e.g,r),qe(t.b,e.b,r),qe(t.a,e.a,r))},array:function(t,e,r){return t.map((function(t,n){return qe(t,e[n],r)}))}}),Ye=6/29,We=3*Ye*Ye,Xe=Math.PI/180,Ze=180/Math.PI;function Je(t){return t>.008856451679035631?Math.pow(t,1/3):t/We+4/29}function Ke(t){return t>Ye?t*t*t:We*(t-4/29)}function Qe(t){return 255*(t<=.0031308?12.92*t:1.055*Math.pow(t,1/2.4)-.055)}function $e(t){return(t/=255)<=.04045?t/12.92:Math.pow((t+.055)/1.055,2.4)}function tr(t){var e=$e(t.r),r=$e(t.g),n=$e(t.b),i=Je((.4124564*e+.3575761*r+.1804375*n)/.95047),a=Je((.2126729*e+.7151522*r+.072175*n)/1);return{l:116*a-16,a:500*(i-a),b:200*(a-Je((.0193339*e+.119192*r+.9503041*n)/1.08883)),alpha:t.a}}function er(t){var e=(t.l+16)/116,r=isNaN(t.a)?e:e+t.a/500,n=isNaN(t.b)?e:e-t.b/200;return e=1*Ke(e),r=.95047*Ke(r),n=1.08883*Ke(n),new te(Qe(3.2404542*r-1.5371385*e-.4985314*n),Qe(-.969266*r+1.8760108*e+.041556*n),Qe(.0556434*r-.2040259*e+1.0572252*n),t.alpha)}function rr(t,e,r){var n=e-t;return t+r*(n>180||n<-180?n-360*Math.round(n/360):n)}var nr={forward:tr,reverse:er,interpolate:function(t,e,r){return{l:qe(t.l,e.l,r),a:qe(t.a,e.a,r),b:qe(t.b,e.b,r),alpha:qe(t.alpha,e.alpha,r)}}},ir={forward:function(t){var e=tr(t),r=e.l,n=e.a,i=e.b,a=Math.atan2(i,n)*Ze;return{h:a<0?a+360:a,c:Math.sqrt(n*n+i*i),l:r,alpha:t.a}},reverse:function(t){var e=t.h*Xe,r=t.c;return er({l:t.l,a:Math.cos(e)*r,b:Math.sin(e)*r,alpha:t.alpha})},interpolate:function(t,e,r){return{h:rr(t.h,e.h,r),c:qe(t.c,e.c,r),l:qe(t.l,e.l,r),alpha:qe(t.alpha,e.alpha,r)}}},ar=Object.freeze({__proto__:null,lab:nr,hcl:ir}),or=function(t,e,r,n,i){this.type=t,this.operator=e,this.interpolation=r,this.input=n,this.labels=[],this.outputs=[];for(var a=0,o=i;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1];this.labels.push(l),this.outputs.push(c)}};function sr(t,e,r,n){var i=n-r,a=t-r;return 0===i?0:1===e?a/i:(Math.pow(e,a)-1)/(Math.pow(e,i)-1)}or.interpolationFactor=function(t,e,n,i){var a=0;if(\"exponential\"===t.name)a=sr(e,t.base,n,i);else if(\"linear\"===t.name)a=sr(e,1,n,i);else if(\"cubic-bezier\"===t.name){var o=t.controlPoints;a=new r(o[0],o[1],o[2],o[3]).solve(sr(e,1,n,i))}return a},or.parse=function(t,e){var r=t[0],n=t[1],i=t[2],a=t.slice(3);if(!Array.isArray(n)||0===n.length)return e.error(\"Expected an interpolation type expression.\",1);if(\"linear\"===n[0])n={name:\"linear\"};else if(\"exponential\"===n[0]){var o=n[1];if(\"number\"!=typeof o)return e.error(\"Exponential interpolation requires a numeric base.\",1,1);n={name:\"exponential\",base:o}}else{if(\"cubic-bezier\"!==n[0])return e.error(\"Unknown interpolation type \"+String(n[0]),1,0);var s=n.slice(1);if(4!==s.length||s.some((function(t){return\"number\"!=typeof t||t<0||t>1})))return e.error(\"Cubic bezier interpolation requires four numeric arguments with values between 0 and 1.\",1);n={name:\"cubic-bezier\",controlPoints:s}}if(t.length-1<4)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if((t.length-1)%2!=0)return e.error(\"Expected an even number of arguments.\");if(!(i=e.parse(i,2,Bt)))return null;var l=[],c=null;\"interpolate-hcl\"===r||\"interpolate-lab\"===r?c=Ut:e.expectedType&&\"value\"!==e.expectedType.kind&&(c=e.expectedType);for(var u=0;u<a.length;u+=2){var f=a[u],h=a[u+1],p=u+3,d=u+4;if(\"number\"!=typeof f)return e.error('Input/output pairs for 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a=Ve(e,n),o=e[a],s=e[a+1],l=or.interpolationFactor(this.interpolation,n,o,s),c=r[a].evaluate(t),u=r[a+1].evaluate(t);return\"interpolate\"===this.operator?Ge[this.type.kind.toLowerCase()](c,u,l):\"interpolate-hcl\"===this.operator?ir.reverse(ir.interpolate(ir.forward(c),ir.forward(u),l)):nr.reverse(nr.interpolate(nr.forward(c),nr.forward(u),l))},or.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},or.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},or.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var lr=function(t,e){this.type=t,this.args=e};lr.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var i=[],a=0,o=t.slice(1);a<o.length;a+=1){var s=o[a],l=e.parse(s,1+i.length,r,void 0,{typeAnnotation:\"omit\"});if(!l)return null;r=r||l.type,i.push(l)}var c=n&&i.some((function(t){return Jt(n,t.type)}));return new lr(c?Ht:r,i)},lr.prototype.evaluate=function(t){for(var e,r=null,n=0,i=0,a=this.args;i<a.length;i+=1){if(n++,(r=a[i].evaluate(t))&&r instanceof ie&&!r.available&&(e||(e=r.name),r=null,n===this.args.length&&(r=e)),null!==r)break}return r},lr.prototype.eachChild=function(t){this.args.forEach(t)},lr.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},lr.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild((function(e){t.push(e.serialize())})),t};var cr=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};cr.prototype.evaluate=function(t){return this.result.evaluate(t)},cr.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1){t(r[e][1])}t(this.result)},cr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var i=t[n];if(\"string\"!=typeof i)return e.error(\"Expected string, but found \"+typeof i+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(i))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var a=e.parse(t[n+1],n+1);if(!a)return null;r.push([i,a])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new cr(r,o):null},cr.prototype.outputDefined=function(){return this.result.outputDefined()},cr.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t.push(i,a.serialize())}return t.push(this.result.serialize()),t};var ur=function(t,e,r){this.type=t,this.index=e,this.input=r};ur.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Bt),n=e.parse(t[2],2,Wt(e.expectedType||Ht));if(!r||!n)return null;var i=n.type;return new ur(i.itemType,r,n)},ur.prototype.evaluate=function(t){var e=this.index.evaluate(t),r=this.input.evaluate(t);if(e<0)throw new ue(\"Array index out of bounds: \"+e+\" < 0.\");if(e>=r.length)throw new ue(\"Array index out of bounds: \"+e+\" > \"+(r.length-1)+\".\");if(e!==Math.floor(e))throw new ue(\"Array index must be an integer, but found \"+e+\" instead.\");return r[e]},ur.prototype.eachChild=function(t){t(this.index),t(this.input)},ur.prototype.outputDefined=function(){return!1},ur.prototype.serialize=function(){return[\"at\",this.index.serialize(),this.input.serialize()]};var fr=function(t,e){this.type=jt,this.needle=t,this.haystack=e};fr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Ht),n=e.parse(t[2],2,Ht);return r&&n?Kt(r.type,[jt,Nt,Bt,Ft,Ht])?new fr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\"):null},fr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");return r.indexOf(e)>=0},fr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},fr.prototype.outputDefined=function(){return!0},fr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var hr=function(t,e,r){this.type=Bt,this.needle=t,this.haystack=e,this.fromIndex=r};hr.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Ht),n=e.parse(t[2],2,Ht);if(!r||!n)return null;if(!Kt(r.type,[jt,Nt,Bt,Ft,Ht]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Bt);return i?new hr(r,n,i):null}return new hr(r,n)},hr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");if(this.fromIndex){var n=this.fromIndex.evaluate(t);return r.indexOf(e,n)}return r.indexOf(e)},hr.prototype.eachChild=function(t){t(this.needle),t(this.haystack),this.fromIndex&&t(this.fromIndex)},hr.prototype.outputDefined=function(){return!1},hr.prototype.serialize=function(){if(null!=this.fromIndex&&void 0!==this.fromIndex){var t=this.fromIndex.serialize();return[\"index-of\",this.needle.serialize(),this.haystack.serialize(),t]}return[\"index-of\",this.needle.serialize(),this.haystack.serialize()]};var pr=function(t,e,r,n,i,a){this.inputType=t,this.type=e,this.input=r,this.cases=n,this.outputs=i,this.otherwise=a};pr.parse=function(t,e){if(t.length<5)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=1)return e.error(\"Expected an even number of 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m?\"value\"!==d.type.kind&&e.concat(1).checkSubtype(r,d.type)?null:new pr(r,n,d,i,a,m):null},pr.prototype.evaluate=function(t){var e=this.input.evaluate(t);return(se(e)===this.inputType&&this.outputs[this.cases[e]]||this.otherwise).evaluate(t)},pr.prototype.eachChild=function(t){t(this.input),this.outputs.forEach(t),t(this.otherwise)},pr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))&&this.otherwise.outputDefined()},pr.prototype.serialize=function(){for(var t=this,e=[\"match\",this.input.serialize()],r=[],n={},i=0,a=Object.keys(this.cases).sort();i<a.length;i+=1){var o=a[i];void 0===(f=n[this.cases[o]])?(n[this.cases[o]]=r.length,r.push([this.cases[o],[o]])):r[f][1].push(o)}for(var s=function(e){return\"number\"===t.inputType.kind?Number(e):e},l=0,c=r;l<c.length;l+=1){var u=c[l],f=u[0],h=u[1];1===h.length?e.push(s(h[0])):e.push(h.map(s)),e.push(this.outputs[outputIndex$1].serialize())}return e.push(this.otherwise.serialize()),e};var dr=function(t,e,r){this.type=t,this.branches=e,this.otherwise=r};dr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=0)return e.error(\"Expected an odd number of arguments.\");var r;e.expectedType&&\"value\"!==e.expectedType.kind&&(r=e.expectedType);for(var n=[],i=1;i<t.length-1;i+=2){var a=e.parse(t[i],i,jt);if(!a)return null;var o=e.parse(t[i+1],i+1,r);if(!o)return null;n.push([a,o]),r=r||o.type}var s=e.parse(t[t.length-1],t.length-1,r);return s?new dr(r,n,s):null},dr.prototype.evaluate=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];if(i.evaluate(t))return a.evaluate(t)}return this.otherwise.evaluate(t)},dr.prototype.eachChild=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t(i),t(a)}t(this.otherwise)},dr.prototype.outputDefined=function(){return this.branches.every((function(t){t[0];return 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or?a.interpolation:void 0;return Ir(new Zr(n?\"camera\":\"composite\",t.value,a.labels,o))}Zr.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},Zr.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)},Zr.prototype.interpolationFactor=function(t,e,r){return this.interpolationType?or.interpolationFactor(this.interpolationType,t,e,r):0};var Kr=function(t,e){this._parameters=t,this._specification=e,It(this,function t(e,r){var n,i,a,o=\"color\"===r.type,s=e.stops&&\"object\"==typeof e.stops[0][0],l=s||void 0!==e.property,c=s||!l,u=e.type||(Rr(r)?\"exponential\":\"interval\");if(o&&((e=It({},e)).stops&&(e.stops=e.stops.map((function(t){return[t[0],te.parse(t[1])]}))),e.default?e.default=te.parse(e.default):e.default=te.parse(r.default)),e.colorSpace&&\"rgb\"!==e.colorSpace&&!ar[e.colorSpace])throw new Error(\"Unknown color space: 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n&&r<n.minimum?[new Ct(e,r,r+\" is less than the minimum value \"+n.minimum)]:\"maximum\"in n&&r>n.maximum?[new Ct(e,r,r+\" is greater than the maximum value \"+n.maximum)]:[]}function en(t){var e,r,n,i=t.valueSpec,a=Ot(t.value.type),o={},s=\"categorical\"!==a&&void 0===t.value.property,l=!s,c=\"array\"===Fr(t.value.stops)&&\"array\"===Fr(t.value.stops[0])&&\"object\"===Fr(t.value.stops[0][0]),u=Qr({key:t.key,value:t.value,valueSpec:t.styleSpec.function,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if(\"identity\"===a)return[new Ct(t.key,t.value,'identity function may not have a \"stops\" property')];var e=[],r=t.value;e=e.concat($r({key:t.key,value:r,valueSpec:t.valueSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:f})),\"array\"===Fr(r)&&0===r.length&&e.push(new Ct(t.key,r,\"array must have at least one stop\"));return e},default:function(t){return kn({key:t.key,value:t.value,valueSpec:i,style:t.style,styleSpec:t.styleSpec})}}});return\"identity\"===a&&s&&u.push(new Ct(t.key,t.value,'missing required property \"property\"')),\"identity\"===a||t.value.stops||u.push(new Ct(t.key,t.value,'missing required property \"stops\"')),\"exponential\"===a&&t.valueSpec.expression&&!Rr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!zr(t.valueSpec)?u.push(new Ct(t.key,t.value,\"property functions not supported\")):s&&!Dr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==a&&!c||void 0!==t.value.property||u.push(new Ct(t.key,t.value,'\"property\" property is required')),u;function f(t){var e=[],a=t.value,s=t.key;if(\"array\"!==Fr(a))return[new Ct(s,a,\"array expected, \"+Fr(a)+\" found\")];if(2!==a.length)return[new Ct(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(c){if(\"object\"!==Fr(a[0]))return[new Ct(s,a,\"object expected, \"+Fr(a[0])+\" found\")];if(void 0===a[0].zoom)return[new Ct(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new Ct(s,a,\"object stop key must have value\")];if(n&&n>Ot(a[0].zoom))return[new Ct(s,a[0].zoom,\"stop zoom values must appear in ascending order\")];Ot(a[0].zoom)!==n&&(n=Ot(a[0].zoom),r=void 0,o={}),e=e.concat(Qr({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:tn,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return Yr(zt(a[1]))?e.concat([new Ct(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(kn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=Fr(t.value),l=Ot(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new Ct(t.key,c,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new Ct(t.key,c,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var u=\"number expected, \"+s+\" found\";return zr(i)&&void 0===a&&(u+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new Ct(t.key,c,u)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new Ct(t.key,c,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new Ct(t.key,c,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new Ct(t.key,c,\"integer expected, found \"+l)]}}function rn(t){var e=(\"property\"===t.expressionContext?Jr:Wr)(zt(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new Ct(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new Ct(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". Output values must be contained as literals within the expression.')];if(\"property\"===t.expressionContext&&\"layout\"===t.propertyType&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(\"filter\"===t.expressionContext&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf(\"cluster\")){if(!Ne(r,[\"zoom\",\"feature-state\"]))return[new Ct(t.key,t.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(\"cluster-initial\"===t.expressionContext&&!Fe(r))return[new Ct(t.key,t.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function nn(t){var e=t.key,r=t.value,n=t.valueSpec,i=[];return Array.isArray(n.values)?-1===n.values.indexOf(Ot(r))&&i.push(new Ct(e,r,\"expected one of [\"+n.values.join(\", \")+\"], 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on={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function sn(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};an(t)||(t=cn(t));var e=Wr(t,on);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:function t(e){if(!Array.isArray(e))return!1;if(\"within\"===e[0])return!0;for(var r=1;r<e.length;r++)if(t(e[r]))return!0;return!1}(t)}}function ln(t,e){return t<e?-1:t>e?1:0}function cn(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?un(t[1],t[2],\"==\"):\"!=\"===r?pn(un(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?un(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(cn))):\"all\"===r?[\"all\"].concat(t.slice(1).map(cn)):\"none\"===r?[\"all\"].concat(t.slice(1).map(cn).map(pn)):\"in\"===r?fn(t[1],t.slice(2)):\"!in\"===r?pn(fn(t[1],t.slice(2))):\"has\"===r?hn(t[1]):\"!has\"===r?pn(hn(t[1])):\"within\"!==r||t}function un(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function fn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(ln)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function hn(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function pn(t){return[\"!\",t]}function dn(t){return an(zt(t.value))?rn(It({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):function t(e){var r=e.value,n=e.key;if(\"array\"!==Fr(r))return[new Ct(n,r,\"array expected, \"+Fr(r)+\" found\")];var i,a=e.styleSpec,o=[];if(r.length<1)return[new Ct(n,r,\"filter array must have at least 1 element\")];switch(o=o.concat(nn({key:n+\"[0]\",value:r[0],valueSpec:a.filter_operator,style:e.style,styleSpec:e.styleSpec})),Ot(r[0])){case\"<\":case\"<=\":case\">\":case\">=\":r.length>=2&&\"$type\"===Ot(r[1])&&o.push(new Ct(n,r,'\"$type\" cannot be use with operator \"'+r[0]+'\"'));case\"==\":case\"!=\":3!==r.length&&o.push(new Ct(n,r,'filter array for operator \"'+r[0]+'\" must have 3 elements'));case\"in\":case\"!in\":r.length>=2&&\"string\"!==(i=Fr(r[1]))&&o.push(new Ct(n+\"[1]\",r[1],\"string expected, \"+i+\" 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r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return kn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var c,u=t.valueSpec||s[o];if(!u)return[new Ct(r,a,'unknown property \"'+o+'\"')];if(\"string\"===Fr(a)&&zr(u)&&!u.tokens&&(c=/^{([^}]+)}$/.exec(a)))return[new Ct(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new Ct(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&Br(zt(a))&&\"identity\"===Ot(a.type)&&f.push(new Ct(r,a,'\"text-font\" does not support identity 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null!=hi.applyArabicShaping&&null!=hi.processBidirectionalText&&null!=hi.processStyledBidirectionalText},getPluginURL:function(){return oi}},pi=function(t,e){this.zoom=t,e?(this.now=e.now,this.fadeDuration=e.fadeDuration,this.zoomHistory=e.zoomHistory,this.transition=e.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new Gn,this.transition={})};pi.prototype.isSupportedScript=function(t){return function(t,e){for(var r=0,n=t;r<n.length;r+=1){if(!Qn(n[r].charCodeAt(0),e))return!1}return!0}(t,hi.isLoaded())},pi.prototype.crossFadingFactor=function(){return 0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)},pi.prototype.getCrossfadeParameters=function(){var t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}};var di=function(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(Br(t))return new Kr(t,e);if(Yr(t)){var r=Jr(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=te.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};di.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},di.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var mi=function(t){this.property=t,this.value=new di(t,void 0)};mi.prototype.transitioned=function(t,e){return new vi(this.property,this.value,e,u({},t.transition,this.transition),t.now)},mi.prototype.untransitioned=function(){return new vi(this.property,this.value,null,{},0)};var gi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};gi.prototype.getValue=function(t){return x(this._values[t].value.value)},gi.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new mi(this._values[t].property)),this._values[t].value=new di(this._values[t].property,null===e?void 0:x(e))},gi.prototype.getTransition=function(t){return x(this._values[t].transition)},gi.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new mi(this._values[t].property)),this._values[t].transition=x(e)||void 0},gi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},gi.prototype.transitioned=function(t,e){for(var r=new yi(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},gi.prototype.untransitioned=function(){for(var t=new yi(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var vi=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};vi.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var yi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};yi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},yi.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var xi=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};xi.prototype.getValue=function(t){return x(this._values[t].value)},xi.prototype.setValue=function(t,e){this._values[t]=new di(this._values[t].property,null===e?void 0:x(e))},xi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},xi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var bi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};bi.prototype.isConstant=function(){return\"constant\"===this.value.kind},bi.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},bi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var _i=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};_i.prototype.get=function(t){return this._values[t]};var wi=function(t){this.specification=t};wi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},wi.prototype.interpolate=function(t,e,r){var n=Ge[this.specification.type];return n?n(t,e,r):t};var Ti=function(t,e){this.specification=t,this.overrides=e};Ti.prototype.possiblyEvaluate=function(t,e,r,n){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new bi(this,{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)},e):new bi(this,t.expression,e)},Ti.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new bi(this,{kind:\"constant\",value:void 0},t.parameters);var n=Ge[this.specification.type];return n?new bi(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Ti.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new bi(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new bi(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new bi(this,{kind:\"constant\",value:s},e)}return new bi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ti),Ai=function(t){this.specification=t};Ai.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new pi(Math.floor(e.zoom),e)),t.expression.evaluate(new pi(Math.floor(e.zoom+1),e)),e)}},Ai.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Ai.prototype.interpolate=function(t){return t};var Mi=function(t){this.specification=t};Mi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},Mi.prototype.interpolate=function(){return!1};var Si=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new di(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new mi(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};Nn(\"DataDrivenProperty\",Ti),Nn(\"DataConstantProperty\",wi),Nn(\"CrossFadedDataDrivenProperty\",ki),Nn(\"CrossFadedProperty\",Ai),Nn(\"ColorRampProperty\",Mi);var Ei=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},\"custom\"!==e.type&&(e=e,this.metadata=e.metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new xi(r.layout)),r.paint)){for(var n in this._transitionablePaint=new gi(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new _i(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate(In,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return g(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(Pn,n,t,e,r))return!1}if(g(t,\"-transition\"))return this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0),!1;var i=this._transitionablePaint._values[t],a=\"cross-faded-data-driven\"===i.property.specification[\"property-type\"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||(!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility)},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),y(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&On(this,t.call(Ln,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Lt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof bi&&zr(e.property.specification)&&((\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent))return!0}return!1},e}(Et),Li={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Ci=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Pi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ii(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Li[i].BYTES_PER_ELEMENT),o=r=Oi(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:Oi(r,Math.max(n,e)),alignment:e}}function Oi(t,e){return Math.ceil(t/e)*e}Pi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Pi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Pi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Pi.prototype.clear=function(){this.length=0},Pi.prototype.resize=function(t){this.reserve(t),this.length=t},Pi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Pi.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Pi);zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2i4\",zi);var Di=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t},e}(Pi);Di.prototype.bytesPerElement=8,Nn(\"StructArrayLayout4i8\",Di);var Ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);Ri.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i4i12\",Ri);var Fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Pi);Fi.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2i4ub8\",Fi);var Bi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l,c)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=c,this.uint8[h+17]=u,t},e}(Pi);Bi.prototype.bytesPerElement=18,Nn(\"StructArrayLayout8ui2ub18\",Bi);var Ni=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,c,u,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(Pi);Ni.prototype.bytesPerElement=24,Nn(\"StructArrayLayout4i4ui4i24\",Ni);var ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(Pi);ji.prototype.bytesPerElement=12,Nn(\"StructArrayLayout3f12\",ji);var Ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint32[r+0]=e,t},e}(Pi);Ui.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1ul4\",Ui);var Vi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c){var u=10*t,f=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=i,this.int16[u+4]=a,this.int16[u+5]=o,this.uint32[f+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t},e}(Pi);Vi.prototype.bytesPerElement=20,Nn(\"StructArrayLayout6i1ul2ui20\",Vi);var Hi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);Hi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i2i2i12\",Hi);var qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Pi);qi.prototype.bytesPerElement=16,Nn(\"StructArrayLayout2f1f2i16\",qi);var Gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Pi);Gi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2ub2f12\",Gi);var Yi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t},e}(Pi);Yi.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3ui6\",Yi);var Wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v){var y=24*t,x=12*t,b=48*t;return this.int16[y+0]=e,this.int16[y+1]=r,this.uint16[y+2]=n,this.uint16[y+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[y+10]=l,this.uint16[y+11]=c,this.uint16[y+12]=u,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=m,this.uint32[x+10]=g,this.int16[y+22]=v,t},e}(Pi);Wi.prototype.bytesPerElement=48,Nn(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",Wi);var Xi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,A,M,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=c,this.uint16[L+9]=u,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=m,this.uint16[L+15]=g,this.uint16[L+16]=v,this.uint16[L+17]=y,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=A,this.float32[C+14]=M,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Pi);Xi.prototype.bytesPerElement=68,Nn(\"StructArrayLayout8i15ui1ul4f68\",Xi);var Zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Pi);Zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1f4\",Zi);var Ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Pi);Ji.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3i6\",Ji);var Ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Pi);Ki.prototype.bytesPerElement=8,Nn(\"StructArrayLayout1ul2ui8\",Ki);var Qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(Pi);Qi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2ui4\",Qi);var $i=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint16[r+0]=e,t},e}(Pi);$i.prototype.bytesPerElement=2,Nn(\"StructArrayLayout1ui2\",$i);var ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Pi);ta.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2f8\",ta);var ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Pi);ea.prototype.bytesPerElement=16,Nn(\"StructArrayLayout4f16\",ea);var ra=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new i(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Ci);ra.prototype.size=20;var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ra(this,t)},e}(Vi);Nn(\"CollisionBoxArray\",na);var ia=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(Ci);ia.prototype.size=48;var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ia(this,t)},e}(Wi);Nn(\"PlacedSymbolArray\",aa);var oa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return 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c=t.readVarint();n=7&c,a=c>>3}if(a--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new i(o,s));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},ws.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,c=-1/0;t.pos<e;){if(n<=0){var u=t.readVarint();r=7&u,n=u>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>c&&(c=a);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,c]},ws.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),c=ws.types[this.type];function u(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];u(l=f);break;case 2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=ks(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}r&&i.push(r);return i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)u(l[n][i])}1===l.length?l=l[0]:c=\"Multi\"+c;var h={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var As=Ms;function Ms(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(Ss,this,e),this.length=this._features.length}function Ss(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){var e=null,r=t.readVarint()+t.pos;for(;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Es(t,e,r){if(3===t){var n=new As(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Ms.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new _s(this._pbf,e,this.extent,this._keys,this._values)};var Ls={VectorTile:function(t,e){this.layers=t.readFields(Es,{},e)},VectorTileFeature:_s,VectorTileLayer:As},Cs=Ls.VectorTileFeature.types,Ps=Math.pow(2,13);function Is(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*Ps)+o,i*Ps*2,a*Ps*2,Math.round(s))}var Os=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Ri,this.indexArray=new Yi,this.programConfigurations=new Ua(bs,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function zs(t,e){return t.x===e.x&&(t.x<0||t.x>8192)||t.y===e.y&&(t.y<0||t.y>8192)}function Ds(t){return t.every((function(t){return t.x<0}))||t.every((function(t){return t.x>8192}))||t.every((function(t){return t.y<0}))||t.every((function(t){return t.y>8192}))}Os.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=ds(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,c=a.sourceLayerIndex,u=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:u?Ya(o):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),f,r)){var h={id:s,sourceLayerIndex:c,index:l,geometry:u?f.geometry:Ya(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(ms(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,c,this.index,!0)}}},Os.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},Os.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Os.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Os.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Os.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,bs),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Os.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Os.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=hs(e,500);a<o.length;a+=1){for(var s=o[a],l=0,c=0,u=s;c<u.length;c+=1){l+=u[c].length}for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!Ds(d))for(var m=0,g=0;g<d.length;g++){var v=d[g];if(g>=1){var y=d[g-1];if(!zs(v,y)){f.vertexLength+4>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=v.sub(y)._perp()._unit(),b=y.dist(v);m+b>32768&&(m=0),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,0,m),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,1,m),m+=b,Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,m),Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,m);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===Cs[t.type]){for(var w=[],T=[],k=f.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];Is(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=Do(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Nn(\"FillExtrusionBucket\",Os,{omit:[\"layers\",\"features\"]});var Rs={paint:new Si({\"fill-extrusion-opacity\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new ki(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},Fs=function(t){function e(e){t.call(this,e,Rs)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new Os(t)},e.prototype.queryRadius=function(){return so(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,o,s,l){var c=lo(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),u=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),f=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),h=function(t,e,r,n){for(var a=[],o=0,s=t;o<s.length;o+=1){var l=s[o],c=[l.x,l.y,n,1];xo(c,c,e),a.push(new i(c[0]/c[3],c[1]/c[3]))}return a}(c,l,0,0),p=function(t,e,r,n){for(var a=[],o=[],s=n[8]*e,l=n[9]*e,c=n[10]*e,u=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,m=0,g=t;m<g.length;m+=1){for(var v=g[m],y=[],x=[],b=0,_=v;b<_.length;b+=1){var w=_[b],T=w.x,k=w.y,A=n[0]*T+n[4]*k+n[12],M=n[1]*T+n[5]*k+n[13],S=n[2]*T+n[6]*k+n[14],E=n[3]*T+n[7]*k+n[15],L=S+c,C=E+u,P=A+f,I=M+h,O=S+p,z=E+d,D=new i((A+s)/C,(M+l)/C);D.z=L/C,y.push(D);var R=new i(P/z,I/z);R.z=O/z,x.push(R)}a.push(y),o.push(x)}return[a,o]}(n,f,u,l);return function(t,e,r){var n=1/0;Ka(r,e)&&(n=Ns(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],c=a[s+1],u=o[s],f=o[s+1],h=[l,c,f,u,l];Za(r,h)&&(n=Math.min(n,Ns(r,h)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Ei);function Bs(t,e){return t.x*e.x+t.y*e.y}function Ns(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),c=o.sub(i),u=Bs(s,s),f=Bs(s,l),h=Bs(l,l),p=Bs(c,s),d=Bs(c,l),m=u*h-f*f,g=(h*p-f*d)/m,v=(u*d-f*p)/m,y=1-g-v,x=i.z*y+r.z*g+a.z*v;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var js=Ii([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,Us=Ls.VectorTileFeature.types,Vs=Math.cos(Math.PI/180*37.5),Hs=Math.pow(2,14)/.5,qs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Fi,this.indexArray=new Yi,this.programConfigurations=new Ua(js,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};qs.prototype.populate=function(t,e,r){this.hasPattern=ds(\"line\",this.layers,e);for(var n=this.layers[0].layout.get(\"line-sort-key\"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,c=s.id,u=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p={type:l.type,id:c,properties:l.properties,geometry:h?Ya(l):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),p,r)){h||(p.geometry=Ya(l));var d=n?n.evaluate(p,{},r):void 0,m={id:c,properties:l.properties,type:l.type,sourceLayerIndex:f,index:u,geometry:p.geometry,patterns:{},sortKey:d};i.push(m)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var g=0,v=i;g<v.length;g+=1){var y=v[g],x=y,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=ms(\"line\",this.layers,y,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(y,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},qs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},qs.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},qs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},qs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},qs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,js),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},qs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},qs.prototype.addFeature=function(t,e,r,n,i){for(var a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),c=a.get(\"line-round-limit\"),u=0,f=e;u<f.length;u+=1){var h=f[u];this.addLine(h,t,o,s,l,c)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},qs.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s=\"Polygon\"===Us[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var u,f=this.overscaling<=16?122880/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,m=void 0,g=void 0;this.e1=this.e2=-1,s&&(u=t[l-2],g=t[c].sub(u)._unit()._perp());for(var v=c;v<l;v++)if(!(d=v===l-1?s?t[c+1]:void 0:t[v+1])||!t[v].equals(d)){g&&(m=g),u&&(p=u),u=t[v],g=d?d.sub(u)._unit()._perp():m;var y=(m=m||g).add(g);0===y.x&&0===y.y||y._unit();var x=m.x*g.x+m.y*g.y,b=y.x*g.x+y.y*g.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<Vs&&p&&d,k=m.x*g.y-m.y*g.x>0;if(T&&v>c){var A=u.dist(p);if(A>2*f){var M=u.sub(u.sub(p)._mult(f/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,m,0,0,h),p=M}}var S=p&&d,E=S?r:s?\"butt\":n;if(S&&\"round\"===E&&(_<a?E=\"miter\":_<=2&&(E=\"fakeround\")),\"miter\"===E&&_>i&&(E=\"bevel\"),\"bevel\"===E&&(_>2&&(E=\"flipbevel\"),_<i&&(E=\"miter\")),p&&this.updateDistance(p,u),\"miter\"===E)y._mult(_),this.addCurrentVertex(u,y,0,0,h);else if(\"flipbevel\"===E){if(_>100)y=g.mult(-1);else{var L=_*m.add(g).mag()/m.sub(g).mag();y._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(u,y,0,0,h),this.addCurrentVertex(u,y.mult(-1),0,0,h)}else if(\"bevel\"===E||\"fakeround\"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,I=k?0:C;if(p&&this.addCurrentVertex(u,m,P,I,h),\"fakeround\"===E)for(var O=Math.round(180*w/Math.PI/20),z=1;z<O;z++){var D=z/O;if(.5!==D){var R=D-.5;D+=D*R*(D-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=g.sub(m)._mult(D)._add(m)._unit()._mult(k?-1:1);this.addHalfVertex(u,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(u,g,-P,-I,h)}else if(\"butt\"===E)this.addCurrentVertex(u,y,0,0,h);else if(\"square\"===E){var B=p?1:-1;this.addCurrentVertex(u,y,B,B,h)}else\"round\"===E&&(p&&(this.addCurrentVertex(u,m,0,0,h),this.addCurrentVertex(u,m,1,1,h,!0)),d&&(this.addCurrentVertex(u,g,-1,-1,h,!0),this.addCurrentVertex(u,g,0,0,h)));if(T&&v<l-1){var N=u.dist(d);if(N>2*f){var j=u.add(d.sub(u)._mult(f/N)._round());this.updateDistance(u,j),this.addCurrentVertex(j,g,0,0,h),u=j}}}}},qs.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var o=e.x+e.y*r,s=e.y-e.x*r,l=-e.x+e.y*n,c=-e.y-e.x*n;this.addHalfVertex(t,o,s,a,!1,r,i),this.addHalfVertex(t,l,c,a,!0,-n,i),this.distance>Hs/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},qs.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=t.x,l=t.y,c=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((s<<1)+(n?1:0),(l<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&c)<<2,c>>6);var u=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,u),o.primitiveLength++),i?this.e2=u:this.e1=u},qs.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(Hs-1):this.distance},qs.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},Nn(\"LineBucket\",qs,{omit:[\"layers\",\"patternFeatures\"]});var Gs=new Si({\"line-cap\":new 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e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new pi(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,i){return r=u({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,i)},e}(Ti))(Ys.paint.properties[\"line-width\"].specification);Ws.useIntegerZoom=!0;var Xs=function(t){function e(e){t.call(this,e,Ys)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){\"line-gradient\"===t&&this._updateGradient()},e.prototype._updateGradient=function(){var 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o=t[a],s=[],l=0;l<o.length;l++){var c=o[l-1],u=o[l],f=o[l+1],h=0===l?n:u.sub(c)._unit()._perp(),p=l===o.length-1?n:f.sub(u)._unit()._perp(),d=h._add(p)._unit(),m=d.x*p.x+d.y*p.y;d._mult(1/m),s.push(d._mult(e)._add(u))}r.push(s)}return r}(n,u*s)),function(t,e,r){for(var n=0;n<e.length;n++){var i=e[n];if(t.length>=3)for(var a=0;a<i.length;a++)if(io(t,i[a]))return!0;if(Qa(t,i,r))return!0}return!1}(l,n,c)},e.prototype.isTileClipped=function(){return!0},e}(Ei);function Zs(t,e){return e>0?e+2*t:t}var 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nl=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<<s)-1,c=l>>1,u=-7,f=r?i-1:0,h=r?-1:1,p=t[e+f];for(f+=h,a=p&(1<<-u)-1,p>>=-u,u+=s;u>0;a=256*a+t[e+f],f+=h,u-=8);for(o=a&(1<<-u)-1,a>>=-u,u+=n;u>0;o=256*o+t[e+f],f+=h,u-=8);if(0===a)a=1-c;else{if(a===l)return o?NaN:1/0*(p?-1:1);o+=Math.pow(2,n),a-=c}return(p?-1:1)*o*Math.pow(2,a-n)},il=function(t,e,r,n,i,a){var o,s,l,c=8*a-i-1,u=(1<<c)-1,f=u>>1,h=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,p=n?0:a-1,d=n?1:-1,m=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=u):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+f>=1?h/l:h*Math.pow(2,1-f))*l>=2&&(o++,l/=2),o+f>=u?(s=0,o=u):o+f>=1?(s=(e*l-1)*Math.pow(2,i),o+=f):(s=e*Math.pow(2,f-1)*Math.pow(2,i),o=0));i>=8;t[r+p]=255&s,p+=d,s/=256,i-=8);for(o=o<<i|s,c+=i;c>0;t[r+p]=255&o,p+=d,o/=256,c-=8);t[r+p-d]|=128*m},al=ol;function ol(t){this.buf=ArrayBuffer.isView&&ArrayBuffer.isView(t)?t:new 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e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed32());return t},readPackedFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readFixed64());return t},readPackedSFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readSFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed64());return t},skip:function(t){var e=7&t;if(e===ol.Varint)for(;this.buf[this.pos++]>127;);else if(e===ol.Bytes)this.pos=this.readVarint()+this.pos;else if(e===ol.Fixed32)this.pos+=4;else{if(e!==ol.Fixed64)throw new Error(\"Unimplemented type: \"+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e<this.pos+t;)e*=2;if(e!==this.length){var r=new Uint8Array(e);r.set(this.buf),this.buf=r,this.length=e}},finish:function(){return 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r=(7&t)<<4;if(e.buf[e.pos++]|=r|((t>>>=3)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;e.buf[e.pos++]=127&t}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(Boolean(t))},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&ul(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),il(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),il(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&ul(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,ol.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,fl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,hl,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,ml,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,pl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,dl,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,gl,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,vl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,yl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,xl,e)},writeBytesField:function(t,e){this.writeTag(t,ol.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,ol.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,ol.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};function Tl(t,e,r){1===t&&r.readMessage(kl,e)}function kl(t,e,r){if(3===t){var n=r.readMessage(Al,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,c=n.top,u=n.advance;e.push({id:i,bitmap:new So({width:o+6,height:s+6},a),metrics:{width:o,height:s,left:l,top:c,advance:u}})}}function Al(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}function Ml(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,c=0,u=t;c<u.length;c+=1)for(var f=u[c],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else 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Eo({width:o||1,height:s||1});for(var c in t){var u=t[c],f=r[c].paddedRect;Eo.copy(u.data,l,{x:0,y:0},{x:f.x+1,y:f.y+1},u.data)}for(var h in e){var p=e[h],d=n[h].paddedRect,m=d.x+1,g=d.y+1,v=p.data.width,y=p.data.height;Eo.copy(p.data,l,{x:0,y:0},{x:m,y:g},p.data),Eo.copy(p.data,l,{x:0,y:y-1},{x:m,y:g-1},{width:v,height:1}),Eo.copy(p.data,l,{x:0,y:0},{x:m,y:g+y},{width:v,height:1}),Eo.copy(p.data,l,{x:v-1,y:0},{x:m-1,y:g},{width:1,height:y}),Eo.copy(p.data,l,{x:0,y:0},{x:m+v,y:g},{width:1,height:y})}this.image=l,this.iconPositions=r,this.patternPositions=n};Ll.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2,h:i.data.height+2};r.push(a),e[n]=new Sl(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},Ll.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},Ll.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},Nn(\"ImagePosition\",Sl),Nn(\"ImageAtlas\",Ll);var Cl={horizontal:1,vertical:2,horizontalOnly:3};var Pl=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};Pl.forText=function(t,e){var r=new Pl;return r.scale=t||1,r.fontStack=e,r},Pl.forImage=function(t){var e=new Pl;return e.imageName=t,e};var Il=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function Ol(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m){var g,v=Il.fromFeature(t,i);f===Cl.vertical&&v.verticalizePunctuation();var y=hi.processBidirectionalText,x=hi.processStyledBidirectionalText;if(y&&1===v.sections.length){g=[];for(var b=0,_=y(v.toString(),jl(v,c,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new Il;T.text=w,T.sections=v.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);g.push(T)}}else if(x){g=[];for(var A=0,M=x(v.text,v.sectionIndex,jl(v,c,a,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new Il;E.text=S[0],E.sectionIndex=S[1],E.sections=v.sections,g.push(E)}}else g=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(v,jl(v,c,a,e,n,p,d));var L=[],C={positionedLines:L,text:v.toString(),top:u[1],bottom:u[1],left:u[0],right:u[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=0,p=-17,d=0,m=0,g=\"right\"===s?1:\"left\"===s?0:.5,v=0,y=0,x=i;y<x.length;y+=1){var b=x[y];b.trim();var _=b.getMaxScale(),w=24*(_-1),T={positionedGlyphs:[],lineOffset:0};t.positionedLines[v]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),L=b.getCharCode(M),C=0,P=null,I=null,O=null,z=24,D=!(l===Cl.horizontal||!u&&!Zn(L)||u&&(zl[L]||(Y=L,Yn.Arabic(Y)||Yn[\"Arabic Supplement\"](Y)||Yn[\"Arabic Extended-A\"](Y)||Yn[\"Arabic Presentation Forms-A\"](Y)||Yn[\"Arabic Presentation Forms-B\"](Y))));if(S.imageName){var R=n[S.imageName];if(!R)continue;O=S.imageName,t.iconsInText=t.iconsInText||!0,I=R.paddedRect;var F=R.displaySize;S.scale=24*S.scale/f,P={width:F[0],height:F[1],left:1,top:-3,advance:D?F[1]:F[0]};var B=24-F[1]*S.scale;C=w+B,z=P.advance;var N=D?F[0]*S.scale-24*_:F[1]*S.scale-24*_;N>0&&N>A&&(A=N)}else{var j=r[S.fontStack],U=j&&j[L];if(U&&U.rect)I=U.rect,P=U.metrics;else{var V=e[S.fontStack],H=V&&V[L];if(!H)continue;P=H.metrics}C=24*(_-S.scale)}D?(t.verticalizable=!0,k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=z*S.scale+c):(k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=P.advance*S.scale+c)}if(0!==k.length){var q=h-c;d=Math.max(q,d),Vl(k,0,k.length-1,g,A)}h=0;var G=a*_+A;T.lineOffset=Math.max(A,w),p+=G,m=Math.max(G,m),++v}else p+=a,++v}var Y;var W=p- -17,X=Ul(o),Z=X.horizontalAlign,J=X.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var c=(e-r)*i,u=0;u=a!==o?-s*n- -17:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=h[f],d=0,m=p.positionedGlyphs;d<m.length;d+=1){var g=m[d];g.x+=c,g.y+=u}})(t.positionedLines,g,Z,J,d,m,a,W,i.length),t.top+=-J*W,t.bottom=t.top+W,t.left+=-Z*d,t.right=t.left+d}(C,e,r,n,g,o,s,l,f,c,h,m),!function(t){for(var e=0,r=t;e<r.length;e+=1){if(0!==r[e].positionedGlyphs.length)return!1}return!0}(L)&&C}Il.fromFeature=function(t,e){for(var r=new Il,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},Il.prototype.length=function(){return this.text.length},Il.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},Il.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},Il.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},Il.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;(!n||!Jn(n)||rl[t[r+1]])&&(!i||!Jn(i)||rl[t[r-1]])&&rl[t[r]]?e+=rl[t[r]]:e+=t[r]}return e}(this.text)},Il.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&zl[this.text.charCodeAt(e)];e++)t++;for(var 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e=this.data,r=this.compare,n=this.length>>1,i=e[t];t<n;){var a=1+(t<<1),o=e[a],s=a+1;if(s<this.length&&r(e[s],o)<0&&(a=s,o=e[s]),r(o,i)>=0)break;e[t]=o,t=a}e[t]=i};var pc=Number.POSITIVE_INFINITY;function dc(t,e){return e[1]!==pc?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case\"top-right\":case\"top-left\":case\"top\":i=r-7;break;case\"bottom-right\":case\"bottom-left\":case\"bottom\":i=7-r}switch(t){case\"top-right\":case\"bottom-right\":case\"right\":n=-e;break;case\"top-left\":case\"bottom-left\":case\"left\":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=i-7;break;case\"bottom-right\":case\"bottom-left\":n=7-i;break;case\"bottom\":n=7-e;break;case\"top\":n=e-7}switch(t){case\"top-right\":case\"bottom-right\":r=-i;break;case\"top-left\":case\"bottom-left\":r=i;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}(t,e[0])}function mc(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}function gc(t,e,r,n,a,o,s,l,c,u,f,h,p,d,m){var g=function(t,e,r,n,a,o,s,l){for(var c=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,u=[],f=0,h=e.positionedLines;f<h.length;f+=1)for(var p=h[f],d=0,m=p.positionedGlyphs;d<m.length;d+=1){var g=m[d];if(g.rect){var v=g.rect||{},y=4,x=!0,b=1,_=0,w=(a||l)&&g.vertical,T=g.metrics.advance*g.scale/2;if(l&&e.verticalizable){var k=24*(g.scale-1),A=(24-g.metrics.width*g.scale)/2;_=p.lineOffset/2-(g.imageName?-A:k)}if(g.imageName){var M=s[g.imageName];x=M.sdf,y=1/(b=M.pixelRatio)}var S=a?[g.x+T,g.y]:[0,0],E=a?[0,0]:[g.x+T+r[0],g.y+r[1]-_],L=[0,0];w&&(L=E,E=[0,0]);var C=(g.metrics.left-y)*g.scale-T+E[0],P=(-g.metrics.top-y)*g.scale+E[1],I=C+v.w*g.scale/b,O=P+v.h*g.scale/b,z=new i(C,P),D=new i(I,P),R=new i(C,O),F=new i(I,O);if(w){var B=new i(-T,T- -17),N=-Math.PI/2,j=12-T,U=g.imageName?j:0,V=new i(22-j,-U),H=new(Function.prototype.bind.apply(i,[null].concat(L)));z._rotateAround(N,B)._add(V)._add(H),D._rotateAround(N,B)._add(V)._add(H),R._rotateAround(N,B)._add(V)._add(H),F._rotateAround(N,B)._add(V)._add(H)}if(c){var q=Math.sin(c),G=Math.cos(c),Y=[G,-q,q,G];z._matMult(Y),D._matMult(Y),R._matMult(Y),F._matMult(Y)}var W=new i(0,0),X=new i(0,0);u.push({tl:z,tr:D,bl:R,br:F,tex:v,writingMode:e.writingMode,glyphOffset:S,sectionIndex:g.sectionIndex,isSDF:x,pixelOffsetTL:W,pixelOffsetBR:X,minFontScaleX:0,minFontScaleY:0})}}return u}(0,r,l,a,o,s,n,t.allowVerticalPlacement),v=t.textSizeData,y=null;\"source\"===v.kind?(y=[128*a.layout.get(\"text-size\").evaluate(s,{})])[0]>32640&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'):\"composite\"===v.kind&&((y=[128*d.compositeTextSizes[0].evaluate(s,{},m),128*d.compositeTextSizes[1].evaluate(s,{},m)])[0]>32640||y[1]>32640)&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'),t.addSymbols(t.text,g,y,l,o,s,u,e,c.lineStartIndex,c.lineLength,p,m);for(var x=0,b=f;x<b.length;x+=1){h[b[x]]=t.text.placedSymbolArray.length-1}return 4*g.length}function vc(t){for(var e in t)return t[e];return null}function yc(t,e,r,n){var i=t.compareText;if(e in i){for(var a=i[e],o=a.length-1;o>=0;o--)if(n.dist(a[o])<r)return!0}else i[e]=[];return i[e].push(n),!1}var xc=Ls.VectorTileFeature.types,bc=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function _c(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=s?Math.min(32640,Math.round(s[0])):0,d=s?Math.min(32640,Math.round(s[1])):0;t.emplaceBack(e,r,Math.round(32*n),Math.round(32*i),a,o,(p<<1)+(l?1:0),d,16*c,16*u,256*f,256*h)}function wc(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}function Tc(t){for(var e=0,r=t.sections;e<r.length;e+=1){if($n(r[e].text))return!0}return!1}var kc=function(t){this.layoutVertexArray=new Ni,this.indexArray=new Yi,this.programConfigurations=t,this.segments=new pa,this.dynamicLayoutVertexArray=new ji,this.opacityVertexArray=new Ui,this.placedSymbolArray=new aa};kc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},kc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Js.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Ks.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,bc,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},kc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},Nn(\"SymbolBuffers\",kc);var Ac=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new pa,this.collisionVertexArray=new Gi};Ac.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,Qs.members,!0)},Ac.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},Nn(\"CollisionBuffers\",Ac);var Mc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=ho([]),this.placementViewportMatrix=ho([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Gl(this.zoom,e[\"text-size\"]),this.iconSizeData=Gl(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1);var a=\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return Cl[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};Mc.prototype.createArrays=function(){this.text=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new la,this.lineVertexArray=new ca,this.symbolInstances=new sa},Mc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=rl[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},Mc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof ne&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),c=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=i.get(\"symbol-sort-key\");if(this.features=[],l||c){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new pi(this.zoom),m=0,g=t;m<g.length;m+=1){var v=g[m],y=v.feature,x=v.id,b=v.index,_=v.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:y.type,id:x,properties:y.properties,geometry:w?Ya(y):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=Ya(y));var k=void 0;if(l){var A=n.getValueAndResolveTokens(\"text-field\",T,r,p),M=ne.factory(A);Tc(M)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===ui()||this.hasRTLText&&hi.isParsed())&&(k=el(M,n,T))}var S=void 0;if(c){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof ie?E:ie.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?u.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:Ya(y),properties:y.properties,type:xc[y.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(\",\"),I=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(Cl.vertical)>=0;for(var O=0,z=k.sections;O<z.length;O+=1){var D=z[O];if(D.image)f[D.image.name]=!0;else{var R=Wn(k.toString()),F=D.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(D.text,B,I,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],f=u.geometry,h=u.text?u.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var m=s(p,d,f),g=o(p,d,n[m].geometry);delete e[p],delete r[d],r[l(h,n[g].geometry,!0)]=g,n[m].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(c),e[p]=i-1,r[d]=i-1)}else a(c)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},Mc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},Mc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},Mc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},Mc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},Mc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},Mc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},Mc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=a[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},Mc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),m=this.glyphOffsetArray.length,g=d.vertexLength,v=this.allowVerticalPlacement&&o===Cl.vertical?Math.PI/2:0,y=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,I=b.sectionIndex,O=d.vertexLength,z=C[1];_c(p,s.x,s.y,_.x,z+_.y,A.x,A.y,r,P,M.x,M.y,E,L),_c(p,s.x,s.y,w.x,z+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,L),_c(p,s.x,s.y,T.x,z+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,L),_c(p,s.x,s.y,k.x,z+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,L),wc(t.dynamicLayoutVertexArray,s,v),h.emplaceBack(O,O+1,O+2),h.emplaceBack(O+1,O+2,O+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&I===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,y&&y[I])}t.placedSymbolArray.emplaceBack(s.x,s.y,m,this.glyphOffsetArray.length-m,g,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,u)},Mc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},Mc.prototype.addCollisionDebugVertices=function(t,e,r,n,a,o,s){var l=a.segments.prepareSegment(4,a.layoutVertexArray,a.indexArray),c=l.vertexLength,u=a.layoutVertexArray,f=a.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(u,f,o,h,p,new i(t,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,n)),this._addCollisionDebugVertex(u,f,o,h,p,new i(t,n)),l.vertexLength+=4;var d=a.indexArray;d.emplaceBack(c,c+1),d.emplaceBack(c+1,c+2),d.emplaceBack(c+2,c+3),d.emplaceBack(c+3,c),l.primitiveLength+=4},Mc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,c=a.y2;this.addCollisionDebugVertices(o,s,l,c,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},Mc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new Ac(Hi,$s.members,Qi),this.iconCollisionBox=new Ac(Hi,$s.members,Qi);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},Mc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var c={},u=e;u<r;u++){var f=t.get(u);c.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},c.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);c.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},c.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var m=t.get(d);c.iconBox={x1:m.x1,y1:m.y1,x2:m.x2,y2:m.y2,anchorPointX:m.anchorPointX,anchorPointY:m.anchorPointY},c.iconFeatureIndex=m.featureIndex;break}for(var g=s;g<l;g++){var v=t.get(g);c.verticalIconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},c.verticalIconFeatureIndex=v.featureIndex;break}return c},Mc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},Mc.prototype.hasTextData=function(){return this.text.segments.get().length>0},Mc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},Mc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},Mc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},Mc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},Mc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},Mc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},Mc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},Mc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},Nn(\"SymbolBucket\",Mc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),Mc.MAX_GLYPHS=65535,Mc.addDynamicAttributes=wc;var Sc=new Si({\"symbol-placement\":new wi(Lt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new wi(Lt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new wi(Lt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Ti(Lt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new wi(Lt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new wi(Lt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new wi(Lt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new wi(Lt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new wi(Lt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Ti(Lt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new wi(Lt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new wi(Lt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Ti(Lt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Ti(Lt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new wi(Lt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new wi(Lt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Ti(Lt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Ti(Lt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new wi(Lt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new wi(Lt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new wi(Lt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Ti(Lt.layout_symbol[\"text-field\"]),\"text-font\":new Ti(Lt.layout_symbol[\"text-font\"]),\"text-size\":new Ti(Lt.layout_symbol[\"text-size\"]),\"text-max-width\":new Ti(Lt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new wi(Lt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Ti(Lt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Ti(Lt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Ti(Lt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new wi(Lt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Ti(Lt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new wi(Lt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new wi(Lt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Ti(Lt.layout_symbol[\"text-rotate\"]),\"text-padding\":new wi(Lt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new wi(Lt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Ti(Lt.layout_symbol[\"text-transform\"]),\"text-offset\":new Ti(Lt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new wi(Lt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new wi(Lt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new wi(Lt.layout_symbol[\"text-optional\"])}),Ec={paint:new Si({\"icon-opacity\":new Ti(Lt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Ti(Lt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Ti(Lt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Ti(Lt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Ti(Lt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new wi(Lt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new wi(Lt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Ti(Lt.paint_symbol[\"text-opacity\"]),\"text-color\":new Ti(Lt.paint_symbol[\"text-color\"],{runtimeType:Ut,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Ti(Lt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Ti(Lt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Ti(Lt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new wi(Lt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new wi(Lt.paint_symbol[\"text-translate-anchor\"])}),layout:Sc},Lc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Ft,this.defaultValue=t};Lc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},Lc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},Lc.prototype.outputDefined=function(){return!1},Lc.prototype.serialize=function(){return null},Nn(\"FormatSectionOverride\",Lc,{omit:[\"defaultValue\"]});var Cc=function(t){function e(e){t.call(this,e,Ec)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||Yr(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new Mc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=Ec.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i=this.paint.get(n),a=new Lc(i),o=new Gr(a,i.property.specification),s=null;s=\"constant\"===i.value.kind||\"source\"===i.value.kind?new Xr(\"source\",o):new Zr(\"composite\",o,i.value.zoomStops,i.value._interpolationType),this.paint._values[n]=new bi(i.property,s,i.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=Ec.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof ne)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!i)if(t instanceof ce&&se(t.value)===Gt){var e=t.value;a(e.sections)}else t instanceof pe?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Ei),Pc={paint:new Si({\"background-color\":new wi(Lt.paint_background[\"background-color\"]),\"background-pattern\":new Ai(Lt.paint_background[\"background-pattern\"]),\"background-opacity\":new wi(Lt.paint_background[\"background-opacity\"])})},Ic=function(t){function e(e){t.call(this,e,Pc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei),Oc={paint:new Si({\"raster-opacity\":new wi(Lt.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new wi(Lt.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new wi(Lt.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new wi(Lt.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new wi(Lt.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new wi(Lt.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new wi(Lt.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new wi(Lt.paint_raster[\"raster-fade-duration\"])})},zc=function(t){function e(e){t.call(this,e,Oc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei);var Dc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Ei),Rc={circle:_o,heatmap:Po,hillshade:Oo,fill:xs,\"fill-extrusion\":Fs,line:Xs,symbol:Cc,background:Ic,raster:zc};var Fc=self.HTMLImageElement,Bc=self.HTMLCanvasElement,Nc=self.HTMLVideoElement,jc=self.ImageData,Uc=self.ImageBitmap,Vc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Vc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Vc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Vc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Vc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var Hc=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};Hc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},Hc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var qc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},m([\"receive\",\"process\"],this),this.invoker=new Hc(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=k()?t:self};function Gc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}qc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=S(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:Hn(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},qc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else k()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},qc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},qc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(qn(e.error)):n(null,qn(e.data)))}else{var i=!1,a=S(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?Hn(e):null,data:Hn(n,a)},a)}:function(t){i=!0},s=null,l=qn(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},qc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Yc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Yc.prototype.setNorthEast=function(t){return this._ne=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.setSouthWest=function(t){return this._sw=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Wc)e=t,r=t;else{if(!(t instanceof Yc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Yc.convert(a))}var o=t;return this.extend(Wc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Wc(e.lng,e.lat),this._ne=new Wc(r.lng,r.lat)),this},Yc.prototype.getCenter=function(){return new Wc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Yc.prototype.getSouthWest=function(){return this._sw},Yc.prototype.getNorthEast=function(){return this._ne},Yc.prototype.getNorthWest=function(){return new Wc(this.getWest(),this.getNorth())},Yc.prototype.getSouthEast=function(){return new Wc(this.getEast(),this.getSouth())},Yc.prototype.getWest=function(){return this._sw.lng},Yc.prototype.getSouth=function(){return this._sw.lat},Yc.prototype.getEast=function(){return this._ne.lng},Yc.prototype.getNorth=function(){return this._ne.lat},Yc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Yc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Yc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Yc.prototype.contains=function(t){var e=Wc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Yc.convert=function(t){return!t||t instanceof Yc?t:new Yc(t)};var Wc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Wc.prototype.wrap=function(){return new Wc(c(this.lng,-180,180),this.lat)},Wc.prototype.toArray=function(){return[this.lng,this.lat]},Wc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Wc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return 6371008.8*Math.acos(Math.min(i,1))},Wc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Yc(new Wc(this.lng-r,this.lat-e),new Wc(this.lng+r,this.lat+e))},Wc.convert=function(t){if(t instanceof Wc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Wc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Wc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Xc=2*Math.PI*6371008.8;function Zc(t){return Xc*Math.cos(t*Math.PI/180)}function Jc(t){return(180+t)/360}function Kc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Qc(t,e){return t/Zc(e)}function $c(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var tu=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};tu.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Wc.convert(t);return new tu(Jc(r.lng),Kc(r.lat),Qc(e,r.lat))},tu.prototype.toLngLat=function(){return new Wc(360*this.x-180,$c(this.y))},tu.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Zc($c(e));var t,e},tu.prototype.meterInMercatorCoordinateUnits=function(){return 1/Xc*(t=$c(this.y),1/Math.cos(t*Math.PI/180));var t};var eu=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=iu(0,t,t,e,r)};eu.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},eu.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Gc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Gc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},eu.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new i(8192*(t.x*e-this.x),8192*(t.y*e-this.y))},eu.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var ru=function(t,e){this.wrap=t,this.canonical=e,this.key=iu(t,e.z,e.z,e.x,e.y)},nu=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new eu(r,+n,+i),this.key=iu(e,t,r,n,i)};function iu(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}nu.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},nu.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new nu(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new nu(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},nu.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?iu(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):iu(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},nu.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},nu.prototype.children=function(t){if(this.overscaledZ>=t)return[new nu(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new nu(e,this.wrap,e,r,n),new nu(e,this.wrap,e,r+1,n),new nu(e,this.wrap,e,r,n+1),new nu(e,this.wrap,e,r+1,n+1)]},nu.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},nu.prototype.wrapped=function(){return new nu(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.unwrapTo=function(t){return new nu(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},nu.prototype.toUnwrapped=function(){return new ru(this.wrap,this.canonical)},nu.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},nu.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new tu(t.x-this.wrap,t.y))},Nn(\"CanonicalTileID\",eu),Nn(\"OverscaledTileID\",nu,{omit:[\"posMatrix\"]});var au=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return _('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};au.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},au.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},au.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},au.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},au.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},au.prototype.getPixels=function(){return new Eo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},au.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,c=a;c<o;c++)for(var u=n;u<i;u++)this.data[this._idx(u,c)]=t.data[this._idx(u+s,c+l)]},Nn(\"DEMData\",au);var ou=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};ou.prototype.encode=function(t){return this._stringToNumber[t]},ou.prototype.decode=function(t){return this._numberToString[t]};var su=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},lu={geometry:{configurable:!0}};lu.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},lu.geometry.set=function(t){this._geometry=t},su.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(su.prototype,lu);var cu=function(){this.state={},this.stateChanges={},this.deletedStates={}};cu.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},u(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r){this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]}},cu.prototype.removeFeatureState=function(t,e,r){if(!(null===this.deletedStates[t])){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e){if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null}else this.deletedStates[t]=null}},cu.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=u({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},cu.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},cu.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),u(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var f=0,h=Object.keys(this.deletedStates[o][c]);f<h.length;f+=1){var p=h[f];delete this.state[o][c][p]}s[c]=this.state[o][c]}r[o]=r[o]||{},u(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t){t[d].setFeatureState(r,e)}};var uu=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new zn(8192,16,0),this.grid3D=new zn(8192,16,0),this.featureIndexArray=new fa,this.promoteId=e};function fu(t,e,r,n,i){return v(t,(function(t,a){var o=e instanceof _i?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function hu(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function pu(t,e){return e-t}uu.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],f=0;f<c.length;f++){var h=c[f];u[0]=Math.min(u[0],h.x),u[1]=Math.min(u[1],h.y),u[2]=Math.max(u[2],h.x),u[3]=Math.max(u[3],h.y)}u[0]<8192&&u[1]<8192&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},uu.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Ls.VectorTile(new al(this.rawTileData)).layers,this.sourceLayerCoder=new ou(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},uu.prototype.query=function(t,e,r,n){var a=this;this.loadVTLayers();for(var o=t.params||{},s=8192/t.tileSize/t.scale,l=sn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,f=hu(c),h=this.grid.query(f.minX-u,f.minY-u,f.maxX+u,f.maxY+u),p=hu(t.cameraQueryGeometry),d=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,a){return function(t,e,r,n,a){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&a>=l.y)return!0}var c=[new i(e,r),new i(e,a),new i(n,a),new i(n,r)];if(t.length>2)for(var u=0,f=c;u<f.length;u+=1){if(io(t,f[u]))return!0}for(var h=0;h<t.length-1;h++){if(ao(t[h],t[h+1],c))return!0}return!1}(t.cameraQueryGeometry,e-u,r-u,n+u,a+u)})),m=0,g=d;m<g.length;m+=1){var v=g[m];h.push(v)}h.sort(pu);for(var y,x={},b=function(i){var u=h[i];if(u!==y){y=u;var f=a.featureIndexArray.get(u),p=null;a.loadMatchingFeature(x,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=Ya(e)),r.queryIntersectsFeature(c,e,n,p,a.z,t.transform,s,t.pixelPosMatrix)}))}},_=0;_<h.length;_++)b(_);return x},uu.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,c,u){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),m=0;m<f.length;m++){var g=f[m];if(!(a&&a.indexOf(g)<0)){var v=s[g];if(v){var y={};void 0!==d&&c&&(y=c.getState(v.sourceLayer||\"_geojsonTileLayer\",d));var x=l[g];x.paint=fu(x.paint,v.paint,p,y,o),x.layout=fu(x.layout,v.layout,p,y,o);var b=!u||u(p,v,y);if(b){var _=new su(p,this.z,this.x,this.y,d);_.layer=x;var w=t[g];void 0===w&&(w=t[g]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},uu.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var c=sn(i),u=0,f=t;u<f.length;u+=1){var h=f[u];this.loadMatchingFeature(l,r,n,h,c,a,o,s,e)}return l},uu.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1){if(t===i[n])return!0}return!1},uu.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n=\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e];\"boolean\"==typeof(r=t.properties[n])&&(r=Number(r))}return r},Nn(\"FeatureIndex\",uu,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var du=function(t,e){this.tileID=t,this.uid=h(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};du.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<R.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},du.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},du.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof Mc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof Mc&&o.hasRTLText){this.hasRTLText=!0,hi.isLoading()||hi.isLoaded()||\"deferred\"!==ui()||fi();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new na},du.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},du.prototype.getBucket=function(t){return this.buckets[t.id]},du.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Vc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Vc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},du.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},du.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},du.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=sn(e&&e.filter),s=this.tileID.canonical,l=s.z,c=s.x,u=s.y,f={z:l,x:c,y:u},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new pi(this.tileID.overscaledZ),p)){var d=r.getId(p,i),m=new su(p,l,c,u,d);m.tile=f,t.push(m)}}}},du.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},du.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},du.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=A(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},du.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},du.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},du.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},du.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<R.now()},du.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},du.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=R.now()+t},du.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){r[i[n]]=!0}this.dependencies[t]=r},du.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1){if(a[s[o]])return!0}}return!1};var 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r},t.makeRequest=yt,t.mapObject=v,t.mercatorXfromLng=Jc,t.mercatorYfromLat=Kc,t.mercatorZfromAltitude=Qc,t.mul=mo,t.multiply=po,t.mvt=Ls,t.normalize=function(t,e){var r=e[0],n=e[1],i=e[2],a=r*r+n*n+i*i;return a>0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t},t.number=qe,t.offscreenCanvasSupported=pt,t.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t},t.parseGlyphPBF=function(t){return new al(t).readFields(Tl,[])},t.pbf=al,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=8192/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,c=t.layers[0]._unevaluatedLayout._values,u={};if(\"composite\"===t.textSizeData.kind){var f=t.textSizeData,h=f.minZoom,p=f.maxZoom;u.compositeTextSizes=[c[\"text-size\"].possiblyEvaluate(new 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g=(c+1)%2;(0===c?r-i<=d:n-i<=m)&&(o.push(f),o.push(p-1),o.push(g)),(0===c?r+i>=d:n+i>=m)&&(o.push(p+1),o.push(u),o.push(g))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var j={minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(t){return t}},U=function(t){this.options=X(Object.create(j),t),this.trees=new Array(this.options.maxZoom+1)};function V(t,e,r,n,i){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:i}}function H(t,e){var r=t.geometry.coordinates,n=r[0],i=r[1];return{x:Y(n),y:W(i),zoom:1/0,index:e,parentId:-1}}function q(t){return{type:\"Feature\",id:t.id,properties:G(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function G(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return 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r=0;r<e.length;r+=3)t.minX=Math.min(t.minX,e[r]),t.minY=Math.min(t.minY,e[r+1]),t.maxX=Math.max(t.maxX,e[r]),t.maxY=Math.max(t.maxY,e[r+1])}function tt(t,e,r,n){if(e.geometry){var i=e.geometry.coordinates,a=e.geometry.type,o=Math.pow(r.tolerance/((1<<r.maxZoom)*r.extent),2),s=[],l=e.id;if(r.promoteId?l=e.properties[r.promoteId]:r.generateId&&(l=n||0),\"Point\"===a)et(i,s);else if(\"MultiPoint\"===a)for(var c=0;c<i.length;c++)et(i[c],s);else if(\"LineString\"===a)rt(i,s,o,!1);else if(\"MultiLineString\"===a){if(r.lineMetrics){for(c=0;c<i.length;c++)s=[],rt(i[c],s,o,!1),t.push(Q(l,\"LineString\",s,e.properties));return}nt(i,s,o,!1)}else if(\"Polygon\"===a)nt(i,s,o,!0);else{if(\"MultiPolygon\"!==a){if(\"GeometryCollection\"===a){for(c=0;c<e.geometry.geometries.length;c++)tt(t,{id:l,geometry:e.geometry.geometries[c],properties:e.properties},r,n);return}throw new Error(\"Input data is not a valid GeoJSON object.\")}for(c=0;c<i.length;c++){var 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u=t[c],f=u.geometry,h=u.type,p=0===i?u.minX:u.minY,d=0===i?u.maxX:u.maxY;if(p>=r&&d<n)l.push(u);else if(!(d<r||p>=n)){var m=[];if(\"Point\"===h||\"MultiPoint\"===h)st(f,m,r,n,i);else if(\"LineString\"===h)lt(f,m,r,n,i,!1,s.lineMetrics);else if(\"MultiLineString\"===h)ut(f,m,r,n,i,!1);else if(\"Polygon\"===h)ut(f,m,r,n,i,!0);else if(\"MultiPolygon\"===h)for(var g=0;g<f.length;g++){var v=[];ut(f[g],v,r,n,i,!0),v.length&&m.push(v)}if(m.length){if(s.lineMetrics&&\"LineString\"===h){for(g=0;g<m.length;g++)l.push(Q(u.id,h,m[g],u.tags));continue}\"LineString\"!==h&&\"MultiLineString\"!==h||(1===m.length?(h=\"LineString\",m=m[0]):h=\"MultiLineString\"),\"Point\"!==h&&\"MultiPoint\"!==h||(h=3===m.length?\"Point\":\"MultiPoint\"),l.push(Q(u.id,h,m,u.tags))}}}return l.length?l:null}function st(t,e,r,n,i){for(var a=0;a<t.length;a+=3){var o=t[a+i];o>=r&&o<=n&&(e.push(t[a]),e.push(t[a+1]),e.push(t[a+2]))}}function lt(t,e,r,n,i,a,o){for(var 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r=[],n=0;n<t.length;n++){var i,a=t[n],o=a.type;if(\"Point\"===o||\"MultiPoint\"===o||\"LineString\"===o)i=mt(a.geometry,e);else if(\"MultiLineString\"===o||\"Polygon\"===o){i=[];for(var s=0;s<a.geometry.length;s++)i.push(mt(a.geometry[s],e))}else if(\"MultiPolygon\"===o)for(i=[],s=0;s<a.geometry.length;s++){for(var l=[],c=0;c<a.geometry[s].length;c++)l.push(mt(a.geometry[s][c],e));i.push(l)}r.push(Q(a.id,o,i,a.tags))}return r}function mt(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function gt(t,e){if(t.transformed)return t;var r,n,i,a=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(vt(c[n],c[n+1],e,a,o,s));else for(n=0;n<c.length;n++){var f=[];for(i=0;i<c[n].length;i+=2)f.push(vt(c[n][i],c[n][i+1],e,a,o,s));l.geometry.push(f)}}return t.transformed=!0,t}function 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u={},e.tags)u[f]=e.tags[f];u.mapbox_clip_start=i.start/i.size,u.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:u};null!==e.id&&(h.id=e.id),t.features.push(h)}}function bt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function _t(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)tt(r,t.features[n],e,n);else\"Feature\"===t.type?tt(r,t,e):tt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=ot(t,1,-1-r,r,0,-1,2,e),a=ot(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=ot(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=dt(i,1).concat(n)),a&&(n=n.concat(dt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function wt(t,e,r){return 32*((1<<t)*r+e)+t}function Tt(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}U.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(H(t[l],l));this.trees[i+1]=new N(s,Z,J,a,Float32Array),r&&console.timeEnd(o);for(var c=i;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new N(s,Z,J,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",c,s.length,+Date.now()-u)}return r&&console.timeEnd(\"total time\"),this},U.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,f=l.range(Y(r),W(a),Y(i),W(n));u<f.length;u+=1){var h=f[u],p=l.points[h];c.push(p.numPoints?q(p):this.points[p.index])}return c},U.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=i.within(a.x,a.y,o);l<c.length;l+=1){var u=c[l],f=i.points[u];f.parentId===t&&s.push(f.numPoints?q(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},U.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},U.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,c=(r+1+s)/i,u={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,c),n.points,e,r,i,u),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,c),n.points,i,r,i,u),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,c),n.points,-1,r,i,u),u.features.length?u:null},U.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},U.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},U.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c=l.numPoints,u={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:c?G(l):this.points[l.index].properties},f=void 0;c?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(u.id=f),a.features.push(u)}},U.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},U.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=i/(a*Math.pow(2,e)),l=0;l<t.length;l++){var c=t[l];if(!(c.zoom<=e)){c.zoom=e;for(var u=this.trees[e+1],f=u.within(c.x,c.y,s),h=c.numPoints||1,p=c.x*h,d=c.y*h,m=o&&h>1?this._map(c,!0):null,g=(l<<5)+(e+1)+this.points.length,v=0,y=f;v<y.length;v+=1){var x=y[v],b=u.points[x];if(!(b.zoom<=e)){b.zoom=e;var _=b.numPoints||1;p+=b.x*_,d+=b.y*_,h+=_,b.parentId=g,o&&(m||(m=this._map(c,!0)),o(m,this._map(b)))}}1===h?r.push(c):(c.parentId=g,r.push(V(p/h,d/h,g,h,m)))}}return r},U.prototype._getOriginId=function(t){return t-this.points.length>>5},U.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},U.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},_t.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},_t.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,f=wt(e,r,n),h=this.tiles[f];if(!h&&(c>1&&console.time(\"creation\"),h=this.tiles[f]=yt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){c>1&&console.time(\"clipping\");var m,g,v,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;m=g=v=y=null,x=ot(t,u,r-_,r+T,0,h.minX,h.maxX,l),b=ot(t,u,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(m=ot(x,u,n-_,n+T,1,h.minY,h.maxY,l),g=ot(x,u,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(v=ot(b,u,n-_,n+T,1,h.minY,h.maxY,l),y=ot(b,u,n+w,n+k,1,h.minY,h.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(m||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(v||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},_t.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=wt(t,e=(e%o+o)%o,r);if(this.tiles[s])return gt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,f=r;!l&&c>0;)c--,u=Math.floor(u/2),f=Math.floor(f/2),l=this.tiles[wt(c,u,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?gt(this.tiles[s],i):null):null};var kt=function(e){function r(t,r,n,i){e.call(this,t,r,n,Tt),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{e._geoJSONIndex=n.cluster?new U(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var f=u[c],h=n[f],p=h[0],d=h[1],m=t.createExpression(d),g=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",f]]:p);i[f]=m.value,a[f]=g.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new _t(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON 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t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!t||4===t.length&&(!(t[0]<0||e.data.width<t[0])&&(!(t[1]<0||e.data.height<t[1])&&(!(t[2]<0||e.data.width<t[2])&&(!(t[3]<0||e.data.height<t[3])&&(!(t[2]<t[0])&&!(t[3]<t[1]))))))},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:c,y:u-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c+h,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=g,d=g,m=1e20;function g(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function v(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function y(t,e,r,n,i){r[0]=0,n[0]=-m,n[1]=+m;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+m}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}g.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?m:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?m:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(v(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),v(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1){(0,o[i])(t,e)}delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,\"-transition\")?this._transitionable.setTransition(n.slice(0,-\"-transition\".length),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),T=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};T.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},T.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var c=t[l];i=s*r,a=(s+=c)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===c})}return n},T.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=void 0,d=i/r*(n+1);if(l.isDash){var m=n-Math.abs(d);p=Math.sqrt(h*h+m*m)}else p=n-Math.sqrt(h*h+d*d);this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=l.isDash?h:-h;this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var c={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,c},T.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var k=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function A(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}k.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},k.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},k.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},k.Actor=t.Actor;var M=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};M.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},M.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var S=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(E),C=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),P=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var c=i-r,u=a-n,f=Math.max(c,u),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var O=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var 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e=this.gl;e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e}(_t),Tt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(_t),kt=function(t,e,r,n){this.context=t,this.width=e,this.height=r;var i=t.gl,a=this.framebuffer=i.createFramebuffer();this.colorAttachment=new wt(t,a),n&&(this.depthAttachment=new Tt(t,a))};kt.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var At=function(t,e,r){this.func=t,this.mask=e,this.range=r};At.ReadOnly=!1,At.ReadWrite=!0,At.disabled=new At(519,At.ReadOnly,[0,1]);var Mt=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};Mt.disabled=new Mt({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Lt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new q(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new Z(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new it(this),this.blendEquation=new at(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ft(this),this.bindFramebuffer=new ht(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new mt(this),this.bindElementBuffer=new gt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new vt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\")};Lt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Lt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Lt.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Lt.prototype.createVertexBuffer=function(t,e,r){return new V(this,t,e,r)},Lt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Lt.prototype.createFramebuffer=function(t,e,r){return new kt(this,t,e,r)},Lt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Lt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Lt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Lt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Lt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Lt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ct=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new D[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(It(this._source.type)){for(var c={},u={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],m=this._tiles[p];if(m&&!(m.fadeEndTime&&m.fadeEndTime<=t.browser.now())){var g=this.findLoadedParent(d,o);g&&(this._addTile(g.tileID),c[g.tileID.key]=g.tileID),u[p]=d}}for(var v in this._retainLoadedChildren(u,a,s,l),c)l[v]||(this._coveredTiles[v]=!0,l[v]=c[v])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],f=this._addTile(u);n[u.key]=u,f.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],m=this._tiles[d.key];if(!m.hasData()){if(e+1>this._source.maxzoom){var g=d.children(this._source.maxzoom)[0],v=this.getTile(g);if(v&&v.hasData()){n[g.key]=g;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=m.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(m=this.getTile(_))&&x&&(m=this._addTile(_)),m&&(n[_.key]=_,x=m.wasRequested(),m.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,m=0,g=c;m<g.length;m+=1){var v=g[m];f=Math.min(f,v.x),h=Math.min(h,v.y),p=Math.max(p,v.x),d=Math.max(d,v.y)}for(var y=function(e){var n=i._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,m=Math.pow(2,o.zoom-n.tileID.overscaledZ),g=r*n.queryPadding*t.EXTENT/n.tileSize/m,v=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(v[0].x-g<t.EXTENT&&v[0].y-g<t.EXTENT&&v[1].x+g>=0&&v[1].y+g>=0){var y=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:m})}}},x=0;x<u.length;x++)y(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(It(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles){this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\")}this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function Pt(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function It(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function Ot(){return new t.window.Worker(Zi.workerUrl)}Ct.maxOverzooming=10,Ct.maxUnderzooming=3;var zt=\"mapboxgl_preloaded_worker_pool\",Dt=function(){this.active={}};Dt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Dt.workerCount;)this.workers.push(new Ot);return this.active[t]=!0,this.workers.slice()},Dt.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Dt.prototype.isPreloaded=function(){return!!this.active[zt]},Dt.prototype.numActive=function(){return Object.keys(this.active).length};var Rt,Ft=Math.floor(t.browser.hardwareConcurrency/2);function Bt(){return Rt||(Rt=new Dt),Rt}function Nt(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function jt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Nt(t[n],e[t[n].ref]));return t}Dt.workerCount=Math.max(Math.min(Ft,6),1);var Ut={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Vt(t,e,r){r.push({command:Ut.addSource,args:[t,e[t]]})}function Ht(t,e,r){e.push({command:Ut.removeSource,args:[t]}),r[t]=!0}function qt(t,e,r,n){Ht(t,r,n),Vt(t,e,r)}function Gt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Yt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Wt(t){return t.id}function Xt(t,e){return t[e.id]=e,t}function Zt(e,r){if(!e)return[{command:Ut.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ut.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ut.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ut.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ut.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ut.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ut.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ut.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ut.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ut.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||Ht(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Gt(e,r,a)?n.push({command:Ut.setGeoJSONSourceData,args:[a,r[a].data]}):qt(a,r,n,i)):Vt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ut.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,c,u,f=(e=e||[]).map(Wt),h=r.map(Wt),p=e.reduce(Xt,{}),d=r.reduce(Xt,{}),m=f.slice(),g=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:Ut.removeLayer,args:[o]}),m.splice(m.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],m[m.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:Ut.removeLayer,args:[o]}),m.splice(m.lastIndexOf(o,m.length-a),1)):a++,c=m[m.length-i],n.push({command:Ut.addLayer,args:[d[o],c]}),m.splice(m.length-i,0,o),g[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!g[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(u in Yt(s.layout,l.layout,n,o,null,Ut.setLayoutProperty),Yt(s.paint,l.paint,n,o,null,Ut.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ut.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ut.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Ut.removeLayer,args:[o]}),c=m[m.lastIndexOf(o)+1],n.push({command:Ut.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Ut.setStyle,args:[r]}]}return n}var Jt=function(t,e){this.reset(t,e)};Jt.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},Jt.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Kt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Qt(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function $t(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function te(e,r){var n=[e.x,e.y,0,1];fe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ee(t,e){return.5+t/e*.5}function re(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ne(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,m=n.transform.width/n.transform.height,g=!1,v=0;v<d.length;v++){var y=d.get(v);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!g)ue(y.numGlyphs,h);else{g=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),re(x,f)){var b=x[3],_=ee(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(c,u,y),T=s?w/_:w*_,k=new t.Point(y.anchorX,y.anchorY),A=te(k,a).point,M={},S=oe(y,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,m);g=S.useVertical,(S.notEnoughRoom||g||S.needsFlipping&&oe(y,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,m).notEnoughRoom)&&ue(y.numGlyphs,h)}else ue(y.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function ie(t,e,r,n,i,a,o,s,l,c,u){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),m=e.getoffsetX(f-1),g=le(t*d,r,n,i,a,o,s.segment,h,p,l,c,u);if(!g)return null;var v=le(t*m,r,n,i,a,o,s.segment,h,p,l,c,u);return v?{first:g,last:v}:null}function ae(e,r,n,i){if(e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i)return{useVertical:!0};return(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function oe(e,r,n,i,a,o,s,l,c,u,f,h,p,d){var m,g=r/24,v=e.lineOffsetX*g,y=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ie(g,l,v,y,n,f,h,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=te(w.first.point,s).point,k=te(w.last.point,s).point;if(i&&!n){var A=ae(e.writingMode,T,k,d);if(A)return A}m=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)m.push(le(g*l.getoffsetX(M),v,y,n,f,h,e.segment,b,_,c,o,p));m.push(w.last)}else{if(i&&!n){var S=te(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(c.getx(E),c.gety(E)),C=te(L,a),P=C.signedDistanceFromCamera>0?C.point:se(h,L,S,1,a),I=ae(e.writingMode,S,P,d);if(I)return I}var O=le(g*l.getoffsetX(e.glyphStartIndex),v,y,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!O)return{notEnoughRoom:!0};m=[O]}for(var z=0,D=m;z<D.length;z+=1){var R=D[z];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function se(t,e,r,n,i){var a=te(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function le(e,r,n,i,a,o,s,l,c,u,f,h){var p=i?e-r:e+r,d=p>0?1:-1,m=0;i&&(d*=-1,m=Math.PI),d<0&&(m+=Math.PI);for(var g=d>0?l+s:l+s+1,v=a,y=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)<l||g>=c)return null;if(y=v,w.push(v),void 0===(v=h[g])){var T=new t.Point(u.getx(g),u.gety(g)),k=te(T,f);if(k.signedDistanceFromCamera>0)v=h[g]=k.point;else{var A=g-d;v=se(0===x?o:new t.Point(u.getx(A),u.gety(A)),T,y,_-x+1,f)}}x+=b,b=y.dist(v)}var M=(_-x)/b,S=v.sub(y),E=S.mult(M)._add(y);E._add(S._unit()._perp()._mult(n*d));var L=m+Math.atan2(v.y-y.y,v.x-y.x);return w.push(E),{point:E,angle:L,path:w}}Kt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Kt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Kt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Kt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Kt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Kt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-f,y1:u-f,x2:c+f,y2:u+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Kt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var c=[],u={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,c,u,i),n?c.length>0:c},Kt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Kt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Kt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Kt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,f=0,h=c;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var m=this.circleCells[i];if(null!==m)for(var g=this.circles,v=0,y=m;v<y.length;v+=1){var x=y[v];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(g[b],g[b+1],g[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=g[b],w=g[b+1],T=g[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Kt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[i];if(null!==u)for(var f=this.bboxes,h=0,p=u;h<p.length;h+=1){var d=p[h];if(!c.box[d]){c.box[d]=!0;var m=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[m+0],f[m+1],f[m+2],f[m+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var g=this.circleCells[i];if(null!==g)for(var v=this.circles,y=0,x=g;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(v[_],v[_+1],v[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Kt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Kt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Kt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Kt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Kt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var f=l-s,h=u-c;return f*f+h*h<=r*r};var ce=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ue(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(ce,3*n)}}function fe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var he=function(t,e,r){void 0===e&&(e=new Kt(t.width+200,t.height+200,25)),void 0===r&&(r=new Kt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function pe(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}he.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,c=t.x2*o+a.point.x,u=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,i)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},he.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=[],m=new t.Point(r.anchorX,r.anchorY),g=te(m,o),v=ee(this.transform.cameraToCenterDistance,g.signedDistanceFromCamera),y=(u?a/v:a*v)/t.ONE_EM,x=te(m,s).point,b=ie(y,i,r.lineOffsetX*y,r.lineOffsetY*y,!1,x,m,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*v+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new Jt,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var I=1;I<L.path.length;I++)C.push(L.path[I]);var O=2.5*k;if(l){var z=C.map((function(t){return te(t,l)}));C=z.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:z.map((function(t){return t.point}))}var D=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);D=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=D;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V=0;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/O)+1;for(var H=0;H<V;H++){var q=H/Math.max(V-1,1),G=S.lerp(q),Y=G.x+100,W=G.y+100;d.push(Y,W,k,0);var X=Y-k,Z=W-k,J=Y+k,K=W+k;if(T=T&&this.isOffscreen(X,Z,J,K),w=w||this.isInsideGrid(X,Z,J,K),!e&&this.grid.hitTestCircle(Y,W,k,f)&&(_=!0,!c))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!c&&_||!w?[]:d,offscreen:T,collisionDetected:_}},he.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y),r.push(u)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var m=d[p],g=m.key;if(void 0===f[g.bucketInstanceId]&&(f[g.bucketInstanceId]={}),!f[g.bucketInstanceId][g.featureIndex]){var v=[new t.Point(m.x1,m.y1),new t.Point(m.x2,m.y1),new t.Point(m.x2,m.y2),new t.Point(m.x1,m.y2)];t.polygonIntersectsPolygon(r,v)&&(f[g.bucketInstanceId][g.featureIndex]=!0,void 0===h[g.bucketInstanceId]&&(h[g.bucketInstanceId]=[]),h[g.bucketInstanceId].push(g.featureIndex))}}return h},he.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},he.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},he.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return fe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},he.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},he.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},he.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var de=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};de.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var me=function(t,e,r,n,i){this.text=new de(t?t.text:null,e,r,i),this.icon=new de(t?t.icon:null,e,n,i)};me.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var ge=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},ve=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},ye=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},xe=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function be(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point(s+c[0]*a,l+c[1]*a)}function _e(e,r,n,i,a,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:f,anchorPointY:h}}xe.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var we=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new he(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new xe(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Te(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}we.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,c=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),u=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=pe(n,1,this.transform.zoom),m=Qt(f,h,p,this.transform,d),g=null;if(h){var v=$t(f,h,p,this.transform,d);g=t.multiply([],this.transform.labelPlaneMatrix,v)}this.retainedQueryData[a.bucketInstanceId]=new ye(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var y={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:m,labelToScreenMatrix:g,scale:c,textPixelRatio:u,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:y})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:y})}},we.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d){var m,g=[f.textOffset0,f.textOffset1],v=be(t,r,n,g,i),y=this.collisionIndex.placeCollisionBox(_e(e,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate);if(d&&0===this.collisionIndex.placeCollisionBox(_e(d,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate).box.length)return;if(y.box.length>0)return this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(m=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:m},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:v,placedGlyphBoxes:y}},we.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,c=a.textLabelPlaneMatrix,u=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,m=a.collisionGroup,g=s.get(\"text-optional\"),v=s.get(\"icon-optional\"),y=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=y&&(x||!o.hasIconData()||v),A=x&&(y||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new ge(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,I=null,O=0,z=0,D=0;a.textFeatureIndex?O=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(O=e.featureIndex),a.verticalTextFeatureIndex&&(z=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length;i+=1){if(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),L&&L.box&&L.box.length)break}else L=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,h={box:[],offscreen:!1},p=y?2*N.length:N.length,d=0;d<p;++d){var g=N[d%N.length],v=d>=N.length,k=i.attemptAnchorPlacement(g,t,a,s,c,b,_,f,l,m,v,e,o,n,u);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var H=i.prevPlacement.variableOffsets[e.crossTileID];H&&(i.variableOffsets[e.crossTileID]=H,i.markUsedJustification(o,H.anchor,e,V))}}else{var q=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,y,f,l,m.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return q(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?q(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Y=t.evaluateSizeForFeature(o.textSizeData,d,G),W=s.get(\"text-padding\"),X=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(y,G,o.lineVertexArray,o.glyphOffsetArray,Y,l,c,u,n,_,m.predicate,X,W),T=y||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var Z=function(t){var e=w&&E?_e(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,m.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(I=Z(a.verticalIconBox)).box.length>0:(I=Z(a.iconBox)).box.length>0,S=S&&I.offscreen}var J=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=v||0===e.numIconVertices;if(J||K?K?J||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&z?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,m.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,m.ID)),M&&I&&i.collisionIndex.insertCollisionBox(I.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,m.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,m.ID),n)){var Q=o.bucketInstanceId,$=i.collisionCircleArrays[Q];void 0===$&&($=i.collisionCircleArrays[Q]=new ve);for(var tt=0;tt<P.circles.length;tt+=4)$.circles.push(P.circles[tt+0]),$.circles.push(P.circles[tt+1]),$.circles.push(P.circles[tt+2]),$.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new ge(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)M(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},we.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var c=l[s];c>=0&&(e.text.placedSymbolArray.get(c).crossTileID=a>=0&&c!==a?0:n.crossTileID)}},we.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},we.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=i[s];c?(this.opacities[s]=new me(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new me(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in i){var f=i[u];if(!this.opacities[u]){var h=new me(f,n,!1,!1);h.isHidden()||(this.opacities[u]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},we.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},we.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new me(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),c=a.get(\"text-variable-anchor\"),u=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new me(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},m=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,m=a.crossTileID,g=r[m],v=i.opacities[m];g?v=o:v||(v=p,i.opacities[m]=v),r[m]=!0;var y=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(y){var T=Pe(v.text),k=_?Ie:T;d(e.text,s,k);var A=w?Ie:T;d(e.text,l,A);var M=v.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=Pe(v.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:Ie;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=v.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var I=C?Ie:L;d(e.icon,a.numVerticalIconVertices,I),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=v.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var O=e.collisionArrays[n];if(O){var z=new t.Point(0,0);if(O.textBox||O.verticalTextBox){var D=!0;if(c){var R=i.variableOffsets[m];R?(z=be(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),u&&z._rotate(f?i.transform.angle:-i.transform.angle)):D=!1}O.textBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||_,z.x,z.y),O.verticalTextBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||w,z.x,z.y)}var F=Boolean(!w&&O.verticalIconBox);O.iconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,F,h?z.x:0,h?z.y:0),O.verticalIconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,!F,h?z.x:0,h?z.y:0)}}},g=0;g<e.symbolInstances.length;g++)m(g);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var v=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=v.invProjMatrix,e.placementViewportMatrix=v.viewportMatrix,e.collisionCircleArray=v.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},we.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},we.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},we.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},we.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},we.prototype.setStale=function(){this.stale=!0};var ke=Math.pow(2,25),Ae=Math.pow(2,24),Me=Math.pow(2,17),Se=Math.pow(2,16),Ee=Math.pow(2,9),Le=Math.pow(2,8),Ce=Math.pow(2,1);function Pe(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*ke+e*Ae+r*Me+e*Se+r*Ee+e*Le+r*Ce+e}var Ie=0,Oe=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Oe.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var ze=function(t,e,r,n,i,a,o){this.placement=new we(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};ze.prototype.isDone=function(){return this._done},ze.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Oe(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},ze.prototype.commit=function(t){return this.placement.commit(t),this.placement};var De=512/t.EXTENT/2,Re=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Re.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=De/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Re.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,a.crossTileID=u.crossTileID;break}}}}};var Fe=function(){this.maxCrossTileID=0};Fe.prototype.generate=function(){return++this.maxCrossTileID};var Be=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Be.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Be.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++){e.symbolInstances.get(n).crossTileID=0}this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var c=o[t.scaledTo(Number(a)).key];c&&c.findMatches(e.symbolInstances,t,i)}}for(var u=0;u<e.symbolInstances.length;u++){var f=e.symbolInstances.get(u);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Re(t,e.symbolInstances,e.bucketInstanceId),!0},Be.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Be.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ne=function(){this.layerIndexes={},this.crossTileIDs=new Fe,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ne.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Be);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(i=!0),a[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ne.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var je=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},Ue=t.pick(Ut,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ve=t.pick(Ut,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),He=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a=null;null!=(a=\"version\"===n?r:\"array\"===i.type?[]:{})&&(e[n]=a)}}return e}(),qe=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new k(Bt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new T(256,512),this.crossTileSymbolIndex=new Ne,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast(\"syncRTLPluginState\",r,(function(e,r){if((t.triggerPluginCompletionEvent(e),r)&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(He,!1)},r.prototype._load=function(e,r){if(!r||!je(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=jt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,a=e,u())}));function u(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],c=l.width,u=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,m=l.stretchX,g=l.stretchY,v=l.content,y=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,y,{x:f,y:h},{x:0,y:0},{width:c,height:u}),r[s]={data:y,pixelRatio:d,sdf:p,stretchX:m,stretchY:g,content:v}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];\"custom\"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];h.recalculate(e,this._availableImages),!h.isHidden(e.zoom)&&h.source&&(this.sourceCaches[h.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),je(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=jt(e.layers);var n=Zt(this.serialize(),e).filter((function(t){return!(t.command in Ve)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in Ue)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0)||!this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n)){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ct(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(je(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,f=c;u<f.length;u+=1){var h=f[u];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var m=this._order[d];if(r(m))for(var g=i.length-1;g>=0;g--){var v=i[g].feature;if(n[v.layer.id]<d)break;p.push(v),i.pop()}else for(var y=0,x=t;y<x.length;y+=1){var b=x[y][m];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var c=[];for(var u in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[u]||c.push(F(this.sourceCaches[u],this._layers,this._serializedLayers,e,r,n));return this.placement&&c.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),c=[],u=0,f=Object.keys(l).map(Number);u<f.length;u+=1){var h=f[u];c.push(o[h])}c.sort(B);for(var p=function(){var r=m[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],c=n[a];c.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var u=0,f=c;u<f.length;u+=1){var h=f[u];o.push(h)}}},d=0,m=c;d<m.length;d+=1)p();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=o}))};for(var v in s)g(v);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&je(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers){this._layers[e].setEventedParent(null)}for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];if(\"symbol\"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new ze(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var m=0,g=this._order;m<g.length;m+=1){var v=g[m],y=this._layers[v];\"symbol\"===y.type&&this.placement.updateLayerOpacities(y,l[y.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);qe.getSourceType=function(t){return D[t]},qe.setSourceType=function(t,e){D[t]=e},qe.registerForPluginStateChange=t.registerForPluginStateChange;var Ge=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ye=yr(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),We=yr(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Xe=yr(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),Ze=yr(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Je=yr(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Ke=yr(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),Qe=yr(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),$e=yr(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),tr=yr(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),er=yr(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),rr=yr(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),nr=yr(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ir=yr(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ar=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),or=yr(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),sr=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),lr=yr(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),cr=yr(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),ur=yr(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),fr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),hr=yr(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),pr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),dr=yr(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=yr(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),gr=yr(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),vr=yr(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function yr(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = a_\"+a+\";\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var xr=Object.freeze({__proto__:null,prelude:Ye,background:We,backgroundPattern:Xe,circle:Ze,clippingMask:Je,heatmap:Ke,heatmapTexture:Qe,collisionBox:$e,collisionCircle:tr,debug:er,fill:rr,fillOutline:nr,fillOutlinePattern:ir,fillPattern:ar,fillExtrusion:or,fillExtrusionPattern:sr,hillshadePrepare:lr,hillshade:cr,line:ur,lineGradient:fr,linePattern:hr,lineSDF:pr,raster:dr,symbolIcon:mr,symbolSDF:gr,symbolTextAndIcon:vr}),br=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};br.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);var u=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||u?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},br.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var f=l;f<s;f++)u.disableVertexAttribArray(f)}e.enableAttributes(u,t);for(var h=0,p=r;h<p.length;h+=1){p[h].enableAttributes(u,t)}a&&a.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,i);for(var d=0,m=r;d<m.length;d+=1){var g=m[d];g.bind(),g.setVertexAttribPointers(u,t,i)}a&&(a.bind(),a.setVertexAttribPointers(u,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,i)),c.currentNumAttributes=l},br.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var _r=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Ye.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Ye.vertexSource,e.vertexSource).join(\"\\n\"),c=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,s),a.compileShader(c),a.attachShader(this.program,c);var u=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,l),a.compileShader(u),a.attachShader(this.program,u);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(u),a.deleteShader(c),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var m=a.getActiveAttrib(this.program,d);m&&(this.attributes[m.name]=a.getAttribLocation(this.program,m.name))}for(var g=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),v=0;v<g;v++){var y=a.getActiveUniform(this.program,v);y&&(p[y.name]=a.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function wr(t,e,r){var n=1/pe(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}_r.prototype.draw=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m){var g,v=t.gl;if(!this.failedToCreate){for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[v.LINES]=2,g[v.TRIANGLES]=3,g[v.LINE_STRIP]=1,g)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new br)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,m),v.drawElements(e,w.primitiveLength*x,v.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Tr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:i}},kr=function(e,r,n,i,a,o,s){return t.extend(Tr(e,r,n,i),wr(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Ar=function(t){return{u_matrix:t}},Mr=function(e,r,n,i){return t.extend(Ar(e),wr(n,r,i))},Sr=function(t,e){return{u_matrix:t,u_world:e}},Er=function(e,r,n,i,a){return t.extend(Mr(e,r,n,i),{u_world:a})},Lr=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=pe(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Cr=function(t,e,r){var n=pe(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Pr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Ir=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Or=function(t){return{u_matrix:t}},zr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:pe(e,1,r),u_intensity:n}};function Dr(e,r){var n=Math.pow(2,r.canonical.z),i=r.canonical.y;return[new t.MercatorCoordinate(0,i/n).toLngLat().lat,new t.MercatorCoordinate(0,(i+1)/n).toLngLat().lat]}var Rr=function(e,r,n){var i=e.transform;return{u_matrix:Ur(e,r,n),u_ratio:1/pe(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Fr=function(e,r,n){return t.extend(Rr(e,r,n),{u_image:0})},Br=function(e,r,n,i){var a=e.transform,o=jr(r,a);return{u_matrix:Ur(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/pe(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Nr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=jr(r,o),c=\"round\"===n.layout.get(\"line-cap\"),u=s.getDash(i.from,c),f=s.getDash(i.to,c),h=u.width*a.fromScale,p=f.width*a.toScale;return t.extend(Rr(e,r,n),{u_patternscale_a:[l/h,-u.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:u.y,u_tex_y_b:f.y,u_mix:a.t})};function jr(t,e){return 1/pe(t,1,e.tileZoom)}function Ur(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Vr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Hr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Hr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var qr,Gr=function(t,e,r,n,i,a,o,s,l,c){var u=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Yr=function(e,r,n,i,a,o,s,l,c,u,f){var h=a.transform;return t.extend(Gr(e,r,n,i,a,o,s,l,c,u),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Wr=function(e,r,n,i,a,o,s,l,c,u){return t.extend(Yr(e,r,n,i,a,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Xr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Zr=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,f=u*(n.tileID.canonical.x+n.tileID.wrap*c),h=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/pe(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},Jr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Kr(e,r,n,i,a,o,s){for(var l=e.context,c=l.gl,u=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var m=i[d],g=r.getTile(m),v=g.getBucket(n);if(v){var y=m.posMatrix;0===a[0]&&0===a[1]||(y=e.translatePosMatrix(m.posMatrix,g,a,o));var x=s?v.textCollisionBox:v.iconCollisionBox,b=v.collisionCircleArray;if(b.length>0){var _=t.create(),w=y;t.mul(_,v.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,v.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&u.draw(l,c.LINES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,Cr(y,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M<S.length;M+=1)for(var E=S[M],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],I=E.circleArray[C+1],O=E.circleArray[C+2],z=E.circleArray[C+3];k.emplace(A++,P,I,O,z,0),k.emplace(A++,P,I,O,z,1),k.emplace(A++,P,I,O,z,2),k.emplace(A++,P,I,O,z,3)}(!qr||qr.length<2*h)&&(qr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var D=l.createIndexBuffer(qr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Pr(N.transform,N.invTransform,e.transform);T.draw(l,c.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var Qr=t.identity(new Float32Array(16));function $r(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point((l/a+u[0])*o,(c/a+u[1])*o)}function tn(e,r,n,i,a,o,s,l,c,u,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,m={};p.clear();for(var g=0;g<h.length;g++){var v=h.get(g),y=e.allowVerticalPlacement&&!v.placedOrientation,x=v.hidden||!v.crossTileID||y?null:i[v.crossTileID];if(x){var b=new t.Point(v.anchorX,v.anchorY),_=te(b,n?l:s),w=ee(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,u,v)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/c);for(var k=x.width,A=x.height,M=$r(x.anchor,k,A,x.textOffset,x.textBoxScale,T),S=n?te(b.add(M),s).point:_.point.add(r?M.rotate(-o.angle):M),E=e.allowVerticalPlacement&&v.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<v.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&v.associatedIconIndex>=0&&(m[v.associatedIconIndex]={shiftedAnchor:S,angle:E})}else ue(v.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var I=C.get(P);if(I.hidden)ue(I.numGlyphs,d);else{var O=m[P];if(O)for(var z=0;z<I.numGlyphs;z++)t.addDynamicAttributes(d,O.shiftedAnchor,O.angle);else ue(I.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function en(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function rn(e,r,n,i,a,o,s,l,c,u,f,h){for(var p=e.context,d=p.gl,m=e.transform,g=\"map\"===l,v=\"map\"===c,y=g&&\"point\"!==n.layout.get(\"symbol-placement\"),x=g&&!v&&!y,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=e.depthModeForSublayer(0,At.ReadOnly),w=n.layout.get(\"text-variable-anchor\"),T=[],k=0,A=i;k<A.length;k+=1){var M=A[k],S=r.getTile(M),E=S.getBucket(n);if(E){var L=a?E.text:E.icon;if(L&&L.segments.get().length){var C=L.programConfigurations.get(n.id),P=a||E.sdfIcons,I=a?E.textSizeData:E.iconSizeData,O=v||0!==m.pitch,z=e.useProgram(en(P,a,E),C),D=t.evaluateSizeForZoom(I,m.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a){if(B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText){F=S.imageAtlasTexture.size,j=S.imageAtlasTexture;var V=\"composite\"===I.kind||\"camera\"===I.kind;U=O||e.options.rotating||e.options.zooming||V?d.LINEAR:d.NEAREST}}else{var H=1!==n.layout.get(\"icon-size\").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=P||e.options.rotating||e.options.zooming||H||O?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var q=pe(S,1,e.transform.zoom),G=Qt(M.posMatrix,v,g,e.transform,q),Y=$t(M.posMatrix,v,g,e.transform,q),W=w&&E.hasTextData(),X=\"none\"!==n.layout.get(\"icon-text-fit\")&&W&&E.hasIconData();y&&ne(E,M.posMatrix,e,a,G,Y,v,u);var Z=e.translatePosMatrix(M.posMatrix,S,o,s),J=y||a&&w||X?Qr:G,K=e.translatePosMatrix(Y,S,o,s,!0),Q=P&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),$={program:z,buffers:L,uniformValues:P?E.iconsInText?Wr(I.kind,D,x,v,e,Z,J,K,R,F):Yr(I.kind,D,x,v,e,Z,J,K,a,R,!0):Gr(I.kind,D,x,v,e,Z,J,K,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:P,hasHalo:Q};if(b)for(var tt=0,et=L.segments.get();tt<et.length;tt+=1){var rt=et[tt];T.push({segments:new t.SegmentVector([rt]),sortKey:rt.sortKey,state:$})}else T.push({segments:L.segments,sortKey:0,state:$})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var nt=0,it=T;nt<it.length;nt+=1){var at=it[nt],ot=at.state;if(p.activeTexture.set(d.TEXTURE0),ot.atlasTexture.bind(ot.atlasInterpolation,d.CLAMP_TO_EDGE),ot.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),ot.atlasTextureIcon&&ot.atlasTextureIcon.bind(ot.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),ot.isSDF){var st=ot.uniformValues;ot.hasHalo&&(st.u_is_halo=1,nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,st)),st.u_is_halo=0}nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,ot.uniformValues)}}function nn(t,e,r,n,i,a,o,s,l){var c=n.context,u=c.gl;i.draw(c,u.TRIANGLES,a,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function an(t,e,r,n,i,a,o){var s,l,c,u,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),m=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var g=0,v=n;g<v.length;g+=1){var y=v[g],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(m));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(y.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){u=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];c=\"fillOutlinePattern\"===l&&d?Er(S,t,m,x,E):Sr(S,E)}else u=b.indexBuffer,f=b.segments,c=d?Mr(S,t,m,x):Ar(S);w.draw(t.context,s,i,t.stencilModeForClipping(y),a,Et.disabled,c,r.id,b.layoutVertexBuffer,u,f,r.paint,t.transform.zoom,_)}}}}function on(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=c.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var m=d[p],g=e.getTile(m),v=g.getBucket(r);if(v){var y=v.programConfigurations.get(r.id),x=t.useProgram(u?\"fillExtrusionPattern\":\"fillExtrusion\",y);u&&(t.context.activeTexture.set(l.TEXTURE0),g.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(f));var b=c.constantOr(null);if(b&&g.imageAtlas){var _=g.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&y.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(m.posMatrix,g,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),A=r.paint.get(\"fill-extrusion-vertical-gradient\"),M=u?kr(k,t,A,h,m,f,g):Tr(k,t,A,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Et.backCCW,M,r.id,v.layoutVertexBuffer,v.indexBuffer,v.segments,r.paint,t.transform.zoom,y)}}}function sn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var c=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var u=function(t,e,r){var n=r.paint.get(\"hillshade-shadow-color\"),i=r.paint.get(\"hillshade-highlight-color\"),a=r.paint.get(\"hillshade-accent-color\"),o=r.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===r.paint.get(\"hillshade-illumination-anchor\")&&(o-=t.transform.angle);var s=!t.options.moving;return{u_matrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped(),s),u_image:0,u_latrange:Dr(t,e.tileID),u_light:[r.paint.get(\"hillshade-exaggeration\"),o],u_shadow:n,u_highlight:i,u_accent:a}}(t,e,r);c.draw(o,s.TRIANGLES,n,i,a,Et.disabled,u,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function ln(e,r,n,i,a,o,s){var l=e.context,c=l.gl,u=r.dem;if(u&&u.data){var f=u.dim,h=u.stride,p=u.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var m=r.fbo;if(!m){var g=new t.Texture(l,{width:f,height:f,data:null},c.RGBA);g.bind(c.LINEAR,c.CLAMP_TO_EDGE),(m=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(g.texture)}l.bindFramebuffer.set(m.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram(\"hillshadePrepare\").draw(l,c.TRIANGLES,a,o,s,Et.disabled,function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}}(r.tileID,u,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function cn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),f=a.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var un=new t.Color(1,0,0,1),fn=new t.Color(0,1,0,1),hn=new t.Color(0,0,1,1),pn=new t.Color(1,0,1,1),dn=new t.Color(0,1,1,1);function mn(t){var e=t.transform.padding;gn(t,t.transform.height-(e.top||0),3,un),gn(t,e.bottom||0,3,fn),vn(t,e.left||0,3,hn),vn(t,t.transform.width-(e.right||0),3,pn);var r=t.transform.centerPoint;!function(t,e,r,n){yn(t,e-1,r-10,2,20,n),yn(t,e-10,r-1,20,2,n)}(t,r.x,t.transform.height-r.y,dn)}function gn(t,e,r,n){yn(t,0,e+r/2,t.transform.width,r,n)}function vn(t,e,r,n){yn(t,e-r/2,0,r,t.transform.height,n)}function yn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function xn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=At.disabled,c=Mt.disabled,u=e.colorModeForRenderPass();i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,c,u,Et.disabled,Ir(o,t.Color.red),\"$debug\",e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var f=r.getTileByID(n.key).latestRawTileData,h=f&&f.byteLength||0,p=Math.floor(h/1024),d=r.getTile(n).tileSize,m=512/Math.min(d,512)*(n.overscaledZ/e.transform.zoom)*.5,g=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(g+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,g+\" \"+p+\"kb\"),s.draw(i,a.TRIANGLES,l,c,St.alphaBlended,Et.disabled,Ir(o,t.Color.transparent,m),\"$debug\",e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var bn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Mt.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,c=\"map\"===a,u=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),m=d.getBucket(n);if(m&&m.text&&m.text.segments.get().length){var g=m.textSizeData,v=t.evaluateSizeForZoom(g,l.zoom),y=pe(d,1,r.transform.zoom),x=Qt(p.posMatrix,u,c,r.transform,y),b=\"none\"!==n.layout.get(\"icon-text-fit\")&&m.hasIconData();if(v){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);tn(m,c,u,s,t.symbolSize,l,x,p.posMatrix,_,v,b)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&rn(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&rn(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(Kr(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),Kr(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,f=e.depthModeForSublayer(0,At.ReadOnly),h=Mt.disabled,p=e.colorModeForRenderPass(),d=[],m=0;m<i.length;m++){var g=i[m],v=r.getTile(g),y=v.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:Lr(e,g,v,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,I=S.uniformValues,O=M.segments;L.draw(c,u.TRIANGLES,f,h,p,Et.disabled,I,n.id,C,P,O,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=Mt.disabled,l=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}}(a,e,n),a.clear({color:t.Color.transparent});for(var c=0;c<i.length;c++){var u=i[c];if(!r.hasRenderableParent(u)){var f=r.getTile(u),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),m=e.transform.zoom;d.draw(a,o.TRIANGLES,At.disabled,s,l,Et.disabled,zr(u.posMatrix,f,m,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(!a)return;n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA));o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}}(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,At.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get(\"line-dasharray\"),u=n.paint.get(\"line-pattern\"),f=u.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":c?\"lineSDF\":h?\"lineGradient\":\"line\",m=e.context,g=m.gl,v=!0;if(h){m.activeTexture.set(g.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(m,n.gradient,g.RGBA)),y.bind(g.LINEAR,g.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),A=e.context.program.get(),M=e.useProgram(d,k),S=v||M.program!==A,E=u.constantOr(null);if(E&&w.imageAtlas){var L=w.imageAtlas,C=L.patternPositions[E.to.toString()],P=L.patternPositions[E.from.toString()];C&&P&&k.setConstantPatternPositions(C,P)}var I=f?Br(e,w,n,p):c?Nr(e,w,n,c,p):h?Fr(e,w,n):Rr(e,w,n);f?(m.activeTexture.set(g.TEXTURE0),w.imageAtlasTexture.bind(g.LINEAR,g.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):c&&(S||e.lineAtlas.dirty)&&(m.activeTexture.set(g.TEXTURE0),e.lineAtlas.bind(m)),M.draw(m,g.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,I,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),v=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===c){var u=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?At.ReadWrite:At.ReadOnly);an(e,r,n,i,u,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,At.ReadOnly);an(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))on(t,e,r,n,a,Mt.disabled,St.disabled),on(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();on(t,e,r,n,a,Mt.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,At.ReadOnly),s=t.colorModeForRenderPass(),l=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],c=l[0],u=0,f=l[1];u<f.length;u+=1){var h=f[u],p=e.getTile(h);p.needsHillshadePrepare&&\"offscreen\"===t.renderPass?ln(t,p,r,a,o,Mt.disabled,s):\"translucent\"===t.renderPass&&sn(t,p,r,o,c[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),c=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),u=c[0],f=c[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,m=f;d<m.length;d+=1){var g=m[d],v=t.depthModeForSublayer(g.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?At.ReadWrite:At.ReadOnly,a.LESS),y=e.getTile(g),x=t.transform.calculatePosMatrix(g.toUnwrapped(),p);y.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(g,0),_=cn(y,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-y.tileID.overscaledZ),T=[y.tileID.canonical.x*w%1,y.tileID.canonical.y*w%1]):y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var A=Vr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,v,Mt.disabled,l,Et.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,v,u[g.overscaledZ],l,Et.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===u){var f=Mt.disabled,h=t.depthModeForSublayer(0,\"opaque\"===u?At.ReadWrite:At.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?\"backgroundPattern\":\"background\"),m=s.coveringTiles({tileSize:l});c&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var g=r.getCrossfadeParameters(),v=0,y=m;v<y.length;v+=1){var x=y[v],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?Zr(b,i,t,c,{tileID:x,tileSize:l},g):Xr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)xn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Mt.disabled);var o=\"3d\"===i.renderingMode?new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,At.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},_n=function(t,e){this.context=new Lt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ct.maxUnderzooming+Ct.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ne,this.gpuTimers={}};_n.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},_n.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,Ge.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,Ge.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,P.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,Ge.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Mt({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},_n.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,At.disabled,this.stencilClearMode,St.disabled,Et.disabled,Or(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},_n.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(At.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,At.disabled,new Mt({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Or(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},_n.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Mt({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Mt({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new Mt({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=Mt.disabled,e),n]},_n.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){return new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0])}return\"opaque\"===this.renderPass?St.unblended:St.alphaBlended},_n.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return At.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new At(r||this.context.gl.LEQUAL,e,[n,n])},_n.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},_n.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,c,u={},f={},h={};for(var p in a){var d=a[p];u[p]=d.getVisibleCoordinates(),f[p]=u[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var m=0;m<i.length;m++){var g=i[m];if(this.style._layers[g].is3D()){this.opaquePassCutoff=m;break}}this.renderPass=\"offscreen\";for(var v=0,y=i;v<y.length;v+=1){var x=y[v],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];(\"custom\"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=u[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var A=this.style._layers[i[this.currentLayer]],M=a[A.source],S=(\"symbol\"===A.type?h:f)[A.source];this._renderTileClippingMasks(A,u[A.source]),this.renderLayer(this,M,A,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(c&&c.id)&&(c=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<c.getSource().maxzoom)&&(l=c))})),l&&bn.debug(this,l,l.getVisibleCoordinates()));this.options.showPadding&&mn(this),this.context.setDefault()},_n.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),bn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},_n.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},_n.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},_n.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},_n.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},_n.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[a?n[0]:pe(r,n[0],this.transform.zoom),a?n[1]:pe(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},_n.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},_n.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},_n.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},_n.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new _r(this.context,xr[t],e,Jr[t],this._showOverdrawInspector)),this.cache[r]},_n.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},_n.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},_n.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},_n.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var wn=function(t,e){this.points=t,this.planes=e};wn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new wn(a,o)};var Tn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Tn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new Tn(n,i)},Tn.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},Tn.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},Tn.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];c=Math.min(c,h),u=Math.max(u,h)}if(u<0||c>this.max[l]-this.min[l])return 0}return 1};var kn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};kn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},kn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},kn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},kn.prototype.clone=function(){return new kn(this.top,this.bottom,this.left,this.right)},kn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var An=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new kn,this._posMatrixCache={},this._alignedPosMatrixCache={}},Mn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};An.prototype.clone=function(){var t=new An(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Mn.minZoom.get=function(){return this._minZoom},Mn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Mn.maxZoom.get=function(){return this._maxZoom},Mn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Mn.minPitch.get=function(){return this._minPitch},Mn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Mn.maxPitch.get=function(){return this._maxPitch},Mn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Mn.renderWorldCopies.get=function(){return this._renderWorldCopies},Mn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Mn.worldSize.get=function(){return this.tileSize*this.scale},Mn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Mn.size.get=function(){return new t.Point(this.width,this.height)},Mn.bearing.get=function(){return-this.angle/Math.PI*180},Mn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Mn.pitch.get=function(){return this._pitch/Math.PI*180},Mn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Mn.fov.get=function(){return this._fov/Math.PI*180},Mn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Mn.zoom.get=function(){return this._zoom},Mn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Mn.center.get=function(){return this._center},Mn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Mn.padding.get=function(){return this._edgeInsets.toJSON()},Mn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Mn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},An.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},An.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},An.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},An.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},An.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=wn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new Tn([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var m=u.pop(),g=m.x,v=m.y,y=m.fullyVisible;if(!y){var x=m.aabb.intersects(s);if(0===x)continue;y=2===x}var b=m.aabb.distanceX(o),_=m.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-m.zoom)-2;if(m.zoom===h||w>T&&m.zoom>=l)f.push({tileID:new t.OverscaledTileID(m.zoom===h?p:m.zoom,m.wrap,m.zoom,g,v),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-v])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(v<<1)+(k>>1);u.push({aabb:m.aabb.quadrant(k),zoom:m.zoom+1,x:A,y:M,wrap:m.wrap,fullyVisible:y})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},An.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Mn.unmodified.get=function(){return this._unmodified},An.prototype.zoomScale=function(t){return Math.pow(2,t)},An.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},An.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},An.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Mn.point.get=function(){return this.project(this.center)},An.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},An.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},An.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},An.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},An.prototype.coordinateLocation=function(t){return t.toLngLat()},An.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,c=n[1]/a,u=r[2]/i,f=n[2]/a,h=u===f?0:(0-u)/(f-u);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,c,h)/this.worldSize)},An.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},An.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},An.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},An.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},An.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},An.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},An.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<c.y?c.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var m=p.y,g=c.y/2;m-g<a&&(i=a+g),m+g>o&&(i=o-g)}if(this.lngRange){var v=p.x,y=c.x/2;v-y<s&&(n=s+y),v+y>l&&(n=l-y)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=u,this._constraining=!1}},An.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,c=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),u=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,u,c),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),m=Math.sin(this.angle),g=s-Math.round(s)+d*h+m*p,v=l-Math.round(l)+d*p+m*h,y=new Float64Array(f);if(t.translate(y,y,[g>.5?g-1:g,v>.5?v-1:v,0]),this.alignedProjMatrix=y,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},An.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},An.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},An.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(An.prototype,Mn);var Sn=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};Sn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},Sn.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},Sn.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),c=this._map.getPitch(),u=\"\";if(u+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||c)&&(u+=\"/\"+Math.round(10*l)/10),c&&(u+=\"/\"+Math.round(c)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+u):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+u),\"#\"+p.join(\"&\")}return\"#\"+u},Sn.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},Sn.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},Sn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var En={linearity:.3,easing:t.bezier(0,0,.3,1)},Ln=t.extend({deceleration:2500,maxSpeed:1400},En),Cn=t.extend({deceleration:20,maxSpeed:1400},En),Pn=t.extend({deceleration:1e3,maxSpeed:360},En),In=t.extend({deceleration:1e3,maxSpeed:90},En),On=function(t){this._map=t,this.clear()};function zn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Dn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}On.prototype.clear=function(){this._inertiaBuffer=[]},On.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},On.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},On.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Dn(r.pan.mag(),o,t.extend({},Ln,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,zn(s,l)}if(r.zoom){var c=Dn(r.zoom,o,Cn);s.zoom=this._map.transform.zoom+c.amount,zn(s,c)}if(r.bearing){var u=Dn(r.bearing,o,Pn);s.bearing=this._map.transform.bearing+t.clamp(u.amount,-179,179),zn(s,u)}if(r.pitch){var f=Dn(r.pitch,o,In);s.pitch=this._map.transform.pitch+f.amount,zn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Rn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Fn=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),c=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),u=i.unproject(c);e.call(this,n,{points:s,point:c,lngLats:l,lngLat:u,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Bn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Nn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Nn.prototype.reset=function(){delete this._mousedownPos},Nn.prototype.wheel=function(t){return this._firePreventable(new Bn(t.type,this._map,t))},Nn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseup=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.dblclick=function(t){return this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseover=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.mouseout=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.touchstart=function(t){return this._firePreventable(new Fn(t.type,this._map,t))},Nn.prototype.touchmove=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchend=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchcancel=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Nn.prototype.isEnabled=function(){return!0},Nn.prototype.isActive=function(){return!1},Nn.prototype.enable=function(){},Nn.prototype.disable=function(){};var jn=function(t){this._map=t};jn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},jn.prototype.mousemove=function(t){this._map.fire(new Rn(t.type,this._map,t))},jn.prototype.mousedown=function(){this._delayContextMenu=!0},jn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Rn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},jn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Rn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},jn.prototype.isEnabled=function(){return!0},jn.prototype.isActive=function(){return!1},jn.prototype.enable=function(){},jn.prototype.disable=function(){};var Un=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Vn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Un.prototype.isEnabled=function(){return!!this._enabled},Un.prototype.isActive=function(){return!!this._active},Un.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Un.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Un.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Un.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Un.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Un.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Un.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Un.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var Hn=function(t){this.reset(),this.numTouches=t.numTouches};Hn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},Hn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Vn(n,r)))},Hn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Vn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},Hn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var qn=function(t){this.singleTap=new Hn(t),this.numTaps=t.numTaps,this.reset()};qn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},qn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},qn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},qn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Gn=function(){this._zoomIn=new qn({numTouches:1,numTaps:2}),this._zoomOut=new qn({numTouches:2,numTaps:1}),this.reset()};Gn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Gn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Gn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Gn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Gn.prototype.touchcancel=function(){this.reset()},Gn.prototype.enable=function(){this._enabled=!0},Gn.prototype.disable=function(){this._enabled=!1,this.reset()},Gn.prototype.isEnabled=function(){return this._enabled},Gn.prototype.isActive=function(){return this._active};var Yn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Yn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Yn.prototype._correctButton=function(t,e){return!1},Yn.prototype._move=function(t,e){return{}},Yn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Yn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Yn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Yn.prototype.enable=function(){this._enabled=!0},Yn.prototype.disable=function(){this._enabled=!1,this.reset()},Yn.prototype.isEnabled=function(){return this._enabled},Yn.prototype.isActive=function(){return this._active};var Wn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Yn),Xn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Zn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Jn=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};Jn.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},Jn.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},Jn.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},Jn.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Vn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var c=i[l],u=this._touches[l];u&&(a._add(c),o._add(c.sub(u)),s++,i[l]=c)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(){this.reset()};function Qn(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}Kn.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},Kn.prototype._start=function(t){},Kn.prototype._move=function(t,e,r){return{}},Kn.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},Kn.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=Qn(r,e,i),s=Qn(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},Kn.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=Qn(n,e,a),l=Qn(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},Kn.prototype.touchcancel=function(){this.reset()},Kn.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},Kn.prototype.disable=function(){this._enabled=!1,this.reset()},Kn.prototype.isEnabled=function(){return this._enabled},Kn.prototype.isActive=function(){return this._active};function $n(t,e){return Math.log(t/e)/Math.LN2}var ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs($n(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:$n(this._distance,r),pinchAround:e}},e}(Kn);function ei(t,e){return 180*t.angleWith(e)/Math.PI}var ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:ei(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=ei(t,this._startVector);return Math.abs(r)<e},e}(Kn);function ni(t){return Math.abs(t.y)>Math.abs(t.x)}var ii=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ni(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid){this._lastPoints=t,this._active=!0;return{pitchDelta:-.5*((n.y+i.y)/2)}}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ni(t)&&ni(e)&&a}},e}(Kn),ai={panStep:100,bearingStep:15,pitchStep:10},oi=function(){var t=ai;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function si(t){return t*(2-t)}oi.prototype.reset=function(){this._active=!1},oi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:si,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},oi.prototype.enable=function(){this._enabled=!0},oi.prototype.disable=function(){this._enabled=!1,this.reset()},oi.prototype.isEnabled=function(){return this._enabled},oi.prototype.isActive=function(){return this._active};var li=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};li.prototype.setZoomRate=function(t){this._defaultZoomRate=t},li.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},li.prototype.isEnabled=function(){return!!this._enabled},li.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},li.prototype.isZooming=function(){return!!this._zooming},li.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},li.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},li.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},li.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},li.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},li.prototype.renderFrame=function(){return this._onScrollFrame()},li.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if(\"wheel\"===this._type&&l&&c){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=c(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},li.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},li.prototype.reset=function(){this._active=!1};var ci=function(t,e){this._clickZoom=t,this._tapZoom=e};ci.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},ci.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},ci.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},ci.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var ui=function(){this.reset()};ui.prototype.reset=function(){this._active=!1},ui.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},ui.prototype.enable=function(){this._enabled=!0},ui.prototype.disable=function(){this._enabled=!1,this.reset()},ui.prototype.isEnabled=function(){return this._enabled},ui.prototype.isActive=function(){return this._active};var fi=function(){this._tap=new qn({numTouches:1,numTaps:1}),this.reset()};fi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},fi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},fi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},fi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},fi.prototype.touchcancel=function(){this.reset()},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var hi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};hi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},hi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},hi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},hi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var pi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};pi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},pi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},pi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},pi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var di=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};di.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},di.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},di.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},di.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},di.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},di.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var mi=function(t){return t.zoom||t.drag||t.pitch||t.rotate},gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function vi(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var yi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new On(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1],u=s[2];r.addEventListener(l,c,l===t.window.document?this.handleWindowEvent:this.handleEvent,u)}};yi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},yi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Nn(e,t));var n=e.boxZoom=new Un(e,t);this._add(\"boxZoom\",n);var i=new Gn,a=new ui;e.doubleClickZoom=new ci(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new fi;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new ii;this._add(\"touchPitch\",s);var l=new Xn(t),c=new Zn(t);e.dragRotate=new pi(t,l,c),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",c,[\"mouseRotate\"]);var u=new Wn(t),f=new Jn(t);e.dragPan=new hi(r,u,f),this._add(\"mousePan\",u),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new ri,p=new ti;e.touchZoomRotate=new di(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new li(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var m=e.keyboard=new oi;this._add(\"keyboard\",m),this._add(\"blockableMapEvent\",new jn(e));for(var g=0,v=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];g<v.length;g+=1){var y=v[g];t.interactive&&t[y]&&e[y].enable(t[y])}},yi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},yi.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1){e[t].handler.reset()}this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},yi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1){if(e[t].handler.isActive())return!0}return!1},yi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},yi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},yi.prototype.isMoving=function(){return Boolean(mi(this._eventsInProgress))||this.isZooming()},yi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},yi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},yi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},yi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),c=0,u=this._handlers;c<u.length;c+=1){var f=u[c],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var m=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(m=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,m,h,n),m&&m.needsRenderFrame&&this._triggerRenderFrame()),(m||p.isActive())&&(o[h]=p)}}var g={};for(var v in this._previousActiveHandlers)o[v]||(g[v]=n);this._previousActiveHandlers=o,(Object.keys(g).length||vi(i))&&(this._changes.push([i,a,g]),this._triggerRenderFrame()),(Object.keys(o).length||vi(i))&&this._map._stop(!0),this._updatingCamera=!1;var y=i.cameraAnimation;y&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],y(this._map))}else this.stop()},yi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},yi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],c=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,c)}this._updateMapTransform(e,r,n),this._changes=[]},yi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!vi(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,c=t.around,u=t.pinchAround;void 0!==u&&(c=u),n._stop(!0),c=c||n.transform.centerPoint;var f=i.pointLocation(a?c.sub(a):c);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,c),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},yi.prototype._fireEvents=function(e,r){var n=this,i=mi(this._eventsInProgress),a=mi(e),o={};for(var s in e){var l=e[s].originalEvent;this._eventsInProgress[s]||(o[s+\"start\"]=l),this._eventsInProgress[s]=e[s]}for(var c in!i&&a&&this._fireEvent(\"movestart\",a.originalEvent),o)this._fireEvent(c,o[c]);for(var u in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent(\"move\",a.originalEvent),e){var f=e[u].originalEvent;this._fireEvent(u,f)}var h,p={};for(var d in this._eventsInProgress){var m=this._eventsInProgress[d],g=m.handlerName,v=m.originalEvent;this._handlersById[g].isActive()||(delete this._eventsInProgress[d],h=r[g]||v,p[d+\"end\"]=h)}for(var y in p)this._fireEvent(y,p[y]);var x=mi(this._eventsInProgress);if((i||a)&&!x){this._updatingCamera=!0;var b=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),_=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};b?(_(b.bearing||this._map.getBearing())&&(b.bearing=0),this._map.easeTo(b,{originalEvent:h})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:h})),_(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},yi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},yi.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new gi(\"renderFrame\",{timeStamp:e})),t._applyChanges()})))};var xi=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,c=s.project(t.LngLat.convert(e)),u=s.project(t.LngLat.convert(r)),f=c.rotate(-n*Math.PI/180),h=u.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),m=p.sub(d),g=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/m.x,v=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/m.y;if(!(v<0||g<0)){var y=Math.min(s.scaleZoom(s.scale*Math.min(g,v)),i.maxZoom),x=t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(x.x+b,x.y+_).mult(s.scale/s.zoomScale(y));return{center:s.unproject(c.add(u).div(2).sub(w)),zoom:y,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),c=\"zoom\"in e?+e.zoom:a,u=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),m=i.pointLocation(d),g=t.LngLat.convert(e.center||m);this._normalizeCenter(g);var v,y,x=i.project(m),b=i.project(g).sub(x),_=i.zoomScale(c-a);e.around&&(v=t.LngLat.convert(e.around),y=i.locationPoint(v));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||c!==a,this._rotating=this._rotating||o!==u,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,c,e)),n._rotating&&(i.bearing=t.number(o,u,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),v)i.setLocationAtPoint(v,y);else{var m=i.zoomScale(i.zoom-a),g=c>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(m));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(u-o),m=t.Point.convert(e.offset),g=a.centerPoint.add(m),v=a.pointLocation(g),y=t.LngLat.convert(e.center||v);this._normalizeCenter(y);var x=a.project(v),b=a.project(y).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,u),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),I=function(t){return C(P)/C(P+_*t)},O=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},z=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(z)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;z=Math.abs(Math.log(T/w))/_,O=function(){return 0},I=function(t){return Math.exp(D*_*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var R=\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*z/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*z,d=1/I(i);a.zoom=1===e?u:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(c,p,e),g=a.centerPoint.add(m));var v=1===e?y:a.unproject(x.add(b.mult(O(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?v.wrap():v,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),bi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};bi.prototype.getDefaultPosition=function(){return\"bottom-right\"},bi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},bi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},bi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},bi.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},bi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},bi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var _i=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};_i.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},_i.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},_i.prototype.getDefaultPosition=function(){return\"bottom-left\"},_i.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},_i.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t){if(t[e].getSource().mapbox_logo)return!0}return!1}},_i.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var wi=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};wi.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},wi.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},wi.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},wi.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Ti={\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},ki=t.window.HTMLImageElement,Ai=t.window.HTMLElement,Mi=t.window.ImageBitmap,Si={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Ei=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Si,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new An(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new wi,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Ti,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Ai))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new yi(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new Sn(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new bi({customAttribution:e.customAttribution})),this.addControl(new _i,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?60:t)>60)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Rn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Rn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Rn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new qe(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new qe(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\". Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof ki||Mi&&r instanceof Mi){var c=t.browser.getImageData(r),u=c.width,f=c.height,h=c.data;this.style.addImage(e,{data:new t.RGBAImage({width:u,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var p=r.width,d=r.height,m=r.data,g=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(m)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:g}),g.onAdd&&g.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof ki||Mi&&r instanceof Mi?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof ki||Mi&&r instanceof Mi);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new _n(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var c=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),u=c.crossFadingFactor();1===u&&u===this._crossFadingFactor||(o=!0,this._crossFadingFactor=u),this.style.update(c)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event(\"idle\"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1){r[e].onRemove(this)}this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Li(this._canvasContainer),Li(this._controlContainer),Li(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(xi);function Li(t){t.parentNode&&t.parentNode.removeChild(t)}var Ci={showCompass:!0,showZoom:!0,visualizePitch:!1},Pi=function(e){var n=this;this.options=t.extend({},Ci,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Pi.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Pi.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},Pi.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ii(this._map,this._compass,this.options.visualizePitch)),this._container},Pi.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Pi.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},Pi.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ii=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Xn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new Zn({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Oi(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ii.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ii.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ii.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ii.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ii.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ii.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ii.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ii.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ii.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var zi={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Di(t,e,r){var n=t.classList;for(var i in zi)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Ri,Fi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");o.setAttributeNS(null,\"display\",\"block\"),o.setAttributeNS(null,\"height\",\"41px\"),o.setAttributeNS(null,\"width\",\"27px\"),o.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"stroke\",\"none\"),s.setAttributeNS(null,\"stroke-width\",\"1\"),s.setAttributeNS(null,\"fill\",\"none\"),s.setAttributeNS(null,\"fill-rule\",\"evenodd\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"fill-rule\",\"nonzero\");var c=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");c.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),c.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,f=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<f.length;u+=1){var h=f[u],p=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");p.setAttributeNS(null,\"opacity\",\"0.04\"),p.setAttributeNS(null,\"cx\",\"10.5\"),p.setAttributeNS(null,\"cy\",\"5.80029008\"),p.setAttributeNS(null,\"rx\",h.rx),p.setAttributeNS(null,\"ry\",h.ry),c.appendChild(p)}var d=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");d.setAttributeNS(null,\"fill\",this._color);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");m.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),d.appendChild(m);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");g.setAttributeNS(null,\"opacity\",\"0.25\"),g.setAttributeNS(null,\"fill\",\"#000000\");var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),g.appendChild(v);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");x.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#000000\"),b.setAttributeNS(null,\"opacity\",\"0.25\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\");var _=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");_.setAttributeNS(null,\"fill\",\"#FFFFFF\"),_.setAttributeNS(null,\"cx\",\"5.5\"),_.setAttributeNS(null,\"cy\",\"5.5\"),_.setAttributeNS(null,\"r\",\"5.4999962\"),x.appendChild(b),x.appendChild(_),l.appendChild(c),l.appendChild(d),l.appendChild(g),l.appendChild(y),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),this._element.addEventListener(\"focus\",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Di(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,zi[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Bi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Ni=0,ji=!1,Ui=function(e){function n(r){e.call(this),this.options=t.extend({},Bi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Ri?n(Ri):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Ri=\"denied\"!==t.state,n(Ri)})):(Ri=!!t.window.navigator.geolocation,n(Ri)),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Ni=0,ji=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&ji)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Fi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Fi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Ni--,ji=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Ni>1?(e={maximumAge:6e5,timeout:0},ji=!0):(e=this.options.positionOptions,ji=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Vi={maxWidth:100,unit:\"metric\"},Hi=function(e){this.options=t.extend({},Vi,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function qi(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;if(l>5280)Gi(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\"));else Gi(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else if(r&&\"nautical\"===r.unit){Gi(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\"))}else s>=1e3?Gi(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):Gi(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function Gi(t,e,r,n){var i,a,o,s=(i=r,a=Math.pow(10,(\"\"+Math.floor(i)).length-1),o=(o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o),a*o),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\" \"+n}Hi.prototype.getDefaultPosition=function(){return\"bottom-left\"},Hi.prototype._onMove=function(){qi(this._map,this._container,this.options)},Hi.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},Hi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},Hi.prototype.setUnit=function(t){this.options.unit=t,qi(this._map,this._container,this.options)};var Yi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};Yi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Yi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Yi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Yi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},Yi.prototype._isFullscreen=function(){return this._fullscreen},Yi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},Yi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Wi={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},Xi=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Wi),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"×\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(e){var n=this,i=this._lngLat||this._trackPointer;if(this._map&&i&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return n._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var a=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),o=this.options.anchor,s=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),\"top-left\":new t.Point(n,n),\"top-right\":new t.Point(-n,n),bottom:new t.Point(0,-r),\"bottom-left\":new t.Point(n,-n),\"bottom-right\":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var i=t.Point.convert(r);return{center:i,top:i,\"top-left\":i,\"top-right\":i,bottom:i,\"bottom-left\":i,\"bottom-right\":i,left:i,right:i}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),\"top-left\":t.Point.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(r[\"top-right\"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),\"bottom-left\":t.Point.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(r[\"bottom-right\"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!o){var l,c=this._container.offsetWidth,u=this._container.offsetHeight;l=a.y+s.bottom.y<u?[\"top\"]:a.y>this._map.transform.height-u?[\"bottom\"]:[],a.x<c/2?l.push(\"left\"):a.x>this._map.transform.width-c/2&&l.push(\"right\"),o=0===l.length?\"bottom\":l.join(\"-\")}var f=a.add(s[o]).round();r.setTransform(this._container,zi[o]+\" translate(\"+f.x+\"px,\"+f.y+\"px)\"),Di(this._container,o,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);var Zi={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Ei,NavigationControl:Pi,GeolocateControl:Ui,AttributionControl:bi,ScaleControl:Hi,FullscreenControl:Yi,Popup:Xi,Marker:Fi,Style:qe,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){Bt().acquire(zt)},clearPrewarmedResources:function(){var t=Rt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(zt),Rt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. 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+ " * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc\n",
+ " * @license MIT\n",
+ " * @preserve Project Home: https://github.com/voidqk/polybooljs\n",
+ " */\n",
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r=0,n=t[t.length-1][0],i=t[t.length-1][1],a=[],o=0;o<t.length;o++){var s=t[o][0],l=t[o][1];a.push([s,l]),r+=l*n-s*i,n=s,i=l}return r<0!==e&&a.reverse(),a.push([a[0][0],a[0][1]]),a}var u=[];function f(t){var e=[c(t.region,!1)];u.push(e);for(var r=0;r<t.children.length;r++)e.push(h(t.children[r]))}function h(t){for(var e=0;e<t.children.length;e++)f(t.children[e]);return c(t.region,!0)}for(s=0;s<a.children.length;s++)f(a.children[s]);return u.length<=0?{type:\"Polygon\",coordinates:[]}:1==u.length?{type:\"Polygon\",coordinates:u[0]}:{type:\"MultiPolygon\",coordinates:u}}};e.exports=n},{}],258:[function(t,e,r){var n=t(\"./linked-list\");e.exports=function(t,e,r){function i(t,e,n){return{id:r?r.segmentId():-1,start:t,end:e,myFill:{above:n.myFill.above,below:n.myFill.below},otherFill:null}}var a=n.create();function o(t,r){a.insertBefore(t,(function(n){return function(t,r,n,i,a,o){var s=e.pointsCompare(r,a);return 0!==s?s:e.pointsSame(n,o)?0:t!==i?t?1:-1:e.pointAboveOrOnLine(n,i?a:o,i?o:a)?1:-1}(t.isStart,t.pt,r,n.isStart,n.pt,n.other.pt)<0}))}function s(t,e){var r=function(t,e){var r=n.node({isStart:!0,pt:t.start,seg:t,primary:e,other:null,status:null});return o(r,t.end),r}(t,e);return function(t,e,r){var i=n.node({isStart:!1,pt:e.end,seg:e,primary:r,other:t,status:null});t.other=i,o(i,t.pt)}(r,t,e),r}function l(t,e){var n=i(e,t.seg.end,t.seg);return function(t,e){r&&r.segmentChop(t.seg,e),t.other.remove(),t.seg.end=e,t.other.pt=e,o(t.other,t.pt)}(t,e),s(n,t.primary)}function c(i,o){var s=n.create();function c(t){return s.findTransition((function(r){var n,i,a,o,s,l;return(n=t,i=r.ev,a=n.seg.start,o=n.seg.end,s=i.seg.start,l=i.seg.end,e.pointsCollinear(a,s,l)?e.pointsCollinear(o,s,l)||e.pointAboveOrOnLine(o,s,l)?1:-1:e.pointAboveOrOnLine(a,s,l)?1:-1)>0}))}function u(t,n){var i=t.seg,a=n.seg,o=i.start,s=i.end,c=a.start,u=a.end;r&&r.checkIntersection(i,a);var f=e.linesIntersect(o,s,c,u);if(!1===f){if(!e.pointsCollinear(o,s,c))return!1;if(e.pointsSame(o,u)||e.pointsSame(s,c))return!1;var h=e.pointsSame(o,c),p=e.pointsSame(s,u);if(h&&p)return n;var d=!h&&e.pointBetween(o,c,u),m=!p&&e.pointBetween(s,c,u);if(h)return m?l(n,s):l(t,u),n;d&&(p||(m?l(n,s):l(t,u)),l(n,o))}else 0===f.alongA&&(-1===f.alongB?l(t,c):0===f.alongB?l(t,f.pt):1===f.alongB&&l(t,u)),0===f.alongB&&(-1===f.alongA?l(n,o):0===f.alongA?l(n,f.pt):1===f.alongA&&l(n,s));return!1}for(var f=[];!a.isEmpty();){var h=a.getHead();if(r&&r.vert(h.pt[0]),h.isStart){r&&r.segmentNew(h.seg,h.primary);var p=c(h),d=p.before?p.before.ev:null,m=p.after?p.after.ev:null;function g(){if(d){var t=u(h,d);if(t)return t}return!!m&&u(h,m)}r&&r.tempStatus(h.seg,!!d&&d.seg,!!m&&m.seg);var v,y=g();if(y){var x;if(t)(x=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below)&&(y.seg.myFill.above=!y.seg.myFill.above);else y.seg.otherFill=h.seg.myFill;r&&r.segmentUpdate(y.seg),h.other.remove(),h.remove()}if(a.getHead()!==h){r&&r.rewind(h.seg);continue}if(t)x=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below,h.seg.myFill.below=m?m.seg.myFill.above:i,h.seg.myFill.above=x?!h.seg.myFill.below:h.seg.myFill.below;else if(null===h.seg.otherFill)v=m?h.primary===m.primary?m.seg.otherFill.above:m.seg.myFill.above:h.primary?o:i,h.seg.otherFill={above:v,below:v};r&&r.status(h.seg,!!d&&d.seg,!!m&&m.seg),h.other.status=p.insert(n.node({ev:h}))}else{var b=h.status;if(null===b)throw new Error(\"PolyBool: Zero-length segment detected; your epsilon is probably too small or too large\");if(s.exists(b.prev)&&s.exists(b.next)&&u(b.prev.ev,b.next.ev),r&&r.statusRemove(b.ev.seg),b.remove(),!h.primary){var _=h.seg.myFill;h.seg.myFill=h.seg.otherFill,h.seg.otherFill=_}f.push(h.seg)}a.getHead().remove()}return r&&r.done(),f}return t?{addRegion:function(t){for(var n,i,a,o=t[t.length-1],l=0;l<t.length;l++){n=o,o=t[l];var c=e.pointsCompare(n,o);0!==c&&s((i=c<0?n:o,a=c<0?o:n,{id:r?r.segmentId():-1,start:i,end:a,myFill:{above:null,below:null},otherFill:null}),!0)}},calculate:function(t){return c(t,!1)}}:{calculate:function(t,e,r,n){return t.forEach((function(t){s(i(t.start,t.end,t),!0)})),r.forEach((function(t){s(i(t.start,t.end,t),!1)})),c(e,n)}}}},{\"./linked-list\":259}],259:[function(t,e,r){e.exports={create:function(){var t={root:{root:!0,next:null},exists:function(e){return null!==e&&e!==t.root},isEmpty:function(){return null===t.root.next},getHead:function(){return t.root.next},insertBefore:function(e,r){for(var n=t.root,i=t.root.next;null!==i;){if(r(i))return e.prev=i.prev,e.next=i,i.prev.next=e,void(i.prev=e);n=i,i=i.next}n.next=e,e.prev=n,e.next=null},findTransition:function(e){for(var r=t.root,n=t.root.next;null!==n&&!e(n);)r=n,n=n.next;return{before:r===t.root?null:r,after:n,insert:function(t){return t.prev=r,t.next=n,r.next=t,null!==n&&(n.prev=t),t}}}};return t},node:function(t){return t.prev=null,t.next=null,t.remove=function(){t.prev.next=t.next,t.next&&(t.next.prev=t.prev),t.prev=null,t.next=null},t}}},{}],260:[function(t,e,r){e.exports=function(t,e,r){var n=[],i=[];return t.forEach((function(t){var a=t.start,o=t.end;if(e.pointsSame(a,o))console.warn(\"PolyBool: Warning: Zero-length segment detected; your epsilon is probably too small or too large\");else{r&&r.chainStart(t);for(var s={index:0,matches_head:!1,matches_pt1:!1},l={index:0,matches_head:!1,matches_pt1:!1},c=s,u=0;u<n.length;u++){var f=(g=n[u])[0],h=(g[1],g[g.length-1]);g[g.length-2];if(e.pointsSame(f,a)){if(k(u,!0,!0))break}else if(e.pointsSame(f,o)){if(k(u,!0,!1))break}else if(e.pointsSame(h,a)){if(k(u,!1,!0))break}else if(e.pointsSame(h,o)&&k(u,!1,!1))break}if(c===s)return n.push([a,o]),void(r&&r.chainNew(a,o));if(c===l){r&&r.chainMatch(s.index);var p=s.index,d=s.matches_pt1?o:a,m=s.matches_head,g=n[p],v=m?g[0]:g[g.length-1],y=m?g[1]:g[g.length-2],x=m?g[g.length-1]:g[0],b=m?g[g.length-2]:g[1];return e.pointsCollinear(y,v,d)&&(m?(r&&r.chainRemoveHead(s.index,d),g.shift()):(r&&r.chainRemoveTail(s.index,d),g.pop()),v=y),e.pointsSame(x,d)?(n.splice(p,1),e.pointsCollinear(b,x,v)&&(m?(r&&r.chainRemoveTail(s.index,v),g.pop()):(r&&r.chainRemoveHead(s.index,v),g.shift())),r&&r.chainClose(s.index),void i.push(g)):void(m?(r&&r.chainAddHead(s.index,d),g.unshift(d)):(r&&r.chainAddTail(s.index,d),g.push(d)))}var _=s.index,w=l.index;r&&r.chainConnect(_,w);var T=n[_].length<n[w].length;s.matches_head?l.matches_head?T?(A(_),M(_,w)):(A(w),M(w,_)):M(w,_):l.matches_head?M(_,w):T?(A(_),M(w,_)):(A(w),M(_,w))}function k(t,e,r){return c.index=t,c.matches_head=e,c.matches_pt1=r,c===s?(c=l,!1):(c=null,!0)}function A(t){r&&r.chainReverse(t),n[t].reverse()}function M(t,i){var a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],c=o[0],u=o[1];e.pointsCollinear(l,s,c)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,c,u)&&(r&&r.chainRemoveHead(i,c),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},{}],261:[function(t,e,r){function n(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var i={union:function(t,e){return n(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],e)},intersect:function(t,e){return n(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],e)},difference:function(t,e){return n(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],e)},differenceRev:function(t,e){return n(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],e)},xor:function(t,e){return n(t,[0,2,1,0,2,0,0,1,1,0,0,2,0,1,2,0],e)}};e.exports=i},{}],262:[function(t,e,r){\"use strict\";var n=t(\"stream\").Transform,i=t(\"stream-parser\");function a(){n.call(this,{readableObjectMode:!0})}function o(t,e,r){Error.call(this),Error.captureStackTrace?Error.captureStackTrace(this,this.constructor):this.stack=(new Error).stack||\"\",this.name=this.constructor.name,this.message=t,e&&(this.code=e),r&&(this.statusCode=r)}a.prototype=Object.create(n.prototype),a.prototype.constructor=a,i(a.prototype),r.ParserStream=a,r.sliceEq=function(t,e,r){for(var n=e,i=0;i<r.length;)if(t[n++]!==r[i++])return!1;return!0},r.str2arr=function(t,e){var r=[],n=0;if(e&&\"hex\"===e)for(;n<t.length;)r.push(parseInt(t.slice(n,n+2),16)),n+=2;else for(;n<t.length;n++)r.push(255&t.charCodeAt(n));return r},r.readUInt16LE=function(t,e){return t[e]|t[e+1]<<8},r.readUInt16BE=function(t,e){return t[e+1]|t[e]<<8},r.readUInt32LE=function(t,e){return t[e]|t[e+1]<<8|t[e+2]<<16|16777216*t[e+3]},r.readUInt32BE=function(t,e){return t[e+3]|t[e+2]<<8|t[e+1]<<16|16777216*t[e]},o.prototype=Object.create(Error.prototype),o.prototype.constructor=o,r.ProbeError=o},{stream:285,\"stream-parser\":301}],263:[function(t,e,r){\"use strict\";function n(t,e){var r=new Error(t);return r.code=e,r}function i(t){try{return decodeURIComponent(escape(t))}catch(e){return t}}function a(t,e,r){this.input=t.subarray(e,r),this.start=e;var i=String.fromCharCode.apply(null,this.input.subarray(0,4));if(\"II*\\0\"!==i&&\"MM\\0*\"!==i)throw n(\"invalid TIFF signature\",\"EBADDATA\");this.big_endian=\"M\"===i[0]}a.prototype.each=function(t){this.aborted=!1;var e=this.read_uint32(4);for(this.ifds_to_read=[{id:0,offset:e}];this.ifds_to_read.length>0&&!this.aborted;){var r=this.ifds_to_read.shift();r.offset&&this.scan_ifd(r.id,r.offset,t)}},a.prototype.read_uint16=function(t){var e=this.input;if(t+2>e.length)throw n(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?256*e[t]+e[t+1]:e[t]+256*e[t+1]},a.prototype.read_uint32=function(t){var e=this.input;if(t+4>e.length)throw n(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?16777216*e[t]+65536*e[t+1]+256*e[t+2]+e[t+3]:e[t]+256*e[t+1]+65536*e[t+2]+16777216*e[t+3]},a.prototype.is_subifd_link=function(t,e){return 0===t&&34665===e||0===t&&34853===e||34665===t&&40965===e},a.prototype.exif_format_length=function(t){switch(t){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 0}},a.prototype.exif_format_read=function(t,e){var r;switch(t){case 1:case 2:return r=this.input[e];case 6:return(r=this.input[e])|33554430*(128&r);case 3:return r=this.read_uint16(e);case 8:return(r=this.read_uint16(e))|131070*(32768&r);case 4:return r=this.read_uint32(e);case 9:return 0|(r=this.read_uint32(e));case 5:case 10:case 11:case 12:case 7:default:return null}},a.prototype.scan_ifd=function(t,e,r){var a=this.read_uint16(e);e+=2;for(var o=0;o<a;o++){var s=this.read_uint16(e),l=this.read_uint16(e+2),c=this.read_uint32(e+4),u=this.exif_format_length(l),f=c*u,h=f<=4?e+8:this.read_uint32(e+8),p=!1;if(h+f>this.input.length)throw n(\"unexpected EOF\",\"EBADDATA\");for(var d=[],m=h,g=0;g<c;g++,m+=u){var v=this.exif_format_read(l,m);if(null===v){d=null;break}d.push(v)}if(Array.isArray(d)&&2===l&&(d=i(String.fromCharCode.apply(null,d)))&&\"\\0\"===d[d.length-1]&&(d=d.slice(0,-1)),this.is_subifd_link(t,s)&&Array.isArray(d)&&Number.isInteger(d[0])&&d[0]>0&&(this.ifds_to_read.push({id:s,offset:d[0]}),p=!0),!1===r({is_big_endian:this.big_endian,ifd:t,tag:s,format:l,count:c,entry_offset:e+this.start,data_length:f,data_offset:h+this.start,value:d,is_subifd_link:p}))return void(this.aborted=!0);e+=12}0===t&&this.ifds_to_read.push({id:1,offset:this.read_uint32(e)})},e.exports.ExifParser=a,e.exports.get_orientation=function(t){var e=0;try{return new a(t,0,t.length).each((function(t){if(0===t.ifd&&274===t.tag&&Array.isArray(t.value))return e=t.value[0],!1})),e}catch(t){return-1}}},{}],264:[function(t,e,r){\"use strict\";var n=t(\"./common\").readUInt16BE,i=t(\"./common\").readUInt32BE;function a(t,e){if(t.length<4+e)return null;var r=i(t,e);return t.length<r+e||r<8?null:{boxtype:String.fromCharCode.apply(null,t.slice(e+4,e+8)),data:t.slice(e+8,e+r),end:e+r}}function o(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;switch(n.boxtype){case\"ispe\":e.sizes.push({width:i(n.data,4),height:i(n.data,8)});break;case\"irot\":e.transforms.push({type:\"irot\",value:3&n.data[0]});break;case\"imir\":e.transforms.push({type:\"imir\",value:1&n.data[0]})}r=n.end}}function s(t,e,r){for(var n=0,i=0;i<r;i++)n=256*n+(t[e+i]||0);return n}function l(t,e){for(var r=t[4]>>4&15,i=15&t[4],a=t[5]>>4&15,o=n(t,6),l=8,c=0;c<o;c++){var u=n(t,l),f=n(t,l+=2),h=s(t,l+=2,a),p=n(t,l+=a);if(l+=2,0===f&&1===p){var d=s(t,l,r),m=s(t,l+r,i);e.item_loc[u]={length:m,offset:d+h}}l+=p*(r+i)}}function c(t,e){for(var r=n(t,4),i=6,o=0;o<r;o++){var s=a(t,i);if(!s)break;if(\"infe\"===s.boxtype){for(var l=n(s.data,4),c=\"\",u=8;u<s.data.length&&s.data[u];u++)c+=String.fromCharCode(s.data[u]);e.item_inf[c]=l}i=s.end}}function u(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;\"ipco\"===n.boxtype&&o(n.data,e),r=n.end}}e.exports.unbox=a,e.exports.readSizeFromMeta=function(t){var e={sizes:[],transforms:[],item_inf:{},item_loc:{}};if(function(t,e){for(var r=4;;){var n=a(t,r);if(!n)break;\"iprp\"===n.boxtype&&u(n.data,e),\"iloc\"===n.boxtype&&l(n.data,e),\"iinf\"===n.boxtype&&c(n.data,e),r=n.end}}(t,e),e.sizes.length){var r,n,i,o=(r=e.sizes,n=r.reduce((function(t,e){return t.width>e.width||t.width===e.width&&t.height>e.height?t:e})),i=r.reduce((function(t,e){return t.height>e.height||t.height===e.height&&t.width>e.width?t:e})),n.width>i.height||n.width===i.height&&n.height>i.width?n:i),s=1;e.transforms.forEach((function(t){var e={1:6,2:5,3:8,4:7,5:4,6:3,7:2,8:1},r={1:4,2:3,3:2,4:1,5:6,6:5,7:8,8:7};if(\"imir\"===t.type&&(s=0===t.value?r[s]:e[s=e[s=r[s]]]),\"irot\"===t.type)for(var n=0;n<t.value;n++)s=e[s]}));var f=null;return e.item_inf.Exif&&(f=e.item_loc[e.item_inf.Exif]),{width:o.width,height:o.height,orientation:e.transforms.length?s:null,variants:e.sizes,exif_location:f}}},e.exports.getMimeType=function(t){var e=String.fromCharCode.apply(null,t.slice(0,4)),r={};r[e]=!0;for(var 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h=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},{\"array-bounds\":71,\"color-normalize\":89,\"flatten-vertex-data\":191,\"object-assign\":247,\"pick-by-alias\":253,\"to-float32\":313,\"update-diff\":329}],280:[function(t,e,r){\"use strict\";var n=t(\"color-normalize\"),i=t(\"array-bounds\"),a=t(\"object-assign\"),o=t(\"glslify\"),s=t(\"pick-by-alias\"),l=t(\"flatten-vertex-data\"),c=t(\"earcut\"),u=t(\"array-normalize\"),f=t(\"to-float32\"),h=f.float32,p=f.fract32,d=t(\"es6-weak-map\"),m=t(\"parse-rect\"),g=t(\"array-find-index\");function v(t,e){if(!(this instanceof v))return new v(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=v.shaders.has(t)?v.shaders.get(t):v.shaders.set(t,v.createShaders(t)).get(t),this.update(e)}e.exports=v,v.dashMult=2,v.maxPatternLength=256,v.precisionThreshold=3e6,v.maxPoints=1e4,v.maxLines=2048,v.shaders=new d,v.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashTexture:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashLength:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n + positionFract * scale + translateFract\\n + position * scaleFract\\n + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n vec2 adjustedScale;\\n adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) < length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) < length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id, miterMode;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * 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t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>v.precisionThreshold||e.scale[1]*e.viewport.height>v.precisionThreshold||\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=v.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},v.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin 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Uint8Array})},t=a({},v.defaults,t)),null!=t.thickness&&(d.thickness=parseFloat(t.thickness)),null!=t.opacity&&(d.opacity=parseFloat(t.opacity)),null!=t.miterLimit&&(d.miterLimit=parseFloat(t.miterLimit)),null!=t.overlay&&(d.overlay=!!t.overlay,f<v.maxLines&&(d.depth=2*(v.maxLines-1-f%v.maxLines)/v.maxLines-1)),null!=t.join&&(d.join=t.join),null!=t.hole&&(d.hole=t.hole),null!=t.fill&&(d.fill=t.fill?n(t.fill,\"uint8\"):null),null!=t.viewport&&(d.viewport=m(t.viewport)),d.viewport||(d.viewport=m([o.drawingBufferWidth,o.drawingBufferHeight])),null!=t.close&&(d.close=t.close),null===t.positions&&(t.positions=[]),t.positions){var y,x;if(t.positions.x&&t.positions.y){var b=t.positions.x,_=t.positions.y;x=d.count=Math.max(b.length,_.length),y=new Float64Array(2*x);for(var w=0;w<x;w++)y[2*w]=b[w],y[2*w+1]=_[w]}else y=l(t.positions,\"float64\"),x=d.count=Math.floor(y.length/2);var T=d.bounds=i(y,2);if(d.fill){for(var k=[],A={},M=0,S=0,E=0,L=d.count;S<L;S++){var C=y[2*S],P=y[2*S+1];isNaN(C)||isNaN(P)||null==C||null==P?(C=y[2*M],P=y[2*M+1],A[S]=M):M=S,k[E++]=C,k[E++]=P}if(t.splitNull){d.count-1 in A||(A[d.count]=d.count-1);var I=Object.keys(A).map(Number).sort((function(t,e){return t-e})),O=[],z=0,D=null!=d.hole?d.hole[0]:null;if(null!=D){var R=g(I,(function(t){return t>=D}));(I=I.slice(0,R)).push(D)}for(var F=function(t){var e=k.slice(2*z,2*I[t]).concat(D?k.slice(2*D):[]),r=(d.hole||[]).map((function(e){return e-D+(I[t]-z)})),n=c(e,r);n=n.map((function(e){return e+z+(e+z<I[t]?0:D-I[t])})),O.push.apply(O,n),z=I[t]+1},B=0;B<I.length;B++)F(B);for(var N=0,j=O.length;N<j;N++)null!=A[O[N]]&&(O[N]=A[O[N]]);d.triangles=O}else{for(var U=c(k,d.hole||[]),V=0,H=U.length;V<H;V++)null!=A[U[V]]&&(U[V]=A[U[V]]);d.triangles=U}}var q=new Float64Array(y);u(q,2,T);var G=new Float64Array(2*x+6);d.close?y[0]===y[2*x-2]&&y[1]===y[2*x-1]?(G[0]=q[2*x-4],G[1]=q[2*x-3]):(G[0]=q[2*x-2],G[1]=q[2*x-1]):(G[0]=q[0],G[1]=q[1]),G.set(q,2),d.close?y[0]===y[2*x-2]&&y[1]===y[2*x-1]?(G[2*x+2]=q[2],G[2*x+3]=q[3],d.count-=1):(G[2*x+2]=q[0],G[2*x+3]=q[1],G[2*x+4]=q[2],G[2*x+5]=q[3]):(G[2*x+2]=q[2*x-2],G[2*x+3]=q[2*x-1],G[2*x+4]=q[2*x-2],G[2*x+5]=q[2*x-1]);var Y=h(G);d.positionBuffer(Y);var W=p(G,Y);d.positionFractBuffer(W)}if(t.range?d.range=t.range:d.range||(d.range=d.bounds),(t.range||t.positions)&&d.count){var X=d.bounds,Z=X[2]-X[0],J=X[3]-X[1],K=d.range[2]-d.range[0],Q=d.range[3]-d.range[1];d.scale=[Z/K,J/Q],d.translate=[-d.range[0]/K+X[0]/K||0,-d.range[1]/Q+X[1]/Q||0],d.scaleFract=p(d.scale),d.translateFract=p(d.translate)}if(t.dashes){var $,tt=0;if(!t.dashes||t.dashes.length<2)tt=1,$=new Uint8Array([255,255,255,255,255,255,255,255]);else{tt=0;for(var et=0;et<t.dashes.length;++et)tt+=t.dashes[et];$=new Uint8Array(tt*v.dashMult);for(var rt=0,nt=255,it=0;it<2;it++)for(var at=0;at<t.dashes.length;++at){for(var ot=0,st=t.dashes[at]*v.dashMult*.5;ot<st;++ot)$[rt++]=nt;nt^=255}}d.dashLength=tt,d.dashTexture({channels:1,data:$,width:$.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var lt=d.count,ct=t.color;ct||(ct=\"transparent\");var ut=new Uint8Array(4*lt+4);if(Array.isArray(ct)&&\"number\"!=typeof ct[0]){for(var ft=0;ft<lt;ft++){var ht=n(ct[ft],\"uint8\");ut.set(ht,4*ft)}ut.set(n(ct[0],\"uint8\"),4*lt)}else for(var pt=n(ct,\"uint8\"),dt=0;dt<lt+1;dt++)ut.set(pt,4*dt);d.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:ut})}}else e.passes[f]=null})),t.length<this.passes.length){for(var f=t.length;f<this.passes.length;f++){var d=this.passes[f];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var y=[],x=0;x<this.passes.length;x++)null!==this.passes[x]&&y.push(this.passes[x]);return this.passes=y,this}},v.prototype.destroy=function(){return 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s=t(\"color-normalize\"),l=t(\"array-bounds\"),c=t(\"color-id\"),u=t(\"@plotly/point-cluster\"),f=t(\"object-assign\"),h=t(\"glslify\"),p=t(\"pick-by-alias\"),d=t(\"update-diff\"),m=t(\"flatten-vertex-data\"),g=t(\"is-iexplorer\"),v=t(\"to-float32\"),y=t(\"parse-rect\"),x=b;function b(t,e){var r=this;if(!(this instanceof b))return new b(t,e);\"function\"==typeof t?(e||(e={}),e.regl=t):(e=t,t=null),e&&e.length&&(e.positions=e);var n,i=(t=e.regl)._gl,a=[];this.tooManyColors=g,n=t.texture({data:new Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),f(this,{regl:t,gl:i,groups:[],markerCache:[null],markerTextures:[null],palette:a,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:i.canvas}),this.update(e);var o={uniforms:{constPointSize:!!e.constPointSize,opacity:t.prop(\"opacity\"),paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},pixelRatio:t.context(\"pixelRatio\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),markerTexture:t.prop(\"markerTexture\"),paletteTexture:n},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return e.yAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:4}},size:function(t,e){return e.size.length?{buffer:e.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(255*e.size/r.maxSize)]}},borderSize:function(t,e){return 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highp float;\\n#define GLSLIFY 1\\n\\nuniform float opacity;\\nuniform sampler2D markerTexture;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat smoothStep(float x, float y) {\\n return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n float dist = texture2D(markerTexture, gl_PointCoord).r, delta = fragWidth;\\n\\n // max-distance alpha\\n if (dist < 0.003) discard;\\n\\n // null-border case\\n if (fragBorderColorLevel == fragColorLevel || fragBorderColor.a == 0.) {\\n float colorAmt = smoothstep(.5 - delta, .5 + delta, dist);\\n gl_FragColor = vec4(fragColor.rgb, colorAmt * fragColor.a * opacity);\\n }\\n else {\\n float borderColorAmt = smoothstep(fragBorderColorLevel - delta, fragBorderColorLevel + delta, dist);\\n float colorAmt = smoothstep(fragColorLevel - delta, fragColorLevel + delta, dist);\\n\\n vec4 color = fragBorderColor;\\n color.a *= borderColorAmt;\\n color = mix(color, fragColor, colorAmt);\\n color.a *= opacity;\\n\\n gl_FragColor = color;\\n }\\n\\n}\\n\"]),s.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform bool constPointSize;\\nuniform float pixelRatio;\\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\\nuniform sampler2D paletteTexture;\\n\\nconst float maxSize = 100.;\\nconst float borderLevel = .5;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n return isDirect ? id / 255. : texture2D(paletteTexture,\\n vec2(\\n (id.x + .5) / paletteSize.x,\\n (id.y + .5) / paletteSize.y\\n )\\n );\\n}\\n\\nvoid main() {\\n // ignore inactive points\\n if (isActive == 0.) return;\\n\\n vec2 position = vec2(x, y);\\n vec2 positionFract = vec2(xFract, yFract);\\n\\n vec4 color = getColor(colorId);\\n vec4 borderColor = getColor(borderColorId);\\n\\n float size = size * maxSize / 255.;\\n float borderSize = borderSize * maxSize / 255.;\\n\\n gl_PointSize = 2. * size * pointSizeScale;\\n fragPointSize = size * pixelRatio;\\n\\n vec2 pos = (position + translate) * scale\\n + (positionFract + translateFract) * scale\\n + (position + translate) * scaleFract\\n + (positionFract + translateFract) * scaleFract;\\n\\n gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n fragColor = color;\\n fragBorderColor = borderColor;\\n fragWidth = 1. / gl_PointSize;\\n\\n fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\"]),this.drawMarker=t(s);var l=f({},o);l.frag=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nuniform float opacity;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform bool constPointSize;\\nuniform float pixelRatio;\\nuniform vec2 paletteSize, scale, scaleFract, translate, translateFract;\\nuniform sampler2D paletteTexture;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n return isDirect ? id / 255. : texture2D(paletteTexture,\\n vec2(\\n (id.x + .5) / paletteSize.x,\\n (id.y + .5) / paletteSize.y\\n )\\n );\\n}\\n\\nvoid main() {\\n // ignore inactive points\\n if (isActive == 0.) return;\\n\\n vec2 position = vec2(x, y);\\n vec2 positionFract = vec2(xFract, yFract);\\n\\n vec4 color = getColor(colorId);\\n vec4 borderColor = getColor(borderColorId);\\n\\n float size = size * maxSize / 255.;\\n float borderSize = borderSize * maxSize / 255.;\\n\\n gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n vec2 pos = (position + translate) * scale\\n + (positionFract + translateFract) * scale\\n + (position + translate) * scaleFract\\n + (positionFract + translateFract) * scaleFract;\\n\\n gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n fragColor = color;\\n fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n fragWidth = 1. / gl_PointSize;\\n}\\n\"]),g&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}b.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},b.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},b.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},b.prototype.drawItem=function(t,e){var r=this.groups,n=r[t];if(\"number\"==typeof e&&(t=e,n=r[e],e=null),n&&n.count&&n.opacity){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,e));for(var a=[],o=1;o<n.activation.length;o++)n.activation[o]&&(!0===n.activation[o]||n.activation[o].data.length)&&a.push.apply(a,i(this.getMarkerDrawOptions(o,n,e)));a.length&&this.drawMarker(a)}},b.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,c=e.count;this.regl;if(!a)return r?[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var u=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(c),m=0;m<r.length;m++){var g=r[m];d[g]=p?p[g]:1}l.subdata(d)}for(var v=h.length;v--;){var y=n(h[v],2),x=y[0],b=y[1];u.push(f({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return u},b.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,s=this.maxSize,c=this.maxColors,h=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=p(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(i[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),positionBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"}),positionFractBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"})},e=f({},b.defaults,e)),e.positions&&!(\"marker\"in e)&&(e.marker=n.marker,delete n.marker),e.marker&&!(\"positions\"in e)&&(e.positions=n.positions,delete n.positions);var g=0,x=0;if(d(n,e,[{snap:!0,size:function(t,e){return null==t&&(t=b.defaults.size),g+=t&&t.length?1:0,t},borderSize:function(t,e){return null==t&&(t=b.defaults.borderSize),g+=t&&t.length?1:0,t},opacity:parseFloat,color:function(e,r){return null==e&&(e=b.defaults.color),e=t.updateColor(e),x++,e},borderColor:function(e,r){return null==e&&(e=b.defaults.borderColor),e=t.updateColor(e),x++,e},bounds:function(t,e,r){return\"range\"in r||(r.range=null),t},positions:function(t,e,r){var n=e.snap,i=e.positionBuffer,a=e.positionFractBuffer,s=e.selectionBuffer;if(t.x||t.y)return t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=m(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?l(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}var p=v.float32(t);return i({data:p,usage:\"dynamic\"}),a({data:v.fract32(t,p),usage:\"dynamic\"}),s({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach((function(t){return t&&t.destroy&&t.destroy()})),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var c=t.addMarker(e[s]);a[c]||(a[c]=new Uint8Array(r.count)),a[c][s]=1}for(var u=0;u<a.length;u++)if(a[u]){var f={data:a[u],type:\"uint8\",usage:\"static\"};i[u]?i[u](f):i[u]=o.buffer(f),i[u].data=a[u]}}else{i[t.addMarker(e)]=!0}return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=v.fract(e.scale),e.translateFract=v.fract(e.translate),t},viewport:function(t){return y(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),g){var _=n,w=_.count,T=_.size,k=_.borderSize,A=_.sizeBuffer,M=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)M[2*S]=Math.round(255*(null==T[S]?T:T[S])/s),M[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/s);A({data:M,usage:\"dynamic\"})}if(x){var E,L=n,C=L.count,P=L.color,I=L.borderColor,O=L.colorBuffer;if(t.tooManyColors){if(P.length||I.length){E=new Uint8Array(8*C);for(var z=0;z<C;z++){var D=P[z];E[8*z]=h[4*D],E[8*z+1]=h[4*D+1],E[8*z+2]=h[4*D+2],E[8*z+3]=h[4*D+3];var R=I[z];E[8*z+4]=h[4*R],E[8*z+5]=h[4*R+1],E[8*z+6]=h[4*R+2],E[8*z+7]=h[4*R+3]}}}else if(P.length||I.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%c,E[4*F+1]=Math.floor(P[F]/c)),null!=I[F]&&(E[4*F+2]=I[F]%c,E[4*F+3]=Math.floor(I[F]/c))}O({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},b.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},b.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var a=[];if(Array.isArray(t))for(var o=0;o<t.length;o+=4)a.push(t.slice(o,o+4));else for(var l=0;l<t.length;l+=4)a.push(t.subarray(l,l+4));t=a}for(var u=0;u<t.length;u++){var f=t[u];f=s(f,\"uint8\");var h=c(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[u]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},b.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},b.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var _=t(\"object-assign\");e.exports=function(t,e){var r=new x(t,e),n=r.render.bind(r);return _(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},{\"@plotly/point-cluster\":59,\"array-bounds\":71,\"color-id\":87,\"color-normalize\":89,\"flatten-vertex-data\":191,glslify:227,\"is-iexplorer\":233,\"object-assign\":247,\"parse-rect\":249,\"pick-by-alias\":253,\"to-float32\":313,\"update-diff\":329}],282:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"pick-by-alias\"),a=t(\"array-bounds\"),o=t(\"raf\"),s=t(\"array-range\"),l=t(\"parse-rect\"),c=t(\"flatten-vertex-data\");function u(t,e){if(!(this instanceof u))return new u(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x+s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y+l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,c=0;c<l.length;c++)i.push(this.passes[l[c]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},u.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values dimensions samples x\",snap:\"snap cluster\",size:\"sizes size radius\",color:\"colors color fill fill-color fillColor\",opacity:\"opacity alpha transparency opaque\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",borderColor:\"borderColors borderColor bordercolor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range ranges databox dataBox\",viewport:\"viewport viewBox viewbox\",domain:\"domain domains area areas\",padding:\"pad padding paddings pads margin margins\",transpose:\"transpose transposed\",diagonal:\"diagonal diag showDiagonal\",upper:\"upper up top upperhalf upperHalf showupperhalf showUpper showUpperHalf\",lower:\"lower low bottom lowerhalf lowerHalf showlowerhalf showLowerHalf showLower\"}),s=this.traces[t]||(this.traces[t]={id:t,buffer:r.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array}),color:\"black\",marker:null,size:12,borderColor:\"transparent\",borderSize:1,viewport:l([r._gl.drawingBufferWidth,r._gl.drawingBufferHeight]),padding:[0,0,0,0],opacity:1,diagonal:!0,upper:!0,lower:!0});if(null!=o.color&&(s.color=o.color),null!=o.size&&(s.size=o.size),null!=o.marker&&(s.marker=o.marker),null!=o.borderColor&&(s.borderColor=o.borderColor),null!=o.borderSize&&(s.borderSize=o.borderSize),null!=o.opacity&&(s.opacity=o.opacity),o.viewport&&(s.viewport=l(o.viewport)),null!=o.diagonal&&(s.diagonal=o.diagonal),null!=o.upper&&(s.upper=o.upper),null!=o.lower&&(s.lower=o.lower),o.data){s.buffer(c(o.data)),s.columns=o.data.length,s.count=o.data[0].length,s.bounds=[];for(var u=0;u<s.columns;u++)s.bounds[u]=a(o.data[u],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var m=s.columns,g=s.count,v=s.viewport.width,y=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=v/m,w=y/m;s.passes=[];for(var T=0;T<m;T++)for(var k=0;k<m;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var A=f(s.id,T,k),M=this.passes[A]||(this.passes[A]={});if(o.data&&(o.transpose?M.positions={x:{buffer:s.buffer,offset:k,count:g,stride:m},y:{buffer:s.buffer,offset:T,count:g,stride:m}}:M.positions={x:{buffer:s.buffer,offset:k*g,count:g},y:{buffer:s.buffer,offset:T*g,count:g}},M.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),L=E[0],C=E[1],P=E[2],I=E[3];M.viewport=[x+L*v+S[0],b+C*y+S[1],x+P*v-S[2],b+I*y-S[3]]}else M.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(M.color=s.color),o.size&&(M.size=s.size),o.marker&&(M.marker=s.marker),o.borderSize&&(M.borderSize=s.borderSize),o.borderColor&&(M.borderColor=s.borderColor),o.opacity&&(M.opacity=s.opacity),o.range&&(M.range=n?h(s.range,T,k):s.range||M.bounds),s.passes.push(A)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var c=e[i],u=this.traces[i],f=u.passes,h=u.passOffset;f=f.map((function(t,e){n[h+e]=c}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return 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e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=a},{\"../main\":346,\"object-assign\":247}],335:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.hebrew=a},{\"../main\":346,\"object-assign\":247}],337:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Islamic\",jdEpoch:1948439.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Islamic\",epochs:[\"BH\",\"AH\"],monthNames:[\"Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' al-thani\",\"Jumada al-awwal\",\"Jumada al-thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-ahad\",\"Yawm al-ithnayn\",\"Yawm ath-thulaathaa'\",\"Yawm al-arbi'aa'\",\"Yawm al-kham\\u012bs\",\"Yawm al-jum'a\",\"Yawm as-sabt\"],dayNamesShort:[\"Aha\",\"Ith\",\"Thu\",\"Arb\",\"Kha\",\"Jum\",\"Sab\"],dayNamesMin:[\"Ah\",\"It\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){return(11*this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year()+14)%30<11},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return this.leapYear(t)?355:354},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),t=t<=0?t+1:t,(r=i.day())+Math.ceil(29.5*(e-1))+354*(t-1)+Math.floor((3+11*t)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},{\"../main\":346,\"object-assign\":247}],338:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Julian\",jdEpoch:1721423.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Julian\",epochs:[\"BC\",\"AD\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()<0?e.year()+1:e.year())%4==0},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},{\"../main\":346,\"object-assign\":247}],339:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate).toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s((t-=this.jdEpoch)+20,20),s(t+4,13)]},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return i.day()+20*i.month()+360*i.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=a},{\"../main\":346,\"object-assign\":247}],340:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar;var o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s<i.month();s++)a+=this.daysPerMonth[s-1];return a+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},{\"../main\":346,\"object-assign\":247}],341:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return this.daysInYear(t)!==this.daysPerYear},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){if(t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),void 0===this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),void 0===this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=n.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var c=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(c)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(c,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var c=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,c)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)void 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":346,\"object-assign\":247}],344:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\"),a=n.instance();function 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(e.year());return a.leapYear(t)},weekOfYear:function(t,e,r){var i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)},_g2tYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)}}),n.calendars.thai=o},{\"../main\":346,\"object-assign\":247}],345:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;a<o.length;a++){if(o[a]>r)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=t(\"object-assign\");function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),f={},h=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=a(t.layout,\"annotations\",h[c[r]])).modifyItem(\"visible\",!0),n.extendFlat(f,s.getUpdateObj());for(r=0;r<u.length;r++)(s=a(t.layout,\"annotations\",h[u[r]])).modifyItem(\"visible\",!1),n.extendFlat(f,s.getUpdateObj());return i.call(\"update\",t,{},f)}}},{\"../../lib\":503,\"../../plot_api/plot_template\":543,\"../../registry\":638}],352:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\");e.exports=function(t,e,r,a){a(\"opacity\");var o=a(\"bgcolor\"),s=a(\"bordercolor\"),l=i.opacity(s);a(\"borderpad\");var c=a(\"borderwidth\"),u=a(\"showarrow\");if(a(\"text\",u?\" \":r._dfltTitle.annotation),a(\"textangle\"),n.coerceFont(a,\"font\",r.font),a(\"width\"),a(\"align\"),a(\"height\")&&a(\"valign\"),u){var f,h,p=a(\"arrowside\");-1!==p.indexOf(\"end\")&&(f=a(\"arrowhead\"),h=a(\"arrowsize\")),-1!==p.indexOf(\"start\")&&(a(\"startarrowhead\",f),a(\"startarrowsize\",h)),a(\"arrowcolor\",l?e.bordercolor:i.defaultLine),a(\"arrowwidth\",2*(l&&c||1)),a(\"standoff\"),a(\"startstandoff\")}var d=a(\"hovertext\"),m=r.hoverlabel||{};if(d){var g=a(\"hoverlabel.bgcolor\",m.bgcolor||(i.opacity(o)?i.rgb(o):i.defaultLine)),v=a(\"hoverlabel.bordercolor\",m.bordercolor||i.contrast(g));n.coerceFont(a,\"hoverlabel.font\",{family:m.font.family,size:m.font.size,color:m.font.color||v})}a(\"captureevents\",!!d)}},{\"../../lib\":503,\"../color\":366}],353:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,a){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.annotations,f=e._id.charAt(0),h=0;h<u.length;h++)l=u[h],c=\"annotations[\"+h+\"].\",l[f+\"ref\"]===e._id&&p(f),l[\"a\"+f+\"ref\"]===e._id&&p(\"a\"+f);function p(t){var r=l[t],s=null;s=o?i(r,e.range):Math.pow(10,r),n(s)||(s=null),a(c+t,s)}}},{\"../../lib/to_log_range\":531,\"fast-isnumeric\":190}],354:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../plots/array_container_defaults\"),o=t(\"./common_defaults\"),s=t(\"./attributes\");function l(t,e,r){function a(r,i){return n.coerce(t,e,s,r,i)}var l=a(\"visible\"),c=a(\"clicktoshow\");if(l||c){o(t,e,r,a);for(var u=e.showarrow,f=[\"x\",\"y\"],h=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var m=f[d],g=i.coerceRef(t,e,p,m,\"\",\"paper\");if(\"paper\"!==g)i.getFromId(p,g)._annIndices.push(e._index);if(i.coercePosition(e,p,a,g,m,.5),u){var v=\"a\"+m,y=i.coerceRef(t,e,p,v,\"pixel\",[\"pixel\",\"paper\"]);\"pixel\"!==y&&y!==g&&(y=e[v]=\"pixel\");var 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r=t._fullLayout.annotations[e]||{},n=l.getFromId(t,r.xref),i=l.getFromId(t,r.yref);n&&n.setScale(),i&&i.setScale(),x(t,r,e,!1,n,i)}function y(t,e,r,n,i){var a=i[r],o=i[r+\"ref\"],s=-1!==r.indexOf(\"y\"),c=\"domain\"===l.getRefType(o),u=s?n.h:n.w;return t?c?a+(s?-e:e)/t._length:t.p2r(t.r2p(a)+e):a+(s?-e:e)/u}function x(t,e,r,a,v,x){var b,_,w=t._fullLayout,T=t._fullLayout._size,k=t._context.edits;a?(b=\"annotation-\"+a,_=a+\".annotations\"):(b=\"annotation\",_=\"annotations\");var A=m(t.layout,_,e),M=A.modifyBase,S=A.modifyItem,E=A.getUpdateObj;w._infolayer.selectAll(\".\"+b+'[data-index=\"'+r+'\"]').remove();var L=\"clip\"+w._uid+\"_ann\"+r;if(e._input&&!1!==e.visible){var C={x:{},y:{}},P=+e.textangle||0,I=w._infolayer.append(\"g\").classed(b,!0).attr(\"data-index\",String(r)).style(\"opacity\",e.opacity),O=I.append(\"g\").classed(\"annotation-text-g\",!0),z=k[e.showarrow?\"annotationTail\":\"annotationPosition\"],D=e.captureevents||k.annotationText||z,R=O.append(\"g\").style(\"pointer-events\",D?\"all\":null).call(p,\"pointer\").on(\"click\",(function(){t._dragging=!1,t.emit(\"plotly_clickannotation\",Y(n.event))}));e.hovertext&&R.on(\"mouseover\",(function(){var r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();f.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on(\"mouseout\",(function(){f.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(c.stroke,e.bordercolor).call(c.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+L).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",L).append(\"rect\"),V.exit().remove();var H=e.font,q=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(q);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(W).on(\"edit\",(function(r){e.text=r,this.call(W),S(\"text\",r),v&&v.autorange&&M(v._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(W)}else n.selectAll(\"#\"+L).remove();function Y(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function W(r){return r.call(u.font,H).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,X),r}function X(){var r=G.selectAll(\"a\");1===r.size()&&r.text()===G.text()&&R.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(j.node());var n=R.select(\".annotation-text-math-group\"),f=!n.empty(),m=u.bBox((f?n:G).node()),b=m.width,_=m.height,A=e.width||b,D=e.height||_,B=Math.round(A+2*N),H=Math.round(D+2*N);function q(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var W=!1,X=[\"x\",\"y\"],Z=0;Z<X.length;Z++){var J,K,Q,$,tt,et=X[Z],rt=e[et+\"ref\"]||et,nt=e[\"a\"+et+\"ref\"],it={x:v,y:x}[et],at=(P+(\"x\"===et?0:-90))*Math.PI/180,ot=B*Math.cos(at),st=H*Math.sin(at),lt=Math.abs(ot)+Math.abs(st),ct=e[et+\"anchor\"],ut=e[et+\"shift\"]*(\"x\"===et?1:-1),ft=C[et],ht=l.getRefType(rt);if(it&&\"domain\"!==ht){var pt=it.r2fraction(e[et]);(pt<0||pt>1)&&(nt===rt?((pt=it.r2fraction(e[\"a\"+et]))<0||pt>1)&&(W=!0):W=!0),J=it._offset+it.r2p(e[et]),$=.5}else{var dt=\"domain\"===ht;\"x\"===et?(Q=e[et],J=dt?it._offset+it._length*Q:J=T.l+T.w*Q):(Q=1-e[et],J=dt?it._offset+it._length*Q:J=T.t+T.h*Q),$=e.showarrow?.5:Q}if(e.showarrow){ft.head=J;var mt=e[\"a\"+et];if(tt=ot*q(.5,e.xanchor)-st*q(.5,e.yanchor),nt===rt){var gt=l.getRefType(nt);\"domain\"===gt?(\"y\"===et&&(mt=1-mt),ft.tail=it._offset+it._length*mt):\"paper\"===gt?\"y\"===et?(mt=1-mt,ft.tail=T.t+T.h*mt):ft.tail=T.l+T.w*mt:ft.tail=it._offset+it.r2p(mt),K=tt}else ft.tail=J+mt,K=tt+mt;ft.text=ft.tail+tt;var vt=w[\"x\"===et?\"width\":\"height\"];if(\"paper\"===rt&&(ft.head=o.constrain(ft.head,1,vt-1)),\"pixel\"===nt){var yt=-Math.max(ft.tail-3,ft.text),xt=Math.min(ft.tail+3,ft.text)-vt;yt>0?(ft.tail+=yt,ft.text+=yt):xt>0&&(ft.tail-=xt,ft.text-=xt)}ft.tail+=ut,ft.head+=ut}else K=tt=lt*q($,ct),ft.text=J+tt;ft.text+=ut,tt+=ut,K+=ut,e[\"_\"+et+\"padplus\"]=lt/2+K,e[\"_\"+et+\"padminus\"]=lt/2-K,e[\"_\"+et+\"size\"]=lt,e[\"_\"+et+\"shift\"]=tt}if(W)R.remove();else{var bt=0,_t=0;if(\"left\"!==e.align&&(bt=(A-b)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(_t=(D-_)*(\"middle\"===e.valign?.5:1)),f)n.select(\"svg\").attr({x:N+bt-1,y:N+_t}).call(u.setClipUrl,U?L:null,t);else{var wt=N+_t-m.top,Tt=N+bt-m.left;G.call(h.positionText,Tt,wt).call(u.setClipUrl,U?L:null,t)}V.select(\"rect\").call(u.setRect,N,N,A,D),j.call(u.setRect,F/2,F/2,B-F,H-F),R.call(u.setTranslate,Math.round(C.x.text-B/2),Math.round(C.y.text-H/2)),O.attr({transform:\"rotate(\"+P+\",\"+C.x.text+\",\"+C.y.text+\")\"});var kt,At=function(r,n){I.selectAll(\".annotation-arrow-g\").remove();var l=C.x.head,f=C.y.head,h=C.x.tail+r,p=C.y.tail+n,m=C.x.text+r,b=C.y.text+n,_=o.rotationXYMatrix(P,m,b),w=o.apply2DTransform(_),A=o.apply2DTransform2(_),L=+j.attr(\"width\"),z=+j.attr(\"height\"),D=m-.5*L,F=D+L,B=b-.5*z,N=B+z,U=[[D,B,D,N],[D,N,F,N],[F,N,F,B],[F,B,D,B]].map(A);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,H=e.arrowcolor,q=e.arrowside,G=I.append(\"g\").style({opacity:c.opacity(H)}).classed(\"annotation-arrow-g\",!0),Y=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(c.stroke,c.rgb(H));if(g(Y,q,e),k.annotationPosition&&Y.node().parentNode&&!a){var W=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));W+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var J,K,Q=G.append(\"path\").classed(\"annotation-arrow\",!0).classed(\"anndrag\",!0).classed(\"cursor-move\",!0).attr({d:\"M3,3H-3V-3H3ZM0,0L\"+(h-W)+\",\"+(p-X),transform:s(W,X)}).style(\"stroke-width\",V+6+\"px\").call(c.stroke,\"rgba(0,0,0,0)\").call(c.fill,\"rgba(0,0,0,0)\");d.init({element:Q.node(),gd:t,prepFn:function(){var t=u.getTranslate(R);J=t.x,K=t.y,v&&v.autorange&&M(v._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0)},moveFn:function(t,r){var n=w(J,K),i=n[0]+t,a=n[1]+r;R.call(u.setTranslate,i,a),S(\"x\",y(v,t,\"x\",T,e)),S(\"y\",y(x,r,\"y\",T,e)),e.axref===e.xref&&S(\"ax\",y(v,t,\"ax\",T,e)),e.ayref===e.yref&&S(\"ay\",y(x,r,\"ay\",T,e)),G.attr(\"transform\",s(t,r)),O.attr({transform:\"rotate(\"+P+\",\"+i+\",\"+a+\")\"})},doneFn:function(){i.call(\"_guiRelayout\",t,E());var e=document.querySelector(\".js-notes-box-panel\");e&&e.redraw(e.selectedObj)}})}}};if(e.showarrow&&At(0,0),z)d.init({element:R.node(),gd:t,prepFn:function(){kt=O.attr(\"transform\")},moveFn:function(t,r){var n=\"pointer\";if(e.showarrow)e.axref===e.xref?S(\"ax\",y(v,t,\"ax\",T,e)):S(\"ax\",e.ax+t),e.ayref===e.yref?S(\"ay\",y(x,r,\"ay\",T.w,e)):S(\"ay\",e.ay+r),At(t,r);else{if(a)return;var i,o;if(v)i=y(v,t,\"x\",T,e);else{var l=e._xsize/T.w,c=e.x+(e._xshift-e.xshift)/T.w-l/2;i=d.align(c+t/T.w,l,0,1,e.xanchor)}if(x)o=y(x,r,\"y\",T,e);else{var u=e._ysize/T.h,f=e.y-(e._yshift+e.yshift)/T.h-u/2;o=d.align(f-r/T.h,u,0,1,e.yanchor)}S(\"x\",i),S(\"y\",o),v&&x||(n=d.getCursor(v?.5:i,x?.5:o,e.xanchor,e.yanchor))}O.attr({transform:s(t,r)+kt}),p(R,n)},clickFn:function(r,n){e.captureevents&&t.emit(\"plotly_clickannotation\",Y(n))},doneFn:function(){p(R),i.call(\"_guiRelayout\",t,E());var e=document.querySelector(\".js-notes-box-panel\");e&&e.redraw(e.selectedObj)}})}}}e.exports={draw:function(t){var e=t._fullLayout;e._infolayer.selectAll(\".annotation\").remove();for(var r=0;r<e.annotations.length;r++)e.annotations[r].visible&&v(t,r);return a.previousPromises(t)},drawOne:v,drawRaw:x}},{\"../../lib\":503,\"../../lib/setcursor\":524,\"../../lib/svg_text_utils\":529,\"../../plot_api/plot_template\":543,\"../../plots/cartesian/axes\":554,\"../../plots/plots\":619,\"../../registry\":638,\"../color\":366,\"../dragelement\":385,\"../drawing\":388,\"../fx\":406,\"./draw_arrow_head\":356,\"@plotly/d3\":58}],356:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../color\"),a=t(\"./arrow_paths\"),o=t(\"../../lib\"),s=o.strScale,l=o.strRotate,c=o.strTranslate;e.exports=function(t,e,r){var o,u,f,h,p=t.node(),d=a[r.arrowhead||0],m=a[r.startarrowhead||0],g=(r.arrowwidth||1)*(r.arrowsize||1),v=(r.arrowwidth||1)*(r.startarrowsize||1),y=e.indexOf(\"start\")>=0,x=e.indexOf(\"end\")>=0,b=d.backoff*g+r.standoff,_=m.backoff*v+r.startstandoff;if(\"line\"===p.nodeName){o={x:+t.attr(\"x1\"),y:+t.attr(\"y1\")},u={x:+t.attr(\"x2\"),y:+t.attr(\"y2\")};var w=o.x-u.x,T=o.y-u.y;if(h=(f=Math.atan2(T,w))+Math.PI,b&&_&&b+_>Math.sqrt(w*w+T*T))return void z();if(b){if(b*b>w*w+T*T)return void z();var k=b*Math.cos(f),A=b*Math.sin(f);u.x+=k,u.y+=A,t.attr({x2:u.x,y2:u.y})}if(_){if(_*_>w*w+T*T)return void z();var M=_*Math.cos(f),S=_*Math.sin(f);o.x-=M,o.y-=S,t.attr({x1:o.x,y1:o.y})}}else if(\"path\"===p.nodeName){var E=p.getTotalLength(),L=\"\";if(E<b+_)return void z();var C=p.getPointAtLength(0),P=p.getPointAtLength(.1);f=Math.atan2(C.y-P.y,C.x-P.x),o=p.getPointAtLength(Math.min(_,E)),L=\"0px,\"+_+\"px,\";var 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n=t(\"@plotly/d3\"),i=t(\"tinycolor2\"),a=t(\"../../plots/plots\"),o=t(\"../../registry\"),s=t(\"../../plots/cartesian/axes\"),l=t(\"../dragelement\"),c=t(\"../../lib\"),u=c.strTranslate,f=t(\"../../lib/extend\").extendFlat,h=t(\"../../lib/setcursor\"),p=t(\"../drawing\"),d=t(\"../color\"),m=t(\"../titles\"),g=t(\"../../lib/svg_text_utils\"),v=t(\"../colorscale/helpers\").flipScale,y=t(\"../../plots/cartesian/axis_defaults\"),x=t(\"../../plots/cartesian/position_defaults\"),b=t(\"../../plots/cartesian/layout_attributes\"),_=t(\"../../constants/alignment\"),w=_.LINE_SPACING,T=_.FROM_TL,k=_.FROM_BR,A=t(\"./constants\").cn;e.exports={draw:function(t){var e=t._fullLayout._infolayer.selectAll(\"g.\"+A.colorbar).data(function(t){var e,r,n,i,a=t._fullLayout,o=t.calcdata,s=[];function l(t){return f(t,{_fillcolor:null,_line:{color:null,width:null,dash:null},_levels:{start:null,end:null,size:null},_filllevels:null,_fillgradient:null,_zrange:null})}function c(){\"function\"==typeof 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r=n.select(this);c.ensureSingle(r,\"rect\",A.cbbg),c.ensureSingle(r,\"g\",A.cbfills),c.ensureSingle(r,\"g\",A.cblines),c.ensureSingle(r,\"g\",A.cbaxis,(function(t){t.classed(A.crisp,!0)})),c.ensureSingle(r,\"g\",A.cbtitleunshift,(function(t){t.append(\"g\").classed(A.cbtitle,!0)})),c.ensureSingle(r,\"rect\",A.cboutline);var v=function(t,e,r){var o=\"v\"===e.orientation,l=e.len,h=e.lenmode,v=e.thickness,_=e.thicknessmode,M=e.outlinewidth,S=e.borderwidth,E=e.bgcolor,L=e.xanchor,C=e.yanchor,P=e.xpad,I=e.ypad,O=e.x,z=o?e.y:1-e.y,D=r._fullLayout,R=D._size,F=e._fillcolor,B=e._line,N=e.title,j=N.side,U=e._zrange||n.extent((\"function\"==typeof F?F:B.color).domain()),V=\"function\"==typeof B.color?B.color:function(){return B.color},H=\"function\"==typeof F?F:function(){return F},q=e._levels,G=function(t,e,r){var n,i,a=e._levels,o=[],s=[],l=a.end+a.size/100,c=a.size,u=1.001*r[0]-.001*r[1],f=1.001*r[1]-.001*r[0];for(i=0;i<1e5&&(n=a.start+i*c,!(c>0?n>=l:n<=l));i++)n>u&&n<f&&o.push(n);if(e._fillgradient)s=[0];else if(\"function\"==typeof e._fillcolor){var h=e._filllevels;if(h)for(l=h.end+h.size/100,c=h.size,i=0;i<1e5&&(n=h.start+i*c,!(c>0?n>=l:n<=l));i++)n>r[0]&&n<r[1]&&s.push(n);else(s=o.map((function(t){return t-a.size/2}))).push(s[s.length-1]+a.size)}else e._fillcolor&&\"string\"==typeof e._fillcolor&&(s=[0]);a.size<0&&(o.reverse(),s.reverse());return{line:o,fill:s}}(0,e,U),Y=G.fill,W=G.line,X=Math.round(v*(\"fraction\"===_?o?R.w:R.h:1)),Z=X/(o?R.w:R.h),J=Math.round(l*(\"fraction\"===h?o?R.h:R.w:1)),K=J/(o?R.h:R.w),Q=Math.round(o?O*R.w+P:z*R.h+I),$={center:.5,right:1}[L]||0,tt={top:1,middle:.5}[C]||0,et=o?O-$*Z:z-tt*Z,rt=o?z-tt*K:O-$*K,nt=Math.round(o?R.h*(1-rt):R.w*rt);e._lenFrac=K,e._thickFrac=Z,e._uFrac=et,e._vFrac=rt;var it=e._axis=function(t,e,r){var n=t._fullLayout,i=\"v\"===e.orientation,a={type:\"linear\",range:r,tickmode:e.tickmode,nticks:e.nticks,tick0:e.tick0,dtick:e.dtick,tickvals:e.tickvals,ticktext:e.ticktext,ticks:e.ticks,ticklen:e.ticklen,tickwidth:e.tickwidth,tickcolor:e.tickcolor,showticklabels:e.showticklabels,ticklabelposition:e.ticklabelposition,ticklabeloverflow:e.ticklabeloverflow,ticklabelstep:e.ticklabelstep,tickfont:e.tickfont,tickangle:e.tickangle,tickformat:e.tickformat,exponentformat:e.exponentformat,minexponent:e.minexponent,separatethousands:e.separatethousands,showexponent:e.showexponent,showtickprefix:e.showtickprefix,tickprefix:e.tickprefix,showticksuffix:e.showticksuffix,ticksuffix:e.ticksuffix,title:e.title,showline:!0,anchor:\"free\",side:i?\"right\":\"bottom\",position:1},o=i?\"y\":\"x\",s={type:\"linear\",_id:o+e._id},l={letter:o,font:n.font,noHover:!0,noTickson:!0,noTicklabelmode:!0,calendar:n.calendar};function u(t,e){return c.coerce(a,s,b,t,e)}return y(a,s,u,l,n),x(a,s,u,l),s}(r,e,U);it.position=Z+(o?O+P/R.w:z+I/R.h);var at=-1!==[\"top\",\"bottom\"].indexOf(j);o&&at&&(it.title.side=j,it.titlex=O+P/R.w,it.titley=rt+(\"top\"===N.side?K-I/R.h:I/R.h));o||at||(it.title.side=j,it.titley=z+I/R.h,it.titlex=rt+P/R.w);if(B.color&&\"auto\"===e.tickmode){it.tickmode=\"linear\",it.tick0=q.start;var ot=q.size,st=c.constrain(J/50,4,15)+1,lt=(U[1]-U[0])/((e.nticks||st)*ot);if(lt>1){var ct=Math.pow(10,Math.floor(Math.log(lt)/Math.LN10));ot*=ct*c.roundUp(lt/ct,[2,5,10]),(Math.abs(q.start)/q.size+1e-6)%1<2e-6&&(it.tick0=0)}it.dtick=ot}it.domain=o?[rt+I/R.h,rt+K-I/R.h]:[rt+P/R.w,rt+K-P/R.w],it.setScale(),t.attr(\"transform\",u(Math.round(R.l),Math.round(R.t)));var ut,ft=t.select(\".\"+A.cbtitleunshift).attr(\"transform\",u(-Math.round(R.l),-Math.round(R.t))),ht=it.ticklabelposition,pt=it.title.font.size,dt=t.select(\".\"+A.cbaxis),mt=0,gt=0;function vt(n,i){var a={propContainer:it,propName:e._propPrefix+\"title\",traceIndex:e._traceIndex,_meta:e._meta,placeholder:D._dfltTitle.colorbar,containerGroup:t.select(\".\"+A.cbtitle)},o=\"h\"===n.charAt(0)?n.substr(1):\"h\"+n;t.selectAll(\".\"+o+\",.\"+o+\"-math-group\").remove(),m.draw(r,n,f(a,i||{}))}return c.syncOrAsync([a.previousPromises,function(){var t,e;(o&&at||!o&&!at)&&(\"top\"===j&&(t=P+R.l+R.w*O,e=I+R.t+R.h*(1-rt-K)+3+.75*pt),\"bottom\"===j&&(t=P+R.l+R.w*O,e=I+R.t+R.h*(1-rt)-3-.25*pt),\"right\"===j&&(e=I+R.t+R.h*z+3+.75*pt,t=P+R.l+R.w*rt),vt(it._id+\"title\",{attributes:{x:t,y:e,\"text-anchor\":o?\"start\":\"middle\"}}))},function(){if(!o&&!at||o&&at){var a,l=t.select(\".\"+A.cbtitle),f=l.select(\"text\"),h=[-M/2,M/2],d=l.select(\".h\"+it._id+\"title-math-group\").node(),m=15.6;if(f.node()&&(m=parseInt(f.node().style.fontSize,10)*w),d?(a=p.bBox(d),gt=a.width,(mt=a.height)>m&&(h[1]-=(mt-m)/2)):f.node()&&!f.classed(A.jsPlaceholder)&&(a=p.bBox(f.node()),gt=a.width,mt=a.height),o){if(mt){if(mt+=5,\"top\"===j)it.domain[1]-=mt/R.h,h[1]*=-1;else{it.domain[0]+=mt/R.h;var v=g.lineCount(f);h[1]+=(1-v)*m}l.attr(\"transform\",u(h[0],h[1])),it.setScale()}}else gt&&(\"right\"===j&&(it.domain[0]+=(gt+pt/2)/R.w),l.attr(\"transform\",u(h[0],h[1])),it.setScale())}t.selectAll(\".\"+A.cbfills+\",.\"+A.cblines).attr(\"transform\",o?u(0,Math.round(R.h*(1-it.domain[1]))):u(Math.round(R.w*it.domain[0]),0)),dt.attr(\"transform\",o?u(0,Math.round(-R.t)):u(Math.round(-R.l),0));var y=t.select(\".\"+A.cbfills).selectAll(\"rect.\"+A.cbfill).attr(\"style\",\"\").data(Y);y.enter().append(\"rect\").classed(A.cbfill,!0).style(\"stroke\",\"none\"),y.exit().remove();var x=U.map(it.c2p).map(Math.round).sort((function(t,e){return t-e}));y.each((function(t,a){var s=[0===a?U[0]:(Y[a]+Y[a-1])/2,a===Y.length-1?U[1]:(Y[a]+Y[a+1])/2].map(it.c2p).map(Math.round);o&&(s[1]=c.constrain(s[1]+(s[1]>s[0])?1:-1,x[0],x[1]));var l=n.select(this).attr(o?\"x\":\"y\",Q).attr(o?\"y\":\"x\",n.min(s)).attr(o?\"width\":\"height\",Math.max(X,2)).attr(o?\"height\":\"width\",Math.max(n.max(s)-n.min(s),2));if(e._fillgradient)p.gradient(l,r,e._id,o?\"vertical\":\"horizontalreversed\",e._fillgradient,\"fill\");else{var u=H(t).replace(\"e-\",\"\");l.attr(\"fill\",i(u).toHexString())}}));var b=t.select(\".\"+A.cblines).selectAll(\"path.\"+A.cbline).data(B.color&&B.width?W:[]);b.enter().append(\"path\").classed(A.cbline,!0),b.exit().remove(),b.each((function(t){var e=Q,r=Math.round(it.c2p(t))+B.width/2%1;n.select(this).attr(\"d\",\"M\"+(o?e+\",\"+r:r+\",\"+e)+(o?\"h\":\"v\")+X).call(p.lineGroupStyle,B.width,V(t),B.dash)})),dt.selectAll(\"g.\"+it._id+\"tick,path\").remove();var _=Q+X+(M||0)/2-(\"outside\"===e.ticks?1:0),T=s.calcTicks(it),k=s.getTickSigns(it)[2];return s.drawTicks(r,it,{vals:\"inside\"===it.ticks?s.clipEnds(it,T):T,layer:dt,path:s.makeTickPath(it,_,k),transFn:s.makeTransTickFn(it)}),s.drawLabels(r,it,{vals:T,layer:dt,transFn:s.makeTransTickLabelFn(it),labelFns:s.makeLabelFns(it,_)})},function(){if(o&&!at||!o&&at){var t,i,a=it.position||0,s=it._offset+it._length/2;if(\"right\"===j)i=s,t=R.l+R.w*a+10+pt*(it.showticklabels?1:.5);else if(t=s,\"bottom\"===j&&(i=R.t+R.h*a+10+(-1===ht.indexOf(\"inside\")?it.tickfont.size:0)+(\"intside\"!==it.ticks&&e.ticklen||0)),\"top\"===j){var l=N.text.split(\"<br>\").length;i=R.t+R.h*a+10-X-w*pt*l}vt((o?\"h\":\"v\")+it._id+\"title\",{avoid:{selection:n.select(r).selectAll(\"g.\"+it._id+\"tick\"),side:j,offsetTop:o?0:R.t,offsetLeft:o?R.l:0,maxShift:o?D.width:D.height},attributes:{x:t,y:i,\"text-anchor\":\"middle\"},transform:{rotate:o?-90:0,offset:0}})}},a.previousPromises,function(){var n,s=X+M/2;-1===ht.indexOf(\"inside\")&&(n=p.bBox(dt.node()),s+=o?n.width:n.height),ut=ft.select(\"text\");var c=0,f=o&&\"top\"===j,m=!o&&\"right\"===j,g=0;if(ut.node()&&!ut.classed(A.jsPlaceholder)){var y,x=ft.select(\".h\"+it._id+\"title-math-group\").node();x&&(o&&at||!o&&!at)?(c=(n=p.bBox(x)).width,y=n.height):(c=(n=p.bBox(ft.node())).right-R.l-(o?Q:nt),y=n.bottom-R.t-(o?nt:Q),o||\"top\"!==j||(s+=n.height,g=n.height)),m&&(ut.attr(\"transform\",u(c/2+pt/2,0)),c*=2),s=Math.max(s,o?c:y)}var b=2*(o?P:I)+s+S+M/2,w=0;!o&&N.text&&\"bottom\"===C&&z<=0&&(b+=w=b/2,g+=w),D._hColorbarMoveTitle=w,D._hColorbarMoveCBTitle=g;var F=S+M;t.select(\".\"+A.cbbg).attr(\"x\",(o?Q:nt)-F/2-(o?P:0)).attr(\"y\",(o?nt:Q)-(o?J:I+g-w)).attr(o?\"width\":\"height\",Math.max(b-w,2)).attr(o?\"height\":\"width\",Math.max(J+F,2)).call(d.fill,E).call(d.stroke,e.bordercolor).style(\"stroke-width\",S);var B=m?Math.max(c-10,0):0;if(t.selectAll(\".\"+A.cboutline).attr(\"x\",(o?Q:nt+P)+B).attr(\"y\",(o?nt+I-J:Q)+(f?mt:0)).attr(o?\"width\":\"height\",Math.max(X,2)).attr(o?\"height\":\"width\",Math.max(J-(o?2*I+mt:2*P+B),2)).call(d.stroke,e.outlinecolor).style({fill:\"none\",\"stroke-width\":M}),t.attr(\"transform\",u(R.l-(o?$*b:0),R.t-(o?0:(1-tt)*b-g))),!o&&(S||i(E).getAlpha()&&!i.equals(D.paper_bgcolor,E))){var U=dt.selectAll(\"text\"),V=U[0].length,H=t.select(\".\"+A.cbbg).node(),q=p.bBox(H),G=p.getTranslate(t);U.each((function(t,e){var r=V-1;if(0===e||e===r){var n,i=p.bBox(this),a=p.getTranslate(this);if(e===r){var o=i.right+a.x;(n=q.right+G.x+nt-S-2+O-o)>0&&(n=0)}else if(0===e){var s=i.left+a.x;(n=q.left+G.x+nt+S+2-s)<0&&(n=0)}n&&(V<3?this.setAttribute(\"transform\",\"translate(\"+n+\",0) \"+this.getAttribute(\"transform\")):this.setAttribute(\"visibility\",\"hidden\"))}}))}var Y={},W=T[L],Z=k[L],K=T[C],et=k[C],rt=b-X;o?(\"pixels\"===h?(Y.y=z,Y.t=J*K,Y.b=J*et):(Y.t=Y.b=0,Y.yt=z+l*K,Y.yb=z-l*et),\"pixels\"===_?(Y.x=O,Y.l=b*W,Y.r=b*Z):(Y.l=rt*W,Y.r=rt*Z,Y.xl=O-v*W,Y.xr=O+v*Z)):(\"pixels\"===h?(Y.x=O,Y.l=J*W,Y.r=J*Z):(Y.l=Y.r=0,Y.xl=O+l*W,Y.xr=O-l*Z),\"pixels\"===_?(Y.y=1-z,Y.t=b*K,Y.b=b*et):(Y.t=rt*K,Y.b=rt*et,Y.yt=z-v*K,Y.yb=z+v*et)),a.autoMargin(r,e._id,Y)}],r)}(r,e,t);v&&v.then&&(t._promises||[]).push(v),t._context.edits.colorbarPosition&&function(t,e,r){var n,i,a,s=\"v\"===e.orientation,c=r._fullLayout._size;l.init({element:t.node(),gd:r,prepFn:function(){n=t.attr(\"transform\"),h(t)},moveFn:function(r,o){t.attr(\"transform\",n+u(r,o)),i=l.align((s?e._uFrac:e._vFrac)+r/c.w,s?e._thickFrac:e._lenFrac,0,1,e.xanchor),a=l.align((s?e._vFrac:1-e._uFrac)-o/c.h,s?e._lenFrac:e._thickFrac,0,1,e.yanchor);var f=l.getCursor(i,a,e.xanchor,e.yanchor);h(t,f)},doneFn:function(){if(h(t),void 0!==i&&void 0!==a){var n={};n[e._propPrefix+\"x\"]=i,n[e._propPrefix+\"y\"]=a,void 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o.warn(\"Fx.hover failed\",e,t),d.unhoverRaw(t,e)}var ct=1/0;function ut(t,r){for(G=0;G<rt.length;G++)if((Y=rt[G])&&Y[0]&&Y[0].trace&&!0===(W=Y[0].trace).visible&&0!==W._length&&-1===[\"carpet\",\"contourcarpet\"].indexOf(W._module.name)){if(\"splom\"===W.type?X=l[Z=0]:(X=v.getSubplot(W),Z=l.indexOf(X)),J=P,v.isUnifiedHover(J)&&(J=J.charAt(0)),$={cd:Y,trace:W,xa:_[Z],ya:w[Z],maxHoverDistance:O,maxSpikeDistance:B,index:!1,distance:Math.min(ct,O),spikeDistance:1/0,xSpike:void 0,ySpike:void 0,color:p.defaultLine,name:W.name,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},u[X]&&($.subplot=u[X]._subplot),u._splomScenes&&u._splomScenes[W.uid]&&($.scene=u._splomScenes[W.uid]),tt=et.length,\"array\"===J){var n=e[G];\"pointNumber\"in n?($.index=n.pointNumber,J=\"closest\"):(J=\"\",\"xval\"in n&&(K=n.xval,J=\"x\"),\"yval\"in n&&(Q=n.yval,J=J?\"closest\":\"y\"))}else void 0!==t&&void 0!==r?(K=t,Q=r):(K=V[Z],Q=H[Z]);if(0!==O)if(W._module&&W._module.hoverPoints){var a=W._module.hoverPoints($,K,Q,J,{finiteRange:!0,hoverLayer:u._hoverlayer});if(a)for(var s,c=0;c<a.length;c++)s=a[c],i(s.x0)&&i(s.y0)&&et.push(D(s,P))}else o.log(\"Unrecognized trace type in hover:\",W);if(\"closest\"===P&&et.length>tt&&(et.splice(0,tt),ct=et[0].distance),y&&0!==B&&0===et.length){$.distance=B,$.index=!1;var f=W._module.hoverPoints($,K,Q,\"closest\",{hoverLayer:u._hoverlayer});if(f&&(f=f.filter((function(t){return t.spikeDistance<=B}))),f&&f.length){var h,d=f.filter((function(t){return t.xa.showspikes&&\"hovered data\"!==t.xa.spikesnap}));if(d.length){var m=d[0];i(m.x0)&&i(m.y0)&&(h=ht(m),(!nt.vLinePoint||nt.vLinePoint.spikeDistance>h.spikeDistance)&&(nt.vLinePoint=h))}var g=f.filter((function(t){return t.ya.showspikes&&\"hovered data\"!==t.ya.spikesnap}));if(g.length){var x=g[0];i(x.x0)&&i(x.y0)&&(h=ht(x),(!nt.hLinePoint||nt.hLinePoint.spikeDistance>h.spikeDistance)&&(nt.hLinePoint=h))}}}}}function ft(t,e,r){for(var n,i=null,a=1/0,o=0;o<t.length;o++)n=t[o].spikeDistance,r&&0===o&&(n=-1/0),n<=a&&n<=e&&(i=t[o],a=n);return i}function ht(t){return t?{xa:t.xa,ya:t.ya,x:void 0!==t.xSpike?t.xSpike:(t.x0+t.x1)/2,y:void 0!==t.ySpike?t.ySpike:(t.y0+t.y1)/2,distance:t.distance,spikeDistance:t.spikeDistance,curveNumber:t.trace.index,color:t.color,pointNumber:t.index}:null}ut();var pt={fullLayout:u,container:u._hoverlayer,event:e},dt=t._spikepoints,mt={vLinePoint:nt.vLinePoint,hLinePoint:nt.hLinePoint};t._spikepoints=mt;var gt=function(){et.sort((function(t,e){return t.distance-e.distance})),et=function(t,e){for(var r=e.charAt(0),n=[],i=[],a=[],o=0;o<t.length;o++){var s=t[o];g.traceIs(s.trace,\"bar-like\")||g.traceIs(s.trace,\"box-violin\")?a.push(s):s.trace[r+\"period\"]?i.push(s):n.push(s)}return n.concat(i).concat(a)}(et,P)};gt();var vt=P.charAt(0),yt=(\"x\"===vt||\"y\"===vt)&&et[0]&&L[et[0].trace.type];if(y&&0!==B&&0!==et.length){var xt=ft(et.filter((function(t){return t.ya.showspikes})),B,yt);nt.hLinePoint=ht(xt);var bt=ft(et.filter((function(t){return t.xa.showspikes})),B,yt);nt.vLinePoint=ht(bt)}if(0===et.length){var _t=d.unhoverRaw(t,e);return!y||null===nt.hLinePoint&&null===nt.vLinePoint||F(dt)&&R(t,nt,pt),_t}y&&F(dt)&&R(t,nt,pt);if(v.isXYhover(J)&&0!==et[0].length&&\"splom\"!==et[0].trace.type){var wt=et[0],Tt=(et=E[wt.trace.type]?et.filter((function(t){return t.trace.index===wt.trace.index})):[wt]).length,kt=N(\"x\",wt,u),At=N(\"y\",wt,u);ut(kt,At);var Mt,St=[],Et={},Lt=0,Ct=function(t){var e=E[t.trace.type]?C(t):t.trace.index;if(Et[e]){var r=Et[e]-1,n=St[r];r>0&&Math.abs(t.distance)<Math.abs(n.distance)&&(St[r]=t)}else Lt++,Et[e]=Lt,St.push(t)};for(Mt=0;Mt<Tt;Mt++)Ct(et[Mt]);for(Mt=et.length-1;Mt>Tt-1;Mt--)Ct(et[Mt]);et=St,gt()}var Pt=t._hoverdata,It=[],Ot=j(t),zt=U(t);for(q=0;q<et.length;q++){var Dt=et[q],Rt=v.makeEventData(Dt,Dt.trace,Dt.cd);if(!1!==Dt.hovertemplate){var Ft=!1;Dt.cd[Dt.index]&&Dt.cd[Dt.index].ht&&(Ft=Dt.cd[Dt.index].ht),Dt.hovertemplate=Ft||Dt.trace.hovertemplate||!1}if(Dt.xa&&Dt.ya){var Bt=Dt.x0+Dt.xa._offset,Nt=Dt.x1+Dt.xa._offset,jt=Dt.y0+Dt.ya._offset,Ut=Dt.y1+Dt.ya._offset,Vt=Math.min(Bt,Nt),Ht=Math.max(Bt,Nt),qt=Math.min(jt,Ut),Gt=Math.max(jt,Ut);Rt.bbox={x0:Vt+zt,x1:Ht+zt,y0:qt+Ot,y1:Gt+Ot}}Dt.eventData=[Rt],It.push(Rt)}t._hoverdata=It;var Yt=\"y\"===P&&(rt.length>1||et.length>1)||\"closest\"===P&&it&&et.length>1,Wt=p.combine(u.plot_bgcolor||p.background,u.paper_bgcolor),Xt=I(et,{gd:t,hovermode:P,rotateLabels:Yt,bgColor:Wt,container:u._hoverlayer,outerContainer:u._paper.node(),commonLabelOpts:u.hoverlabel,hoverdistance:u.hoverdistance});v.isUnifiedHover(P)||(!function(t,e,r){var n,i,a,o,s,l,c,u=0,f=1,h=t.size(),p=new Array(h),d=0;function m(t){var e=t[0],r=t[t.length-1];if(i=e.pmin-e.pos-e.dp+e.size,a=r.pos+r.dp+r.size-e.pmax,i>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=i;n=!1}if(!(a<.01)){if(i<-.01){for(s=t.length-1;s>=0;s--)t[s].dp-=a;n=!1}if(n){var c=0;for(o=0;o<t.length;o++)(l=t[o]).pos+l.dp+l.size>e.pmax&&c++;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos>e.pmax-1&&(l.del=!0,c--);for(o=0;o<t.length&&!(c<=0);o++)if((l=t[o]).pos<e.pmin+1)for(l.del=!0,c--,a=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=a;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos+l.dp+l.size>e.pmax&&(l.del=!0,c--)}}}t.each((function(t){var n=t[e],i=\"x\"===n._id.charAt(0),a=n.range;0===d&&a&&a[0]>a[1]!==i&&(f=-1),p[d++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(i?T:1)/2,pmin:0,pmax:i?r.width:r.height}]})),p.sort((function(t,e){return t[0].posref-e[0].posref||f*(e[0].traceIndex-t[0].traceIndex)}));for(;!n&&u<=h;){for(u++,n=!0,o=0;o<p.length-1;){var g=p[o],v=p[o+1],y=g[g.length-1],x=v[0];if((i=y.pos+y.dp+y.size-x.pos-x.dp+x.size)>.01&&y.pmin===x.pmin&&y.pmax===x.pmax){for(s=v.length-1;s>=0;s--)v[s].dp+=i;for(g.push.apply(g,v),p.splice(o+1,1),c=0,s=g.length-1;s>=0;s--)c+=g[s].dp;for(a=c/g.length,s=g.length-1;s>=0;s--)g[s].dp-=a;n=!1}else o++}p.forEach(m)}for(o=p.length-1;o>=0;o--){var b=p[o];for(s=b.length-1;s>=0;s--){var _=b[s],w=_.datum;w.offset=_.dp,w.del=_.del}}}(Xt,Yt?\"xa\":\"ya\",u),z(Xt,Yt,u._invScaleX,u._invScaleY));if(s&&s.tagName){var Zt=g.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,It);f(n.select(s),Zt?\"pointer\":\"\")}if(!s||a||!function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,Pt))return;Pt&&t.emit(\"plotly_unhover\",{event:e,points:Pt});t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:_,yaxes:w,xvals:V,yvals:H})}(t,e,r,a,s)}))},r.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=e.gd,a=j(i),o=U(i),s=I(t.map((function(t){var r=t._x0||t.x0||t.x||0,n=t._x1||t.x1||t.x||0,s=t._y0||t.y0||t.y||0,l=t._y1||t.y1||t.y||0,c=t.eventData;if(c){var u=Math.min(r,n),f=Math.max(r,n),h=Math.min(s,l),d=Math.max(s,l),m=t.trace;if(g.traceIs(m,\"gl3d\")){var v=i._fullLayout[m.scene]._scene.container,y=v.offsetLeft,x=v.offsetTop;u+=y,f+=y,h+=x,d+=x}c.bbox={x0:u+o,x1:f+o,y0:h+a,y1:d+a},e.inOut_bbox&&e.inOut_bbox.push(c.bbox)}else c=!1;return{color:t.color||p.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,hovertemplateLabels:t.hovertemplateLabels||!1,eventData:c}})),{gd:i,hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||p.background,container:n.select(e.container),outerContainer:e.outerContainer||e.container}),l=0,c=0;return s.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5<l?l-n+5:0,l=n+t.by+t.offset,r===e.anchorIndex&&(c=t.offset)})).each((function(t){t.offset-=c})),z(s,!1,i._fullLayout._invScaleX,i._fullLayout._invScaleY),r?s:s.node()};var P=/<extra>([\\s\\S]*)<\\/extra>/;function I(t,e){var r=e.gd,i=r._fullLayout,a=e.hovermode,c=e.rotateLabels,f=e.bgColor,d=e.container,m=e.outerContainer,w=e.commonLabelOpts||{};if(0===t.length)return[[]];var T=e.fontFamily||y.HOVERFONT,k=e.fontSize||y.HOVERFONTSIZE,A=t[0],E=A.xa,L=A.ya,P=a.charAt(0),I=A[P+\"Label\"],z=V(r,m),D=z.top,R=z.width,F=z.height,B=void 0!==I&&A.distance<=e.hoverdistance&&(\"x\"===a||\"y\"===a);if(B){var N,j,U=!0;for(N=0;N<t.length;N++)if(U&&void 0===t[N].zLabel&&(U=!1),j=t[N].hoverinfo||t[N].trace.hoverinfo){var H=Array.isArray(j)?j:j.split(\"+\");if(-1===H.indexOf(\"all\")&&-1===H.indexOf(a)){B=!1;break}}U&&(B=!1)}var q=d.selectAll(\"g.axistext\").data(B?[0]:[]);if(q.enter().append(\"g\").classed(\"axistext\",!0),q.exit().remove(),q.each((function(){var t=n.select(this),e=o.ensureSingle(t,\"path\",\"\",(function(t){t.style({\"stroke-width\":\"1px\"})})),l=o.ensureSingle(t,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),c=w.bgcolor||p.defaultLine,f=w.bordercolor||p.contrast(c),d=p.contrast(c),m={family:w.font.family||T,size:w.font.size||k,color:w.font.color||d};e.style({fill:c,stroke:f}),l.text(I).call(h.font,m).call(u.positionText,0,0).call(u.convertToTspans,r),t.attr(\"transform\",\"\");var g,v,y=V(r,l.node());if(\"x\"===a){var x=\"top\"===E.side?\"-\":\"\";l.attr(\"text-anchor\",\"middle\").call(u.positionText,0,\"top\"===E.side?D-y.bottom-M-S:D-y.top+M+S),g=E._offset+(A.x0+A.x1)/2,v=L._offset+(\"top\"===E.side?0:L._length);var b=y.width/2+S;g<b?(g=b,e.attr(\"d\",\"M-\"+(b-M)+\",0L-\"+(b-2*M)+\",\"+x+M+\"H\"+(S+y.width/2)+\"v\"+x+(2*S+y.height)+\"H-\"+b+\"V\"+x+M+\"Z\")):g>i.width-b?(g=i.width-b,e.attr(\"d\",\"M\"+(b-M)+\",0L\"+b+\",\"+x+M+\"v\"+x+(2*S+y.height)+\"H-\"+b+\"V\"+x+M+\"H\"+(b-2*M)+\"Z\")):e.attr(\"d\",\"M0,0L\"+M+\",\"+x+M+\"H\"+(S+y.width/2)+\"v\"+x+(2*S+y.height)+\"H-\"+(S+y.width/2)+\"V\"+x+M+\"H-\"+M+\"Z\")}else{var _,C,P;\"right\"===L.side?(_=\"start\",C=1,P=\"\",g=E._offset+E._length):(_=\"end\",C=-1,P=\"-\",g=E._offset),v=L._offset+(A.y0+A.y1)/2,l.attr(\"text-anchor\",_),e.attr(\"d\",\"M0,0L\"+P+M+\",\"+M+\"V\"+(S+y.height/2)+\"h\"+P+(2*S+y.width)+\"V-\"+(S+y.height/2)+\"H\"+P+M+\"V-\"+M+\"Z\");var O,z=y.height/2,R=D-y.top-z,F=\"clip\"+i._uid+\"commonlabel\"+L._id;if(g<y.width+2*S+M){O=\"M-\"+(M+S)+\"-\"+z+\"h-\"+(y.width-S)+\"V\"+z+\"h\"+(y.width-S)+\"Z\";var B=y.width-g+S;u.positionText(l,B,R),\"end\"===_&&l.selectAll(\"tspan\").each((function(){var t=n.select(this),e=h.tester.append(\"text\").text(t.text()).call(h.font,m),i=V(r,e.node());Math.round(i.width)<Math.round(y.width)&&t.attr(\"x\",B-i.width),e.remove()}))}else u.positionText(l,C*(S+M),R),O=null;var N=i._topclips.selectAll(\"#\"+F).data(O?[0]:[]);N.enter().append(\"clipPath\").attr(\"id\",F).append(\"path\"),N.exit().remove(),N.select(\"path\").attr(\"d\",O),h.setClipUrl(l,O?F:null,r)}t.attr(\"transform\",s(g,v))})),v.isUnifiedHover(a)){d.selectAll(\"g.hovertext\").remove();var G=t.filter((function(t){return\"none\"!==t.hoverinfo}));if(0===G.length)return;var Y=i.hoverlabel,W=Y.font,X={showlegend:!0,legend:{title:{text:I,font:W},font:W,bgcolor:Y.bgcolor,bordercolor:Y.bordercolor,borderwidth:1,tracegroupgap:7,traceorder:i.legend?i.legend.traceorder:void 0,orientation:\"v\"}},Z={font:W};x(X,Z,r._fullData);var J=Z.legend;J.entries=[];for(var K=0;K<G.length;K++){var Q=G[K];if(\"none\"!==Q.hoverinfo){var $=O(Q,!0,a,i,I),tt=$[0],et=$[1];Q.name=et,Q.text=\"\"!==et?et+\" : 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n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=t(\"../../plots/plots\"),o=t(\"../../registry\"),s=t(\"../../lib/events\"),l=t(\"../dragelement\"),c=t(\"../drawing\"),u=t(\"../color\"),f=t(\"../../lib/svg_text_utils\"),h=t(\"./handle_click\"),p=t(\"./constants\"),d=t(\"../../constants/alignment\"),m=d.LINE_SPACING,g=d.FROM_TL,v=d.FROM_BR,y=t(\"./get_legend_data\"),x=t(\"./style\"),b=t(\"./helpers\");function _(t,e,r,n,i){var a=r.data()[0][0].trace,l={event:i,node:r.node(),curveNumber:a.index,expandedIndex:a._expandedIndex,data:t.data,layout:t.layout,frames:t._transitionData._frames,config:t._context,fullData:t._fullData,fullLayout:t._fullLayout};if(a._group&&(l.group=a._group),o.traceIs(a,\"pie-like\")&&(l.label=r.datum()[0].label),!1!==s.triggerHandler(t,\"plotly_legendclick\",l))if(1===n)e._clickTimeout=setTimeout((function(){t._fullLayout&&h(r,t,n)}),t._context.doubleClickDelay);else 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rectangle\")},attr:\"dragmode\",val:\"drawrect\",icon:o.drawrect,click:f},u.drawcircle={name:\"drawcircle\",title:function(t){return c(t,\"Draw circle\")},attr:\"dragmode\",val:\"drawcircle\",icon:o.drawcircle,click:f},u.eraseshape={name:\"eraseshape\",title:function(t){return c(t,\"Erase active shape\")},icon:o.eraseshape,click:s},u.zoomIn2d={name:\"zoomIn2d\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:f},u.zoomOut2d={name:\"zoomOut2d\",_cat:\"zoomout\",title:function(t){return c(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:f},u.autoScale2d={name:\"autoScale2d\",_cat:\"autoscale\",title:function(t){return c(t,\"Autoscale\")},attr:\"zoom\",val:\"auto\",icon:o.autoscale,click:f},u.resetScale2d={name:\"resetScale2d\",_cat:\"resetscale\",title:function(t){return c(t,\"Reset axes\")},attr:\"zoom\",val:\"reset\",icon:o.home,click:f},u.hoverClosestCartesian={name:\"hoverClosestCartesian\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:o.tooltip_basic,gravity:\"ne\",click:f},u.hoverCompareCartesian={name:\"hoverCompareCartesian\",_cat:\"hoverCompare\",title:function(t){return c(t,\"Compare data on hover\")},attr:\"hovermode\",val:function(t){return t._fullLayout._isHoriz?\"y\":\"x\"},icon:o.tooltip_compare,gravity:\"ne\",click:f},u.zoom3d={name:\"zoom3d\",_cat:\"zoom\",title:function(t){return c(t,\"Zoom\")},attr:\"scene.dragmode\",val:\"zoom\",icon:o.zoombox,click:h},u.pan3d={name:\"pan3d\",_cat:\"pan\",title:function(t){return c(t,\"Pan\")},attr:\"scene.dragmode\",val:\"pan\",icon:o.pan,click:h},u.orbitRotation={name:\"orbitRotation\",title:function(t){return c(t,\"Orbital rotation\")},attr:\"scene.dragmode\",val:\"orbit\",icon:o[\"3d_rotate\"],click:h},u.tableRotation={name:\"tableRotation\",title:function(t){return c(t,\"Turntable rotation\")},attr:\"scene.dragmode\",val:\"turntable\",icon:o[\"z-axis\"],click:h},u.resetCameraDefault3d={name:\"resetCameraDefault3d\",_cat:\"resetCameraDefault\",title:function(t){return c(t,\"Reset camera to default\")},attr:\"resetDefault\",icon:o.home,click:p},u.resetCameraLastSave3d={name:\"resetCameraLastSave3d\",_cat:\"resetCameraLastSave\",title:function(t){return c(t,\"Reset camera to last save\")},attr:\"resetLastSave\",icon:o.movie,click:p},u.hoverClosest3d={name:\"hoverClosest3d\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=d(t,e);n.call(\"_guiRelayout\",t,r)}},u.zoomInGeo={name:\"zoomInGeo\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:m},u.zoomOutGeo={name:\"zoomOutGeo\",_cat:\"zoomout\",title:function(t){return c(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:m},u.resetGeo={name:\"resetGeo\",_cat:\"reset\",title:function(t){return c(t,\"Reset\")},attr:\"reset\",val:null,icon:o.autoscale,click:m},u.hoverClosestGeo={name:\"hoverClosestGeo\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:v},u.hoverClosestGl2d={name:\"hoverClosestGl2d\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:v},u.hoverClosestPie={name:\"hoverClosestPie\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:o.tooltip_basic,gravity:\"ne\",click:v},u.resetViewSankey={name:\"resetSankeyGroup\",title:function(t){return c(t,\"Reset view\")},icon:o.home,click:function(t){for(var e={\"node.groups\":[],\"node.x\":[],\"node.y\":[]},r=0;r<t._fullData.length;r++){var i=t._fullData[r]._viewInitial;e[\"node.groups\"].push(i.node.groups.slice()),e[\"node.x\"].push(i.node.x.slice()),e[\"node.y\"].push(i.node.y.slice())}n.call(\"restyle\",t,e)}},u.toggleHover={name:\"toggleHover\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=d(t,e);r.hovermode=g(t),n.call(\"_guiRelayout\",t,r)}},u.resetViews={name:\"resetViews\",title:function(t){return c(t,\"Reset views\")},icon:o.home,click:function(t,e){var r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),f(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),p(t,e),x(t,\"geo\"),x(t,\"mapbox\")}},u.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return c(t,\"Toggle Spike Lines\")},icon:o.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=a.list(t,null,!0),n={},i=0;i<r.length;i++){var o=r[i];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},u.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(t){return c(t,\"Reset view\")},attr:\"reset\",icon:o.home,click:function(t){x(t,\"mapbox\")}},u.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:y},u.zoomOutMapbox={name:\"zoomOutMapbox\",_cat:\"zoomout\",title:function(t){return c(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:y}},{\"../../fonts/ploticon\":482,\"../../lib\":503,\"../../plots/cartesian/axis_ids\":558,\"../../plots/plots\":619,\"../../registry\":638,\"../shapes/draw\":450}],427:[function(t,e,r){\"use strict\";var n=t(\"./buttons\"),i=Object.keys(n),a=[\"drawline\",\"drawopenpath\",\"drawclosedpath\",\"drawcircle\",\"drawrect\",\"eraseshape\"],o=[\"v1hovermode\",\"hoverclosest\",\"hovercompare\",\"togglehover\",\"togglespikelines\"].concat(a),s=[];i.forEach((function(t){!function(t){if(-1===o.indexOf(t._cat||t.name)){var e=t.name,r=(t._cat||t.name).toLowerCase();-1===s.indexOf(e)&&s.push(e),-1===s.indexOf(r)&&s.push(r)}}(n[t])})),s.sort(),e.exports={DRAW_MODES:a,backButtons:o,foreButtons:s}},{\"./buttons\":426}],428:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\"),a=t(\"../../plot_api/plot_template\"),o=t(\"./attributes\");e.exports=function(t,e){var r=t.modebar||{},s=a.newContainer(e,\"modebar\");function l(t,e){return n.coerce(r,s,o,t,e)}l(\"orientation\"),l(\"bgcolor\",i.addOpacity(e.paper_bgcolor,.5));var c=i.contrast(i.rgb(e.modebar.bgcolor));l(\"color\",i.addOpacity(c,.3)),l(\"activecolor\",i.addOpacity(c,.7)),l(\"uirevision\",e.uirevision),l(\"add\"),l(\"remove\")}},{\"../../lib\":503,\"../../plot_api/plot_template\":543,\"../color\":366,\"./attributes\":425}],429:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"modebar\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),manage:t(\"./manage\")}},{\"./attributes\":425,\"./defaults\":428,\"./manage\":430}],430:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axis_ids\"),i=t(\"../../traces/scatter/subtypes\"),a=t(\"../../registry\"),o=t(\"../fx/helpers\").isUnifiedHover,s=t(\"./modebar\"),l=t(\"./buttons\"),c=t(\"./constants\").DRAW_MODES,u=t(\"../../lib\").extendDeep;e.exports=function(t){var e=t._fullLayout,r=t._context,f=e._modeBar;if(r.displayModeBar||r.watermark){if(!Array.isArray(r.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(r.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var h,p=r.modeBarButtons;h=Array.isArray(p)&&p.length?function(t){for(var e=u([],t),r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++){var a=n[i];if(\"string\"==typeof a){if(void 0===l[a])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));e[r][i]=l[a]}}return e}(p):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,s=t._context;function u(t,e){if(\"string\"==typeof e){if(e.toLowerCase()===t.toLowerCase())return!0}else{var r=e.name,n=e._cat||e.name;if(r===t||n===t.toLowerCase())return!0}return!1}var f=e.modebar.add;\"string\"==typeof f&&(f=[f]);var h=e.modebar.remove;\"string\"==typeof h&&(h=[h]);var p=s.modeBarButtonsToAdd.concat(f.filter((function(t){for(var e=0;e<s.modeBarButtonsToRemove.length;e++)if(u(t,s.modeBarButtonsToRemove[e]))return!1;return!0}))),d=s.modeBarButtonsToRemove.concat(h.filter((function(t){for(var e=0;e<s.modeBarButtonsToAdd.length;e++)if(u(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),m=e._has(\"cartesian\"),g=e._has(\"gl3d\"),v=e._has(\"geo\"),y=e._has(\"pie\"),x=e._has(\"funnelarea\"),b=e._has(\"gl2d\"),_=e._has(\"ternary\"),w=e._has(\"mapbox\"),T=e._has(\"polar\"),k=e._has(\"smith\"),A=e._has(\"sankey\"),M=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),S=o(e.hovermode),E=[];function L(t){if(t.length){for(var e=[],r=0;r<t.length;r++){for(var n=t[r],i=l[n],a=i.name.toLowerCase(),o=(i._cat||i.name).toLowerCase(),s=!1,c=0;c<d.length;c++){var u=d[c].toLowerCase();if(u===a||u===o){s=!0;break}}s||e.push(l[n])}E.push(e)}}var C=[\"toImage\"];s.showEditInChartStudio?C.push(\"editInChartStudio\"):s.showSendToCloud&&C.push(\"sendDataToCloud\");L(C);var P=[],I=[],O=[],z=[];(m||b||y||x||_)+v+g+w+T+k>1?(I=[\"toggleHover\"],O=[\"resetViews\"]):v?(P=[\"zoomInGeo\",\"zoomOutGeo\"],I=[\"hoverClosestGeo\"],O=[\"resetGeo\"]):g?(I=[\"hoverClosest3d\"],O=[\"resetCameraDefault3d\",\"resetCameraLastSave3d\"]):w?(P=[\"zoomInMapbox\",\"zoomOutMapbox\"],I=[\"toggleHover\"],O=[\"resetViewMapbox\"]):b?I=[\"hoverClosestGl2d\"]:y?I=[\"hoverClosestPie\"]:A?(I=[\"hoverClosestCartesian\",\"hoverCompareCartesian\"],O=[\"resetViewSankey\"]):I=[\"toggleHover\"];m&&(I=[\"toggleSpikelines\",\"hoverClosestCartesian\",\"hoverCompareCartesian\"]);(function(t){for(var e=0;e<t.length;e++)if(!a.traceIs(t[e],\"noHover\"))return!1;return!0}(r)||S)&&(I=[]);!m&&!b||M||(P=[\"zoomIn2d\",\"zoomOut2d\",\"autoScale2d\"],\"resetViews\"!==O[0]&&(O=[\"resetScale2d\"]));g?z=[\"zoom3d\",\"pan3d\",\"orbitRotation\",\"tableRotation\"]:(m||b)&&!M||_?z=[\"zoom2d\",\"pan2d\"]:w||v?z=[\"pan2d\"]:T&&(z=[\"zoom2d\"]);(function(t){for(var e=!1,r=0;r<t.length&&!e;r++){var n=t[r];n._module&&n._module.selectPoints&&(a.traceIs(n,\"scatter-like\")?(i.hasMarkers(n)||i.hasText(n))&&(e=!0):a.traceIs(n,\"box-violin\")&&\"all\"!==n.boxpoints&&\"all\"!==n.points||(e=!0))}return e})(r)&&z.push(\"select2d\",\"lasso2d\");var D=[],R=function(t){-1===D.indexOf(t)&&-1!==I.indexOf(t)&&D.push(t)};if(Array.isArray(p)){for(var F=[],B=0;B<p.length;B++){var N=p[B];\"string\"==typeof N?(N=N.toLowerCase(),-1!==c.indexOf(N)?(e._has(\"mapbox\")||e._has(\"cartesian\"))&&z.push(N):\"togglespikelines\"===N?R(\"toggleSpikelines\"):\"togglehover\"===N?R(\"toggleHover\"):\"hovercompare\"===N?R(\"hoverCompareCartesian\"):\"hoverclosest\"===N?(R(\"hoverClosestCartesian\"),R(\"hoverClosestGeo\"),R(\"hoverClosest3d\"),R(\"hoverClosestGl2d\"),R(\"hoverClosestPie\")):\"v1hovermode\"===N&&(R(\"toggleHover\"),R(\"hoverClosestCartesian\"),R(\"hoverCompareCartesian\"),R(\"hoverClosestGeo\"),R(\"hoverClosest3d\"),R(\"hoverClosestGl2d\"),R(\"hoverClosestPie\"))):F.push(N)}p=F}return L(z),L(P.concat(O)),L(D),function(t,e){if(e.length)if(Array.isArray(e[0]))for(var r=0;r<e.length;r++)t.push(e[r]);else t.push(e);return t}(E,p)}(t),f?f.update(t,h):e._modeBar=s(t,h)}else f&&(f.destroy(),delete e._modeBar)}},{\"../../lib\":503,\"../../plots/cartesian/axis_ids\":558,\"../../registry\":638,\"../../traces/scatter/subtypes\":952,\"../fx/helpers\":402,\"./buttons\":426,\"./constants\":427,\"./modebar\":431}],431:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"fast-isnumeric\"),a=t(\"../../lib\"),o=t(\"../../fonts/ploticon\"),s=t(\"../../version\").version,l=new DOMParser;function c(t){this.container=t.container,this.element=document.createElement(\"div\"),this.update(t.graphInfo,t.buttons),this.container.appendChild(this.element)}var u=c.prototype;u.update=function(t,e){this.graphInfo=t;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,i=\"modebar-\"+n._uid;this.element.setAttribute(\"id\",i),this._uid=i,this.element.className=\"modebar\",\"hover\"===r.displayModeBar&&(this.element.className+=\" modebar--hover ease-bg\"),\"v\"===n.modebar.orientation&&(this.element.className+=\" vertical\",e=e.reverse());var o=n.modebar,s=\"hover\"===r.displayModeBar?\".js-plotly-plot .plotly:hover \":\"\";a.deleteRelatedStyleRule(i),a.addRelatedStyleRule(i,s+\"#\"+i+\" .modebar-group\",\"background-color: \"+o.bgcolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn .icon path\",\"fill: \"+o.color),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn:hover .icon path\",\"fill: \"+o.activecolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn.active .icon path\",\"fill: \"+o.activecolor);var l=!this.hasButtons(e),c=this.hasLogo!==r.displaylogo,u=this.locale!==r.locale;if(this.locale=r.locale,(l||c||u)&&(this.removeAllButtons(),this.updateButtons(e),r.watermark||r.displaylogo)){var f=this.getLogo();r.watermark&&(f.className=f.className+\" watermark\"),\"v\"===n.modebar.orientation?this.element.insertBefore(f,this.element.childNodes[0]):this.element.appendChild(f),this.hasLogo=!0}this.updateActiveButton()},u.updateButtons=function(t){var e=this;this.buttons=t,this.buttonElements=[],this.buttonsNames=[],this.buttons.forEach((function(t){var r=e.createGroup();t.forEach((function(t){var n=t.name;if(!n)throw new Error(\"must provide button 'name' in button config\");if(-1!==e.buttonsNames.indexOf(n))throw new Error(\"button name '\"+n+\"' is taken\");e.buttonsNames.push(n);var i=e.createButton(t);e.buttonElements.push(i),r.appendChild(i)})),e.element.appendChild(r)}))},u.createGroup=function(){var t=document.createElement(\"div\");return t.className=\"modebar-group\",t},u.createButton=function(t){var e=this,r=document.createElement(\"a\");r.setAttribute(\"rel\",\"tooltip\"),r.className=\"modebar-btn\";var i=t.title;void 0===i?i=t.name:\"function\"==typeof i&&(i=i(this.graphInfo)),(i||0===i)&&r.setAttribute(\"data-title\",i),void 0!==t.attr&&r.setAttribute(\"data-attr\",t.attr);var a=t.val;if(void 0!==a&&(\"function\"==typeof a&&(a=a(this.graphInfo)),r.setAttribute(\"data-val\",a)),\"function\"!=typeof t.click)throw new Error(\"must provide button 'click' function in button config\");r.addEventListener(\"click\",(function(r){t.click(e.graphInfo,r),e.updateActiveButton(r.currentTarget)})),r.setAttribute(\"data-toggle\",t.toggle||!1),t.toggle&&n.select(r).classed(\"active\",!0);var s=t.icon;return\"function\"==typeof s?r.appendChild(s()):r.appendChild(this.createIcon(s||o.question)),r.setAttribute(\"data-gravity\",t.gravity||\"n\"),r},u.createIcon=function(t){var e,r=i(t.height)?Number(t.height):t.ascent-t.descent,n=\"http://www.w3.org/2000/svg\";if(t.path){(e=document.createElementNS(n,\"svg\")).setAttribute(\"viewBox\",[0,0,t.width,r].join(\" \")),e.setAttribute(\"class\",\"icon\");var a=document.createElementNS(n,\"path\");a.setAttribute(\"d\",t.path),t.transform?a.setAttribute(\"transform\",t.transform):void 0!==t.ascent&&a.setAttribute(\"transform\",\"matrix(1 0 0 -1 0 \"+t.ascent+\")\"),e.appendChild(a)}t.svg&&(e=l.parseFromString(t.svg,\"application/xml\").childNodes[0]);return e.setAttribute(\"height\",\"1em\"),e.setAttribute(\"width\",\"1em\"),e},u.updateActiveButton=function(t){var e=this.graphInfo._fullLayout,r=void 0!==t?t.getAttribute(\"data-attr\"):null;this.buttonElements.forEach((function(t){var i=t.getAttribute(\"data-val\")||!0,o=t.getAttribute(\"data-attr\"),s=\"true\"===t.getAttribute(\"data-toggle\"),l=n.select(t);if(s)o===r&&l.classed(\"active\",!l.classed(\"active\"));else{var c=null===o?o:a.nestedProperty(e,o).get();l.classed(\"active\",c===i)}}))},u.hasButtons=function(t){var e=this.buttons;if(!e)return!1;if(t.length!==e.length)return!1;for(var r=0;r<t.length;++r){if(t[r].length!==e[r].length)return!1;for(var 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t.match(n.segmentRE).forEach((function(t){var a=e[t.charAt(0)].drawn;if(void 0!==a){var o=t.substr(1).match(n.paramRE);!o||o.length<a||r.push(i.cleanNumber(o[a]))}})),r},r.getDataToPixel=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){return e._length*(n?1-t:t)+e._offset};else{var s=r.shapePositionToRange(e);a=function(t){return e._offset+e.r2p(s(t,!0))},\"date\"===e.type&&(a=r.decodeDate(a))}else a=n?function(t){return o.t+o.h*(1-t)}:function(t){return o.l+o.w*t};return a},r.getPixelToData=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){var r=(t-e._offset)/e._length;return n?1-r:r};else{var s=r.rangeToShapePosition(e);a=function(t){return s(e.p2r(t-e._offset))}}else a=n?function(t){return 1-(t-o.t)/o.h}:function(t){return(t-o.l)/o.w};return a},r.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n},r.makeOptionsAndPlotinfo=function(t,e){var 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n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/pad_attributes\"),a=t(\"../../lib/extend\").extendDeepAll,o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../plots/animation_attributes\"),l=t(\"../../plot_api/plot_template\").templatedArray,c=t(\"./constants\"),u=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});e.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:u,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:c.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:c.railBgColor},bordercolor:{valType:\"color\",dflt:c.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:c.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:c.tickLength},tickcolor:{valType:\"color\",dflt:c.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:c.minorTickLength}}),\"arraydraw\",\"from-root\")},{\"../../lib/extend\":493,\"../../plot_api/edit_types\":536,\"../../plot_api/plot_template\":543,\"../../plots/animation_attributes\":548,\"../../plots/font_attributes\":585,\"../../plots/pad_attributes\":618,\"./constants\":460}],460:[function(t,e,r){\"use 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T={y:e.y,b:u.height*m[w],t:u.height*d[w]};\"fraction\"===e.lenmode?(T.l=0,T.xl=e.x-e.len*d[b],T.r=0,T.xr=e.x+e.len*m[b]):(T.x=e.x,T.l=u.outerLength*d[b],T.r=u.outerLength*m[b]),i.autoMargin(t,g(e),T)}function x(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=a.inputAreaLength-f.currentValueInset-a.currentValueMaxWidth,i=\"left\";break;case\"center\":n=.5*a.inputAreaLength,i=\"middle\";break;default:n=f.currentValueInset,i=\"left\"}var l=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":i,\"data-notex\":1})})),u=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)u+=r;else{var h=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(h=s.templateString(h,d)),u+=h}e.currentvalue.suffix&&(u+=e.currentvalue.suffix),l.call(o.font,e.currentvalue.font).text(u).call(c.convertToTspans,e._gd);var m=c.lineCount(l),g=(a.currentValueMaxLines+1-m)*e.currentvalue.font.size*p;return 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t=s(),a=L(t,n.mouse(i)[0]);T(e,r,t,a,!1)}function h(){var t=s();t._dragging=!1,l.call(a.fill,t.bgcolor),o.on(\"mouseup\",null),o.on(\"mousemove\",null),o.on(\"touchend\",null),o.on(\"touchmove\",null),e.emit(\"plotly_sliderend\",{slider:t,step:t.steps[t.active]})}T(e,r,t,c,!0),t._dragging=!0,o.on(\"mousemove\",u),o.on(\"touchmove\",u),o.on(\"mouseup\",h),o.on(\"touchend\",h)}t.on(\"mousedown\",l),t.on(\"touchstart\",l)}function M(t,e){var r=t.selectAll(\"rect.\"+f.tickRectClass).data(e._visibleSteps),i=e._dims;r.enter().append(\"rect\").classed(f.tickRectClass,!0),r.exit().remove(),r.attr({width:e.tickwidth+\"px\",\"shape-rendering\":\"crispEdges\"}),r.each((function(t,r){var s=r%i.labelStride==0,l=n.select(this);l.attr({height:s?e.ticklen:e.minorticklen}).call(a.fill,e.tickcolor),o.setTranslate(l,E(e,r/(e._stepCount-1))-.5*e.tickwidth,(s?f.tickOffset:f.minorTickOffset)+i.currentValueTotalHeight)}))}function S(t,e,r){for(var 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n=t(\"@plotly/d3\"),i=t(\"d3-time-format\").utcFormat,a=t(\"d3-format\").format,o=t(\"fast-isnumeric\"),s=t(\"../constants/numerical\"),l=s.FP_SAFE,c=-l,u=s.BADNUM,f=e.exports={};f.adjustFormat=function(t){return!t||/^\\d[.]\\df/.test(t)||/[.]\\d%/.test(t)?t:\"0.f\"===t?\"~f\":/^\\d%/.test(t)?\"~%\":/^\\ds/.test(t)?\"~s\":!/^[~,.0$]/.test(t)&&/[&fps]/.test(t)?\"~\"+t:t};var h={};f.warnBadFormat=function(t){var e=String(t);h[e]||(h[e]=1,f.warn('encountered bad format: \"'+e+'\"'))},f.noFormat=function(t){return String(t)},f.numberFormat=function(t){var e;try{e=a(f.adjustFormat(t))}catch(e){return f.warnBadFormat(t),f.noFormat}return e},f.nestedProperty=t(\"./nested_property\"),f.keyedContainer=t(\"./keyed_container\"),f.relativeAttr=t(\"./relative_attr\"),f.isPlainObject=t(\"./is_plain_object\"),f.toLogRange=t(\"./to_log_range\"),f.relinkPrivateKeys=t(\"./relink_private\");var 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b=0;b<t.calcdata.length;b++)t.calcdata[b][0].trace=t._fullData[b];t._context.responsive?t._responsiveChartHandler||(t._responsiveChartHandler=function(){o.isHidden(t)||h.resize(t)},window.addEventListener(\"resize\",t._responsiveChartHandler)):o.clearResponsive(t);var T=o.extendFlat({},m._size),k=0;function A(){if(h.clearAutoMarginIds(t),w.drawMarginPushers(t),p.allowAutoMargin(t),m._has(\"pie\"))for(var e=t._fullData,r=0;r<e.length;r++){var n=e[r];\"pie\"===n.type&&n.automargin&&h.allowAutoMargin(t,\"pie.\"+n.uid+\".automargin\")}return h.doAutoMargin(t),h.previousPromises(t)}function S(){t._transitioning||(w.doAutoRangeAndConstraints(t),f&&p.saveRangeInitial(t),u.getComponentMethod(\"rangeslider\",\"calcAutorange\")(t))}var E=[h.previousPromises,function(){if(s)return r.addFrames(t,s)},function e(){for(var 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u=e._clips.selectAll(\".axesclip\").data(c,(function(t){return t.x._id+t.y._id}));u.enter().append(\"clipPath\").classed(\"axesclip\",!0).attr(\"id\",(function(t){return\"clip\"+e._uid+t.x._id+t.y._id})).append(\"rect\"),u.exit().remove(),u.each((function(t){n.select(this).select(\"rect\").attr({x:t.x._offset||0,y:t.y._offset||0,width:t.x._length||1,height:t.y._length||1})}))}},H.draw=function(t,e,r){var n=t._fullLayout;\"redraw\"===e&&n._paper.selectAll(\"g.subplot\").each((function(t){var e=t[0],r=n._plots[e];if(r){var i=r.xaxis,a=r.yaxis;r.xaxislayer.selectAll(\".\"+i._id+\"tick\").remove(),r.yaxislayer.selectAll(\".\"+a._id+\"tick\").remove(),r.xaxislayer.selectAll(\".\"+i._id+\"tick2\").remove(),r.yaxislayer.selectAll(\".\"+a._id+\"tick2\").remove(),r.xaxislayer.selectAll(\".\"+i._id+\"divider\").remove(),r.yaxislayer.selectAll(\".\"+a._id+\"divider\").remove(),r.minorGridlayer&&r.minorGridlayer.selectAll(\"path\").remove(),r.gridlayer&&r.gridlayer.selectAll(\"path\").remove(),r.zerolinelayer&&r.zerolinelayer.selectAll(\"path\").remove(),n._infolayer.select(\".g-\"+i._id+\"title\").remove(),n._infolayer.select(\".g-\"+a._id+\"title\").remove()}}));var i=e&&\"redraw\"!==e?e:H.listIds(t);return s.syncOrAsync(i.map((function(e){return function(){if(e){var n=H.getFromId(t,e),i=H.drawOne(t,n,r);return n._r=n.range.slice(),n._rl=s.simpleMap(n._r,n.r2l),i}}})))},H.drawOne=function(t,e,r){var n,i,l;r=r||{},e.setScale();var c=t._fullLayout,p=e._id,d=p.charAt(0),m=H.counterLetter(p),g=c._plots[e._mainSubplot];if(g){var v=g[d+\"axislayer\"],y=e._mainLinePosition,x=e._mainMirrorPosition,b=e._vals=H.calcTicks(e),_=[e.mirror,y,x].join(\"_\");for(n=0;n<b.length;n++)b[n].axInfo=_;e._selections={},e._tickAngles&&(e._prevTickAngles=e._tickAngles),e._tickAngles={},e._depth=null;var w={};if(e.visible){var T,k,A=H.makeTransTickFn(e),M=H.makeTransTickLabelFn(e),S=\"inside\"===e.ticks,E=\"outside\"===e.ticks;if(\"boundaries\"===e.tickson){var L=function(t,e){var r,n=[],i=function(t,e){var r=t.xbnd[e];null!==r&&n.push(s.extendFlat({},t,{x:r}))};if(e.length){for(r=0;r<e.length;r++)i(e[r],0);i(e[r-1],1)}return n}(0,b);k=H.clipEnds(e,L),T=S?k:L}else k=H.clipEnds(e,b),T=S&&\"period\"!==e.ticklabelmode?k:b;var C,P=e._gridVals=k,I=function(t,e){var r,n,i=[],a=e.length&&e[e.length-1].x<e[0].x,o=function(t,e){var r=t.xbnd[e];null!==r&&i.push(s.extendFlat({},t,{x:r}))};if(t.showdividers&&e.length){for(r=0;r<e.length;r++){var l=e[r];l.text2!==n&&o(l,a?1:0),n=l.text2}o(e[r-1],a?0:1)}return i}(e,b);if(!c._hasOnlyLargeSploms){var O=e._subplotsWith,z={};for(n=0;n<O.length;n++){i=O[n];var D=(l=c._plots[i])[m+\"axis\"],R=D._mainAxis._id;if(!z[R]){z[R]=1;var F=\"x\"===d?\"M0,\"+D._offset+\"v\"+D._length:\"M\"+D._offset+\",0h\"+D._length;H.drawGrid(t,e,{vals:P,counterAxis:D,layer:l.gridlayer.select(\".\"+p),minorLayer:l.minorGridlayer.select(\".\"+p),path:F,transFn:A}),H.drawZeroLine(t,e,{counterAxis:D,layer:l.zerolinelayer,path:F,transFn:A})}}}var B=H.getTickSigns(e),N=H.getTickSigns(e,\"minor\");if(e.ticks||e.minor&&e.minor.ticks){var j,q,G,Y,W=H.makeTickPath(e,y,B[2]),X=H.makeTickPath(e,y,N[2],{minor:!0});if(e._anchorAxis&&e.mirror&&!0!==e.mirror?(j=H.makeTickPath(e,x,B[3]),q=H.makeTickPath(e,x,N[3],{minor:!0}),G=W+j,Y=X+q):(j=\"\",q=\"\",G=W,Y=X),e.showdividers&&E&&\"boundaries\"===e.tickson){var Z={};for(n=0;n<I.length;n++)Z[I[n].x]=1;C=function(t){return Z[t.x]?j:G}}else C=function(t){return t.minor?Y:G}}if(H.drawTicks(t,e,{vals:T,layer:v,path:C,transFn:A}),\"allticks\"===e.mirror){var J=Object.keys(e._linepositions||{});for(n=0;n<J.length;n++){i=J[n],l=c._plots[i];var K=e._linepositions[i]||[],Q=K[0],$=K[1],tt=K[2],et=H.makeTickPath(e,Q,tt?B[0]:N[0],{minor:tt})+H.makeTickPath(e,$,tt?B[1]:N[1],{minor:tt});H.drawTicks(t,e,{vals:T,layer:l[d+\"axislayer\"],path:et,transFn:A})}}var rt=[];if(rt.push((function(){return H.drawLabels(t,e,{vals:b,layer:v,plotinfo:l,transFn:M,labelFns:H.makeLabelFns(e,y)})})),\"multicategory\"===e.type){var nt={x:2,y:10}[d];rt.push((function(){var r={x:\"height\",y:\"width\"}[d],n=at()[r]+nt+(e._tickAngles[p+\"tick\"]?e.tickfont.size*U:0);return H.drawLabels(t,e,{vals:vt(e,b),layer:v,cls:p+\"tick2\",repositionOnUpdate:!0,secondary:!0,transFn:A,labelFns:H.makeLabelFns(e,y+n*B[4])})})),rt.push((function(){return e._depth=B[4]*(at(\"tick2\")[e.side]-y),function(t,e,r){var n=e._id+\"divider\",i=r.vals,a=r.layer.selectAll(\"path.\"+n).data(i,xt);a.exit().remove(),a.enter().insert(\"path\",\":first-child\").classed(n,1).classed(\"crisp\",1).call(f.stroke,e.dividercolor).style(\"stroke-width\",h.crispRound(t,e.dividerwidth,1)+\"px\"),a.attr(\"transform\",r.transFn).attr(\"d\",r.path)}(t,e,{vals:I,layer:v,path:H.makeTickPath(e,y,B[4],{len:e._depth}),transFn:A})}))}else e.title.hasOwnProperty(\"standoff\")&&rt.push((function(){e._depth=B[4]*(at()[e.side]-y)}));var it=o.getComponentMethod(\"rangeslider\",\"isVisible\")(e);return rt.push((function(){var r,n,i,s,l=e.side.charAt(0),u=V[e.side].charAt(0),f=H.getPxPosition(t,e),h=E?e.ticklen:0;if((e.automargin||it)&&(\"multicategory\"===e.type?r=at(\"tick2\"):(r=at(),\"x\"===d&&\"b\"===l&&(e._depth=Math.max(r.width>0?r.bottom-f:0,h)))),e.automargin){n={x:0,y:0,r:0,l:0,t:0,b:0};var p=[0,1];if(\"x\"===d){if(\"b\"===l?n[l]=e._depth:(n[l]=e._depth=Math.max(r.width>0?f-r.top:0,h),p.reverse()),r.width>0){var g=r.right-(e._offset+e._length);g>0&&(n.xr=1,n.r=g);var v=e._offset-r.left;v>0&&(n.xl=0,n.l=v)}}else if(\"l\"===l?n[l]=e._depth=Math.max(r.height>0?f-r.left:0,h):(n[l]=e._depth=Math.max(r.height>0?r.right-f:0,h),p.reverse()),r.height>0){var y=r.bottom-(e._offset+e._length);y>0&&(n.yb=0,n.b=y);var x=e._offset-r.top;x>0&&(n.yt=1,n.t=x)}n[m]=\"free\"===e.anchor?e.position:e._anchorAxis.domain[p[0]],e.title.text!==c._dfltTitle[d]&&(n[l]+=bt(e)+(e.title.standoff||0)),e.mirror&&\"free\"!==e.anchor&&((i={x:0,y:0,r:0,l:0,t:0,b:0})[u]=e.linewidth,e.mirror&&!0!==e.mirror&&(i[u]+=h),!0===e.mirror||\"ticks\"===e.mirror?i[m]=e._anchorAxis.domain[p[1]]:\"all\"!==e.mirror&&\"allticks\"!==e.mirror||(i[m]=[e._counterDomainMin,e._counterDomainMax][p[1]]))}it&&(s=o.getComponentMethod(\"rangeslider\",\"autoMarginOpts\")(t,e)),a.autoMargin(t,Tt(e),n),a.autoMargin(t,kt(e),i),a.autoMargin(t,At(e),s)})),r.skipTitle||it&&\"bottom\"===e.side||rt.push((function(){return function(t,e){var r,n=t._fullLayout,i=e._id,a=i.charAt(0),o=e.title.font.size;if(e.title.hasOwnProperty(\"standoff\"))r=e._depth+e.title.standoff+bt(e);else{var s=Pt(e);if(\"multicategory\"===e.type)r=e._depth;else{var l=1.5*o;s&&(l=.5*o,\"outside\"===e.ticks&&(l+=e.ticklen)),r=10+l+(e.linewidth?e.linewidth-1:0)}s||(r+=\"x\"===a?\"top\"===e.side?o*(e.showticklabels?1:0):o*(e.showticklabels?1.5:.5):\"right\"===e.side?o*(e.showticklabels?1:.5):o*(e.showticklabels?.5:0))}var c,f,p,d,m=H.getPxPosition(t,e);\"x\"===a?(f=e._offset+e._length/2,p=\"top\"===e.side?m-r:m+r):(p=e._offset+e._length/2,f=\"right\"===e.side?m+r:m-r,c={rotate:\"-90\",offset:0});if(\"multicategory\"!==e.type){var g=e._selections[e._id+\"tick\"];if(d={selection:g,side:e.side},g&&g.node()&&g.node().parentNode){var v=h.getTranslate(g.node().parentNode);d.offsetLeft=v.x,d.offsetTop=v.y}e.title.hasOwnProperty(\"standoff\")&&(d.pad=0)}return u.draw(t,i+\"title\",{propContainer:e,propName:e._name+\".title.text\",placeholder:n._dfltTitle[a],avoid:d,transform:c,attributes:{x:f,y:p,\"text-anchor\":\"middle\"}})}(t,e)})),s.syncOrAsync(rt)}}function at(t){var r=p+(t||\"tick\");return w[r]||(w[r]=function(t,e){var r,n,i,a;t._selections[e].size()?(r=1/0,n=-1/0,i=1/0,a=-1/0,t._selections[e].each((function(){var t=wt(this),e=h.bBox(t.node().parentNode);r=Math.min(r,e.top),n=Math.max(n,e.bottom),i=Math.min(i,e.left),a=Math.max(a,e.right)}))):(r=0,n=0,i=0,a=0);return{top:r,bottom:n,left:i,right:a,height:n-r,width:a-i}}(e,r)),w[r]}},H.getTickSigns=function(t,e){var r=t._id.charAt(0),n={x:\"top\",y:\"right\"}[r],i=t.side===n?1:-1,a=[-1,1,i,-i];return\"inside\"!==(e?(t.minor||{}).ticks:t.ticks)==(\"x\"===r)&&(a=a.map((function(t){return-t}))),t.side&&a.push({l:-1,t:-1,r:1,b:1}[t.side.charAt(0)]),a},H.makeTransTickFn=function(t){return\"x\"===t._id.charAt(0)?function(e){return l(t._offset+t.l2p(e.x),0)}:function(e){return l(0,t._offset+t.l2p(e.x))}},H.makeTransTickLabelFn=function(t){var e=function(t){var e=t.ticklabelposition||\"\",r=function(t){return-1!==e.indexOf(t)},n=r(\"top\"),i=r(\"left\"),a=r(\"right\"),o=r(\"bottom\"),s=r(\"inside\"),l=o||i||n||a;if(!l&&!s)return[0,0];var c=t.side,u=l?(t.tickwidth||0)/2:0,f=3,h=t.tickfont?t.tickfont.size:12;(o||n)&&(u+=h*j,f+=(t.linewidth||0)/2);(i||a)&&(u+=(t.linewidth||0)/2,f+=3);s&&\"top\"===c&&(f-=h*(1-j));(i||n)&&(u=-u);\"bottom\"!==c&&\"right\"!==c||(f=-f);return[l?u:0,s?f:0]}(t),r=e[0],n=e[1];return\"x\"===t._id.charAt(0)?function(e){return l(r+t._offset+t.l2p(yt(e)),n)}:function(e){return l(n,r+t._offset+t.l2p(yt(e)))}},H.makeTickPath=function(t,e,r,n){n||(n={});var i=n.minor;if(i&&!t.minor)return\"\";var a=void 0!==n.len?n.len:i?t.minor.ticklen:t.ticklen,o=t._id.charAt(0),s=(t.linewidth||1)/2;return\"x\"===o?\"M0,\"+(e+s*r)+\"v\"+a*r:\"M\"+(e+s*r)+\",0h\"+a*r},H.makeLabelFns=function(t,e,r){var n=t.ticklabelposition||\"\",a=function(t){return-1!==n.indexOf(t)},o=a(\"top\"),l=a(\"left\"),c=a(\"right\"),u=a(\"bottom\")||l||o||c,f=a(\"inside\"),h=\"inside\"===n&&\"inside\"===t.ticks||!f&&\"outside\"===t.ticks&&\"boundaries\"!==t.tickson,p=0,d=0,m=h?t.ticklen:0;if(f?m*=-1:u&&(m=0),h&&(p+=m,r)){var g=s.deg2rad(r);p=m*Math.cos(g)+1,d=m*Math.sin(g)}t.showticklabels&&(h||t.showline)&&(p+=.2*t.tickfont.size);var v,y,x,b,_,w={labelStandoff:p+=(t.linewidth||1)/2*(f?-1:1),labelShift:d},T=0,k=t.side,A=t._id.charAt(0),M=t.tickangle;if(\"x\"===A)b=(_=!f&&\"bottom\"===k||f&&\"top\"===k)?1:-1,f&&(b*=-1),v=d*b,y=e+p*b,x=_?1:-.2,90===Math.abs(M)&&(f?x+=N:x=-90===M&&\"bottom\"===k?j:90===M&&\"top\"===k?N:.5,T=N/2*(M/90)),w.xFn=function(t){return t.dx+v+T*t.fontSize},w.yFn=function(t){return t.dy+y+t.fontSize*x},w.anchorFn=function(t,e){if(u){if(l)return\"end\";if(c)return\"start\"}return i(e)&&0!==e&&180!==e?e*b<0!==f?\"end\":\"start\":\"middle\"},w.heightFn=function(e,r,n){return r<-60||r>60?-.5*n:\"top\"===t.side!==f?-n:0};else if(\"y\"===A){if(b=(_=!f&&\"left\"===k||f&&\"right\"===k)?1:-1,f&&(b*=-1),v=p,y=d*b,x=0,f||90!==Math.abs(M)||(x=-90===M&&\"left\"===k||90===M&&\"right\"===k?j:.5),f){var S=i(M)?+M:0;if(0!==S){var E=s.deg2rad(S);T=Math.abs(Math.sin(E))*j*b,x=0}}w.xFn=function(t){return t.dx+e-(v+t.fontSize*x)*b+T*t.fontSize},w.yFn=function(t){return t.dy+y+t.fontSize*N},w.anchorFn=function(t,e){return i(e)&&90===Math.abs(e)?\"middle\":_?\"end\":\"start\"},w.heightFn=function(e,r,n){return\"right\"===t.side&&(r*=-1),r<-30?-n:r<30?-.5*n:0}}return w},H.drawTicks=function(t,e,r){r=r||{};var i=e._id+\"tick\",a=[].concat(e.minor&&e.minor.ticks?r.vals.filter((function(t){return t.minor&&!t.noTick})):[]).concat(e.ticks?r.vals.filter((function(t){return!t.minor&&!t.noTick})):[]),o=r.layer.selectAll(\"path.\"+i).data(a,xt);o.exit().remove(),o.enter().append(\"path\").classed(i,1).classed(\"ticks\",1).classed(\"crisp\",!1!==r.crisp).each((function(t){return f.stroke(n.select(this),t.minor?e.minor.tickcolor:e.tickcolor)})).style(\"stroke-width\",(function(r){return h.crispRound(t,r.minor?e.minor.tickwidth:e.tickwidth,1)+\"px\"})).attr(\"d\",r.path).style(\"display\",null),It(e,[R]),o.attr(\"transform\",r.transFn)},H.drawGrid=function(t,e,r){r=r||{};var i=e._id+\"grid\",a=e.minor&&e.minor.showgrid,o=a?r.vals.filter((function(t){return t.minor})):[],s=e.showgrid?r.vals.filter((function(t){return!t.minor})):[],l=r.counterAxis;if(l&&H.shouldShowZeroLine(t,e,l))for(var c=\"array\"===e.tickmode,u=0;u<s.length;u++){var p=s[u].x;if(c?!p:Math.abs(p)<e.dtick/100){if(s=s.slice(0,u).concat(s.slice(u+1)),!c)break;u--}}e._gw=h.crispRound(t,e.gridwidth,1);for(var d=a?h.crispRound(t,e.minor.gridwidth,1):0,m=r.layer,g=r.minorLayer,v=1;v>=0;v--){var y=v?m:g;if(y){var x=y.selectAll(\"path.\"+i).data(v?s:o,xt);x.exit().remove(),x.enter().append(\"path\").classed(i,1).classed(\"crisp\",!1!==r.crisp),x.attr(\"transform\",r.transFn).attr(\"d\",r.path).each((function(t){return f.stroke(n.select(this),t.minor?e.minor.gridcolor:e.gridcolor||\"#ddd\")})).style(\"stroke-dasharray\",(function(t){return h.dashStyle(t.minor?e.minor.griddash:e.griddash,t.minor?e.minor.gridwidth:e.gridwidth)})).style(\"stroke-width\",(function(t){return(t.minor?d:e._gw)+\"px\"})).style(\"display\",null),\"function\"==typeof r.path&&x.attr(\"d\",r.path)}}It(e,[z,D])},H.drawZeroLine=function(t,e,r){r=r||r;var n=e._id+\"zl\",i=H.shouldShowZeroLine(t,e,r.counterAxis),a=r.layer.selectAll(\"path.\"+n).data(i?[{x:0,id:e._id}]:[]);a.exit().remove(),a.enter().append(\"path\").classed(n,1).classed(\"zl\",1).classed(\"crisp\",!1!==r.crisp).each((function(){r.layer.selectAll(\"path\").sort((function(t,e){return Y(t.id,e.id)}))})),a.attr(\"transform\",r.transFn).attr(\"d\",r.path).call(f.stroke,e.zerolinecolor||f.defaultLine).style(\"stroke-width\",h.crispRound(t,e.zerolinewidth,e._gw||1)+\"px\").style(\"display\",null),It(e,[O])},H.drawLabels=function(t,e,r){r=r||{};var a=t._fullLayout,o=e._id,u=o.charAt(0),f=r.cls||o+\"tick\",p=r.vals.filter((function(t){return t.text})),d=r.labelFns,m=r.secondary?0:e.tickangle,g=(e._prevTickAngles||{})[f],v=r.layer.selectAll(\"g.\"+f).data(e.showticklabels?p:[],xt),y=[];function x(t,a){t.each((function(t){var o=n.select(this),s=o.select(\".text-math-group\"),u=d.anchorFn(t,a),f=r.transFn.call(o.node(),t)+(i(a)&&0!=+a?\" rotate(\"+a+\",\"+d.xFn(t)+\",\"+(d.yFn(t)-t.fontSize/2)+\")\":\"\"),p=c.lineCount(o),m=U*t.fontSize,g=d.heightFn(t,i(a)?+a:0,(p-1)*m);if(g&&(f+=l(0,g)),s.empty()){var v=o.select(\"text\");v.attr({transform:f,\"text-anchor\":u}),v.style(\"opacity\",1),e._adjustTickLabelsOverflow&&e._adjustTickLabelsOverflow()}else{var y=h.bBox(s.node()).width*{end:-.5,start:.5}[u];s.attr(\"transform\",f+l(y,0))}}))}v.enter().append(\"g\").classed(f,1).append(\"text\").attr(\"text-anchor\",\"middle\").each((function(e){var r=n.select(this),i=t._promises.length;r.call(c.positionText,d.xFn(e),d.yFn(e)).call(h.font,e.font,e.fontSize,e.fontColor).text(e.text).call(c.convertToTspans,t),t._promises[i]?y.push(t._promises.pop().then((function(){x(r,m)}))):x(r,m)})),It(e,[F]),v.exit().remove(),r.repositionOnUpdate&&v.each((function(t){n.select(this).select(\"text\").call(c.positionText,d.xFn(t),d.yFn(t))})),e._adjustTickLabelsOverflow=function(){var r=e.ticklabeloverflow;if(r&&\"allow\"!==r){var i=-1!==r.indexOf(\"hide\"),o=\"x\"===e._id.charAt(0),l=0,c=o?t._fullLayout.width:t._fullLayout.height;if(-1!==r.indexOf(\"domain\")){var u=s.simpleMap(e.range,e.r2l);l=e.l2p(u[0])+e._offset,c=e.l2p(u[1])+e._offset}var f=Math.min(l,c),p=Math.max(l,c),d=e.side,m=1/0,g=-1/0;for(var y in v.each((function(t){var 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o=\"tick\"===t.K&&\"text\"===t.L&&\"period\"===e.ticklabelmode,s=a._plots[e._mainSubplot];(t.K===O.K?s.zerolinelayer.selectAll(\".\"+e._id+\"zl\"):t.K===D.K?s.minorGridlayer.selectAll(\".\"+e._id):t.K===z.K?s.gridlayer.selectAll(\".\"+e._id):s[e._id.charAt(0)+\"axislayer\"]).each((function(){var a=n.select(this);t.L&&(a=a.selectAll(t.L)),a.each((function(a){var s=e.l2p(o?yt(a):a.x)+e._offset,l=n.select(this);s<e[\"_visibleLabelMax_\"+r._id]&&s>e[\"_visibleLabelMin_\"+r._id]?l.style(\"display\",\"none\"):\"tick\"!==t.K||i||l.style(\"display\",null)}))}))}))}))},x(v,g+1?g:m);var b=null;e._selections&&(e._selections[f]=v);var _=[function(){return y.length&&Promise.all(y)}];e.automargin&&a._redrawFromAutoMarginCount&&90===g?(b=90,_.push((function(){x(v,g)}))):_.push((function(){if(x(v,m),p.length&&\"x\"===u&&!i(m)&&(\"log\"!==e.type||\"D\"!==String(e.dtick).charAt(0))){b=0;var t,n=0,a=[];if(v.each((function(t){n=Math.max(n,t.fontSize);var 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n=t(\"fast-isnumeric\"),i=t(\"../../registry\"),a=t(\"../../lib\"),o=t(\"../../plot_api/plot_template\"),s=t(\"../array_container_defaults\"),l=t(\"./layout_attributes\"),c=t(\"./tick_value_defaults\"),u=t(\"./tick_mark_defaults\"),f=t(\"./tick_label_defaults\"),h=t(\"./prefix_suffix_defaults\"),p=t(\"./category_order_defaults\"),d=t(\"./line_grid_defaults\"),m=t(\"./set_convert\"),g=t(\"./constants\").WEEKDAY_PATTERN,v=t(\"./constants\").HOUR_PATTERN;function y(t,e,r){function i(r,n){return a.coerce(t,e,l.rangebreaks,r,n)}if(i(\"enabled\")){var o=i(\"bounds\");if(o&&o.length>=2){var s,c,u=\"\";if(2===o.length)for(s=0;s<2;s++)if(c=b(o[s])){u=g;break}var f=i(\"pattern\",u);if(f===g)for(s=0;s<2;s++)(c=b(o[s]))&&(e.bounds[s]=o[s]=c-1);if(f)for(s=0;s<2;s++)switch(c=o[s],f){case g:if(!n(c))return void(e.enabled=!1);if((c=+c)!==Math.floor(c)||c<0||c>=7)return void(e.enabled=!1);e.bounds[s]=o[s]=c;break;case v:if(!n(c))return void(e.enabled=!1);if((c=+c)<0||c>24)return 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a=Pt.dragmode,s=t._fullLayout.dragmode;s!==a&&(Pt.dragmode=s),yt(),pt=t._fullLayout._invScaleX,dt=t._fullLayout._invScaleY,ot||(gt?e.shiftKey?\"pan\"===s?s=\"zoom\":y(s)||(s=\"pan\"):e.ctrlKey&&(s=\"pan\"):s=\"pan\"),x(s)?Pt.minDrag=1:Pt.minDrag=void 0,y(s)?(Pt.xaxes=J,Pt.yaxes=K,A(e,r,n,Pt,s)):(Pt.clickFn=Ot,y(a)&&It(),ot||(\"zoom\"===s?(Pt.moveFn=zt,Pt.doneFn=Rt,Pt.minDrag=1,function(e,r,n){var a=bt.getBoundingClientRect();_t=r-a.left,wt=n-a.top,t._fullLayout._calcInverseTransform(t);var s=i.apply3DTransform(t._fullLayout._invTransform)(_t,wt);_t=s[0],wt=s[1],Tt={l:_t,r:_t,w:0,t:wt,b:wt,h:0},kt=t._hmpixcount?t._hmlumcount/t._hmpixcount:o(t._fullLayout.plot_bgcolor).getLuminance(),Mt=!1,St=\"xy\",Ct=!1,Et=N(mt,kt,Q,$,At=\"M0,0H\"+tt+\"V\"+et+\"H0V0\"),Lt=j(mt,Q,$)}(0,r,n)):\"pan\"===s&&(Pt.moveFn=Ut,Pt.doneFn=Gt))),t._fullLayout._redrag=function(){var e=t._dragdata;if(e&&e.element===bt){var r=t._fullLayout.dragmode;y(r)||(yt(),Yt([0,0,tt,et]),Pt.moveFn(e.dx,e.dy))}}},g.init(Pt);var 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r,n,a,o,s=t._fullLayout,c=s._plots,u=s._subplots.cartesian;if(ut&&l.subplotsRegistry.splom.drag(t),ct)for(r=0;r<u.length;r++)if(a=(n=c[u[r]]).xaxis,o=n.yaxis,n._scene){var f=i.simpleMap(a.range,a.r2l),p=i.simpleMap(o.range,o.r2l);n._scene.update({range:[f[0],p[0],f[1],p[1]]})}if((ut||ct)&&(_(t),w(t)),ft){var d=e[2]/I._length,g=e[3]/O._length;for(r=0;r<u.length;r++){a=(n=c[u[r]]).xaxis,o=n.yaxis;var y,x,b,T,k=(st||nt.isSubplotConstrained)&&!a.fixedrange&&V[a._id],A=(lt||nt.isSubplotConstrained)&&!o.fixedrange&&Z[o._id];if(k?(y=d,b=v||nt.isSubplotConstrained?e[0]:Zt(a,y)):nt.xaHash[a._id]?(y=d,b=e[0]*a._length/I._length):nt.yaHash[a._id]?(y=g,b=\"ns\"===at?-e[1]*a._length/O._length:Zt(a,y,{n:\"top\",s:\"bottom\"}[at])):b=Xt(a,y=Wt(a,d,g)),A?(x=g,T=m||nt.isSubplotConstrained?e[1]:Zt(o,x)):nt.yaHash[o._id]?(x=g,T=e[1]*o._length/O._length):nt.xaHash[o._id]?(x=d,T=\"ew\"===it?-e[0]*o._length/I._length:Zt(o,x,{e:\"right\",w:\"left\"}[it])):T=Xt(o,x=Wt(o,d,g)),y||x){y||(y=1),x||(x=1);var M=a._offset-b/y,S=o._offset-T/x;n.clipRect.call(h.setTranslate,b,T).call(h.setScale,y,x),n.plot.call(h.setTranslate,M,S).call(h.setScale,1/y,1/x),y===n.xScaleFactor&&x===n.yScaleFactor||(h.setPointGroupScale(n.zoomScalePts,y,x),h.setTextPointsScale(n.zoomScaleTxt,y,x)),h.hideOutsideRangePoints(n.clipOnAxisFalseTraces,n),n.xScaleFactor=y,n.yScaleFactor=x}}}}function Wt(t,e,r){return t.fixedrange?0:st&&rt.xaHash[t._id]?e:lt&&(rt.isSubplotConstrained?rt.xaHash:rt.yaHash)[t._id]?r:0}function Xt(t,e){return e?(t.range=t._r.slice(),E(t,e),Zt(t,e)):0}function Zt(t,e,r){return t._length*(1-e)*b[r||t.constraintoward||\"middle\"]}return m.length*v.length!=1&&W(bt,(function(e){if(t._context._scrollZoom.cartesian||t._fullLayout._enablescrollzoom){if(It(),t._transitioningWithDuration)return e.preventDefault(),void e.stopPropagation();yt(),clearTimeout(Bt);var r=-e.deltaY;if(isFinite(r)||(r=e.wheelDelta/10),isFinite(r)){var n,a=Math.exp(-Math.min(Math.max(r,-20),20)/200),o=jt.draglayer.select(\".nsewdrag\").node().getBoundingClientRect(),s=(e.clientX-o.left)/o.width,l=(o.bottom-e.clientY)/o.height;if(st){for(v||(s=.5),n=0;n<J.length;n++)c(J[n],s,a);Vt(\"x\"),Ft[2]*=a,Ft[0]+=Ft[2]*s*(1/a-1)}if(lt){for(m||(l=.5),n=0;n<K.length;n++)c(K[n],l,a);Vt(\"y\"),Ft[3]*=a,Ft[1]+=Ft[3]*(1-l)*(1/a-1)}Yt(Ft),Ht(),t.emit(\"plotly_relayouting\",ht),Bt=setTimeout((function(){t._fullLayout&&(Ft=[0,0,tt,et],Gt())}),Nt),e.preventDefault()}else i.log(\"Did not find wheel motion attributes: \",e)}function c(t,e,r){if(!t.fixedrange){var n=i.simpleMap(t.range,t.r2l),a=n[0]+(n[1]-n[0])*e;t.range=n.map((function(e){return t.l2r(a+(e-a)*r)}))}}})),bt},makeDragger:O,makeRectDragger:z,makeZoombox:N,makeCorners:j,updateZoombox:U,xyCorners:G,transitionZoombox:V,removeZoombox:H,showDoubleClickNotifier:q,attachWheelEventHandler:W}},{\"../../components/color\":366,\"../../components/dragelement\":385,\"../../components/dragelement/helpers\":384,\"../../components/drawing\":388,\"../../components/fx\":406,\"../../constants/alignment\":471,\"../../lib\":503,\"../../lib/clear_gl_canvases\":487,\"../../lib/setcursor\":524,\"../../lib/svg_text_utils\":529,\"../../plot_api/subroutines\":544,\"../../registry\":638,\"../plots\":619,\"./axes\":554,\"./axis_ids\":558,\"./constants\":561,\"./scale_zoom\":574,\"./select\":575,\"@plotly/d3\":58,\"has-passive-events\":229,tinycolor2:312}],564:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../components/fx\"),a=t(\"../../components/dragelement\"),o=t(\"../../lib/setcursor\"),s=t(\"./dragbox\").makeDragBox,l=t(\"./constants\").DRAGGERSIZE;r.initInteractions=function(t){var e=t._fullLayout;if(t._context.staticPlot)n.select(t).selectAll(\".drag\").remove();else if(e._has(\"cartesian\")||e._has(\"splom\")){Object.keys(e._plots||{}).sort((function(t,r){if((e._plots[t].mainplot&&!0)===(e._plots[r].mainplot&&!0)){var n=t.split(\"y\"),i=r.split(\"y\");return n[0]===i[0]?Number(n[1]||1)-Number(i[1]||1):Number(n[0]||1)-Number(i[0]||1)}return e._plots[t].mainplot?1:-1})).forEach((function(r){var n=e._plots[r],o=n.xaxis,c=n.yaxis;if(!n.mainplot){var u=s(t,n,o._offset,c._offset,o._length,c._length,\"ns\",\"ew\");u.onmousemove=function(e){t._fullLayout._rehover=function(){t._fullLayout._hoversubplot===r&&t._fullLayout._plots[r]&&i.hover(t,e,r)},i.hover(t,e,r),t._fullLayout._lasthover=u,t._fullLayout._hoversubplot=r},u.onmouseout=function(e){t._dragging||(t._fullLayout._hoversubplot=null,a.unhover(t,e))},t._context.showAxisDragHandles&&(s(t,n,o._offset-l,c._offset-l,l,l,\"n\",\"w\"),s(t,n,o._offset+o._length,c._offset-l,l,l,\"n\",\"e\"),s(t,n,o._offset-l,c._offset+c._length,l,l,\"s\",\"w\"),s(t,n,o._offset+o._length,c._offset+c._length,l,l,\"s\",\"e\"))}if(t._context.showAxisDragHandles){if(r===o._mainSubplot){var f=o._mainLinePosition;\"top\"===o.side&&(f-=l),s(t,n,o._offset+.1*o._length,f,.8*o._length,l,\"\",\"ew\"),s(t,n,o._offset,f,.1*o._length,l,\"\",\"w\"),s(t,n,o._offset+.9*o._length,f,.1*o._length,l,\"\",\"e\")}if(r===c._mainSubplot){var h=c._mainLinePosition;\"right\"!==c.side&&(h-=l),s(t,n,h,c._offset+.1*c._length,l,.8*c._length,\"ns\",\"\"),s(t,n,h,c._offset+.9*c._length,l,.1*c._length,\"s\",\"\"),s(t,n,h,c._offset,l,.1*c._length,\"n\",\"\")}}}));var o=e._hoverlayer.node();o.onmousemove=function(r){r.target=t._fullLayout._lasthover,i.hover(t,r,e._hoversubplot)},o.onclick=function(e){e.target=t._fullLayout._lasthover,i.click(t,e)},o.onmousedown=function(e){t._fullLayout._lasthover.onmousedown(e)},r.updateFx(t)}},r.updateFx=function(t){var e=t._fullLayout,r=\"pan\"===e.dragmode?\"move\":\"crosshair\";o(e._draggers,r)}},{\"../../components/dragelement\":385,\"../../components/fx\":406,\"../../lib/setcursor\":524,\"./constants\":561,\"./dragbox\":563,\"@plotly/d3\":58}],565:[function(t,e,r){\"use strict\";e.exports={clearOutlineControllers:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".outline-controllers\").remove()},clearSelect:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".select-outline\").remove(),t._fullLayout._drawing=!1}}},{}],566:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").strTranslate;function i(t,e){switch(t.type){case\"log\":return t.p2d(e);case\"date\":return t.p2r(e,0,t.calendar);default:return t.p2r(e)}}e.exports={p2r:i,r2p:function(t,e){switch(t.type){case\"log\":return t.d2p(e);case\"date\":return t.r2p(e,0,t.calendar);default:return t.r2p(e)}},axValue:function(t){var e=\"y\"===t._id.charAt(0)?1:0;return function(r){return i(t,r[e])}},getTransform:function(t){return n(t.xaxis._offset,t.yaxis._offset)}}},{\"../../lib\":503}],567:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"./axis_ids\");e.exports=function(t){return function(e,r){var o=e[t];if(Array.isArray(o))for(var s=n.subplotsRegistry.cartesian,l=s.idRegex,c=r._subplots,u=c.xaxis,f=c.yaxis,h=c.cartesian,p=r._has(\"cartesian\")||r._has(\"gl2d\"),d=0;d<o.length;d++){var m=o[d];if(i.isPlainObject(m)){var g=a.cleanId(m.xref,\"x\",!1),v=a.cleanId(m.yref,\"y\",!1),y=l.x.test(g),x=l.y.test(v);if(y||x){p||i.pushUnique(r._basePlotModules,s);var b=!1;y&&-1===u.indexOf(g)&&(u.push(g),b=!0),x&&-1===f.indexOf(v)&&(f.push(v),b=!0),b&&y&&x&&h.push(g+v)}}}}}},{\"../../lib\":503,\"../../registry\":638,\"./axis_ids\":558}],568:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../registry\"),a=t(\"../../lib\"),o=t(\"../plots\"),s=t(\"../../components/drawing\"),l=t(\"../get_data\").getModuleCalcData,c=t(\"./axis_ids\"),u=t(\"./constants\"),f=t(\"../../constants/xmlns_namespaces\"),h=a.ensureSingle;function p(t,e,r){return a.ensureSingle(t,e,r,(function(t){t.datum(r)}))}function d(t,e,r,a,o){for(var c,f,h,p=u.traceLayerClasses,d=t._fullLayout,m=d._modules,g=[],v=[],y=0;y<m.length;y++){var x=(c=m[y]).name,b=i.modules[x].categories;if(b.svg){var _=c.layerName||x+\"layer\",w=c.plot;h=(f=l(r,w))[0],r=f[1],h.length&&g.push({i:p.indexOf(_),className:_,plotMethod:w,cdModule:h}),b.zoomScale&&v.push(\".\"+_)}}g.sort((function(t,e){return t.i-e.i}));var T=e.plot.selectAll(\"g.mlayer\").data(g,(function(t){return t.className}));if(T.enter().append(\"g\").attr(\"class\",(function(t){return t.className})).classed(\"mlayer\",!0).classed(\"rangeplot\",e.isRangePlot),T.exit().remove(),T.order(),T.each((function(r){var i=n.select(this),l=r.className;r.plotMethod(t,e,r.cdModule,i,a,o),-1===u.clipOnAxisFalseQuery.indexOf(\".\"+l)&&s.setClipUrl(i,e.layerClipId,t)})),d._has(\"scattergl\")&&(c=i.getModule(\"scattergl\"),h=l(r,c)[0],c.plot(t,e,h)),!t._context.staticPlot&&(e._hasClipOnAxisFalse&&(e.clipOnAxisFalseTraces=e.plot.selectAll(u.clipOnAxisFalseQuery.join(\",\")).selectAll(\".trace\")),v.length)){var k=e.plot.selectAll(v.join(\",\")).selectAll(\".trace\");e.zoomScalePts=k.selectAll(\"path.point\"),e.zoomScaleTxt=k.selectAll(\".textpoint\")}}function m(t,e){var r=e.plotgroup,n=e.id,i=u.layerValue2layerClass[e.xaxis.layer],a=u.layerValue2layerClass[e.yaxis.layer],o=t._fullLayout._hasOnlyLargeSploms;if(e.mainplot){var s=e.mainplotinfo,l=s.plotgroup,f=n+\"-x\",d=n+\"-y\";e.minorGridlayer=s.minorGridlayer,e.gridlayer=s.gridlayer,e.zerolinelayer=s.zerolinelayer,h(s.overlinesBelow,\"path\",f),h(s.overlinesBelow,\"path\",d),h(s.overaxesBelow,\"g\",f),h(s.overaxesBelow,\"g\",d),e.plot=h(s.overplot,\"g\",n),h(s.overlinesAbove,\"path\",f),h(s.overlinesAbove,\"path\",d),h(s.overaxesAbove,\"g\",f),h(s.overaxesAbove,\"g\",d),e.xlines=l.select(\".overlines-\"+i).select(\".\"+f),e.ylines=l.select(\".overlines-\"+a).select(\".\"+d),e.xaxislayer=l.select(\".overaxes-\"+i).select(\".\"+f),e.yaxislayer=l.select(\".overaxes-\"+a).select(\".\"+d)}else 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yt=b(\"rangeslider\",\"handleDefaults\"),xt=b(\"rangeselector\",\"handleDefaults\");for(y=0;y<j.length;y++)q=j[y],W=t[q],X=e[q],yt(t,e,q),\"date\"===X.type&&xt(W,X,e,U,X.calendar),K(\"fixedrange\");for(y=0;y<U.length;y++){q=U[y],W=t[q],X=e[q];var bt=e[m(X.anchor)];K(\"fixedrange\",b(\"rangeslider\",\"isVisible\")(bt))}h.handleDefaults(t,e,{axIds:rt.concat(it).sort(d.idSort),axHasImage:P})}},{\"../../components/color\":366,\"../../components/fx/helpers\":402,\"../../components/fx/hovermode_defaults\":405,\"../../lib\":503,\"../../plot_api/plot_template\":543,\"../../registry\":638,\"../layout_attributes\":610,\"./axis_defaults\":556,\"./axis_ids\":558,\"./constants\":561,\"./constraints\":562,\"./layout_attributes\":569,\"./position_defaults\":572,\"./type_defaults\":582}],571:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../components/color/attributes\"),a=t(\"../../lib\");e.exports=function(t,e,r,o){var s=(o=o||{}).dfltColor;function l(r,n){return a.coerce2(t,e,o.attributes,r,n)}var c=l(\"linecolor\",s),u=l(\"linewidth\");r(\"showline\",o.showLine||!!c||!!u)||(delete e.linecolor,delete e.linewidth);var f=l(\"gridcolor\",n(s,o.bgColor,o.blend||i.lightFraction).toRgbString()),h=l(\"gridwidth\"),p=l(\"griddash\");if(r(\"showgrid\",o.showGrid||!!f||!!h||!!p)||(delete e.gridcolor,delete e.gridwidth,delete e.griddash),o.hasMinor){var d=l(\"minor.gridcolor\",n(e.gridcolor,o.bgColor,67).toRgbString()),m=l(\"minor.gridwidth\",e.gridwidth||1),g=l(\"minor.griddash\",e.griddash||\"solid\");r(\"minor.showgrid\",!!d||!!m||!!g)||(delete e.minor.gridcolor,delete e.minor.gridwidth,delete e.minor.griddash)}if(!o.noZeroLine){var v=l(\"zerolinecolor\",s),y=l(\"zerolinewidth\");r(\"zeroline\",o.showGrid||!!v||!!y)||(delete e.zerolinecolor,delete e.zerolinewidth)}}},{\"../../components/color/attributes\":365,\"../../lib\":503,tinycolor2:312}],572:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\");e.exports=function(t,e,r,a){var o,s,l,c,u=a.counterAxes||[],f=a.overlayableAxes||[],h=a.letter,p=a.grid;p&&(s=p._domains[h][p._axisMap[e._id]],o=p._anchors[e._id],s&&(l=p[h+\"side\"].split(\" \")[0],c=p.domain[h][\"right\"===l||\"top\"===l?1:0])),s=s||[0,1],o=o||(n(t.position)?\"free\":u[0]||\"free\"),l=l||(\"x\"===h?\"bottom\":\"left\"),c=c||0,\"free\"===i.coerce(t,e,{anchor:{valType:\"enumerated\",values:[\"free\"].concat(u),dflt:o}},\"anchor\")&&r(\"position\",c),i.coerce(t,e,{side:{valType:\"enumerated\",values:\"x\"===h?[\"bottom\",\"top\"]:[\"left\",\"right\"],dflt:l}},\"side\");var d=!1;if(f.length&&(d=i.coerce(t,e,{overlaying:{valType:\"enumerated\",values:[!1].concat(f),dflt:!1}},\"overlaying\")),!d){var m=r(\"domain\",s);m[0]>m[1]-1/4096&&(e.domain=s),i.noneOrAll(t.domain,e.domain,s)}return r(\"layer\"),e}},{\"../../lib\":503,\"fast-isnumeric\":190}],573:[function(t,e,r){\"use strict\";var n=t(\"./show_dflt\");e.exports=function(t,e,r,i,a){a||(a={});var o=a.tickSuffixDflt,s=n(t);r(\"tickprefix\")&&r(\"showtickprefix\",s),r(\"ticksuffix\",o)&&r(\"showticksuffix\",s)}},{\"./show_dflt\":577}],574:[function(t,e,r){\"use strict\";var n=t(\"../../constants/alignment\").FROM_BL;e.exports=function(t,e,r){void 0===r&&(r=n[t.constraintoward||\"center\"]);var i=[t.r2l(t.range[0]),t.r2l(t.range[1])],a=i[0]+(i[1]-i[0])*r;t.range=t._input.range=[t.l2r(a+(i[0]-a)*e),t.l2r(a+(i[1]-a)*e)],t.setScale()}},{\"../../constants/alignment\":471}],575:[function(t,e,r){\"use strict\";var n=t(\"polybooljs\"),i=t(\"../../registry\"),a=t(\"../../components/drawing\").dashStyle,o=t(\"../../components/color\"),s=t(\"../../components/fx\"),l=t(\"../../components/fx/helpers\").makeEventData,c=t(\"../../components/dragelement/helpers\"),u=c.freeMode,f=c.rectMode,h=c.drawMode,p=c.openMode,d=c.selectMode,m=t(\"../../components/shapes/draw_newshape/display_outlines\"),g=t(\"../../components/shapes/draw_newshape/helpers\").handleEllipse,v=t(\"../../components/shapes/draw_newshape/newshapes\"),y=t(\"../../lib\"),x=t(\"../../lib/polygon\"),b=t(\"../../lib/throttle\"),_=t(\"./axis_ids\").getFromId,w=t(\"../../lib/clear_gl_canvases\"),T=t(\"../../plot_api/subroutines\").redrawReglTraces,k=t(\"./constants\"),A=k.MINSELECT,M=x.filter,S=x.tester,E=t(\"./handle_outline\").clearSelect,L=t(\"./helpers\"),C=L.p2r,P=L.axValue,I=L.getTransform;function O(t,e,r,n,i,a,o){var s,l,c,u,f,h,d,g,v,y=e._hoverdata,x=e._fullLayout.clickmode.indexOf(\"event\")>-1,b=[];if(function(t){return 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e=[],r=z(t[0])?0:t[0][0][0],n=r,i=z(t[0])?0:t[0][0][1],a=i,o=0;o<t.length;o++)if(z(t[o]))e.push(D(t[o]));else{var s=x.tester(t[o]);s.subtract=t[o].subtract,e.push(s),r=Math.min(r,s.xmin),n=Math.max(n,s.xmax),i=Math.min(i,s.ymin),a=Math.max(a,s.ymax)}return{xmin:r,xmax:n,ymin:i,ymax:a,pts:[],contains:function(t,r,n,i){for(var a=!1,o=0;o<e.length;o++)e[o].contains(t,r,n,i)&&(a=!1===e[o].subtract);return a},isRect:!1,degenerate:!1}}function F(t,e,r){e._fullLayout._drawing=!1;var n=e._fullLayout,i=r.plotinfo,a=r.dragmode,o=n._lastSelectedSubplot&&n._lastSelectedSubplot===i.id,s=(t.shiftKey||t.altKey)&&!(h(a)&&p(a));o&&s&&i.selection&&i.selection.selectionDefs&&!r.selectionDefs?(r.selectionDefs=i.selection.selectionDefs,r.mergedPolygons=i.selection.mergedPolygons):s&&i.selection||B(r),o||(E(e),n._lastSelectedSubplot=i.id)}function B(t){var e=t.dragmode,r=t.plotinfo,n=t.gd;if(n._fullLayout._activeShapeIndex>=0&&n._fullLayout._deactivateShape(n),h(e)){var 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r=this.bounds,n=(e.framewidth||0)/2,i=r[0][0]-n,a=r[0][1]-n,o=r[1][0]-i+n,s=r[1][1]-a+n;h.setRect(this.clipRect,i,a,o,s),this.bgRect.call(h.setRect,i,a,o,s).call(f.fill,e.bgcolor),this.xaxis._offset=i,this.xaxis._length=o,this.yaxis._offset=a,this.yaxis._length=s},S.updateFx=function(t,e){var r=this,i=r.graphDiv,a=r.bgRect,o=t.dragmode,s=t.clickmode;if(!r.isStatic){var u;\"select\"===o?u=function(t,e){(t.range={})[r.id]=[h([e.xmin,e.ymin]),h([e.xmax,e.ymax])]}:\"lasso\"===o&&(u=function(t,e,n){(t.lassoPoints={})[r.id]=n.filtered.map(h)});var f={element:r.bgRect.node(),gd:i,plotinfo:{id:r.id,xaxis:r.xaxis,yaxis:r.yaxis,fillRangeItems:u},xaxes:[r.xaxis],yaxes:[r.yaxis],subplot:r.id,clickFn:function(t){2===t&&x(i)}};\"pan\"===o?(a.node().onmousedown=null,a.call(_(r,e)),a.on(\"dblclick.zoom\",(function(){var t=r.viewInitial,e={};for(var n in 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t=this,e=t.graphDiv,r=e._fullLayout,i=\"clip\"+r._uid+t.id;t.clipDef=r._clips.append(\"clipPath\").attr(\"id\",i),t.clipRect=t.clipDef.append(\"rect\"),t.framework=n.select(t.container).append(\"g\").attr(\"class\",\"geo \"+t.id).call(h.setClipUrl,i,e),t.project=function(e){var r=t.projection(e);return r?[r[0]-t.xaxis._offset,r[1]-t.yaxis._offset]:[null,null]},t.xaxis={_id:\"x\",c2p:function(e){return t.project(e)[0]}},t.yaxis={_id:\"y\",c2p:function(e){return t.project(e)[1]}},t.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},m.setConvert(t.mockAxis,r)},S.saveViewInitial=function(t){var 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e=t._fullLayout,r=t.calcdata,i=e._subplots.geo,s=0;s<i.length;s++){var l=i[s],c=n(r,o,l),u=e[l]._subplot;u||(u=a({id:l,graphDiv:t,container:e._geolayer.node(),topojsonURL:t._context.topojsonURL,staticPlot:t._context.staticPlot}),e[l]._subplot=u),u.plot(c,e,t._promises)}},updateFx:function(t){for(var e=t._fullLayout,r=e._subplots.geo,n=0;n<r.length;n++){var i=e[r[n]];i._subplot.updateFx(e,i)}},clean:function(t,e,r,n){for(var i=n._subplots.geo||[],a=0;a<i.length;a++){var o=i[a],s=n[o]._subplot;!e[o]&&s&&(s.framework.remove(),s.clipDef.remove())}}}},{\"../../lib\":503,\"../../plots/get_data\":593,\"./geo\":588,\"./layout_attributes\":590,\"./layout_defaults\":591}],590:[function(t,e,r){\"use strict\";var n=t(\"../../components/color/attributes\"),i=t(\"../domain\").attributes,a=t(\"../../components/drawing/attributes\").dash,o=t(\"./constants\"),s=t(\"../../plot_api/edit_types\").overrideAll,l=t(\"../../lib/sort_object_keys\"),c={range:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},showgrid:{valType:\"boolean\",dflt:!1},tick0:{valType:\"number\",dflt:0},dtick:{valType:\"number\"},gridcolor:{valType:\"color\",dflt:n.lightLine},gridwidth:{valType:\"number\",min:0,dflt:1},griddash:a};(e.exports=s({domain:i({name:\"geo\"},{}),fitbounds:{valType:\"enumerated\",values:[!1,\"locations\",\"geojson\"],dflt:!1,editType:\"plot\"},resolution:{valType:\"enumerated\",values:[110,50],dflt:110,coerceNumber:!0},scope:{valType:\"enumerated\",values:l(o.scopeDefaults),dflt:\"world\"},projection:{type:{valType:\"enumerated\",values:l(o.projNames)},rotation:{lon:{valType:\"number\"},lat:{valType:\"number\"},roll:{valType:\"number\"}},tilt:{valType:\"number\",dflt:0},distance:{valType:\"number\",min:1.001,dflt:2},parallels:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},scale:{valType:\"number\",min:0,dflt:1}},center:{lon:{valType:\"number\"},lat:{valType:\"number\"}},visible:{valType:\"boolean\",dflt:!0},showcoastlines:{valType:\"boolean\"},coastlinecolor:{valType:\"color\",dflt:n.defaultLine},coastlinewidth:{valType:\"number\",min:0,dflt:1},showland:{valType:\"boolean\",dflt:!1},landcolor:{valType:\"color\",dflt:o.landColor},showocean:{valType:\"boolean\",dflt:!1},oceancolor:{valType:\"color\",dflt:o.waterColor},showlakes:{valType:\"boolean\",dflt:!1},lakecolor:{valType:\"color\",dflt:o.waterColor},showrivers:{valType:\"boolean\",dflt:!1},rivercolor:{valType:\"color\",dflt:o.waterColor},riverwidth:{valType:\"number\",min:0,dflt:1},showcountries:{valType:\"boolean\"},countrycolor:{valType:\"color\",dflt:n.defaultLine},countrywidth:{valType:\"number\",min:0,dflt:1},showsubunits:{valType:\"boolean\"},subunitcolor:{valType:\"color\",dflt:n.defaultLine},subunitwidth:{valType:\"number\",min:0,dflt:1},showframe:{valType:\"boolean\"},framecolor:{valType:\"color\",dflt:n.defaultLine},framewidth:{valType:\"number\",min:0,dflt:1},bgcolor:{valType:\"color\",dflt:n.background},lonaxis:c,lataxis:c},\"plot\",\"from-root\")).uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color/attributes\":365,\"../../components/drawing/attributes\":387,\"../../lib/sort_object_keys\":526,\"../../plot_api/edit_types\":536,\"../domain\":584,\"./constants\":587}],591:[function(t,e,r){\"use 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d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,a=r.mirror||!1,u=c?-1!==String(a).indexOf(\"all\"):!!a,f=c?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[h]=r.showline),(l||u)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var 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n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./scene2d\"),a=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];if(s._scene2d){var c=u(t,\"gl2d\",o);0===c.length&&(s._scene2d.destroy(),delete n._plots[o])}}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":407,\"../../constants/xmlns_namespaces\":480,\"../../plot_api/edit_types\":536,\"../cartesian\":568,\"../cartesian/attributes\":552,\"../cartesian/constants\":561,\"../get_data\":593,\"../layout_attributes\":610,\"./scene2d\":597}],597:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"../../../stackgl_modules\").gl_plot2d,c=t(\"../../../stackgl_modules\").gl_spikes2d,u=t(\"../../../stackgl_modules\").gl_select_box,f=t(\"webgl-context\"),h=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),m=t(\"../cartesian/constraints\"),g=m.enforce,v=m.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=t(\"../../components/dragelement/helpers\"),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=a[4*(r*o+l)+c];a[4*(r*o+l)+c]=a[4*(r*s+l)+c],a[4*(r*s+l)+c]=u}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\",{willReadFrequently:!0}),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};v(s,this.xaxis),v(s,this.yaxis);var l,c,u=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[u.l+f[0]*u.w,u.b+h[0]*u.h,i-u.r-(1-f[1])*u.w,a-u.t-(1-h[1])*u.h],this.mouseContainer.style.width=u.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=u.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=u.h*(h[1]-h[0]),this.mouseContainer.style.left=u.l+f[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-h[1])*u.h+\"px\",c=0;c<2;++c)(l=this[w[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();g(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},A.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],c=this.traces[i.uid];c?c.update(i,l):(c=i._module.plot(this,i,l),this.traces[i.uid]=c)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var m=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),m.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var g=this.fullData[m.trace.index]||{},v=m.pointIndex,y=s.castHoverinfo(g,i,v);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(m.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(m.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(m.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(m.textLabel=void 0),-1===x.indexOf(\"name\")&&(m.name=void 0)}s.loneHover({x:m.screenCoord[0],y:m.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",m.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",m.traceCoord[1]),zLabel:m.traceCoord[2],text:m.textLabel,name:m.name,color:s.castHoverOption(g,v,\"bgcolor\")||m.color,borderColor:s.castHoverOption(g,v,\"bordercolor\"),fontFamily:s.castHoverOption(g,v,\"font.family\"),fontSize:s.castHoverOption(g,v,\"font.size\"),fontColor:s.castHoverOption(g,v,\"font.color\"),nameLength:s.castHoverOption(g,v,\"namelength\"),textAlign:s.castHoverOption(g,v,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../../stackgl_modules\":1124,\"../../components/dragelement/helpers\":384,\"../../components/fx\":406,\"../../lib/show_no_webgl_msg\":525,\"../../plots/cartesian/axes\":554,\"../../registry\":638,\"../cartesian/autorange\":553,\"../cartesian/constants\":561,\"../cartesian/constraints\":562,\"./camera\":594,\"./convert\":595,\"webgl-context\":331}],598:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../components/fx/layout_attributes\"),a=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,i=0;i<n.length;i++){var s=n[i],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,f=c._scene;f||(f=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=f),f.viewInitial||(f.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),f.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl3d||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":407,\"../../constants/xmlns_namespaces\":480,\"../../lib\":503,\"../../plot_api/edit_types\":536,\"../get_data\":593,\"./layout/attributes\":599,\"./layout/defaults\":603,\"./layout/layout_attributes\":604,\"./scene\":608}],599:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],600:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":366,\"../../../lib/extend\":493,\"../../../plot_api/edit_types\":536,\"../../cartesian/layout_attributes\":569}],601:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,f;function h(t,e){return i.coerce(u,f,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(u,f,h,r),l(u,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelstep:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,13600/187).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},{\"../../../lib\":503,\"../../../plot_api/plot_template\":543,\"../../cartesian/axis_defaults\":556,\"../../cartesian/type_defaults\":582,\"./axis_attributes\":600,tinycolor2:312}],602:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[a[r]];o.visible?(this.labels[r]=t._meta?i.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":503,\"../../../lib/str2rgbarray\":528}],603:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"../../../components/color\"),a=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData;function u(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),u=[\"up\",\"center\",\"eye\"],f=0;f<u.length;f++)r(\"camera.\"+u[f]+\".x\"),r(\"camera.\"+u[f]+\".y\"),r(\"camera.\"+u[f]+\".z\");r(\"camera.projection.type\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),p=r(\"aspectmode\",h?\"manual\":\"auto\");h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===p&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var d=c(n.fullData,\"gl3d\",n.id);s(t,e,{font:n.font,scene:n.id,data:d,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var m=n.getDfltFromLayout(\"dragmode\");if(!1!==m&&!m)if(m=\"orbit\",t.camera&&t.camera.up){var g=t.camera.up.x,v=t.camera.up.y,y=t.camera.up.z;0!==y&&(g&&v&&y?y/Math.sqrt(g*g+v*v+y*y)>.999&&(m=\"turntable\"):m=\"turntable\")}else m=\"turntable\";r(\"dragmode\",m),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:\"gl3d\",attributes:l,handleDefaults:u,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":366,\"../../../lib\":503,\"../../../registry\":638,\"../../get_data\":593,\"../../subplot_defaults\":632,\"./axis_defaults\":601,\"./layout_attributes\":604}],604:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),i=t(\"../../domain\").attributes,a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":503,\"../../../lib/extend\":493,\"../../domain\":584,\"./axis_attributes\":600}],605:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new a;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":528}],606:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[a[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var f=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var h=u.nticks||i.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/h)}for(var p=n.calcTicks(u,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=f}}e.ticks=l;for(c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=t(\"../../cartesian/axes\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":503,\"../../cartesian/axes\":554}],607:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],608:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../../stackgl_modules\").gl_plot3d,o=a.createCamera,s=a.createScene,l=t(\"webgl-context\"),c=t(\"has-passive-events\"),u=t(\"../../registry\"),f=t(\"../../lib\"),h=f.preserveDrawingBuffer(),p=t(\"../../plots/cartesian/axes\"),d=t(\"../../components/fx\"),m=t(\"../../lib/str2rgbarray\"),g=t(\"../../lib/show_no_webgl_msg\"),v=t(\"./project\"),y=t(\"./layout/convert\"),x=t(\"./layout/spikes\"),b=t(\"./layout/tick_marks\");function _(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=y(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=u.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var w=_.prototype;w.prepareOptions=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");t.gl=i,t.canvas=n}return t};var T=!0;w.tryCreatePlot=function(){var t=this.prepareOptions(),e=!0;try{this.glplot=s(t)}catch(r){if(this.staticMode||!T||h)e=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=t.glOptions.preserveDrawingBuffer=!0,this.glplot=s(t)}catch(r){h=t.glOptions.preserveDrawingBuffer=!1,e=!1}}}return T=!1,e},w.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},w.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!c&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},w.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var c=Object.keys(e.traces),u=null,h=e.glplot.selection,m=0;m<c.length;++m)\"skip\"!==(t=e.traces[c[m]]).data.hoverinfo&&t.handlePick(h)&&(u=t),t.setContourLevels&&t.setContourLevels();function g(t,r,n){var i=e.fullSceneLayout[t+\"axis\"];return\"log\"!==i.type&&(r=i.d2l(r)),p.hoverLabelText(i,r,n)}if(null!==u){var y=v(e.glplot.cameraParams,h.dataCoordinate);t=u.data;var x,_=r._fullData[t.index],w=h.index,T={xLabel:g(\"x\",h.traceCoordinate[0],t.xhoverformat),yLabel:g(\"y\",h.traceCoordinate[1],t.yhoverformat),zLabel:g(\"z\",h.traceCoordinate[2],t.zhoverformat)},k=d.castHoverinfo(_,e.fullLayout,w),A=(k||\"\").split(\"+\"),M=k&&\"all\"===k;_.hovertemplate||M||(-1===A.indexOf(\"x\")&&(T.xLabel=void 0),-1===A.indexOf(\"y\")&&(T.yLabel=void 0),-1===A.indexOf(\"z\")&&(T.zLabel=void 0),-1===A.indexOf(\"text\")&&(h.textLabel=void 0),-1===A.indexOf(\"name\")&&(u.name=void 0));var S=[];\"cone\"===t.type||\"streamtube\"===t.type?(T.uLabel=g(\"x\",h.traceCoordinate[3],t.uhoverformat),(M||-1!==A.indexOf(\"u\"))&&S.push(\"u: \"+T.uLabel),T.vLabel=g(\"y\",h.traceCoordinate[4],t.vhoverformat),(M||-1!==A.indexOf(\"v\"))&&S.push(\"v: \"+T.vLabel),T.wLabel=g(\"z\",h.traceCoordinate[5],t.whoverformat),(M||-1!==A.indexOf(\"w\"))&&S.push(\"w: \"+T.wLabel),T.normLabel=h.traceCoordinate[6].toPrecision(3),(M||-1!==A.indexOf(\"norm\"))&&S.push(\"norm: \"+T.normLabel),\"streamtube\"===t.type&&(T.divergenceLabel=h.traceCoordinate[7].toPrecision(3),(M||-1!==A.indexOf(\"divergence\"))&&S.push(\"divergence: \"+T.divergenceLabel)),h.textLabel&&S.push(h.textLabel),x=S.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(T.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(h.traceCoordinate[3]),t.valuehoverformat),S.push(\"value: \"+T.valueLabel),h.textLabel&&S.push(h.textLabel),x=S.join(\"<br>\")):x=h.textLabel;var E={x:h.traceCoordinate[0],y:h.traceCoordinate[1],z:h.traceCoordinate[2],data:_._input,fullData:_,curveNumber:_.index,pointNumber:w};d.appendArrayPointValue(E,_,w),t._module.eventData&&(E=_._module.eventData(E,h,_,{},w));var L={points:[E]};if(e.fullSceneLayout.hovermode){var C=[];d.loneHover({trace:_,x:(.5+.5*y[0]/y[3])*s,y:(.5-.5*y[1]/y[3])*l,xLabel:T.xLabel,yLabel:T.yLabel,zLabel:T.zLabel,text:x,name:u.name,color:d.castHoverOption(_,w,\"bgcolor\")||u.color,borderColor:d.castHoverOption(_,w,\"bordercolor\"),fontFamily:d.castHoverOption(_,w,\"font.family\"),fontSize:d.castHoverOption(_,w,\"font.size\"),fontColor:d.castHoverOption(_,w,\"font.color\"),nameLength:d.castHoverOption(_,w,\"namelength\"),textAlign:d.castHoverOption(_,w,\"align\"),hovertemplate:f.castOption(_,w,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},E,T),eventData:[E]},{container:n,gd:r,inOut_bbox:C}),E.bbox=C[0]}h.buttons&&h.distance<5?r.emit(\"plotly_click\",L):r.emit(\"plotly_hover\",L),this.oldEventData=L}else d.loneUnhover(n),this.oldEventData&&r.emit(\"plotly_unhover\",this.oldEventData),this.oldEventData=void 0;e.drawAnnotations(e)},w.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var k=[\"xaxis\",\"yaxis\",\"zaxis\"];function A(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=k[i],o=a.charAt(0),s=n[a],l=e[o],c=e[o+\"calendar\"],u=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(u||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],u-1)}}w.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,i,a,o,s,l,c=e[this.id],u=r[this.id];this.fullLayout=e,this.fullSceneLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setViewport(c),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.setClearColor(m(c.bgcolor)),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&A(this,n,f);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=k[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][i]=Math.min(e[0][i],u),e[1][i]=Math.max(e[1][i],u))}}}(this,f);var h=[1,1,1];for(o=0;o<3;++o)f[1][o]===f[0][o]?h[o]=1:h[o]=1/(f[1][o]-f[0][o]);for(this.dataScale=h,this.convertAnnotations(this),a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&((i=this.traces[n.uid])?i.data.type===n.type?i.update(n):(i.dispose(),i=n._module.plot(this,n),this.traces[n.uid]=i):(i=n._module.plot(this,n),this.traces[n.uid]=i),i.name=n.name);var p=Object.keys(this.traces);t:for(a=0;a<p.length;++a){for(o=0;o<t.length;++o)if(t[o].uid===p[a]&&!0===t[o].visible&&0!==t[o]._length)continue t;(i=this.traces[p[a]]).dispose(),delete this.traces[p[a]]}this.glplot.objects.sort((function(t,e){return t._trace.data.index-e._trace.data.index}));var d,g=[[0,0,0],[0,0,0]],v=[],y={};for(a=0;a<3;++a){if((l=(s=c[k[a]]).type)in y?(y[l].acc*=h[a],y[l].count+=1):y[l]={acc:h[a],count:1},s.autorange){g[0][a]=1/0,g[1][a]=-1/0;var x=this.glplot.objects,b=this.fullSceneLayout.annotations||[],_=s._name.charAt(0);for(o=0;o<x.length;o++){var w=x[o],T=w.bounds,M=w._trace.data._pad||0;\"ErrorBars\"===w.constructor.name&&s._lowerLogErrorBound?g[0][a]=Math.min(g[0][a],s._lowerLogErrorBound):g[0][a]=Math.min(g[0][a],T[0][a]/h[a]-M),g[1][a]=Math.max(g[1][a],T[1][a]/h[a]+M)}for(o=0;o<b.length;o++){var S=b[o];if(S.visible){var E=s.r2l(S[_]);g[0][a]=Math.min(g[0][a],E),g[1][a]=Math.max(g[1][a],E)}}if(\"rangemode\"in s&&\"tozero\"===s.rangemode&&(g[0][a]=Math.min(g[0][a],0),g[1][a]=Math.max(g[1][a],0)),g[0][a]>g[1][a])g[0][a]=-1,g[1][a]=1;else{var L=g[1][a]-g[0][a];g[0][a]-=L/32,g[1][a]+=L/32}if(\"reversed\"===s.autorange){var C=g[0][a];g[0][a]=g[1][a],g[1][a]=C}}else{var P=s.range;g[0][a]=s.r2l(P[0]),g[1][a]=s.r2l(P[1])}g[0][a]===g[1][a]&&(g[0][a]-=1,g[1][a]+=1),v[a]=g[1][a]-g[0][a],this.glplot.setBounds(a,{min:g[0][a]*h[a],max:g[1][a]*h[a]})}var I=c.aspectmode;if(\"cube\"===I)d=[1,1,1];else if(\"manual\"===I){var O=c.aspectratio;d=[O.x,O.y,O.z]}else{if(\"auto\"!==I&&\"data\"!==I)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var z=[1,1,1];for(a=0;a<3;++a){var D=y[l=(s=c[k[a]]).type];z[a]=Math.pow(D.acc,1/D.count)/h[a]}d=\"data\"===I||Math.max.apply(null,z)/Math.min.apply(null,z)<=4?z:[1,1,1]}c.aspectratio.x=u.aspectratio.x=d[0],c.aspectratio.y=u.aspectratio.y=d[1],c.aspectratio.z=u.aspectratio.z=d[2],this.glplot.setAspectratio(c.aspectratio),this.viewInitial.aspectratio||(this.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),this.viewInitial.aspectmode||(this.viewInitial.aspectmode=c.aspectmode);var R=c.domain||null,F=e._size||null;if(R&&F){var B=this.container.style;B.position=\"absolute\",B.left=F.l+R.x[0]*F.w+\"px\",B.top=F.t+(1-R.y[1])*F.h+\"px\",B.width=F.w*(R.x[1]-R.x[0])+\"px\",B.height=F.h*(R.y[1]-R.y[0])+\"px\"}this.glplot.redraw()}},w.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},w.getCamera=function(){var t;return this.camera.view.recalcMatrix(this.camera.view.lastT()),{up:{x:(t=this.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},w.setViewport=function(t){var e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),\"orthographic\"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},w.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},w.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},w.saveLayout=function(t){var e,r,n,i,a,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),h=l||c;if(h){var p={};if(l&&(e=this.getCamera(),n=(r=f.nestedProperty(t,this.id+\".camera\")).get(),p[this.id+\".camera\"]=n),c&&(i=this.glplot.getAspectratio(),o=(a=f.nestedProperty(t,this.id+\".aspectratio\")).get(),p[this.id+\".aspectratio\"]=o),u.call(\"_storeDirectGUIEdit\",t,s._preGUI,p),l)r.set(e),f.nestedProperty(s,this.id+\".camera\").set(e);if(c)a.set(i),f.nestedProperty(s,this.id+\".aspectratio\").set(i),this.glplot.redraw()}return h},w.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else if(\"turntable\"===t){r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\";var n=this.graphDiv,i=n._fullLayout,a=this.fullSceneLayout.camera,o=a.up.x,s=a.up.y,l=a.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+\".camera.up\",h={x:0,y:0,z:1},p={};p[c]=h;var d=n.layout;u.call(\"_storeDirectGUIEdit\",d,i._preGUI,p),a.up=h,f.nestedProperty(d,c).set(h)}}else r.keyBindingMode=t;this.fullSceneLayout.hovermode=e},w.toImage=function(t){t||(t=\"png\"),this.staticMode&&this.container.appendChild(n),this.glplot.redraw();var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a),function(t,e,r){for(var n=0,i=r-1;n<i;++n,--i)for(var a=0;a<e;++a)for(var o=0;o<4;++o){var s=4*(e*n+a)+o,l=4*(e*i+a)+o,c=t[s];t[s]=t[l],t[l]=c}}(a,r,i),function(t,e,r){for(var n=0;n<r;++n)for(var i=0;i<e;++i){var a=4*(e*n+i),o=t[a+3];if(o>0)for(var s=255/o,l=0;l<3;++l)t[a+l]=Math.min(s*t[a+l],255)}}(a,r,i);var o=document.createElement(\"canvas\");o.width=r,o.height=i;var s,l=o.getContext(\"2d\",{willReadFrequently:!0}),c=l.createImageData(r,i);switch(c.data.set(a),l.putImageData(c,0,0),t){case\"jpeg\":s=o.toDataURL(\"image/jpeg\");break;case\"webp\":s=o.toDataURL(\"image/webp\");break;default:s=o.toDataURL(\"image/png\")}return this.staticMode&&this.container.removeChild(n),s},w.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[k[t]];p.setConvert(e,this.fullLayout),e.setScale=f.noop}},w.make4thDimension=function(){var t=this.graphDiv._fullLayout;this._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},p.setConvert(this._mockAxis,t)},e.exports=_},{\"../../../stackgl_modules\":1124,\"../../components/fx\":406,\"../../lib\":503,\"../../lib/show_no_webgl_msg\":525,\"../../lib/str2rgbarray\":528,\"../../plots/cartesian/axes\":554,\"../../registry\":638,\"./layout/convert\":602,\"./layout/spikes\":605,\"./layout/tick_marks\":606,\"./project\":607,\"has-passive-events\":229,\"webgl-context\":331}],609:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;a<n;a++)i[a]=[t[a],e[a],r[a]];return i}},{}],610:[function(t,e,r){\"use strict\";var n=t(\"./font_attributes\"),i=t(\"./animation_attributes\"),a=t(\"../components/color/attributes\"),o=t(\"../components/shapes/draw_newshape/attributes\"),s=t(\"./pad_attributes\"),l=t(\"../lib/extend\").extendFlat,c=n({editType:\"calc\"});c.family.dflt='\"Open Sans\", verdana, arial, sans-serif',c.size.dflt=12,c.color.dflt=a.defaultLine,e.exports={font:c,title:{text:{valType:\"string\",editType:\"layoutstyle\"},font:n({editType:\"layoutstyle\"}),xref:{valType:\"enumerated\",dflt:\"container\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},yref:{valType:\"enumerated\",dflt:\"container\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},x:{valType:\"number\",min:0,max:1,dflt:.5,editType:\"layoutstyle\"},y:{valType:\"number\",min:0,max:1,dflt:\"auto\",editType:\"layoutstyle\"},xanchor:{valType:\"enumerated\",dflt:\"auto\",values:[\"auto\",\"left\",\"center\",\"right\"],editType:\"layoutstyle\"},yanchor:{valType:\"enumerated\",dflt:\"auto\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],editType:\"layoutstyle\"},pad:l(s({editType:\"layoutstyle\"}),{}),editType:\"layoutstyle\"},uniformtext:{mode:{valType:\"enumerated\",values:[!1,\"hide\",\"show\"],dflt:!1,editType:\"plot\"},minsize:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"plot\"},autosize:{valType:\"boolean\",dflt:!1,editType:\"none\"},width:{valType:\"number\",min:10,dflt:700,editType:\"plot\"},height:{valType:\"number\",min:10,dflt:450,editType:\"plot\"},margin:{l:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},r:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},t:{valType:\"number\",min:0,dflt:100,editType:\"plot\"},b:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},pad:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},autoexpand:{valType:\"boolean\",dflt:!0,editType:\"plot\"},editType:\"plot\"},computed:{valType:\"any\",editType:\"none\"},paper_bgcolor:{valType:\"color\",dflt:a.background,editType:\"plot\"},plot_bgcolor:{valType:\"color\",dflt:a.background,editType:\"layoutstyle\"},autotypenumbers:{valType:\"enumerated\",values:[\"convert types\",\"strict\"],dflt:\"convert types\",editType:\"calc\"},separators:{valType:\"string\",editType:\"plot\"},hidesources:{valType:\"boolean\",dflt:!1,editType:\"plot\"},showlegend:{valType:\"boolean\",editType:\"legend\"},colorway:{valType:\"colorlist\",dflt:a.defaults,editType:\"calc\"},datarevision:{valType:\"any\",editType:\"calc\"},uirevision:{valType:\"any\",editType:\"none\"},editrevision:{valType:\"any\",editType:\"none\"},selectionrevision:{valType:\"any\",editType:\"none\"},template:{valType:\"any\",editType:\"calc\"},newshape:o.newshape,activeshape:o.activeshape,meta:{valType:\"any\",arrayOk:!0,editType:\"plot\"},transition:l({},i.transition,{editType:\"none\"}),_deprecated:{title:{valType:\"string\",editType:\"layoutstyle\"},titlefont:n({editType:\"layoutstyle\"})}}},{\"../components/color/attributes\":365,\"../components/shapes/draw_newshape/attributes\":451,\"../lib/extend\":493,\"./animation_attributes\":548,\"./font_attributes\":585,\"./pad_attributes\":618}],611:[function(t,e,r){\"use strict\";var n=t(\"../../lib/sort_object_keys\"),i='\\xa9 <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">OpenStreetMap</a> contributors',a=['\\xa9 <a target=\"_blank\" href=\"https://carto.com/\">Carto</a>',i].join(\" \"),o=['Map tiles by <a target=\"_blank\" href=\"https://stamen.com\">Stamen Design</a>','under <a target=\"_blank\" href=\"https://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a>',\"|\",'Data by <a target=\"_blank\" href=\"https://openstreetmap.org\">OpenStreetMap</a> contributors','under <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">ODbL</a>'].join(\" \"),s={\"open-street-map\":{id:\"osm\",version:8,sources:{\"plotly-osm-tiles\":{type:\"raster\",attribution:i,tiles:[\"https://a.tile.openstreetmap.org/{z}/{x}/{y}.png\",\"https://b.tile.openstreetmap.org/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-osm-tiles\",type:\"raster\",source:\"plotly-osm-tiles\",minzoom:0,maxzoom:22}]},\"white-bg\":{id:\"white-bg\",version:8,sources:{},layers:[{id:\"white-bg\",type:\"background\",paint:{\"background-color\":\"#FFFFFF\"},minzoom:0,maxzoom:22}]},\"carto-positron\":{id:\"carto-positron\",version:8,sources:{\"plotly-carto-positron\":{type:\"raster\",attribution:a,tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-positron\",type:\"raster\",source:\"plotly-carto-positron\",minzoom:0,maxzoom:22}]},\"carto-darkmatter\":{id:\"carto-darkmatter\",version:8,sources:{\"plotly-carto-darkmatter\":{type:\"raster\",attribution:a,tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-darkmatter\",type:\"raster\",source:\"plotly-carto-darkmatter\",minzoom:0,maxzoom:22}]},\"stamen-terrain\":{id:\"stamen-terrain\",version:8,sources:{\"plotly-stamen-terrain\":{type:\"raster\",attribution:o,tiles:[\"https://stamen-tiles.a.ssl.fastly.net/terrain/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-terrain\",type:\"raster\",source:\"plotly-stamen-terrain\",minzoom:0,maxzoom:22}]},\"stamen-toner\":{id:\"stamen-toner\",version:8,sources:{\"plotly-stamen-toner\":{type:\"raster\",attribution:o,tiles:[\"https://stamen-tiles.a.ssl.fastly.net/toner/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-toner\",type:\"raster\",source:\"plotly-stamen-toner\",minzoom:0,maxzoom:22}]},\"stamen-watercolor\":{id:\"stamen-watercolor\",version:8,sources:{\"plotly-stamen-watercolor\":{type:\"raster\",attribution:['Map 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t&&(-1!==p.styleValuesMapbox.indexOf(t)||0===t.indexOf(\"mapbox://\"))}r.name=\"mapbox\",r.attr=\"subplot\",r.idRoot=\"mapbox\",r.idRegex=r.attrRegex=i.counterRegex(\"mapbox\"),r.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){var e=t._fullLayout,r=t.calcdata,a=e._subplots.mapbox;if(n.version!==p.requiredVersion)throw new Error(p.wrongVersionErrorMsg);var o=function(t,e){var r=t._fullLayout;if(\"\"===t._context.mapboxAccessToken)return\"\";for(var n=[],a=[],o=!1,s=!1,l=0;l<e.length;l++){var c=r[e[l]],u=c.accesstoken;d(c.style)&&(u?i.pushUnique(n,u):(d(c._input.style)&&(i.error(\"Uses Mapbox map style, but did not set an access token.\"),o=!0),s=!0)),u&&i.pushUnique(a,u)}if(s){var f=o?p.noAccessTokenErrorMsg:p.missingStyleErrorMsg;throw i.error(f),new Error(f)}return 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m=c.select(s._subplot.div);if(!(null===m.select(\".mapboxgl-ctrl-logo\").node().offsetParent)){var g=e._glimages.append(\"g\");g.attr(\"transform\",a(n.l+n.w*h.x[0]+10,n.t+n.h*(1-h.y[0])-31)),g.append(\"path\").attr(\"d\",p.mapboxLogo.path0).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"}),g.append(\"path\").attr(\"d\",p.mapboxLogo.path1).style(\"opacity\",.35).style(\"enable-background\",\"new\"),g.append(\"path\").attr(\"d\",p.mapboxLogo.path2).style(\"opacity\",.35).style(\"enable-background\",\"new\"),g.append(\"polygon\").attr(\"points\",p.mapboxLogo.polygon).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"})}var v=m.select(\".mapboxgl-ctrl-attrib\").text().replace(\"Improve this map\",\"\"),y=e._glimages.append(\"g\"),x=y.append(\"text\");x.text(v).classed(\"static-attribution\",!0).attr({\"font-size\":12,\"font-family\":\"Arial\",color:\"rgba(0, 0, 0, 0.75)\",\"text-anchor\":\"end\",\"data-unformatted\":v});var b=u.bBox(x.node()),_=n.w*(h.x[1]-h.x[0]);if(b.width>_/2){var w=v.split(\"|\").join(\"<br>\");x.text(w).attr(\"data-unformatted\",w).call(f.convertToTspans,t),b=u.bBox(x.node())}x.attr(\"transform\",a(-3,8-b.height)),y.insert(\"rect\",\".static-attribution\").attr({x:-b.width-6,y:-b.height-3,width:b.width+6,height:b.height+3,fill:\"rgba(255, 255, 255, 0.75)\"});var T=1;b.width+6>_&&(T=_/(b.width+6));var k=[n.l+n.w*h.x[1],n.t+n.h*(1-h.y[0])];y.attr(\"transform\",a(k[0],k[1])+o(T))}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.mapbox,n=0;n<r.length;n++){e[r[n]]._subplot.updateFx(e)}}},{\"../../components/drawing\":388,\"../../constants/xmlns_namespaces\":480,\"../../lib\":503,\"../../lib/svg_text_utils\":529,\"../../plots/get_data\":593,\"./constants\":611,\"./layout_attributes\":615,\"./layout_defaults\":616,\"./mapbox\":617,\"@plotly/d3\":58,\"mapbox-gl/dist/mapbox-gl-unminified\":239}],614:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../lib/svg_text_utils\").sanitizeHTML,a=t(\"./convert_text_opts\"),o=t(\"./constants\");function s(t,e){this.subplot=t,this.uid=t.uid+\"-\"+e,this.index=e,this.idSource=\"source-\"+this.uid,this.idLayer=o.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var l=s.prototype;function c(t){if(!t.visible)return!1;var e=t.source;if(Array.isArray(e)&&e.length>0){for(var r=0;r<e.length;r++)if(\"string\"!=typeof e[r]||0===e[r].length)return!1;return!0}return n.isPlainObject(e)||\"string\"==typeof e&&e.length>0}function u(t){var e={},r={};switch(t.type){case\"circle\":n.extendFlat(r,{\"circle-radius\":t.circle.radius,\"circle-color\":t.color,\"circle-opacity\":t.opacity});break;case\"line\":n.extendFlat(r,{\"line-width\":t.line.width,\"line-color\":t.color,\"line-opacity\":t.opacity,\"line-dasharray\":t.line.dash});break;case\"fill\":n.extendFlat(r,{\"fill-color\":t.color,\"fill-outline-color\":t.fill.outlinecolor,\"fill-opacity\":t.opacity});break;case\"symbol\":var i=t.symbol,o=a(i.textposition,i.iconsize);n.extendFlat(e,{\"icon-image\":i.icon+\"-15\",\"icon-size\":i.iconsize/10,\"text-field\":i.text,\"text-size\":i.textfont.size,\"text-anchor\":o.anchor,\"text-offset\":o.offset,\"symbol-placement\":i.placement}),n.extendFlat(r,{\"icon-color\":t.color,\"text-color\":i.textfont.color,\"text-opacity\":t.opacity});break;case\"raster\":n.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":t.opacity})}return{layout:e,paint:r}}l.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=c(t)},l.needsNewImage=function(t){return this.subplot.map.getSource(this.idSource)&&\"image\"===this.sourceType&&\"image\"===t.sourcetype&&(this.source!==t.source||JSON.stringify(this.coordinates)!==JSON.stringify(t.coordinates))},l.needsNewSource=function(t){return this.sourceType!==t.sourcetype||JSON.stringify(this.source)!==JSON.stringify(t.source)||this.layerType!==t.type},l.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]},l.lookupBelow=function(){return this.subplot.belowLookup[\"layout-\"+this.index]},l.updateImage=function(t){this.subplot.map.getSource(this.idSource).updateImage({url:t.source,coordinates:t.coordinates});var e=this.findFollowingMapboxLayerId(this.lookupBelow());null!==e&&this.subplot.map.moveLayer(this.idLayer,e)},l.updateSource=function(t){var e=this.subplot.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,c(t)){var r=function(t){var e,r=t.sourcetype,n=t.source,a={type:r};\"geojson\"===r?e=\"data\":\"vector\"===r?e=\"string\"==typeof n?\"url\":\"tiles\":\"raster\"===r?(e=\"tiles\",a.tileSize=256):\"image\"===r&&(e=\"url\",a.coordinates=t.coordinates);a[e]=n,t.sourceattribution&&(a.attribution=i(t.sourceattribution));return a}(t);e.addSource(this.idSource,r)}},l.findFollowingMapboxLayerId=function(t){if(\"traces\"===t)for(var e=this.subplot.getMapLayers(),r=0;r<e.length;r++){var n=e[r].id;if(\"string\"==typeof n&&0===n.indexOf(o.traceLayerPrefix)){t=n;break}}return t},l.updateLayer=function(t){var e=this.subplot,r=u(t),n=this.lookupBelow(),i=this.findFollowingMapboxLayerId(n);this.removeLayer(),c(t)&&e.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type,minzoom:t.minzoom,maxzoom:t.maxzoom,layout:r.layout,paint:r.paint},i),this.layerType=t.type,this.below=n},l.updateStyle=function(t){if(c(t)){var e=u(t);this.subplot.setOptions(this.idLayer,\"setLayoutProperty\",e.layout),this.subplot.setOptions(this.idLayer,\"setPaintProperty\",e.paint)}},l.removeLayer=function(){var t=this.subplot.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer)},l.dispose=function(){var t=this.subplot.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer),t.getSource(this.idSource)&&t.removeSource(this.idSource)},e.exports=function(t,e,r){var n=new s(t,e);return n.update(r),n}},{\"../../lib\":503,\"../../lib/svg_text_utils\":529,\"./constants\":611,\"./convert_text_opts\":612}],615:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\").defaultLine,a=t(\"../domain\").attributes,o=t(\"../font_attributes\"),s=t(\"../../traces/scatter/attributes\").textposition,l=t(\"../../plot_api/edit_types\").overrideAll,c=t(\"../../plot_api/plot_template\").templatedArray,u=t(\"./constants\"),f=o({});f.family.dflt=\"Open Sans Regular, Arial Unicode MS 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e,r,s=this,c=s.isSmith,u=s.gd,f=s.layers,h=t._zoomlayer,p=S.MINZOOM,d=S.OFFEDGE,m=s.radius,x=s.innerRadius,T=s.cx,k=s.cy,A=s.cxx,M=s.cyy,L=s.sectorInRad,C=s.vangles,P=s.radialAxis,I=E.clampTiny,O=E.findXYatLength,z=E.findEnclosingVertexAngles,D=S.cornerHalfWidth,R=S.cornerLen/2,F=g.makeDragger(f,\"path\",\"maindrag\",!1===t.dragmode?\"none\":\"crosshair\");n.select(F).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(T,k)),F.onmousemove=function(t){y.hover(u,t,s.id),u._fullLayout._lasthover=F,u._fullLayout._hoversubplot=s.id},F.onmouseout=function(t){u._dragging||v.unhover(u,t)};var B,N,j,U,V,H,q,G,Y,W={element:F,gd:u,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function X(t,e){return Math.sqrt(t*t+e*e)}function Z(t,e){return X(t-A,e-M)}function J(t,e){return Math.atan2(M-e,t-A)}function K(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function Q(t,e){if(0===t)return s.pathSector(2*D);var 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O,z,D,B=g.makeRectDragger(u,T,\"crosshair\",-x,-x,y,y),N={element:B,gd:c};!1===t.dragmode&&(N.dragmode=!1),V(n.select(B),m.visible&&h<f,{transform:l(b,_)}),N.prepFn=function(){O=null,z=null,D=null,N.moveFn=j,N.doneFn=H,w(c)},N.clampFn=function(t,e){return Math.sqrt(t*t+e*e)<S.MINDRAG&&(t=0,e=0),[t,e]},v.init(N)}function j(t,e){if(O)O(t,e);else{var n=[t,-e],a=[Math.cos(M),Math.sin(M)],s=Math.abs(o.dot(n,a)/Math.sqrt(o.dot(n,n)));isNaN(s)||(O=s<.5?q:G)}var l={};!function(t){null!==z?t[i.id+\".radialaxis.angle\"]=z:null!==D&&(t[i.id+\".radialaxis.range[\"+r+\"]\"]=D)}(l),c.emit(\"plotly_relayouting\",l)}function H(){null!==z?a.call(\"_guiRelayout\",c,i.id+\".radialaxis.angle\",z):null!==D&&a.call(\"_guiRelayout\",c,i.id+\".radialaxis.range[\"+r+\"]\",D)}function q(t,e){if(0!==r){var n=b+t,a=_+e;z=Math.atan2(d-a,n-p),i.vangles&&(z=U(z,i.vangles)),z=F(z);var o=l(p,d)+s(-z);u[\"radial-axis\"].attr(\"transform\",o),u[\"radial-line\"].select(\"line\").attr(\"transform\",o);var 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e=this.graphDiv,r=t[this.id],n=this.clipId=\"clip\"+this.layoutId+this.id,i=this.clipIdRelative=\"clip-relative\"+this.layoutId+this.id;this.clipDef=o.ensureSingleById(t._clips,\"clipPath\",n,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.clipDefRelative=o.ensureSingleById(t._clips,\"clipPath\",i,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.plotContainer=o.ensureSingle(this.container,\"g\",this.id),this.updateLayers(r),u.setClipUrl(this.layers.backplot,n,e),u.setClipUrl(this.layers.grids,n,e)},S.updateLayers=function(t){var e=this.layers,r=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];\"below traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"below traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"below traces\"===t.caxis.layer&&r.push(\"caxis\",\"cline\"),r.push(\"frontplot\"),\"above traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"above traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"above 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r,n,i,a,o,l,p=this,d=t.domain,m=(d.x[0]+d.x[1])/2,g=(d.y[0]+d.y[1])/2,v=d.x[1]-d.x[0],y=d.y[1]-d.y[0],x=v*e.w,b=y*e.h,_=t.sum,w=t.aaxis.min,T=t.baxis.min,k=t.caxis.min;x>E*b?i=(a=b)*E:a=(i=x)/E,o=v*i/x,l=y*a/b,r=e.l+e.w*m-i/2,n=e.t+e.h*(1-g)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[m-o/2,m+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[g-l/2,g+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var A=p.yaxis.domain[0],M=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(M,p.graphDiv._fullLayout),M.setScale();var 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D=s(r+i/2,n)+\"rotate(-30)\"+s(0,-L._offset);p.layers.caxis.attr(\"transform\",D),p.layers.cgrid.attr(\"transform\",D),p.drawAxes(!0),p.layers.aline.select(\"path\").attr(\"d\",M.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(c.stroke,M.linecolor||\"#000\").style(\"stroke-width\",(M.linewidth||0)+\"px\"),p.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(c.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),p.layers.cline.select(\"path\").attr(\"d\",L.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(c.stroke,L.linecolor||\"#000\").style(\"stroke-width\",(L.linewidth||0)+\"px\"),p.graphDiv._context.staticPlot||p.initInteractions(),u.setClipUrl(p.layers.frontplot,p._hasClipOnAxisFalse?null:p.clipId,p.graphDiv)},S.drawAxes=function(t){var 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L=A.MINZOOM/2+.87,C=\"m-0.87,.5h\"+L+\"v3h-\"+(L+5.2)+\"l\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l2.6,1.5l-\"+L/2+\",\"+.87*L+\"Z\",P=\"m0.87,.5h-\"+L+\"v3h\"+(L+5.2)+\"l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-2.6,1.5l\"+L/2+\",\"+.87*L+\"Z\",I=\"m0,1l\"+L/2+\",\"+.87*L+\"l2.6,-1.5l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-\"+(L/2+2.6)+\",\"+(.87*L+4.5)+\"l2.6,1.5l\"+L/2+\",-\"+.87*L+\"Z\",O=!0;function z(t){n.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}S.clearSelect=function(){k(this.dragOptions),T(this.dragOptions.gd)},S.initInteractions=function(){var t,e,r,n,f,h,p,d,v,b,T,k,M=this,S=M.layers.plotbg.select(\"path\").node(),L=M.graphDiv,D=L._fullLayout._zoomlayer;function R(t){var e={};return e[M.id+\".aaxis.min\"]=t.a,e[M.id+\".baxis.min\"]=t.b,e[M.id+\".caxis.min\"]=t.c,e}function F(t,e){var 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r=t/M.xaxis._m,n=e/M.yaxis._m,i=[(p={a:f.a-n,b:f.b+(r+n)/2,c:f.c-(r-n)/2}).a,p.b,p.c].sort(o.sorterAsc),a=i.indexOf(p.a),l=i.indexOf(p.b),c=i.indexOf(p.c);i[0]<0&&(i[1]+i[0]/2<0?(i[2]+=i[0]+i[1],i[0]=i[1]=0):(i[2]+=i[0]/2,i[1]+=i[0]/2,i[0]=0),p={a:i[a],b:i[l],c:i[c]},e=(f.a-p.a)*M.yaxis._m,t=(f.c-p.c-f.b+p.b)*M.xaxis._m);var h=s(M.x0+t,M.y0+e);M.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",h);var d=s(-t,-e);M.clipDefRelative.select(\"path\").attr(\"transform\",d),M.aaxis.range=[p.a,M.sum-p.b-p.c],M.baxis.range=[M.sum-p.a-p.c,p.b],M.caxis.range=[M.sum-p.a-p.b,p.c],M.drawAxes(!1),M._hasClipOnAxisFalse&&M.plotContainer.select(\".scatterlayer\").selectAll(\".trace\").call(u.hideOutsideRangePoints,M),L.emit(\"plotly_relayouting\",R(p))}function 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n=t(\"../../components/colorscale/defaults\"),i=t(\"./label_defaults\");e.exports=function(t,e,r,a,o){var s,l=r(\"contours.coloring\"),c=\"\";\"fill\"===l&&(s=r(\"contours.showlines\")),!1!==s&&(\"lines\"!==l&&(c=r(\"line.color\",\"#000\")),r(\"line.width\",.5),r(\"line.dash\")),\"none\"!==l&&(!0!==t.showlegend&&(e.showlegend=!1),e._dfltShowLegend=!1,n(t,e,a,r,{prefix:\"\",cLetter:\"z\"})),r(\"line.smoothing\"),i(r,a,c,o)}},{\"../../components/colorscale/defaults\":376,\"./label_defaults\":750}],757:[function(t,e,r){\"use strict\";var n=t(\"../heatmap/attributes\"),i=t(\"../contour/attributes\"),a=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat,s=i.contours;e.exports=o({carpet:{valType:\"string\",editType:\"calc\"},z:n.z,a:n.x,a0:n.x0,da:n.dx,b:n.y,b0:n.y0,db:n.dy,text:n.text,hovertext:n.hovertext,transpose:n.transpose,atype:n.xtype,btype:n.ytype,fillcolor:i.fillcolor,autocontour:i.autocontour,ncontours:i.ncontours,contours:{type:s.type,start:s.start,end:s.end,size:s.size,coloring:{valType:\"enumerated\",values:[\"fill\",\"lines\",\"none\"],dflt:\"fill\",editType:\"calc\"},showlines:s.showlines,showlabels:s.showlabels,labelfont:s.labelfont,labelformat:s.labelformat,operation:s.operation,value:s.value,editType:\"calc\",impliedEdits:{autocontour:!1}},line:{color:i.line.color,width:i.line.width,dash:i.line.dash,smoothing:i.line.smoothing,editType:\"plot\"},transforms:void 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n=t(\"../pie/layout_attributes\").hiddenlabels;e.exports={hiddenlabels:n,funnelareacolorway:{valType:\"colorlist\",editType:\"calc\"},extendfunnelareacolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{\"../pie/layout_attributes\":908}],789:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":503,\"./layout_attributes\":788}],790:[function(t,e,r){\"use strict\";var 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n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat;e.exports=u({z:{valType:\"data_array\",editType:\"calc\"},x:u({},n.x,{impliedEdits:{xtype:\"array\"}}),x0:u({},n.x0,{impliedEdits:{xtype:\"scaled\"}}),dx:u({},n.dx,{impliedEdits:{xtype:\"scaled\"}}),y:u({},n.y,{impliedEdits:{ytype:\"array\"}}),y0:u({},n.y0,{impliedEdits:{ytype:\"scaled\"}}),dy:u({},n.dy,{impliedEdits:{ytype:\"scaled\"}}),xperiod:u({},n.xperiod,{impliedEdits:{xtype:\"scaled\"}}),yperiod:u({},n.yperiod,{impliedEdits:{ytype:\"scaled\"}}),xperiod0:u({},n.xperiod0,{impliedEdits:{xtype:\"scaled\"}}),yperiod0:u({},n.yperiod0,{impliedEdits:{ytype:\"scaled\"}}),xperiodalignment:u({},n.xperiodalignment,{impliedEdits:{xtype:\"scaled\"}}),yperiodalignment:u({},n.yperiodalignment,{impliedEdits:{ytype:\"scaled\"}}),text:{valType:\"data_array\",editType:\"calc\"},hovertext:{valType:\"data_array\",editType:\"calc\"},transpose:{valType:\"boolean\",dflt:!1,editType:\"calc\"},xtype:{valType:\"enumerated\",values:[\"array\",\"scaled\"],editType:\"calc+clearAxisTypes\"},ytype:{valType:\"enumerated\",values:[\"array\",\"scaled\"],editType:\"calc+clearAxisTypes\"},zsmooth:{valType:\"enumerated\",values:[\"fast\",\"best\",!1],dflt:!1,editType:\"calc\"},hoverongaps:{valType:\"boolean\",dflt:!0,editType:\"none\"},connectgaps:{valType:\"boolean\",editType:\"calc\"},xgap:{valType:\"number\",dflt:0,min:0,editType:\"plot\"},ygap:{valType:\"number\",dflt:0,min:0,editType:\"plot\"},xhoverformat:o(\"x\"),yhoverformat:o(\"y\"),zhoverformat:o(\"z\",1),hovertemplate:s(),texttemplate:l({arrayOk:!1,editType:\"plot\"},{keys:[\"x\",\"y\",\"z\",\"text\"]}),textfont:a({editType:\"plot\",autoSize:!0,autoColor:!0,colorEditType:\"style\"}),showlegend:u({},i.showlegend,{dflt:!1})},{transforms:void 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W=_.selectAll(\"g.gauge-outline\").data([x]);W.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),W.select(\"path\").call(P).call(T),W.exit().remove()}(t,0,e,{radius:U,innerRadius:V,gauge:Y,layer:W,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:g});var X=O.selectAll(\"g.bullet\").data(R?e:[]);X.exit().remove();var Z=O.selectAll(\"g.bulletaxis\").data(R?e:[]);Z.exit().remove(),R&&function(t,e,r,n){var i,a,o,s,c,u=r[0].trace,f=n.gauge,p=n.layer,m=n.gaugeBg,g=n.gaugeOutline,v=n.size,x=u.domain,b=n.transitionOpts,_=n.onComplete;f.enter().append(\"g\").classed(\"bullet\",!0),f.attr(\"transform\",l(v.l,v.t)),p.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),p.selectAll(\"g.xbulletaxistick,path,text\").remove();var A=v.h,M=u.gauge.bar.thickness*A,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(u._hasNumber||u._hasDelta?1-h.bulletNumberDomainSize:1);(i=k(t,u.gauge.axis))._id=\"xbulletaxis\",i.domain=[S,E],i.setScale(),a=d.calcTicks(i),o=d.makeTransTickFn(i),s=d.getTickSigns(i)[2],c=v.t+v.h,i.visible&&(d.drawTicks(t,i,{vals:\"inside\"===i.ticks?d.clipEnds(i,a):a,layer:p,path:d.makeTickPath(i,c,s),transFn:o}),d.drawLabels(t,i,{vals:a,layer:p,transFn:o,labelFns:d.makeLabelFns(i,c)}));function L(t){t.attr(\"width\",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr(\"x\",(function(t){return i.c2p(t.range[0])})).attr(\"y\",(function(t){return.5*(1-t.thickness)*A})).attr(\"height\",(function(t){return t.thickness*A}))}var C=[m].concat(u.gauge.steps),P=f.selectAll(\"g.bg-bullet\").data(C);P.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),P.select(\"rect\").call(L).call(T),P.exit().remove();var 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../surface/attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat;e.exports=l({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 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n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.intensity&&n(t,e,{vals:e.intensity,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":374}],869:[function(t,e,r){\"use strict\";var n=t(\"../../../stackgl_modules\").gl_mesh3d,i=t(\"../../../stackgl_modules\").delaunay_triangulate,a=t(\"../../../stackgl_modules\").alpha_shape,o=t(\"../../../stackgl_modules\").convex_hull,s=t(\"../../lib/gl_format_color\").parseColorScale,l=t(\"../../lib/str2rgbarray\"),c=t(\"../../components/colorscale\").extractOpts,u=t(\"../../plots/gl3d/zip3\");function f(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var h=f.prototype;function p(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=l(t[n]);return e}function d(t,e,r,n){for(var i=[],a=e.length,o=0;o<a;o++)i[o]=t.d2l(e[o],0,n)*r;return i}function m(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=Math.round(t[n]);return e}function g(t,e){for(var r=t.length,n=0;n<r;n++)if(t[n]<=-.5||t[n]>=e-.5)return!1;return!0}h.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index;t.data._cellCenter?t.traceCoordinate=t.data.dataCoordinate:t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]];var r=this.data.hovertext||this.data.text;return Array.isArray(r)&&void 0!==r[e]?t.textLabel=r[e]:r&&(t.textLabel=r),!0}},h.update=function(t){var e=this.scene,r=e.fullSceneLayout;this.data=t;var n,f=t.x.length,h=u(d(r.xaxis,t.x,e.dataScale[0],t.xcalendar),d(r.yaxis,t.y,e.dataScale[1],t.ycalendar),d(r.zaxis,t.z,e.dataScale[2],t.zcalendar));if(t.i&&t.j&&t.k){if(t.i.length!==t.j.length||t.j.length!==t.k.length||!g(t.i,f)||!g(t.j,f)||!g(t.k,f))return;n=u(m(t.i),m(t.j),m(t.k))}else n=0===t.alphahull?o(h):t.alphahull>0?a(t.alphahull,h):function(t,e){for(var r=[\"x\",\"y\",\"z\"].indexOf(t),n=[],a=e.length,o=0;o<a;o++)n[o]=[e[o][(r+1)%3],e[o][(r+2)%3]];return i(n)}(t.delaunayaxis,h);var v={positions:h,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:l(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var y=c(t);this.color=\"#fff\";var x=t.intensitymode;v[x+\"Intensity\"]=t.intensity,v[x+\"IntensityBounds\"]=[y.min,y.max],v.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],v.vertexColors=p(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],v.cellColors=p(t.facecolor)):(this.color=t.color,v.meshColor=l(t.color));this.mesh.update(v)},h.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new 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n=t(\"../../lib\").extendFlat,i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../components/drawing/attributes\").dash,s=t(\"../../components/fx/attributes\"),l=t(\"../../constants/delta.js\"),c=l.INCREASING.COLOR,u=l.DECREASING.COLOR,f=i.line;function 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E=S.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);S.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),k(E),S.exit().remove(),M.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;A.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(z)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){c.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),M.append(\"text\").attr(\"class\",\"dimlabel\"),A.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){c.font(n.select(this),t.parcatsViewModel.labelfont)})),A.selectAll(\"rect.bandrect\").on(\"mouseover\",L).on(\"mouseout\",C),A.exit().remove(),w.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",P).on(\"drag\",I).on(\"dragend\",O)),u.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),u.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function m(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function g(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){s.raiseToTop(this),w(n.select(this));var e=y(t),r=x(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var i,a,l,c=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),m=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=c&&c<=t.leftXs[l+1]+2){var g=t.parcatsViewModel.dimensions[l],v=t.parcatsViewModel.dimensions[l+1];i=(g.x+g.width+v.x)/2,a=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,_=t.parcatsViewModel.y+a,T=u.mostReadable(t.model.color,[\"black\",\"white\"]),k=t.model.count,A=k/t.parcatsViewModel.model.count,M={countLabel:k,probabilityLabel:A.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",M.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",M.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),L=n.mouse(f)[0];o.loneHover({trace:h,x:b-d.left+m.left,y:_-d.top+m.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:L<b?\"right\":\"left\",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:M,eventData:[{data:h._input,fullData:h,count:k,probability:A}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function v(t){if(!t.parcatsViewModel.dragDimension&&(_(n.select(this)),o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(m),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=y(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function y(t){for(var e=[],r=z(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function x(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function b(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=y(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function _(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function w(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return u.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function T(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function k(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function A(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each((function(t){A(t).each((function(t){Array.prototype.push.apply(l,y(t))}))}));var c={};c[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function S(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=A(i),l=[];s.each((function(t){Array.prototype.push.apply(l,y(t))}));var c={};c[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(c.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function E(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select(\"rect.catrect\"),c=l.node().getBoundingClientRect(),u=l.datum(),f=u.parcatsViewModel,h=f.model.dimensions[u.model.dimensionInd],p=f.trace,d=c.top+c.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=c.left,a=\"left\"):(i=c.left+c.width,a=\"right\");var m=u.model.count,g=u.model.categoryLabel,v=m/u.parcatsViewModel.model.count,y={countLabel:m,categoryLabel:g,probabilityLabel:v.toFixed(3)},x=[];-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",y.countLabel].join(\" \")),-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+y.categoryLabel+\"):\",y.probabilityLabel].join(\" \"));var b=x.join(\"<br>\");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:12,fontColor:\"black\",idealAlign:a,hovertemplate:p.hovertemplate,hovertemplateLabels:y,eventData:[{data:p._input,fullData:p,count:m,category:g,probability:v}]}}function L(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){if(n.mouse(this)[1]<-1)return;var e,r=t.parcatsViewModel.graphDiv,i=r._fullLayout,a=i._paperdiv.node().getBoundingClientRect(),l=t.parcatsViewModel.hoveron;if(\"color\"===l?(!function(t){var e=n.select(t).datum(),r=A(e);w(r),r.each((function(){s.raiseToTop(this)})),n.select(t.parentNode).selectAll(\"rect.bandrect\").filter((function(t){return t.color===e.color})).each((function(){s.raiseToTop(this),n.select(this).attr(\"stroke\",\"black\").attr(\"stroke-width\",1.5)}))}(this),S(this,\"plotly_hover\",n.event)):(!function(t){n.select(t.parentNode).selectAll(\"rect.bandrect\").each((function(t){var e=A(t);w(e),e.each((function(){s.raiseToTop(this)}))})),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),M(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===l?e=E(r,a,this):\"color\"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),c=n.select(r).datum(),f=c.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,m=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a=\"left\"):(i=l.left+l.width,a=\"right\");var g=f.model.categoryLabel,v=c.parcatsViewModel.model.count,y=0;c.categoryViewModel.bands.forEach((function(t){t.color===c.color&&(y+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===c.color&&(b+=t.model.count)}));var _=y/v,w=y/b,T=y/x,k={countLabel:v,categoryLabel:g,probabilityLabel:_.toFixed(3)},A=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&A.push([\"Count:\",k.countLabel].join(\" \")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(A.push(\"P(color \\u2229 \"+g+\"): \"+k.probabilityLabel),A.push(\"P(\"+g+\" | color): \"+w.toFixed(3)),A.push(\"P(color | \"+g+\"): \"+T.toFixed(3)));var M=A.join(\"<br>\"),S=u.mostReadable(c.color,[\"black\",\"white\"]);return{trace:d,x:o*(i-e.left),y:s*(m-e.top),text:M,color:c.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:g,count:v,probability:_,categorycount:x,colorcount:b,bandcolorcount:y}]}}(r,a,this):\"dimension\"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each((function(){i.push(E(t,e,this))})),i}(r,a,this)),e&&o.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r})}}function C(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(_(e.pathSelection),T(e.dimensionSelection.selectAll(\"g.category\")),k(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),o.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(m),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?S(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event)}}function P(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,s.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=a.categories,u=c[l-1],f=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}j(t.parcatsViewModel),N(t.parcatsViewModel),R(t.parcatsViewModel),D(t.parcatsViewModel)}}function O(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=z(t.parcatsViewModel),i=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==i[e]}));o&&i.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var c=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),u=c.map((function(t){return t.categoryValue})),f=c.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?S(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,j(t.parcatsViewModel),N(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){R(t.parcatsViewModel,!0),D(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function z(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function D(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),p),(r=t.pathSelection,e?r.transition():r).attr(\"d\",(function(t){return t.svgD}))}function R(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),p);var i=t.dimensionSelection.selectAll(\"g.category\").data((function(t){return t.categories}),p);r(t.dimensionSelection).attr(\"transform\",(function(t){return l(t.x,0)})),r(i).attr(\"transform\",(function(t){return l(0,t.y)})),i.select(\".dimlabel\").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),i.select(\".catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"x\",(function(t){return d(t)?t.width+5:-5})).each((function(t){var e,r;d(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)}));var a=i.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),p),o=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);a.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})),k(o),a.each((function(){s.raiseToTop(this)})),a.exit().remove()}function F(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(c*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var m={trace:o,key:o.uid,model:i,x:h,y:p,width:u,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return i.dimensions&&(j(m),N(m)),m}function B(t,e,r,n,a){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=i(r[s]+t[s],t[s+1]),l.push(o(a)),c.push(o(1-a));var u=\"M \"+t[0]+\",\"+e[0];for(u+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)u+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+c[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],u+=\"l\"+r[s]+\",0 \";for(u+=\"l0,\"+n+\" \",u+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)u+=\"C\"+c[s]+\",\"+(e[s+1]+n)+\" \"+l[s]+\",\"+(e[s]+n)+\" \"+(t[s]+r[s])+\",\"+(e[s]+n),u+=\"l-\"+r[s]+\",0 \";return u+=\"Z\"}function N(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}c.sort((function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0}));for(var h=new Array(c.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),m=0;m<c.length;m++){var g,v=c[m];g=p>0?d*(v.count/p):0;for(var y,x=new Array(n.length),b=0;b<v.categoryInds.length;b++){var 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n=t(\"../../lib\").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!(\"visible\"in t)}},{\"../../lib\":503}],896:[function(t,e,r){\"use strict\";var n=t(\"./base_index\");n.plot=t(\"./plot\"),e.exports=n},{\"./base_index\":890,\"./plot\":900}],897:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n p17_20, p21_24, p25_28, p29_32,\\n p33_36, p37_40, p41_44, p45_48,\\n p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\nuniform sampler2D maskTexture, palette;\\n\\nbool isPick = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n return (\\n fOutside(p[0], lo[0], hi[0]) ||\\n fOutside(p[1], lo[1], hi[1]) ||\\n fOutside(p[2], lo[2], hi[2]) ||\\n fOutside(p[3], lo[3], hi[3])\\n );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n return (\\n vOutside(p[0], lo[0], hi[0]) ||\\n 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isContext ? 0.0 : 2.0 * float(\\n outsideBoundingBox(A, B, C, D) ||\\n outsideRasterMask(A, B, C, D)\\n );\\n\\n return vec4(\\n 2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n z,\\n 1.0\\n );\\n}\\n\\nvoid main() {\\n mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n float v = colors[3];\\n\\n gl_Position = position(isContext, v, A, B, C, D);\\n\\n fragColor =\\n isContext ? vec4(contextColor) :\\n isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n gl_FragColor = fragColor;\\n}\\n\"]),o=t(\"./constants\").maxDimensionCount,s=t(\"../../lib\"),l=new Uint8Array(4),c=new Uint8Array(4),u={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*c,a.offset=2*l*n,e(a),l*n+c<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function m(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*a+l];63===l&&0===o&&(c*=-1),n[i++]=c}return n}function g(t){var e=\"0\"+t;return e.substr(e.length-2)}function v(t){return t<o?\"p\"+g(t+1)+\"_\"+g(t+4):\"colors\"}function 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e=Math.max(0,Math.floor(2047*t[0]),0),r=Math.min(2047,Math.ceil(2047*t[1]),2047);return[Math.min(e,r),Math.max(e,r)]}e.exports=function(t,e){var r,n,l,g,b,_=e.context,w=e.pick,T=e.regl,k=T._gl,A=k.getParameter(k.ALIASED_LINE_WIDTH_RANGE),M=Math.max(A[0],Math.min(A[1],e.viewModel.plotGlPixelRatio)),S={currentRafs:{},drawCompleted:!0,clearOnly:!1},E=function(t){for(var e={},r=0;r<=o;r+=4)e[v(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(T),L=T.texture(u),C=[];I(e);var P=T({profile:!1,blend:{enable:_,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src 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I(t){r=t.model,n=t.viewModel,l=n.dimensions.slice(),g=l[0]?l[0].values.length:0;var e=r.lines,i=w?e.color.map((function(t,r){return r/e.color.length})):e.color,a=function(t,e,r){for(var n,i=new Array(t*(o+4)),a=0,s=0;s<t;s++){for(var l=0;l<o;l++)i[a++]=l<e.length?e[l].paddedUnitValues[s]:.5;i[a++]=d(s,2),i[a++]=d(s,1),i[a++]=d(s,0),i[a++]=(n=r[s],Math.max(1e-6,Math.min(.999999,n)))}return i}(g,l,i);!function(t,e,r){for(var n=0;n<=o;n+=4)t[v(n)](m(n/4,e,r))}(E,g,a),_||w||(L=T.texture(s.extendFlat({data:p(r.unitToColor,255)},u)))}return{render:function(t,e,n){var i,a,o,s=t.length,c=1/0,u=-1/0;for(i=0;i<s;i++)t[i].dim0.canvasX<c&&(c=t[i].dim0.canvasX,a=i),t[i].dim1.canvasX>u&&(u=t[i].dim1.canvasX,o=i);0===s&&f(T,0,0,r.canvasWidth,r.canvasHeight);var p=function(t){var e,r,n,i=[[],[]];for(n=0;n<64;n++){var a=!t&&n<l.length?l[n].brush.filter.getBounds():[-1/0,1/0];i[0][n]=a[0],i[1][n]=a[1]}var o=new Array(16384);for(e=0;e<16384;e++)o[e]=255;if(!t)for(e=0;e<l.length;e++){var 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i=new Uint8Array(4*r*n);return T.read({x:t,y:e,width:r,height:n,data:i}),i},destroy:function(){for(var e in t.style[\"pointer-events\"]=\"none\",L.destroy(),b&&b.destroy(),E)E[e].destroy()},update:I}}},{\"../../lib\":503,\"./constants\":893,glslify:227}],898:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var i,a;for(n||(n=1/0),i=0;i<e.length;i++)(a=e[i]).visible&&(n=Math.min(n,a[r].length));for(n===1/0&&(n=0),t._length=n,i=0;i<e.length;i++)(a=e[i]).visible&&(a._length=n);return n}},{}],899:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=i.numberFormat,o=t(\"color-rgba\"),s=t(\"../../plots/cartesian/axes\"),l=i.strRotate,c=i.strTranslate,u=t(\"../../lib/svg_text_utils\"),f=t(\"../../components/drawing\"),h=t(\"../../components/colorscale\"),p=t(\"../../lib/gup\"),d=p.keyFun,m=p.repeat,g=p.unwrap,v=t(\"./helpers\"),y=t(\"./constants\"),x=t(\"./axisbrush\"),b=t(\"./lines\");function _(t,e,r){return i.aggNums(t,null,e,r)}function w(t,e){return k(_(Math.min,t,e),_(Math.max,t,e))}function T(t){var e=t.range;return e?k(e[0],e[1]):w(t.values,t._length)}function k(t,e){return!isNaN(t)&&isFinite(t)||(t=0),!isNaN(e)&&isFinite(e)||(e=0),t===e&&(0===t?(t-=1,e+=1):(t*=.9,e*=1.1)),[t,e]}function A(t,e,r,i,o){var s,l,c=T(r);return i?n.scale.ordinal().domain(i.map((s=a(r.tickformat),l=o,l?function(t,e){var r=l[e];return null==r?s(t):r}:s))).range(i.map((function(r){var n=(r-c[0])/(c[1]-c[0]);return t-e+n*(2*e-t)}))):n.scale.linear().domain(c).range([t-e,e])}function M(t){if(t.tickvals){var e=T(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map((function(t){return(t-e[0])/(e[1]-e[0])})))}}function S(t){var e=t.map((function(t){return t[0]})),r=t.map((function(t){var e=o(t[1]);return n.rgb(\"rgb(\"+e[0]+\",\"+e[1]+\",\"+e[2]+\")\")})),i=\"rgb\".split(\"\").map((function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((i=t,function(t){return t[i]})));var i}));return function(t){return i.map((function(e){return 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n=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,a=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../lib/extend\").extendFlat,u=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:c({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:c({},u,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:c({},u,{}),position:{valType:\"enumerated\",values:[\"top 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r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(c=new Array(h),r=0;r<h;r++)c[r]=String(e.label0+r*e.dlabel);var d={},m=s(o[\"_\"+e.type+\"colormap\"]),g=0,v=!1;for(r=0;r<h;r++){var y,x,b;if(p){if(y=f[r],!n(y))continue;y=+y}else y=1;void 0!==(x=c[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(g+=y),a.push({v:y,label:x,color:m(u[r],x),i:r,pts:[r],hidden:b})):(v=!0,(i=a[_]).v+=y,i.pts.push(r),i.hidden||(g+=y),!1===i.color&&u[r]&&(i.color=m(u[r],x)))}return a=a.filter((function(t){return t.v>=0})),(\"funnelarea\"===e.type?v:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=g),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var c=0,u=0;u<i.length;u++){var f=i[u];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[c%a.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{\"../../components/color\":366,\"fast-isnumeric\":190,tinycolor2:312}],904:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText;function l(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return i.coerce(t,e,a,r,n)}var u=l(c(\"labels\"),c(\"values\")),f=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),f){e._length=f,c(\"marker.line.width\")&&c(\"marker.line.color\"),c(\"marker.colors\"),c(\"scalegroup\");var h,p=c(\"text\"),d=c(\"texttemplate\");if(d||(h=c(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),d||h&&\"none\"!==h){var m=c(\"textposition\");s(t,e,n,c,m,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(m)||\"auto\"===m||\"outside\"===m)&&c(\"automargin\"),(\"inside\"===m||\"auto\"===m||Array.isArray(m))&&c(\"insidetextorientation\")}o(e,n,c);var g=c(\"hole\");if(c(\"title.text\")){var v=c(\"title.position\",g?\"middle center\":\"top center\");g||\"middle center\"!==v||(e.title.position=\"top center\"),i.coerceFont(c,\"title.font\",n.font)}c(\"sort\"),c(\"direction\"),c(\"rotation\"),c(\"pull\")}else e.visible=!1}}},{\"../../lib\":503,\"../../plots/domain\":584,\"../bar/defaults\":652,\"./attributes\":901,\"fast-isnumeric\":190}],905:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/helpers\").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},{\"../../components/fx/helpers\":402}],906:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}r.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0},r.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},{\"../../lib\":503}],907:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":901,\"./base_plot\":902,\"./calc\":903,\"./defaults\":904,\"./layout_attributes\":908,\"./layout_defaults\":909,\"./plot\":910,\"./style\":911,\"./style_one\":912}],908:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],909:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":503,\"./layout_attributes\":908}],910:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../plots/plots\"),a=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\"),c=l.strScale,u=l.strTranslate,f=t(\"../../lib/svg_text_utils\"),h=t(\"../bar/uniform_text\"),p=h.recordMinTextSize,d=h.clearMinTextSize,m=t(\"../bar/constants\").TEXTPAD,g=t(\"./helpers\"),v=t(\"./event_data\"),y=t(\"../../lib\").isValidTextValue;function x(t,e,r){var i=r[0],o=i.cx,s=i.cy,c=i.trace,u=\"funnelarea\"===c.type;\"_hasHoverLabel\"in c||(c._hasHoverLabel=!1),\"_hasHoverEvent\"in c||(c._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,f=e._fullData[c.index];if(!e._dragging&&!1!==r.hovermode){var h=f.hoverinfo;if(Array.isArray(h)&&(h=a.castHoverinfo({hoverinfo:[g.castOption(h,t.pts)],_module:c._module},r,0)),\"all\"===h&&(h=\"label+text+value+percent+name\"),f.hovertemplate||\"none\"!==h&&\"skip\"!==h&&h){var p=t.rInscribed||0,d=o+t.pxmid[0]*(1-p),m=s+t.pxmid[1]*(1-p),y=r.separators,x=[];if(h&&-1!==h.indexOf(\"label\")&&x.push(t.label),t.text=g.castOption(f.hovertext||f.text,t.pts),h&&-1!==h.indexOf(\"text\")){var b=t.text;l.isValidTextValue(b)&&x.push(b)}t.value=t.v,t.valueLabel=g.formatPieValue(t.v,y),h&&-1!==h.indexOf(\"value\")&&x.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=g.formatPiePercent(t.percent,y),h&&-1!==h.indexOf(\"percent\")&&x.push(t.percentLabel);var _=f.hoverlabel,w=_.font,T=[];a.loneHover({trace:c,x0:d-p*i.r,x1:d+p*i.r,y:m,_x0:u?o+t.TL[0]:d-p*i.r,_x1:u?o+t.TR[0]:d+p*i.r,_y0:u?s+t.TL[1]:m-p*i.r,_y1:u?s+t.BL[1]:m+p*i.r,text:x.join(\"<br>\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:g.castOption(_.bgcolor,t.pts)||t.color,borderColor:g.castOption(_.bordercolor,t.pts),fontFamily:g.castOption(w.family,t.pts),fontSize:g.castOption(w.size,t.pts),fontColor:g.castOption(w.color,t.pts),nameLength:g.castOption(_.namelength,t.pts),textAlign:g.castOption(_.align,t.pts),hovertemplate:g.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[v(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],c._hasHoverLabel=!0}c._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[v(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[c.index],o=n.select(this).datum();c._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[v(o,i)],event:n.event}),c._hasHoverEvent=!1),c._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),c._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[c.index];e._dragging||!1===r.hovermode||(e._hoverdata=[v(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),c=s.bBox(o.node(),!0);r.titleBox={width:c.width,height:c.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,c=e.midangle,u=r.trace.insidetextorientation,f=\"horizontal\"===u,h=\"tangential\"===u,p=\"radial\"===u,d=\"auto\"===u,m=[];if(!d){var g,v=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),c=s<l?s:l;(a=\"tan\"===i?k(t,n,o,c,0):T(t,n,o,c,Math.PI/2)).textPosAngle=r,m.push(a)}};if(f||h){for(g=4;g>=-4;g-=2)v(Math.PI*g,\"tan\");for(g=4;g>=-4;g-=2)v(Math.PI*(g+1),\"tan\")}if(f||p){for(g=4;g>=-4;g-=2)v(Math.PI*(g+1.5),\"rad\");for(g=4;g>=-4;g-=2)v(Math.PI*(g+.5),\"rad\")}}if(s||d||f){var y=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/y,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;m.push(a)}(d||p)&&((a=T(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,m.push(a)),(d||h)&&((a=k(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,m.push(a));for(var x=0,b=0,_=0;_<m.length;_++){var w=m[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return m[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*m);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:A(a,o/e),rotate:M(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*m);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:A(a,o/e),rotate:M(i+Math.PI/2)}}function A(t,e){return Math.cos(e)-t*e}function M(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=I(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),f=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(f+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?f*=2:-1!==a.title.position.indexOf(\"right\")&&(f+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=f/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function I(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function O(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=P(i,e));var c=s/2,u=l/2;\"funnelarea\"!==a.type||a.scalegroup||(u/=a.aspectratio),i.r=Math.min(c,u)/(1+I(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var c,u;i.aspectratio>1?(c=r.r,u=c/i.aspectratio):(u=r.r,c=u*i.aspectratio),c*=(1+i.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function z(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function D(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,c=o.split(\"+\"),u=function(t){return-1!==c.indexOf(t)},f=u(\"label\"),h=u(\"text\"),p=u(\"value\"),d=u(\"percent\"),m=n.separators;if(s=f?[e.label]:[],h){var v=g.getFirstFilled(i.text,e.pts);y(v)&&s.push(v)}p&&s.push(g.formatPieValue(e.v,m)),d&&s.push(g.formatPiePercent(e.v/r.vTotal,m)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(y(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,a=r._size;d(\"pie\",r),_(e,t),O(e,a);var h=l.makeTraceGroups(r._pielayer,e,\"trace\").each((function(e){var h=n.select(this),d=e[0],m=d.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=g.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,c=\"px0\",u=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c=\"px1\",u=\"px0\"}for(n=z(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=z(a,s),r.midangle=s,s+=l*r.v/2,n=z(a,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),h.attr(\"stroke-linejoin\",\"round\"),h.each((function(){var v=n.select(this).selectAll(\"g.slice\").data(e);v.enter().append(\"g\").classed(\"slice\",!0),v.exit().remove();var y=[[[],[]],[[],[]]],_=!1;v.each((function(i,a){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=m.index,y[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var o=d.cx,c=d.cy,u=n.select(this),h=u.selectAll(\"path.surface\").data([i]);if(h.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),u.call(x,t,e),m.pull){var v=+g.castOption(m.pull,i.pts)||0;v>0&&(o+=v*i.pxmid[0],c+=v*i.pxmid[1])}i.cxFinal=o,i.cyFinal=c;var T=m.hole;if(i.v===d.vTotal){var k=\"M\"+(o+i.px0[0])+\",\"+(c+i.px0[1])+C(i.px0,i.pxmid,!0,1)+C(i.pxmid,i.px0,!0,1)+\"Z\";T?h.attr(\"d\",\"M\"+(o+T*i.px0[0])+\",\"+(c+T*i.px0[1])+C(i.px0,i.pxmid,!1,T)+C(i.pxmid,i.px0,!1,T)+\"Z\"+k):h.attr(\"d\",k)}else{var A=C(i.px0,i.px1,!0,1);if(T){var M=1-T;h.attr(\"d\",\"M\"+(o+T*i.px1[0])+\",\"+(c+T*i.px1[1])+C(i.px1,i.px0,!1,T)+\"l\"+M*i.px0[0]+\",\"+M*i.px0[1]+A+\"Z\")}else h.attr(\"d\",\"M\"+o+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+A+\"Z\")}D(t,i,d);var S=g.castOption(m.textposition,i.pts),E=u.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==S?[0]:[]);E.enter().append(\"g\").classed(\"slicetext\",!0),E.exit().remove(),E.each((function(){var u=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===S?function(t,e,r){var n=g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,i=g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:i,size:a}}(m,i,r.font):b(m,i,r.font));u.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var v,y=s.bBox(u.node());if(\"outside\"===S)v=L(y,i);else if(v=w(y,i,d),\"auto\"===S&&v.scale<1){var x=l.ensureUniformFontSize(t,m.outsidetextfont);u.call(s.font,x),v=L(y=s.bBox(u.node()),i)}var T=v.textPosAngle,k=void 0===T?i.pxmid:z(d.r,T);if(v.targetX=o+k[0]*v.rCenter+(v.x||0),v.targetY=c+k[1]*v.rCenter+(v.y||0),R(v,y),v.outside){var A=v.targetY;i.yLabelMin=A-y.height/2,i.yLabelMid=A,i.yLabelMax=A+y.height/2,i.labelExtraX=0,i.labelExtraY=0,_=!0}v.fontSize=h.size,p(m.type,v,r),e[a].transform=v,u.attr(\"transform\",l.getTextTransform(v))}))}function C(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*d.r+\",\"+n*d.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var T=n.select(this).selectAll(\"g.titletext\").data(m.title.text?[0]:[]);if(T.enter().append(\"g\").classed(\"titletext\",!0),T.exit().remove(),T.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=m.title.text;m._meta&&(i=l.templateString(i,m._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,m.title.font).call(f.convertToTspans,t),e=\"middle center\"===m.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(d):C(d,a),r.attr(\"transform\",u(e.x,e.y)+c(Math.min(1,e.scale))+u(e.tx,e.ty))})),_&&function(t,e){var r,n,i,a,o,s,l,c,u,f,h,p,d;function m(t,e){return t.pxmid[1]-e.pxmid[1]}function v(t,e){return e.pxmid[1]-t.pxmid[1]}function y(t,r){r||(r={});var 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n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=i.numberFormat,o=t(\"./render\"),s=t(\"../../components/fx\"),l=t(\"../../components/color\"),c=t(\"./constants\").cn,u=i._;function f(t){return\"\"!==t}function h(t,e){return t.filter((function(t){return t.key===e.traceId}))}function p(t,e){n.select(t).select(\"path\").style(\"fill-opacity\",e),n.select(t).select(\"rect\").style(\"fill-opacity\",e)}function d(t){n.select(t).select(\"text.name\").style(\"fill\",\"black\")}function m(t){return function(e){return-1!==t.node.sourceLinks.indexOf(e.link)||-1!==t.node.targetLinks.indexOf(e.link)}}function g(t){return function(e){return-1!==e.node.sourceLinks.indexOf(t.link)||-1!==e.node.targetLinks.indexOf(t.link)}}function v(t,e,r){e&&r&&h(r,e).selectAll(\".\"+c.sankeyLink).filter(m(e)).call(x.bind(0,e,r,!1))}function y(t,e,r){e&&r&&h(r,e).selectAll(\".\"+c.sankeyLink).filter(m(e)).call(b.bind(0,e,r,!1))}function x(t,e,r,n){var i=n.datum().link.label;n.style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return.4})),i&&h(e,t).selectAll(\".\"+c.sankeyLink).filter((function(t){return t.link.label===i})).style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return.4})),r&&h(e,t).selectAll(\".\"+c.sankeyNode).filter(g(t)).call(v)}function b(t,e,r,n){var i=n.datum().link.label;n.style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),i&&h(e,t).selectAll(\".\"+c.sankeyLink).filter((function(t){return t.link.label===i})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),r&&h(e,t).selectAll(c.sankeyNode).filter(g(t)).call(y)}function _(t,e){var r=t.hoverlabel||{},n=i.nestedProperty(r,e).get();return!Array.isArray(n)&&n}e.exports=function(t,e){for(var r=t._fullLayout,i=r._paper,h=r._size,m=0;m<t._fullData.length;m++)if(t._fullData[m].visible&&t._fullData[m].type===c.sankey&&!t._fullData[m]._viewInitial){var g=t._fullData[m].node;t._fullData[m]._viewInitial={node:{groups:g.groups.slice(),x:g.x.slice(),y:g.y.slice()}}}var w=u(t,\"source:\")+\" \",T=u(t,\"target:\")+\" \",k=u(t,\"concentration:\")+\" \",A=u(t,\"incoming flow count:\")+\" \",M=u(t,\"outgoing flow count:\")+\" \";o(t,i,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{linkEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(x.bind(0,r,i,!0)),\"skip\"!==r.link.trace.link.hoverinfo&&(r.link.fullData=r.link.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.link]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.link.trace.link;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){for(var c=[],u=0,h=0;h<i.flow.links.length;h++){var m=i.flow.links[h];if(\"closest\"!==t._fullLayout.hovermode||i.link.pointNumber===m.pointNumber){i.link.pointNumber===m.pointNumber&&(u=h),m.fullData=m.trace,o=i.link.trace.link;var g=y(m),v={valueLabel:a(i.valueFormat)(m.value)+i.valueSuffix};c.push({x:g[0],y:g[1],name:v.valueLabel,text:[m.label||\"\",w+m.source.label,T+m.target.label,m.concentrationscale?k+a(\"%0.2f\")(m.flow.labelConcentration):\"\"].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||l.addOpacity(m.color,1),borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:n.event.x<g[0]?\"right\":\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:v,eventData:[m]})}}s.loneHover(c,{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t,anchorIndex:u}).each((function(){i.link.concentrationscale||p(this,.65),d(this)}))}}function y(t){var e,r;t.circular?(e=(t.circularPathData.leftInnerExtent+t.circularPathData.rightInnerExtent)/2,r=t.circularPathData.verticalFullExtent):(e=(t.source.x1+t.target.x0)/2,r=(t.y0+t.y1)/2);var n=[e,r];return\"v\"===t.trace.orientation&&n.reverse(),n[0]+=i.parent.translateX,n[1]+=i.parent.translateY,n}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(b.bind(0,i,a,!0)),\"skip\"!==i.link.trace.link.hoverinfo&&(i.link.fullData=i.link.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.link]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r){var i=r.link;i.originalEvent=n.event,t._hoverdata=[i],s.click(t,{target:!0})}},nodeEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(v,r,i),\"skip\"!==r.node.trace.node.hoverinfo&&(r.node.fullData=r.node.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.node]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.node.trace.node;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){var l=n.select(e).select(\".\"+c.nodeRect),u=t._fullLayout._paperdiv.node().getBoundingClientRect(),h=l.node().getBoundingClientRect(),m=h.left-2-u.left,g=h.right+2-u.left,v=h.top+h.height/4-u.top,y={valueLabel:a(i.valueFormat)(i.node.value)+i.valueSuffix};i.node.fullData=i.node.trace,t._fullLayout._calcInverseTransform(t);var x=t._fullLayout._invScaleX,b=t._fullLayout._invScaleY,w=s.loneHover({x0:x*m,x1:x*g,y:b*v,name:a(i.valueFormat)(i.node.value)+i.valueSuffix,text:[i.node.label,A+i.node.targetLinks.length,M+i.node.sourceLinks.length].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||i.tinyColorHue,borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:y,eventData:[i.node]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t});p(w,.85),d(w)}}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(y,i,a),\"skip\"!==i.node.trace.node.hoverinfo&&(i.node.fullData=i.node.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.node]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r,i){var a=r.node;a.originalEvent=n.event,t._hoverdata=[a],n.select(e).call(y,r,i),s.click(t,{target:!0})}}})}},{\"../../components/color\":366,\"../../components/fx\":406,\"../../lib\":503,\"./constants\":920,\"./render\":924,\"@plotly/d3\":58}],924:[function(t,e,r){\"use strict\";var n=t(\"d3-force\"),i=t(\"d3-interpolate\").interpolateNumber,a=t(\"@plotly/d3\"),o=t(\"@plotly/d3-sankey\"),s=t(\"@plotly/d3-sankey-circular\"),l=t(\"./constants\"),c=t(\"tinycolor2\"),u=t(\"../../components/color\"),f=t(\"../../components/drawing\"),h=t(\"../../lib\"),p=h.strTranslate,d=h.strRotate,m=t(\"../../lib/gup\"),g=m.keyFun,v=m.repeat,y=m.unwrap,x=t(\"../../lib/svg_text_utils\"),b=t(\"../../registry\"),_=t(\"../../constants/alignment\"),w=_.CAP_SHIFT,T=_.LINE_SPACING;function k(t,e,r){var n,i=y(e),a=i.trace,u=a.domain,f=\"h\"===a.orientation,p=a.node.pad,d=a.node.thickness,m=t.width*(u.x[1]-u.x[0]),g=t.height*(u.y[1]-u.y[0]),v=i._nodes,x=i._links,b=i.circular;(n=b?s.sankeyCircular().circularLinkGap(0):o.sankey()).iterations(l.sankeyIterations).size(f?[m,g]:[g,m]).nodeWidth(d).nodePadding(p).nodeId((function(t){return t.pointNumber})).nodes(v).links(x);var _,w,T,k=n();for(var A in n.nodePadding()<p&&h.warn(\"node.pad was reduced to \",n.nodePadding(),\" to fit within the figure.\"),i._groupLookup){var M,S=parseInt(i._groupLookup[A]);for(_=0;_<k.nodes.length;_++)if(k.nodes[_].pointNumber===S){M=k.nodes[_];break}if(M){var E={pointNumber:parseInt(A),x0:M.x0,x1:M.x1,y0:M.y0,y1:M.y1,partOfGroup:!0,sourceLinks:[],targetLinks:[]};k.nodes.unshift(E),M.childrenNodes.unshift(E)}}if(function(){for(_=0;_<k.nodes.length;_++){var t,e,r=k.nodes[_],n={};for(w=0;w<r.targetLinks.length;w++)t=(e=r.targetLinks[w]).source.pointNumber+\":\"+e.target.pointNumber,n.hasOwnProperty(t)||(n[t]=[]),n[t].push(e);var i=Object.keys(n);for(w=0;w<i.length;w++){var a=n[t=i[w]],o=0,s={};for(T=0;T<a.length;T++)s[(e=a[T]).label]||(s[e.label]=0),s[e.label]+=e.value,o+=e.value;for(T=0;T<a.length;T++)(e=a[T]).flow={value:o,labelConcentration:s[e.label]/o,concentration:e.value/o,links:a},e.concentrationscale&&(e.color=c(e.concentrationscale(e.flow.labelConcentration)))}var l=0;for(w=0;w<r.sourceLinks.length;w++)l+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/l;var u=0;for(w=0;w<r.targetLinks.length;w++)u+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/u}}(),a.node.x.length&&a.node.y.length){for(_=0;_<Math.min(a.node.x.length,a.node.y.length,k.nodes.length);_++)if(a.node.x[_]&&a.node.y[_]){var L=[a.node.x[_]*m,a.node.y[_]*g];k.nodes[_].x0=L[0]-d/2,k.nodes[_].x1=L[0]+d/2;var C=k.nodes[_].y1-k.nodes[_].y0;k.nodes[_].y0=L[1]-C/2,k.nodes[_].y1=L[1]+C/2}if(\"snap\"===a.arrangement)!function(t){t.forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return t.y0-e.y0})),n=0;n<a;++n)(e=t[n]).y0>=i||(r=i-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),i=e.y1+p}))}(function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return i}(v=k.nodes));n.update(k)}return{circular:b,key:r,trace:a,guid:h.randstr(),horizontal:f,width:m,height:g,nodePad:a.node.pad,nodeLineColor:a.node.line.color,nodeLineWidth:a.node.line.width,linkLineColor:a.link.line.color,linkLineWidth:a.link.line.width,valueFormat:a.valueformat,valueSuffix:a.valuesuffix,textFont:a.textfont,translateX:u.x[0]*t.width+t.margin.l,translateY:t.height-u.y[1]*t.height+t.margin.t,dragParallel:f?g:m,dragPerpendicular:f?m:g,arrangement:a.arrangement,sankey:n,graph:k,forceLayouts:{},interactionState:{dragInProgress:!1,hovered:!1}}}function A(t,e,r){var n=c(e.color),i=e.source.label+\"|\"+e.target.label+\"__\"+r;return e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:u.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:M,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function M(){return function(t){if(t.link.circular)return e=t.link,r=e.width/2,n=e.circularPathData,\"top\"===e.circularLinkType?\"M \"+n.targetX+\" \"+(n.targetY+r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 0 \"+n.rightInnerExtent+\" \"+(n.targetY-r)+\"L\"+n.targetX+\" \"+(n.targetY-r)+\"Z\":\"M \"+n.targetX+\" \"+(n.targetY-r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY-r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 0 \"+(n.rightFullExtent-r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 0 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 0 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"L\"+n.targetX+\" \"+(n.targetY+r)+\"Z\";var e,r,n,a=t.link.source.x1,o=t.link.target.x0,s=i(a,o),l=s(.5),c=s(.5),u=t.link.y0-t.link.width/2,f=t.link.y0+t.link.width/2,h=t.link.y1-t.link.width/2,p=t.link.y1+t.link.width/2;return\"M\"+a+\",\"+u+\"C\"+l+\",\"+u+\" \"+c+\",\"+h+\" 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e.group&&(s=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:s,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:u.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,s].join(\"_\"),interactionState:t.interactionState,figure:t}}function E(t){t.attr(\"transform\",(function(t){return p(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function L(t){t.call(E)}function 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g=\"projection.\"+d[m];f(g+\".show\")&&(f(g+\".opacity\"),f(g+\".scale\"))}var v=n.getComponentMethod(\"errorbars\",\"supplyDefaults\");v(t,e,h||p||r,{axis:\"z\"}),v(t,e,h||p||r,{axis:\"y\",inherit:\"z\"}),v(t,e,h||p||r,{axis:\"x\",inherit:\"z\"})}else e.visible=!1}},{\"../../lib\":503,\"../../registry\":638,\"../scatter/line_defaults\":940,\"../scatter/marker_defaults\":946,\"../scatter/subtypes\":952,\"../scatter/text_defaults\":953,\"./attributes\":955}],960:[function(t,e,r){\"use 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n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/template_attributes\").texttemplateAttrs,s=t(\"../../components/colorscale/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=n.marker,u=n.line,f=c.line;e.exports={carpet:{valType:\"string\",editType:\"calc\"},a:{valType:\"data_array\",editType:\"calc\"},b:{valType:\"data_array\",editType:\"calc\"},mode:l({},n.mode,{dflt:\"markers\"}),text:l({},n.text,{}),texttemplate:o({editType:\"plot\"},{keys:[\"a\",\"b\",\"text\"]}),hovertext:l({},n.hovertext,{}),line:{color:u.color,width:u.width,dash:u.dash,shape:l({},u.shape,{values:[\"linear\",\"spline\"]}),smoothing:u.smoothing,editType:\"calc\"},connectgaps:n.connectgaps,fill:l({},n.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:n.fillcolor,marker:l({symbol:c.symbol,opacity:c.opacity,maxdisplayed:c.maxdisplayed,size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,line:l({width:f.width,editType:\"calc\"},s(\"marker.line\")),gradient:c.gradient,editType:\"calc\"},s(\"marker\")),textfont:n.textfont,textposition:n.textposition,selected:n.selected,unselected:n.unselected,hoverinfo:l({},i.hoverinfo,{flags:[\"a\",\"b\",\"text\",\"name\"]}),hoveron:n.hoveron,hovertemplate:a()}},{\"../../components/colorscale/attributes\":373,\"../../lib/extend\":493,\"../../plots/attributes\":550,\"../../plots/template_attributes\":633,\"../scatter/attributes\":927}],962:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),m=p(\"b\"),g=Math.min(d.length,m.length);if(g){e._length=g,p(\"text\"),p(\"texttemplate\"),p(\"hovertext\"),p(\"mode\",g<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(s(t,e,r,h,p),l(t,e,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,p,{gradient:!0}),a.hasText(e)&&c(t,e,h,p);var v=[];(a.hasMarkers(e)||a.hasText(e))&&(p(\"marker.maxdisplayed\"),v.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),a.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),\"fills\"!==p(\"hoveron\",v.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":503,\"../scatter/constants\":931,\"../scatter/fillcolor_defaults\":935,\"../scatter/line_defaults\":940,\"../scatter/line_shape_defaults\":942,\"../scatter/marker_defaults\":946,\"../scatter/subtypes\":952,\"../scatter/text_defaults\":953,\"./attributes\":961}],964:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){var a=n[i];return t.a=a.a,t.b=a.b,t.y=a.y,t}},{}],965:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r={},n=e._carpet,i=n.ab2ij([t.a,t.b]),a=Math.floor(i[0]),o=i[0]-a,s=Math.floor(i[1]),l=i[1]-s,c=n.evalxy([],a,s,o,l);return r.yLabel=c[1].toFixed(3),r}},{}],966:[function(t,e,r){\"use strict\";var n=t(\"../scatter/hover\"),i=t(\"../../lib\").fillText;e.exports=function(t,e,r,a){var o=n(t,e,r,a);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index){var l=1-s.y0/t.ya._length,c=t.xa._length,u=c*l/2,f=c-u;return s.x0=Math.max(Math.min(s.x0,f),u),s.x1=Math.max(Math.min(s.x1,f),u),o}var h=s.cd[s.index];s.a=h.a,s.b=h.b,s.xLabelVal=void 0,s.yLabelVal=void 0;var p=s.trace,d=p._carpet,m=p._module.formatLabels(h,p);s.yLabel=m.yLabel,delete s.text;var g=[];if(!p.hovertemplate){var v=(h.hi||p.hoverinfo).split(\"+\");-1!==v.indexOf(\"all\")&&(v=[\"a\",\"b\",\"text\"]),-1!==v.indexOf(\"a\")&&y(d.aaxis,h.a),-1!==v.indexOf(\"b\")&&y(d.baxis,h.b),g.push(\"y: \"+s.yLabel),-1!==v.indexOf(\"text\")&&i(h,p,g),s.extraText=g.join(\"<br>\")}return o}function y(t,e){var r;r=t.labelprefix&&t.labelprefix.length>0?t.labelprefix.replace(/ = $/,\"\"):t._hovertitle,g.push(r+\": \"+e.toFixed(3)+t.labelsuffix)}}},{\"../../lib\":503,\"../scatter/hover\":938}],967:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,i){return n.coerce(t,e,c,r,i)}var h,p=f(\"locations\");if(p&&p.length){var d,m=f(\"geojson\");(\"string\"==typeof m&&\"\"!==m||n.isPlainObject(m))&&(d=\"geojson-id\"),\"geojson-id\"===f(\"locationmode\",d)&&f(\"featureidkey\"),h=p.length}else{var 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M=p.font[r]={};M.size=(s.isTypedArray(f)?f[r]:Array.isArray(f)?n(f[r])?f[r]:0:f)*d,M.family=Array.isArray(h)?h[r]:h}else p.font={size:f*d,family:h};return p}function x(t){var e,r,n=t._length,i=t.marker,o={},l=s.isArrayOrTypedArray(i.symbol),c=s.isArrayOrTypedArray(i.color),f=s.isArrayOrTypedArray(i.line.color),d=s.isArrayOrTypedArray(i.opacity),m=s.isArrayOrTypedArray(i.size),g=s.isArrayOrTypedArray(i.line.width);if(l||(r=p.isOpenSymbol(i.symbol)),l||c||f||d){o.colors=new Array(n),o.borderColors=new Array(n);var v=u(i,i.opacity,n),y=u(i.line,i.opacity,n);if(!Array.isArray(y[0])){var x=y;for(y=Array(n),e=0;e<n;e++)y[e]=x}if(!Array.isArray(v[0])){var b=v;for(v=Array(n),e=0;e<n;e++)v[e]=b}for(o.colors=v,o.borderColors=y,e=0;e<n;e++){if(l){var _=i.symbol[e];r=p.isOpenSymbol(_)}r&&(y[e]=v[e].slice(),v[e]=v[e].slice(),v[e][3]=0)}o.opacity=t.opacity}else 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i={opacity:1,text:e.text,texttemplate:e.texttemplate,textposition:e.textposition,textfont:s.extendFlat({},e.textfont)};r.textfont&&s.extendFlat(i.textfont,r.textfont),n=y(t,i)}return n}function w(t,e,r){var n={capSize:2*e.width*r,lineWidth:e.thickness*r,color:e.color};return e.copy_ystyle&&(n=t.error_y),n}var T=d.SYMBOL_SDF_SIZE,k=d.SYMBOL_SIZE,A=d.SYMBOL_STROKE,M={},S=l.symbolFuncs[0](.05*k);function E(t){if(\"circle\"===t)return null;var e,r,n=l.symbolNumber(t),a=l.symbolFuncs[n%100],o=!!l.symbolNoDot[n%100],s=!!l.symbolNoFill[n%100],c=p.isDotSymbol(t);return M[t]?M[t]:(e=c&&!o?a(1.1*k)+S:a(k),r=i(e,{w:T,h:T,viewBox:[-k,-k,k,k],stroke:s?A:-A}),M[t]=r,r||null)}e.exports={style:function(t,e){var r,n={marker:void 0,markerSel:void 0,markerUnsel:void 0,line:void 0,fill:void 0,errorX:void 0,errorY:void 0,text:void 0,textSel:void 0,textUnsel:void 0},i=t._context.plotGlPixelRatio;if(!0!==e.visible)return 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T=y-_,k=y+w;p[v+u[0]]=x-i.c2l(T),p[v+u[1]]=i.c2l(k)-x,p[v+u[2]]=0,p[v+u[3]]=0,d=Math.min(d,y-_),m=Math.max(m,y+w)}}}h[a]={positions:r,errors:p,_bnds:[d,m]}}}return p(i,l),p(a,u),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(f.hasMarkers(e)){var s=r.font,l=r.align,c=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var u=n.sizes?n.sizes[i]:n.size,h=Array.isArray(s)?s[i].size:s.size,p=Array.isArray(l)?l.length>1?l[i]:l[0]:l,d=Array.isArray(c)?c.length>1?c[i]:c[0]:c,m=g[p],v=g[d],y=u?u/.8+1:0,x=-v*y-.5*v;o.offset[i]=[m*y/h,x/h]}}return o}}},{\"../../components/drawing\":388,\"../../components/fx/helpers\":402,\"../../constants/interactions\":478,\"../../lib\":503,\"../../lib/gl_format_color\":499,\"../../plots/cartesian/axis_ids\":558,\"../../registry\":638,\"../scatter/make_bubble_size_func\":944,\"../scatter/subtypes\":952,\"./constants\":982,\"./helpers\":987,\"color-normalize\":89,\"fast-isnumeric\":190,\"svg-path-sdf\":310}],984:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../registry\"),a=t(\"./helpers\"),o=t(\"./attributes\"),s=t(\"../scatter/constants\"),l=t(\"../scatter/subtypes\"),c=t(\"../scatter/xy_defaults\"),u=t(\"../scatter/period_defaults\"),f=t(\"../scatter/marker_defaults\"),h=t(\"../scatter/line_defaults\"),p=t(\"../scatter/fillcolor_defaults\"),d=t(\"../scatter/text_defaults\");e.exports=function(t,e,r,m){function g(r,i){return n.coerce(t,e,o,r,i)}var v=!!t.marker&&a.isOpenSymbol(t.marker.symbol),y=l.isBubble(t),x=c(t,e,m,g);if(x){u(t,e,m,g),g(\"xhoverformat\"),g(\"yhoverformat\");var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";g(\"text\"),g(\"hovertext\"),g(\"hovertemplate\"),g(\"mode\",b),l.hasLines(e)&&(g(\"connectgaps\"),h(t,e,r,m,g),g(\"line.shape\")),l.hasMarkers(e)&&(f(t,e,r,m,g),g(\"marker.line.width\",v||y?1:0)),l.hasText(e)&&(g(\"texttemplate\"),d(t,e,m,g));var _=(e.line||{}).color,w=(e.marker||{}).color;g(\"fill\"),\"none\"!==e.fill&&p(t,e,r,g);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,g)}else e.visible=!1}},{\"../../lib\":503,\"../../registry\":638,\"../scatter/constants\":931,\"../scatter/fillcolor_defaults\":935,\"../scatter/line_defaults\":940,\"../scatter/marker_defaults\":946,\"../scatter/period_defaults\":947,\"../scatter/subtypes\":952,\"../scatter/text_defaults\":953,\"../scatter/xy_defaults\":954,\"./attributes\":979,\"./helpers\":987}],985:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../constants/interactions\").DESELECTDIM;e.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,c=l._scene,u=l.index,f=c.selectBatch[u],h=c.unselectBatch[u],p=c.textOptions[u],d=c.textSelectedOptions[u]||{},m=c.textUnselectedOptions[u]||{},g=n.extendFlat({},p);if(f.length||h.length){var v=d.color,y=m.color,x=p.color,b=Array.isArray(x);for(g.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],g.color[r]=v||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;g.color[r]=y||(v?_:i.addOpacity(_,a))}}c.glText[u].update(g)}}},{\"../../components/color\":366,\"../../constants/interactions\":478,\"../../lib\":503}],986:[function(t,e,r){\"use strict\";var n=t(\"../scatter/format_labels\");e.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},{\"../scatter/format_labels\":936}],987:[function(t,e,r){\"use strict\";var n=t(\"./constants\");r.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},r.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},{\"./constants\":982}],988:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/get_trace_color\");function o(t,e,r,o){var s=t.xa,l=t.ya,c=t.distance,u=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var m=d&&d.line;m&&(h.mlc=Array.isArray(m.color)?m.color[f]:m.color,h.mlw=i.isArrayOrTypedArray(m.width)?m.width[f]:m.width);var g=d&&d.gradient;g&&\"none\"!==g.type&&(h.mgt=Array.isArray(g.type)?g.type[f]:g.type,h.mgc=Array.isArray(g.color)?g.color[f]:g.color);var v=s.c2p(h.x,!0),y=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,A=o._origY,M=i.extendFlat({},t,{color:a(o,h),x0:v-x,x1:v+x,xLabelVal:k?k[f]:h.x,y0:y-x,y1:y+x,yLabelVal:A?A[f]:h.y,cd:T,distance:c,spikeDistance:u,hovertemplate:h.ht});return h.htx?M.text=h.htx:h.tx?M.text=h.tx:o.text&&(M.text=o.text),i.fillText(h,o,M),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,M),M}e.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,c,u,f,h,p,d,m=t.cd,g=m[0].t,v=m[0].trace,y=t.xa,x=t.ya,b=g.x,_=g.y,w=y.c2p(e),T=x.c2p(r),k=t.distance;if(g.tree){var A=y.p2c(w-k),M=y.p2c(w+k),S=x.p2c(T-k),E=x.p2c(T+k);i=\"x\"===n?g.tree.range(Math.min(A,M),Math.min(x._rl[0],x._rl[1]),Math.max(A,M),Math.max(x._rl[0],x._rl[1])):g.tree.range(Math.min(A,M),Math.min(S,E),Math.max(A,M),Math.max(S,E))}else i=g.ids;var L=k;if(\"x\"===n){var C=!!v.xperiodalignment,P=!!v.yperiodalignment;for(u=0;u<i.length;u++){if(l=b[a=i[u]],f=Math.abs(y.c2p(l)-w),C){var I=y.c2p(v._xStarts[a]),O=y.c2p(v._xEnds[a]);f=w>=Math.min(I,O)&&w<=Math.max(I,O)?0:1/0}if(f<L){if(L=f,c=_[a],h=x.c2p(c)-T,P){var z=x.c2p(v._yStarts[a]),D=x.c2p(v._yEnds[a]);h=T>=Math.min(z,D)&&T<=Math.max(z,D)?0:1/0}d=Math.sqrt(f*f+h*h),s=i[u]}}}else for(u=i.length-1;u>-1;u--)l=b[a=i[u]],c=_[a],f=y.c2p(l)-w,h=x.c2p(c)-T,(p=Math.sqrt(f*f+h*h))<L&&(L=d=p,s=a);return t.index=s,t.distance=L,t.dxy=d,void 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_=y.count,w=v._glcanvas.data()[0].regl;if(f(t,e,r),y.dirty){if(!0===y.error2d&&(y.error2d=a(w)),!0===y.line2d&&(y.line2d=i(w)),!0===y.scatter2d&&(y.scatter2d=n(w)),!0===y.fill2d&&(y.fill2d=i(w)),!0===y.glText)for(y.glText=new Array(_),m=0;m<_;m++)y.glText[m]=new o(w);if(y.glText){if(_>y.glText.length){var T=_-y.glText.length;for(m=0;m<T;m++)y.glText.push(new o(w))}else if(_<y.glText.length){var k=y.glText.length-_;y.glText.splice(_,k).forEach((function(t){t.destroy()}))}for(m=0;m<_;m++)y.glText[m].update(y.textOptions[m])}if(y.line2d&&(y.line2d.update(y.lineOptions),y.lineOptions=y.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),y.line2d.update(y.lineOptions)),y.error2d){var A=(y.errorXOptions||[]).concat(y.errorYOptions||[]);y.error2d.update(A)}y.scatter2d&&y.scatter2d.update(y.markerOptions),y.fillOrder=s.repeat(null,_),y.fill2d&&(y.fillOptions=y.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,c=y.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(y.fillOrder[e]=u);var f,h,p=[],d=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else 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R=y.selectBatch[I]=s.selIndices2selPoints(C),F={};for(g=0;g<R.length;g++)F[R[g]]=1;var B=[];for(g=0;g<O;g++)F[g]||B.push(g);y.unselectBatch[I]=B}var N=P.xpx=new Array(O),j=P.ypx=new Array(O);for(g=0;g<O;g++)N[g]=x.c2p(z[g]),j[g]=b.c2p(D[g])}else P.xpx=P.ypx=null}if(S){if(y.select2d||(y.select2d=n(v._glcanvas.data()[1].regl)),y.scatter2d){var U=new Array(_);for(m=0;m<_;m++)U[m]=y.selectBatch[m].length||y.unselectBatch[m].length?y.markerUnselectedOptions[m]:{};y.scatter2d.update(U)}y.select2d&&(y.select2d.update(y.markerOptions),y.select2d.update(y.markerSelectedOptions)),y.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};u.hasText(e)&&h(t)}))}else y.scatter2d&&y.scatter2d.update(y.markerOptions);var V={viewport:d(v,x,b,t._context.plotGlPixelRatio),range:[(x._rl||x.range)[0],(b._rl||b.range)[0],(x._rl||x.range)[1],(b._rl||b.range)[1]]},H=s.repeat(V,y.count);y.fill2d&&y.fill2d.update(H),y.line2d&&y.line2d.update(H),y.error2d&&y.error2d.update(H.concat(H)),y.scatter2d&&y.scatter2d.update(H),y.select2d&&y.select2d.update(H),y.glText&&y.glText.forEach((function(t){t.update(V)}))}else y.init()}}).reglPrecompiled=p},{\"../../components/dragelement/helpers\":384,\"../../lib\":503,\"../../lib/prepare_regl\":516,\"../scatter/link_traces\":943,\"../scatter/subtypes\":952,\"./edit_style\":985,\"gl-text\":225,\"regl-error2d\":279,\"regl-line2d\":280,\"regl-scatter2d\":281}],991:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(u[f].length){var h=n.repeat([],r.count);h[f]=u[f],o.draw(h)}else c[f].length||o.draw(f);s[f]&&r.textOptions[f]&&s[f].render()}l&&l.draw(c),r.dirty=!1},r.destroy=function(){r.fill2d&&r.fill2d.destroy&&r.fill2d.destroy(),r.scatter2d&&r.scatter2d.destroy&&r.scatter2d.destroy(),r.error2d&&r.error2d.destroy&&r.error2d.destroy(),r.line2d&&r.line2d.destroy&&r.line2d.destroy(),r.select2d&&r.select2d.destroy&&r.select2d.destroy(),r.glText&&r.glText.forEach((function(t){t.destroy&&t.destroy()})),r.lineOptions=null,r.fillOptions=null,r.markerOptions=null,r.markerSelectedOptions=null,r.markerUnselectedOptions=null,r.errorXOptions=null,r.errorYOptions=null,r.textOptions=null,r.textSelectedOptions=null,r.textUnselectedOptions=null,r.selectBatch=null,r.unselectBatch=null,e._scene=null}),r.dirty||n.extendFlat(r,i),r}},{\"../../lib\":503}],992:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),i=t(\"./edit_style\").styleTextSelection;e.exports=function(t,e){var r=t.cd,a=t.xaxis,o=t.yaxis,s=[],l=r[0].trace,c=r[0].t,u=l._length,f=c.x,h=c.y,p=c._scene,d=c.index;if(!p)return s;var m=n.hasText(l),g=n.hasMarkers(l),v=!g&&!m;if(!0!==l.visible||v)return s;var y=[],x=[];if(!1!==e&&!e.degenerate)for(var b=0;b<u;b++)e.contains([c.xpx[b],c.ypx[b]],!1,b,t)?(y.push(b),s.push({pointNumber:b,x:a.c2d(f[b]),y:o.c2d(h[b])})):x.push(b);if(g){var _=p.scatter2d;if(y.length||x.length){if(!p.selectBatch[d].length&&!p.unselectBatch[d].length){var w=new Array(p.count);w[d]=p.markerUnselectedOptions[d],_.update.apply(_,w)}}else{var T=new Array(p.count);T[d]=p.markerOptions[d],_.update.apply(_,T)}}return p.selectBatch[d]=y,p.unselectBatch[d]=x,m&&i(r),s}},{\"../scatter/subtypes\":952,\"./edit_style\":985}],993:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scattergeo/attributes\"),o=t(\"../scatter/attributes\"),s=t(\"../../plots/mapbox/layout_attributes\"),l=t(\"../../plots/attributes\"),c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat,f=t(\"../../plot_api/edit_types\").overrideAll,h=a.line,p=a.marker;e.exports=f({lon:a.lon,lat:a.lat,mode:u({},o.mode,{dflt:\"markers\"}),text:u({},o.text,{}),texttemplate:i({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:u({},o.hovertext,{}),line:{color:h.color,width:h.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},angle:{valType:\"number\",dflt:\"auto\",arrayOk:!0},allowoverlap:{valType:\"boolean\",dflt:!1},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c(\"marker\")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":373,\"../../lib/extend\":493,\"../../plot_api/edit_types\":536,\"../../plots/attributes\":550,\"../../plots/mapbox/layout_attributes\":615,\"../../plots/template_attributes\":633,\"../scatter/attributes\":927,\"../scattergeo/attributes\":969}],994:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../constants/numerical\").BADNUM,o=t(\"../../lib/geojson_utils\"),s=t(\"../../components/colorscale\"),l=t(\"../../components/drawing\"),c=t(\"../scatter/make_bubble_size_func\"),u=t(\"../scatter/subtypes\"),f=t(\"../../plots/mapbox/convert_text_opts\"),h=t(\"../../components/fx/helpers\").appendArrayPointValue,p=t(\"../../lib/svg_text_utils\").NEWLINES,d=t(\"../../lib/svg_text_utils\").BR_TAG_ALL;function m(){return{geojson:o.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function g(t,e){return i.isArrayOrTypedArray(t)?e?function(e){return n(t[e])?+t[e]:0}:function(e){return t[e]}:t?function(){return t}:v}function v(){return\"\"}function y(t){return t[0]===a}e.exports=function(t,e){var r,a=e[0].trace,x=!0===a.visible&&0!==a._length,b=\"none\"!==a.fill,_=u.hasLines(a),w=u.hasMarkers(a),T=u.hasText(a),k=w&&\"circle\"===a.marker.symbol,A=w&&\"circle\"!==a.marker.symbol,M=m(),S=m(),E=m(),L=m(),C={fill:M,line:S,circle:E,symbol:L};if(!x)return C;if((b||_)&&(r=o.calcTraceToLineCoords(e)),b&&(M.geojson=o.makePolygon(r),M.layout.visibility=\"visible\",i.extendFlat(M.paint,{\"fill-color\":a.fillcolor})),_&&(S.geojson=o.makeLine(r),S.layout.visibility=\"visible\",i.extendFlat(S.paint,{\"line-width\":a.line.width,\"line-color\":a.line.color,\"line-opacity\":a.opacity})),k){var P=function(t){var e,r,a,o,u=t[0].trace,f=u.marker,h=u.selectedpoints,p=i.isArrayOrTypedArray(f.color),d=i.isArrayOrTypedArray(f.size),m=i.isArrayOrTypedArray(f.opacity);function g(t){return u.opacity*t}p&&(r=s.hasColorscale(u,\"marker\")?s.makeColorScaleFuncFromTrace(f):i.identity);d&&(a=c(u));m&&(o=function(t){return g(n(t)?+i.constrain(t,0,1):0)});var v,x=[];for(e=0;e<t.length;e++){var 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n=t(\"../scatterpolar/attributes\"),i=t(\"../scattergl/attributes\"),a=t(\"../../plots/template_attributes\").texttemplateAttrs;e.exports={mode:n.mode,r:n.r,theta:n.theta,r0:n.r0,dr:n.dr,theta0:n.theta0,dtheta:n.dtheta,thetaunit:n.thetaunit,text:n.text,texttemplate:a({editType:\"plot\"},{keys:[\"r\",\"theta\",\"text\"]}),hovertext:n.hovertext,hovertemplate:n.hovertemplate,line:i.line,connectgaps:i.connectgaps,marker:i.marker,fill:i.fill,fillcolor:i.fillcolor,textposition:i.textposition,textfont:i.textfont,hoverinfo:n.hoverinfo,selected:n.selected,unselected:n.unselected}},{\"../../plots/template_attributes\":633,\"../scattergl/attributes\":979,\"../scatterpolar/attributes\":1002}],1010:[function(t,e,r){\"use 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A={};u.label&&(A.label=u.label),u.hasOwnProperty(\"v\")&&(A.value=u.v,A.valueLabel=b.formatValue(u.v,l)),A.currentPath=b.getPath(t.data),h||(A.percentParent=d/b.getValue(p),A.percentParentLabel=b.formatPercent(A.percentParent,l),A.parent=b.getPtLabel(p)),A.percentEntry=d/b.getValue(e),A.percentEntryLabel=b.formatPercent(A.percentEntry,l),A.entry=b.getPtLabel(e),A.percentRoot=d/b.getValue(f),A.percentRootLabel=b.formatPercent(A.percentRoot,l),A.root=b.getPtLabel(f),u.hasOwnProperty(\"color\")&&(A.color=u.color);var M=s.castOption(r,u.i,\"text\");return(s.isValidTextValue(M)||\"\"===M)&&(A.text=M),A.customdata=s.castOption(r,u.i,\"customdata\"),s.texttemplateString(k,A,i._d3locale,A,r._meta||{})}},{\"../../components/drawing\":388,\"../../lib\":503,\"../../lib/svg_text_utils\":529,\"../bar/style\":662,\"../bar/uniform_text\":664,\"../pie/helpers\":906,\"../pie/plot\":910,\"./constants\":1052,\"./fx\":1054,\"./helpers\":1055,\"./style\":1060,\"@plotly/d3\":58,\"d3-hierarchy\":115,\"d3-interpolate\":116}],1060:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../components/color\"),a=t(\"../../lib\"),o=t(\"../bar/uniform_text\").resizeText;function s(t,e,r){var n=e.data.data,o=!e.children,s=n.i,l=a.castOption(r,s,\"marker.line.color\")||i.defaultLine,c=a.castOption(r,s,\"marker.line.width\")||0;t.style(\"stroke-width\",c).call(i.fill,n.color).call(i.stroke,l).style(\"opacity\",o?r.leaf.opacity:null)}e.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(\".trace\");o(t,e,\"sunburst\"),e.each((function(t){var e=n.select(this),r=t[0].trace;e.style(\"opacity\",r.opacity),e.selectAll(\"path.surface\").each((function(t){n.select(this).call(s,t,r)}))}))},styleOne:s}},{\"../../components/color\":366,\"../../lib\":503,\"../bar/uniform_text\":664,\"@plotly/d3\":58}],1061:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll;function u(t){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:{valType:\"boolean\",dflt:!1},y:{valType:\"boolean\",dflt:!1},z:{valType:\"boolean\",dflt:!1}},color:{valType:\"color\",dflt:n.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:n.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var f=e.exports=c(l({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:o(),xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),zhoverformat:a(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:u(),y:u(),z:u()},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},opacityscale:{valType:\"any\",editType:\"calc\"},_deprecated:{zauto:l({},i.zauto,{}),zmin:l({},i.zmin,{}),zmax:l({},i.zmax,{})},hoverinfo:l({},s.hoverinfo),showlegend:l({},s.showlegend,{dflt:!1})}),\"calc\",\"nested\");f.x.editType=f.y.editType=f.z.editType=\"calc+clearAxisTypes\",f.transforms=void 0},{\"../../components/color\":366,\"../../components/colorscale/attributes\":373,\"../../lib/extend\":493,\"../../plot_api/edit_types\":536,\"../../plots/attributes\":550,\"../../plots/cartesian/axis_format_attributes\":557,\"../../plots/template_attributes\":633}],1062:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":374}],1063:[function(t,e,r){\"use strict\";var n=t(\"../../../stackgl_modules\").gl_surface3d,i=t(\"../../../stackgl_modules\").ndarray,a=t(\"../../../stackgl_modules\").ndarray_linear_interpolate.d2,o=t(\"../heatmap/interp2d\"),s=t(\"../heatmap/find_empties\"),l=t(\"../../lib\").isArrayOrTypedArray,c=t(\"../../lib/gl_format_color\").parseColorScale,u=t(\"../../lib/str2rgbarray\"),f=t(\"../../components/colorscale\").extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=t.dataCoordinate[a];null!=o&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[i]&&void 0!==s[i][n]?t.textLabel=s[i][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var d=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function m(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function g(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(m(t,n))}return e}function v(t){for(var e=g(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function y(t,e){if(!(t<1||e<1)){for(var r=g(t),n=g(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++)r(i,[l,c],n),t.set(l,c,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=y(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=v(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,c=1+a+1,u=i(new Float32Array(l*c),[l,c]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(u,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,u,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=c(t),m=l.dataScale,g=t.z[0].length,v=t._ylength,y=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<g;r++)x[e][r]=[];for(r=0;r<g;r++)for(n=0;n<v;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<g;r++)for(t._interpolatedZ[r]=[],n=0;n<v;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=m[e];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(g*v),[g,v]),i(new Float32Array(g*v),[g,v]),i(new Float32Array(g*v),[g,v])];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)b[e].set(r,n,x[e][r][n]);x=[];var w={colormap:d,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacityscale:t.opacityscale,opacity:t.opacity},T=f(t);if(w.intensityBounds=[T.min,T.max],t.surfacecolor){var k=i(new Float32Array(g*v),[g,v]);for(r=0;r<g;r++)for(n=0;n<v;n++)k.set(r,n,t.surfacecolor[n][r]);b.push(k)}else w.intensityBounds[0]*=m[2],w.intensityBounds[1]*=m[2];(_<b[0].shape[0]||_<b[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(b[0].shape[0],0),this.dataScaleY=this.estimateScale(b[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(b)),t.surfacecolor&&(w.intensity=b.pop());var A=[!0,!0,!0],M=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[M[e]];A[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=y[e],p.highlightColor[e]=w.contourColor[e]=u(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=u(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=A,p.enableHighlight=A,p.snapToData=!0,\"lighting\"in t&&(p.ambientLight=t.lighting.ambient,p.diffuseLight=t.lighting.diffuse,p.specularLight=t.lighting.specular,p.roughness=t.lighting.roughness,p.fresnel=t.lighting.fresnel),\"lightposition\"in t&&(p.lightPosition=[t.lightposition.x,t.lightposition.y,t.lightposition.z])},p.dispose=function(){this.scene.glplot.remove(this.surface),this.surface.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new h(t,i,e.uid);return i._trace=a,a.update(e),t.glplot.add(i),a}},{\"../../../stackgl_modules\":1124,\"../../components/colorscale\":378,\"../../lib\":503,\"../../lib/gl_format_color\":499,\"../../lib/str2rgbarray\":528,\"../heatmap/find_empties\":798,\"../heatmap/interp2d\":801}],1064:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");function s(t,e,r,n){var 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this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var d=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],f=8191&u,h=u>>>13,p=0|o[1],d=8191&p,m=p>>>13,g=0|o[2],v=8191&g,y=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],I=8191&P,O=P>>>13,z=0|o[8],D=8191&z,R=z>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,H=0|s[1],q=8191&H,G=H>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,K=Z>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ft=8191&ut,ht=ut>>>13,pt=0|s[9],dt=8191&pt,mt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(c+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;c=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(m,U)|0,a=Math.imul(m,V);var vt=(c+(n=n+Math.imul(f,q)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,q)|0))<<13)|0;c=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(v,U),i=(i=Math.imul(v,V))+Math.imul(y,U)|0,a=Math.imul(y,V),n=n+Math.imul(d,q)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(m,q)|0,a=a+Math.imul(m,G)|0;var yt=(c+(n=n+Math.imul(f,W)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,W)|0))<<13)|0;c=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(v,q)|0,i=(i=i+Math.imul(v,G)|0)+Math.imul(y,q)|0,a=a+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(m,W)|0,a=a+Math.imul(m,X)|0;var xt=(c+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;c=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,q)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,q)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,i=(i=i+Math.imul(v,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(m,J)|0,a=a+Math.imul(m,K)|0;var bt=(c+(n=n+Math.imul(f,$)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,$)|0))<<13)|0;c=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,q)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,q)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,W)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(v,J)|0,i=(i=i+Math.imul(v,K)|0)+Math.imul(y,J)|0,a=a+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(m,$)|0,a=a+Math.imul(m,tt)|0;var _t=(c+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;c=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,q)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,q)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,W)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,W)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(v,$)|0,i=(i=i+Math.imul(v,tt)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0;var wt=(c+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;c=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(I,U),i=(i=Math.imul(I,V))+Math.imul(O,U)|0,a=Math.imul(O,V),n=n+Math.imul(L,q)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,q)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,W)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,$)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,i=(i=i+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0;var Tt=(c+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ct)|0)+Math.imul(h,lt)|0))<<13)|0;c=((a=a+Math.imul(h,ct)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(I,q)|0,i=(i=i+Math.imul(I,G)|0)+Math.imul(O,q)|0,a=a+Math.imul(O,G)|0,n=n+Math.imul(L,W)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,W)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(v,at)|0,i=(i=i+Math.imul(v,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ct)|0;var kt=(c+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;c=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,q)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,q)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(I,W)|0,i=(i=i+Math.imul(I,X)|0)+Math.imul(O,W)|0,a=a+Math.imul(O,X)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(M,$)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,i=(i=i+Math.imul(v,ct)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ct)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var At=(c+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,mt)|0)+Math.imul(h,dt)|0))<<13)|0;c=((a=a+Math.imul(h,mt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,q),i=(i=Math.imul(B,G))+Math.imul(N,q)|0,a=Math.imul(N,G),n=n+Math.imul(D,W)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,W)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(I,J)|0,i=(i=i+Math.imul(I,K)|0)+Math.imul(O,J)|0,a=a+Math.imul(O,K)|0,n=n+Math.imul(L,$)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,$)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ct)|0,n=n+Math.imul(v,ft)|0,i=(i=i+Math.imul(v,ht)|0)+Math.imul(y,ft)|0,a=a+Math.imul(y,ht)|0;var Mt=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,mt)|0)+Math.imul(m,dt)|0))<<13)|0;c=((a=a+Math.imul(m,mt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,W),i=(i=Math.imul(B,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(D,J)|0,i=(i=i+Math.imul(D,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(I,$)|0,i=(i=i+Math.imul(I,tt)|0)+Math.imul(O,$)|0,a=a+Math.imul(O,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ct)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(c+(n=n+Math.imul(v,dt)|0)|0)+((8191&(i=(i=i+Math.imul(v,mt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((a=a+Math.imul(y,mt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(D,$)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(I,rt)|0,i=(i=i+Math.imul(I,nt)|0)+Math.imul(O,rt)|0,a=a+Math.imul(O,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,mt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((a=a+Math.imul(_,mt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,tt))+Math.imul(N,$)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(I,at)|0,i=(i=i+Math.imul(I,ot)|0)+Math.imul(O,at)|0,a=a+Math.imul(O,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ct)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ct)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,mt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((a=a+Math.imul(k,mt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(I,lt)|0,i=(i=i+Math.imul(I,ct)|0)+Math.imul(O,lt)|0,a=a+Math.imul(O,ct)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(c+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,mt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,mt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(I,ft)|0,i=(i=i+Math.imul(I,ht)|0)+Math.imul(O,ft)|0,a=a+Math.imul(O,ht)|0;var Pt=(c+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,mt)|0)+Math.imul(C,dt)|0))<<13)|0;c=((a=a+Math.imul(C,mt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(N,lt)|0,a=Math.imul(N,ct),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var It=(c+(n=n+Math.imul(I,dt)|0)|0)+((8191&(i=(i=i+Math.imul(I,mt)|0)+Math.imul(O,dt)|0))<<13)|0;c=((a=a+Math.imul(O,mt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var Ot=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,mt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,mt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863;var zt=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,mt))+Math.imul(N,dt)|0))<<13)|0;return c=((a=Math.imul(N,mt))+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,l[0]=gt,l[1]=vt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=It,l[17]=Ot,l[18]=zt,0!==c&&(l[19]=c,r.length++),r};function m(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?d(this,t,e):r<63?p(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),c=Math.max(0,a-t.length+1);c<=l;c++){var u=a-c,f=(0|t.words[u])*(0|e.words[c]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):m(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<i;u+=s)for(var f=l,h=c,p=0;p<o;p++){var d=r[u+p],m=n[u+p],g=r[u+p+o],v=n[u+p+o],y=f*g-h*v;v=f*v+h*g,g=y,r[u+p]=d+g,n[u+p]=m+v,r[u+p+o]=d-g,n[u+p+o]=m-v,p!==s&&(y=l*f-c*h,h=l*h+c*f,f=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,a,s,l,n,i),this.transform(c,a,u,f,n,i);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),m(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=i);c--){var f=0|this.words[c];this.words[c]=u<<26-a|f>>>a,u=f&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r)&&!!(this.words[r]&i)},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!==(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(i,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,m=1;0==(r.words[0]&m)&&d<26;++d,m<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return 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numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var v={k256:null,p224:null,p192:null,p25519:null};function y(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){y.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function b(){y.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function _(){y.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function w(){y.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function T(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}y.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},y.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},y.prototype.split=function(t,e){t.iushrn(this.n,0,e)},y.prototype.imulK=function(t){return t.imul(this.k)},i(x,y),x.prototype.split=function(t,e){for(var r=Math.min(t.length,9),n=0;n<r;n++)e.words[n]=t.words[n];if(e.length=r,t.length<=9)return t.words[0]=0,void(t.length=1);var i=t.words[9];for(e.words[e.length++]=4194303&i,n=10;n<t.length;n++){var a=0|t.words[n];t.words[n-10]=(4194303&a)<<4|i>>>22,i=a}i>>>=22,t.words[n-10]=i,0===i&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(b,y),i(_,y),i(w,y),w.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(v[t])return v[t];var e;if(\"k256\"===t)e=new x;else if(\"p224\"===t)e=new b;else if(\"p192\"===t)e=new _;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new w}return v[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},T.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},T.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},T.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},T.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},T.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},T.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},T.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},T.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},T.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},T.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},T.prototype.isqr=function(t){return this.imul(t,t.clone())},T.prototype.sqr=function(t){return this.mul(t,t)},T.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),c=this.m.subn(1).iushrn(1),u=this.m.bitLength();for(u=new a(2*u*u).toRed(this);0!==this.pow(u,c).cmp(l);)u.redIAdd(l);for(var f=this.pow(u,i),h=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var m=p,g=0;0!==m.cmp(s);g++)m=m.redSqr();n(g<d);var v=this.pow(f,new a(1).iushln(d-g-1));h=h.redMul(v),f=v.redSqr(),p=p.redMul(f),d=g}return h},T.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},T.prototype.pow=function(t,e){if(e.isZero())return new a(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new a(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var i=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var c=e.words[n],u=l-1;u>=0;u--){var f=c>>u&1;i!==r[0]&&(i=this.sqr(i)),0!==f||0!==o?(o<<=1,o|=f,(4===++s||0===n&&0===u)&&(i=this.mul(i,r[o]),s=0,o=0)):s=0}l=26}return i},T.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},T.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},a.mont=function(t){return new k(t)},i(k,T),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new a(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),o=i;return i.cmp(this.m)>=0?o=i.isub(this.m):i.cmpn(0)<0&&(o=i.iadd(this.m)),o._forceRed(this)},k.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(void 0===e||e,this)},{buffer:2}],34:[function(t,e,r){\"use strict\";e.exports=function(t){var e,r,n,i=t.length,a=0;for(e=0;e<i;++e)a+=t[e].length;var o=new Array(a),s=0;for(e=0;e<i;++e){var l=t[e],c=l.length;for(r=0;r<c;++r){var u=o[s++]=new Array(c-1),f=0;for(n=0;n<c;++n)n!==r&&(u[f++]=l[n]);if(1&r){var h=u[1];u[1]=u[0],u[0]=h}}}return o}},{}],35:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){switch(arguments.length){case 1:return f(t);case 2:return\"function\"==typeof e?c(t,t,e,!0):h(t,e);case 3:return c(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}};var n,i=t(\"typedarray-pool\"),a=t(\"./lib/sweep\"),o=t(\"./lib/intersect\");function s(t,e){for(var r=0;r<t;++r)if(!(e[r]<=e[r+t]))return!0;return!1}function l(t,e,r,n){for(var i=0,a=0,o=0,l=t.length;o<l;++o){var c=t[o];if(!s(e,c)){for(var u=0;u<2*e;++u)r[i++]=c[u];n[a++]=o}}return a}function c(t,e,r,n){var s=t.length,c=e.length;if(!(s<=0||c<=0)){var u=t[0].length>>>1;if(!(u<=0)){var f,h=i.mallocDouble(2*u*s),p=i.mallocInt32(s);if((s=l(t,u,h,p))>0){if(1===u&&n)a.init(s),f=a.sweepComplete(u,r,0,s,h,p,0,s,h,p);else{var d=i.mallocDouble(2*u*c),m=i.mallocInt32(c);(c=l(e,u,d,m))>0&&(a.init(s+c),f=1===u?a.sweepBipartite(u,r,0,s,h,p,0,c,d,m):o(u,r,n,s,h,p,c,d,m),i.free(d),i.free(m))}i.free(h),i.free(p)}return f}}}function u(t,e){n.push([t,e])}function f(t){return n=[],c(t,t,u,!0),n}function h(t,e){return n=[],c(t,e,u,!1),n}},{\"./lib/intersect\":37,\"./lib/sweep\":41,\"typedarray-pool\":308}],36:[function(t,e,r){\"use strict\";function n(t){return t?function(t,e,r,n,i,a,o,s,l,c,u){return i-n>l-s?function(t,e,r,n,i,a,o,s,l,c,u){for(var f=2*t,h=n,p=f*n;h<i;++h,p+=f){var d=a[e+p],m=a[e+p+t],g=o[h];t:for(var v=s,y=f*s;v<l;++v,y+=f){var x=c[e+y],b=c[e+y+t],_=u[v];if(!(b<d||m<x)){for(var w=e+1;w<t;++w){var T=a[w+p],k=a[w+t+p],A=c[w+y],M=c[w+t+y];if(k<A||M<T)continue t}var S=r(g,_);if(void 0!==S)return S}}}}(t,e,r,n,i,a,o,s,l,c,u):function(t,e,r,n,i,a,o,s,l,c,u){for(var f=2*t,h=s,p=f*s;h<l;++h,p+=f){var d=c[e+p],m=c[e+p+t],g=u[h];t:for(var v=n,y=f*n;v<i;++v,y+=f){var x=a[e+y],b=a[e+y+t],_=o[v];if(!(m<x||b<d)){for(var w=e+1;w<t;++w){var T=a[w+y],k=a[w+t+y],A=c[w+p],M=c[w+t+p];if(k<A||M<T)continue t}var S=r(_,g);if(void 0!==S)return S}}}}(t,e,r,n,i,a,o,s,l,c,u)}:function(t,e,r,n,i,a,o,s,l,c,u,f){return a-i>c-l?n?function(t,e,r,n,i,a,o,s,l,c,u){for(var f=2*t,h=n,p=f*n;h<i;++h,p+=f){var d=a[e+p],m=a[e+p+t],g=o[h];t:for(var v=s,y=f*s;v<l;++v,y+=f){var x=c[e+y],b=u[v];if(!(x<=d||m<x)){for(var _=e+1;_<t;++_){var w=a[_+p],T=a[_+t+p],k=c[_+y],A=c[_+t+y];if(T<k||A<w)continue t}var M=r(b,g);if(void 0!==M)return 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e=i.nextPow2(t);o.length<e&&(n.free(o),o=n.mallocInt32(e));s.length<e&&(n.free(s),s=n.mallocInt32(e));l.length<e&&(n.free(l),l=n.mallocInt32(e));c.length<e&&(n.free(c),c=n.mallocInt32(e));u.length<e&&(n.free(u),u=n.mallocInt32(e));f.length<e&&(n.free(f),f=n.mallocInt32(e));var r=8*e;h.length<r&&(n.free(h),h=n.mallocDouble(r))},sweepBipartite:function(t,e,r,n,i,u,f,m,g,v){for(var y=0,x=2*t,b=t-1,_=x-1,w=r;w<n;++w){var T=u[w],k=x*w;h[y++]=i[k+b],h[y++]=-(T+1),h[y++]=i[k+_],h[y++]=T}for(w=f;w<m;++w){T=v[w]+(1<<28);var A=x*w;h[y++]=g[A+b],h[y++]=-T,h[y++]=g[A+_],h[y++]=T}var M=y>>>1;a(h,M);var S=0,E=0;for(w=0;w<M;++w){var L=0|h[2*w+1];if(L>=1<<28)p(l,c,E--,L=L-(1<<28)|0);else if(L>=0)p(o,s,S--,L);else if(L<=-(1<<28)){L=-L-(1<<28)|0;for(var C=0;C<S;++C){if(void 0!==(P=e(o[C],L)))return P}d(l,c,E++,L)}else{L=-L-1|0;for(C=0;C<E;++C){var P;if(void 0!==(P=e(L,l[C])))return P}d(o,s,S++,L)}}},sweepComplete:function(t,e,r,n,i,m,g,v,y,x){for(var b=0,_=2*t,w=t-1,T=_-1,k=r;k<n;++k){var 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e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<=0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new h(this,n)},l.gt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new h(this,n)},l.lt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new h(this,n)},l.le=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>=0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new h(this,n)},l.find=function(t){for(var e=this._compare,r=this.root,n=[];r;){var i=e(t,r.key);if(n.push(r),0===i)return new h(this,n);r=i<=0?r.left:r.right}return new h(this,[])},l.remove=function(t){var e=this.find(t);return e?e.remove():this},l.get=function(t){for(var e=this._compare,r=this.root;r;){var n=e(t,r.key);if(0===n)return r.value;r=n<=0?r.left:r.right}};var p=h.prototype;function d(t,e){t.key=e.key,t.value=e.value,t.left=e.left,t.right=e.right,t._color=e._color,t._count=e._count}function m(t,e){return t<e?-1:t>e?1:0}Object.defineProperty(p,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(p,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),p.clone=function(){return new h(this.tree,this._stack.slice())},p.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var e=new Array(t.length),r=t[t.length-1];e[e.length-1]=new n(r._color,r.key,r.value,r.left,r.right,r._count);for(var l=t.length-2;l>=0;--l){(r=t[l]).left===t[l+1]?e[l]=new n(r._color,r.key,r.value,e[l+1],r.right,r._count):e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count)}if((r=e[e.length-1]).left&&r.right){var c=e.length;for(r=r.left;r.right;)e.push(r),r=r.right;var u=e[c-1];e.push(new n(r._color,u.key,u.value,r.left,r.right,r._count)),e[c-1].key=r.key,e[c-1].value=r.value;for(l=e.length-2;l>=c;--l)r=e[l],e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count);e[c-1].left=e[c]}if(0===(r=e[e.length-1])._color){var f=e[e.length-2];f.left===r?f.left=null:f.right===r&&(f.right=null),e.pop();for(l=0;l<e.length;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(r.left||r.right){r.left?d(r,r.left):r.right&&d(r,r.right),r._color=1;for(l=0;l<e.length-1;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(1===e.length)return new s(this.tree._compare,null);for(l=0;l<e.length;++l)e[l]._count--;var h=e[e.length-2];return function(t){for(var e,r,n,s,l=t.length-1;l>=0;--l){if(e=t[l],0===l)return void(e._color=1);if((r=t[l-1]).left===e){if((n=r.right).right&&0===n.right._color){if(s=(n=r.right=i(n)).right=i(n.right),r.right=n.left,n.left=r,n.right=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).left===r?c.left=n:c.right=n;return void(t[l-1]=n)}if(n.left&&0===n.left._color){if(s=(n=r.right=i(n)).left=i(n.left),r.right=s.left,n.left=s.right,s.left=r,s.right=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).left===r?c.left=s:c.right=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.right=a(0,n));r.right=a(0,n);continue}n=i(n),r.right=n.left,n.left=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).left===r?c.left=n:c.right=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}else{if((n=r.left).left&&0===n.left._color){if(s=(n=r.left=i(n)).left=i(n.left),r.left=n.right,n.right=r,n.left=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).right===r?c.right=n:c.left=n;return void(t[l-1]=n)}if(n.right&&0===n.right._color){if(s=(n=r.left=i(n)).right=i(n.right),r.left=s.right,n.right=s.left,s.right=r,s.left=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).right===r?c.right=s:c.left=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.left=a(0,n));r.left=a(0,n);continue}var c;n=i(n),r.left=n.right,n.right=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).right===r?c.right=n:c.left=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}}}(e),h.left===r?h.left=null:h.right=null,new s(this.tree._compare,e[0])},Object.defineProperty(p,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(p,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(p,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),p.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),p.update=function(t){var e=this._stack;if(0===e.length)throw new Error(\"Can't update empty node!\");var r=new Array(e.length),i=e[e.length-1];r[r.length-1]=new n(i._color,i.key,t,i.left,i.right,i._count);for(var a=e.length-2;a>=0;--a)(i=e[a]).left===e[a+1]?r[a]=new n(i._color,i.key,i.value,r[a+1],i.right,i._count):r[a]=new n(i._color,i.key,i.value,i.left,r[a+1],i._count);return new s(this.tree._compare,r[0])},p.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},{}],70:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=new u(t);return r.update(e),r};var n=t(\"./lib/text.js\"),i=t(\"./lib/lines.js\"),a=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=u.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),u=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,u=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),c(\"tickColor\");var m=l(\"labels\");l(\"labelFont\")&&(m=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(m||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var f=a,h=s,p=o,d=l;c&1<<u&&(f=s,h=a,p=l,d=o),f[u]=r[0][u],h[u]=r[1][u],i[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var m=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var v=[0,0,0],y=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,u=o(r,n,i,a,s),f=u.cubeEdges,h=u.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E=m;for(A=0;A<3;++A)this.backgroundEnable[A]?E[A]=h[A]:E[A]=0;this._background.draw(r,n,i,a,E,this.backgroundColor),this._lines.bind(r,n,i,this);for(A=0;A<3;++A){var L=[0,0,0];h[A]>0?L[A]=a[1][A]:L[A]=a[0][A];for(var C=0;C<2;++C){var P=(A+1+C)%3,I=(A+1+(1^C))%3;this.gridEnable[P]&&this._lines.drawGrid(P,I,this.bounds,L,this.gridColor[P],this.gridWidth[P]*this.pixelRatio)}for(C=0;C<2;++C){P=(A+1+C)%3,I=(A+1+(1^C))%3;this.zeroEnable[I]&&Math.min(a[0][I],a[1][I])<=0&&Math.max(a[0][I],a[1][I])>=0&&this._lines.drawZero(P,I,this.bounds,L,this.zeroLineColor[I],this.zeroLineWidth[I]*this.pixelRatio)}}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var O=c(v,M[A].primalMinor),z=c(y,M[A].mirrorMinor),D=this.lineTickLength;for(C=0;C<3;++C){var R=k/r[5*C];O[C]*=D[C]*R,z[C]*=D[C]*R}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,O,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,H=c(x,M[A].primalOffset);for(C=0;C<3;++C)this.lineTickEnable[A]&&(H[C]+=k*U[C]*Math.max(this.lineTickLength[C],0)/r[5*C]);var q=[0,0,0];if(q[A]=1,this.tickEnable[A]){-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,F=1,\"auto\"===(S=[this.tickAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(A,U,V);for(C=0;C<3;++C)H[C]+=k*U[C]*this.tickPad[C]/r[5*C];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],H,this.tickColor[A],q,B,S)}if(this.labelEnable[A]){F=0,B=[0,0,0],this.labels[A].length>4&&(N(A),F=1),\"auto\"===(S=[this.labelAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(C=0;C<3;++C)H[C]+=k*U[C]*this.labelPad[C]/r[5*C];H[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],H,this.labelColor[A],[0,0,0],B,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":71,\"./lib/cube.js\":72,\"./lib/lines.js\":73,\"./lib/text.js\":75,\"./lib/ticks.js\":76}],71:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[c]=d;for(var m=-1;m<=1;m+=2)f[u]=m,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=c;c=u,u=g}var v=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,v,x,b)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":74,\"gl-buffer\":78,\"gl-vao\":150}],72:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=a[x][2];for(var b=0;b<2;++b){u[1]=a[b][1];for(var _=0;_<2;++_)u[0]=a[_][0],h(l[y],u,s),y+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)c[x][k]=l[x][k]/T;p&&(c[x][2]*=-1),T<0&&(w<0||c[x][2]<c[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(O=C<<A)+(C<<M)+(1-C<<S),I=O+(1-C<<M)+(C<<S);o(c[O],c[P],c[I],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<A);else{for(C=0;C<2;++C){P=(O=C<<A)+(C<<M)+(1-C<<S),I=O+(1-C<<M)+(C<<S);var O,z=d([l[O],l[P],l[I],l[O+(1<<M)+(1<<S)]]);C?E=z:L=z}L>E&&(w|=1<<A)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||c[R][1]>c[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x){if((N=R^1<<x)!==w&&N!==D)F<0&&(F=N),(S=c[N])[0]<c[F][0]&&(F=N)}var B=-1;for(x=0;x<3;++x){var N;if((N=R^1<<x)!==w&&N!==D&&N!==F)B<0&&(B=N),(S=c[N])[0]>c[B][0]&&(B=N)}var j=m;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,H=w;for(A=0;A<3;++A)V[A]=H&1<<A?-1:1;return v};var n=t(\"bit-twiddle\"),i=t(\"gl-mat4/multiply\"),a=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(c*h-u*f)}return o}var m=[1,1,1],g=[0,0,0],v={cubeEdges:m,axis:g}},{\"bit-twiddle\":32,\"gl-mat4/multiply\":100,\"robust-orientation\":284,\"split-polygon\":300}],73:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var m=+r[f][d].x;o.push(m,0,1,m,1,1,m,0,-1,m,0,-1,m,1,1,m,1,-1)}var g=o.length/3|0;s[f]=h,l[f]=g-h;h=o.length/3|0;for(var v=0;v<r[f].length;++v){m=+r[f][v].x;o.push(m,0,1,m,1,1,m,0,-1,m,0,-1,m,1,1,m,1,-1)}g=o.length/3|0;c[f]=h,u[f]=g-h}var y=n(t,new Float32Array(o)),x=i(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,u=h(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var u=f(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=h(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var m=f(l);m[t]=1,this.shader.uniforms.screenAxis=m,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=h(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":74,\"gl-buffer\":78,\"gl-vao\":150}],74:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n vec4 pp = projection * view * model * vec4(p, 1.0);\\n return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n vec3 major = position.x * majorAxis;\\n vec3 minor = position.y * minorAxis;\\n\\n vec3 vPosition = major + minor + offset;\\n vec3 pPosition = project(vPosition);\\n vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);r.line=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n vec4 pp = projection * view * model * vec4(p, 1.0);\\n return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n vec3 A = project(a);\\n vec3 B = project(b);\\n\\n return atan(\\n (B.y - A.y) * resolution.y,\\n (B.x - A.x) * resolution.x\\n );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio = alignOpt.y;\\nbool enableAlign = (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n return mod_angle((a < 0.0) ?\\n a + TWO_PI :\\n a\\n );\\n}\\n\\nfloat look_upwards(float a) {\\n float b = positive_angle(a);\\n return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n b - PI :\\n b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n // if ratio is set to 0.5 then it is 50%, 50%.\\n // when using a higher ratio e.g. 0.75 the result would\\n // likely be more horizontal than vertical.\\n\\n float b = positive_angle(a);\\n\\n return\\n (b < ( ratio) * HALF_PI) ? 0.0 :\\n (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n 0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n float b = positive_angle(a);\\n float div = TWO_PI / float(n);\\n float c = roundTo(b, div);\\n return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n return\\n (option > 2) ? look_round_n_directions(rawAngle + delta, option) : // option 3-n: round to n directions\\n (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n (option == 1) ? rawAngle + delta : // use free angle, and flip to align with one direction of the axis\\n (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n (option ==-1) ? 0.0 : // useful for backward compatibility, all texts remains horizontal\\n rawAngle; // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n (axis.y == 0.0) &&\\n (axis.z == 0.0);\\n\\nvoid main() {\\n //Compute world offset\\n float axisDistance = position.z;\\n vec3 dataPosition = axisDistance * axis + offset;\\n\\n float beta = angle; // i.e. user defined attributes for each tick\\n\\n float axisAngle;\\n float clipAngle;\\n float flip;\\n\\n if (enableAlign) {\\n axisAngle = (isAxisTitle) ? HALF_PI :\\n computeViewAngle(dataPosition, dataPosition + axis);\\n clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n beta += applyAlignOption(clipAngle, flip * PI);\\n }\\n\\n //Compute plane offset\\n vec2 planeCoord = position.xy * pixelScale;\\n\\n mat2 planeXform = scale * mat2(\\n cos(beta), sin(beta),\\n -sin(beta), cos(beta)\\n );\\n\\n vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n //Compute clip position\\n vec3 clipPosition = project(dataPosition);\\n\\n //Apply text offset in clip coordinates\\n clipPosition += vec3(viewOffset, 0.0);\\n\\n //Done\\n gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);r.text=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n vec3 realNormal = signAxis * normal;\\n\\n if(dot(realNormal, enable) > 0.0) {\\n vec3 minRange = min(bounds[0], bounds[1]);\\n vec3 maxRange = max(bounds[0], bounds[1]);\\n vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n } else {\\n gl_Position = vec4(0,0,0,0);\\n }\\n\\n colorChannel = abs(realNormal);\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n gl_FragColor = colorChannel.x * colors[0] +\\n colorChannel.y * colors[1] +\\n colorChannel.z * colors[2];\\n}\"]);r.bg=function(t){return i(t,c,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":132,glslify:231}],75:[function(t,e,r){(function(r){(function(){\"use strict\";e.exports=function(t,e,r,a,s,l){var u=n(t),f=i(t,[{buffer:u,size:3}]),h=o(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,a,s,l),p};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"vectorize-text\"),o=t(\"./shaders\").text,s=window||r.global||{},l=s.__TEXT_CACHE||{};s.__TEXT_CACHE={};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var u=c.prototype,f=[0,0];u.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,f[0]=this.gl.drawingBufferWidth,f[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=f},u.unbind=function(){this.vao.unbind()},u.update=function(t,e,r,n,i){var o=[];function s(t,e,r,n,i,s){var c=l[r];c||(c=l[r]={});var u=c[e];u||(u=c[e]=function(t,e){try{return a(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:i,styletags:s}));for(var f=(n||12)/12,h=u.positions,p=u.cells,d=0,m=p.length;d<m;++d)for(var g=p[d],v=2;v>=0;--v){var y=h[g[v]];o.push(f*y[0],-f*y[1],t)}}for(var c=[0,0,0],u=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=o.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(o.length/3|0)-f[d],c[d]=o.length/3|0;for(var m=0;m<n[d].length;++m)n[d][m].text&&s(n[d][m].x,n[d][m].text,n[d][m].font||i,n[d][m].fontSize||12,1.25,p);u[d]=(o.length/3|0)-c[d]}this.buffer.update(o),this.tickOffset=c,this.tickCount=u,this.labelOffset=f,this.labelCount=h},u.drawTicks=function(t,e,r,n,i,a,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},u.drawLabel=function(t,e,r,n,i,a,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},u.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}}).call(this)}).call(this,t(\"_process\"))},{\"./shaders\":74,_process:5,\"gl-buffer\":78,\"gl-vao\":150,\"vectorize-text\":311}],76:[function(t,e,r){\"use strict\";function n(t,e){var r=t+\"\",n=r.indexOf(\".\"),i=0;n>=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,c=o%a;o<0?(l=0|-Math.ceil(l),c=0|-c):(l=0|Math.floor(l),c|=0);var u=\"\"+l;if(o<0&&(u=\"-\"+u),i){for(var f=\"\"+c;f.length<i;)f=\"0\"+f;return u+\".\"+f}return u}r.create=function(t,e){for(var r=[],i=0;i<3;++i){for(var a=[],o=(t[0][i],t[1][i],0);o*e[i]<=t[1][i];++o)a.push({x:o*e[i],text:n(e[i],o)});for(o=-1;o*e[i]>=t[0][i];--o)a.push({x:o*e[i],text:n(e[i],o)});r.push(a)}return r},r.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var i=t[r][n],a=e[r][n];if(i.x!==a.x||i.text!==a.text||i.font!==a.font||i.fontColor!==a.fontColor||i.fontSize!==a.fontSize||i.dx!==a.dx||i.dy!==a.dy)return!1}}return!0}},{}],77:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,l,f){var h=e.model||c,p=e.view||c,v=e.projection||c,y=e._ortho||!1,x=t.bounds,b=(f=f||a(h,p,v,x,y)).axis;o(u,p,h),o(u,v,u);for(var _=m,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var T=n(s(u,u));s(u,u);for(var k=0;k<3;++k){var A=(k+1)%3,M=(k+2)%3,S=g;t:for(w=0;w<2;++w){var E=[];if(b[k]<0!=!!w){S[k]=x[w][k];for(var L=0;L<2;++L){S[A]=x[L^w][A];for(var C=0;C<2;++C)S[M]=x[C^L^w][M],E.push(S.slice())}var P=y?5:4;for(L=P;L===P;++L){if(0===E.length)continue t;E=i.positive(E,T[L])}for(L=0;L<E.length;++L){M=E[L];var I=d(g,u,M,r,l);for(C=0;C<3;++C)_[C].lo=Math.min(_[C].lo,M[C]),_[C].hi=Math.max(_[C].hi,M[C]),C!==k&&(_[C].pixelsPerDataUnit=Math.min(_[C].pixelsPerDataUnit,Math.abs(I[C])))}}}}return _};var n=t(\"extract-frustum-planes\"),i=t(\"split-polygon\"),a=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+f*f)}return t}var m=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],g=[0,0,0]},{\"./lib/cube.js\":72,\"extract-frustum-planes\":67,\"gl-mat4/multiply\":100,\"gl-mat4/transpose\":109,\"gl-vec4/transformMat4\":221,\"split-polygon\":300}],78:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),i=t(\"ndarray-ops\"),a=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function c(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function u(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},{ndarray:259,\"ndarray-ops\":254,\"typedarray-pool\":308}],79:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\");e.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,f=1/0,h=-1/0,p=null,d=null,m=[],g=1/0,v=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[y];if(n.length(b)>o&&(o=n.length(b)),y){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(g=Math.min(g,_),v=!1):v=!0}v||(p=x,d=b),m.push(b)}var w=[s,c,f],T=[l,u,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(g)||(g=1),a.vectorScale=g;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A;y=0;for(var M=0;y<r.length;y++)for(var S=(x=r[y])[0],E=x[1],L=x[2],C=m[y],P=n.length(C)*k,I=0;I<8;I++){a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vertexIntensity.push(P,P,P),a.vertexIntensity.push(P,P,P);var O=a.positions.length;a.cells.push([O-6,O-5,O-4],[O-3,O-2,O-1])}return a};var i=t(\"./lib/shaders\");e.exports.createMesh=t(\"./create_mesh\"),e.exports.createConeMesh=function(t,r){return e.exports.createMesh(t,r,{shaders:i,traceType:\"cone\"})}},{\"./create_mesh\":80,\"./lib/shaders\":81,\"gl-vec3\":169}],80:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"gl-mat4/multiply\"),l=t(\"gl-mat4/invert\"),c=t(\"ndarray\"),u=t(\"colormap\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;function d(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}function m(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,m=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],m=+t.vertexIntensityBounds[1];else for(var g=0;g<p.length;++g){var v=p[g];d=Math.min(d,v),m=Math.max(m,v)}else for(g=0;g<n.length;++g){v=n[g][2];d=Math.min(d,v),m=Math.max(m,v)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(g=0;g<n.length;++g)for(var y=n[g],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(g=0;g<r.length;++g){var _=r[g];switch(_.length){case 3:for(x=0;x<3;++x){y=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var T;y=n[T=_[2-x]];a.push(y[0],y[1],y[2],y[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=h;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(m-d),0]:[(y[2]-d)/(m-d),0],l.push(A[0],A[1]),f.push(g)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/h}if(this.triangleCount>0){var m=this.triShader;m.bind(),m.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var n=r.shaders;1===arguments.length&&(t=(e=t).gl);var s=d(t,n),l=m(t,n),u=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));u.generateMipmap(),u.minFilter=t.LINEAR_MIPMAP_LINEAR,u.magFilter=t.LINEAR;var f=i(t),p=i(t),g=i(t),v=i(t),y=i(t),x=a(t,[{buffer:f,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:p,type:t.FLOAT,size:4}]),b=new h(t,u,s,l,f,p,y,g,v,x,r.traceType||\"cone\");return b.update(e),b}},{colormap:53,\"gl-buffer\":78,\"gl-mat4/invert\":98,\"gl-mat4/multiply\":100,\"gl-shader\":132,\"gl-texture2d\":146,\"gl-vao\":150,ndarray:259}],81:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * conePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(conePosition, 1.0);\\n vec4 t_position = view * conePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = conePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n gl_Position = projection * view * conePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, 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y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=h(r,i,a,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):m&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):m&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):m?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),f(x)}u(r,e)}(this)}var m=d.prototype;function g(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,a),f(s)),u(n,a)}}Object.defineProperties(m,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return g(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return g(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,g(this,this._shape[0],t),t},enumerable:!1}}),m.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},m.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":146}],87:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,i=t(\"gl-constants/lookup\"),a=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var m=parseInt(d.split(\":\")[2]);if(isNaN(m))throw new Error(n(\"Could not parse error: %s\",d));h[m]=d}}var g=o(e).split(\"\\n\");for(p=0;p<g.length;p++)if(h[p+3]||h[p+2]||h[p+1]){var v=g[p];if(c+=v+\"\\n\",h[p+1]){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":9,\"gl-constants/lookup\":83,\"glsl-shader-name\":223,\"sprintf-js\":301}],88:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),i=o(r,l.pickVertex,l.pickFragment),a=s(r),u=s(r),f=s(r),h=s(r),p=new c(t,n,i,a,u,f,h);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),i=t(\"iota-array\"),a=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,f=c.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],c=a[3]-a[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-a[0])/l-1,u[7]=2*(r[1]-a[1])/c-1,e.bind();var f=e.uniforms;f.viewTransform=u,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=a[2]-a[0],u=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*c/f,t[4]=2*u/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var m=i.attributes;return this.positionBuffer.bind(),m.position.pointer(),this.weightBuffer.bind(),m.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),m.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var c,u,f,p,d=t.colorLevels||[0],m=t.colorValues||[0,0,0,1],g=d.length,v=this.bounds;l?(c=v[0]=r[0],u=v[1]=o[0],f=v[2]=r[r.length-1],p=v[3]=o[o.length-1]):(c=v[0]=r[0]+(r[1]-r[0])/2,u=v[1]=o[0]+(o[1]-o[0])/2,f=v[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=v[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var y=1/(f-c),x=1/(p-u),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,I;l?(P=x*(o[C]-u),I=x*(o[C+1]-u)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-u):x*(o[C]-(o[C]-o[C-1])/2-u),I=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-u):x*(o[C]+(o[C]-o[C-1])/2-u));for(var O=0;O<E;++O){var z,D;l?(z=y*(r[O]-c),D=y*(r[O+1]-c)):(z=O<b-1?y*(r[O]-(r[O+1]-r[O])/2-c):y*(r[O]-(r[O]-r[O-1])/2-c),D=O<b-1?y*(r[O]+(r[O+1]-r[O])/2-c):y*(r[O]+(r[O]-r[O-1])/2-c));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],H=s[l?(C+V)*b+(O+U):C*b+O],q=n.le(d,H);if(q<0)F=m[0],B=m[1],N=m[2],j=m[3];else if(q===g-1)F=m[4*g-4],B=m[4*g-3],N=m[4*g-2],j=m[4*g-1];else{var G=(H-d[q])/(d[q+1]-d[q]),Y=1-G,W=4*q,X=4*(q+1);F=Y*m[W]+G*m[X],B=Y*m[W+1]+G*m[X+1],N=Y*m[W+2]+G*m[X+2],j=Y*m[W+3]+G*m[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*z+.5*D,k[2*S+1]=.5*P+.5*I,A[2*S]=U,A[2*S+1]=V,M[S]=C*b+O,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(A),this.colorBuffer.update(T),this.idBuffer.update(M),a.free(k),a.free(T),a.free(A),a.free(M)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":89,\"binary-search-bounds\":31,\"gl-buffer\":78,\"gl-shader\":132,\"iota-array\":235,\"typedarray-pool\":308}],89:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n fragColor = color;\\n gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n vec2 d = step(.5, vWeight);\\n vec4 id = fragId + pickOffset;\\n id.x += d.x + d.y*shape.x;\\n\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n vWeight = weight;\\n\\n fragId = pickId;\\n\\n vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:231}],90:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n vec4 startPoint = project(position);\\n vec4 endPoint = project(nextPosition);\\n\\n vec2 A = startPoint.xy / startPoint.w;\\n vec2 B = endPoint.xy / endPoint.w;\\n\\n float clipAngle = atan(\\n (B.y - A.y) * screenShape.y,\\n (B.x - A.x) * screenShape.x\\n );\\n\\n vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n sin(clipAngle),\\n -cos(clipAngle)\\n ) / screenShape;\\n\\n gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n worldPosition = position;\\n pixelArcLength = arcLength;\\n fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float dashScale;\\nuniform float opacity;\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (\\n outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n fragColor.a * opacity == 0.\\n ) discard;\\n\\n float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n if(dashWeight < 0.5) {\\n discard;\\n }\\n gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX 1.70141184e38\\n#define FLOAT_MIN 1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n float av = abs(v);\\n\\n //Handle special cases\\n if(av < FLOAT_MIN) {\\n return vec4(0.0, 0.0, 0.0, 0.0);\\n } else if(v > FLOAT_MAX) {\\n return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n } else if(v < -FLOAT_MAX) {\\n return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n }\\n\\n vec4 c = vec4(0,0,0,0);\\n\\n //Compute exponent and mantissa\\n float e = floor(log2(av));\\n float m = av * pow(2.0, -e) - 1.0;\\n\\n //Unpack mantissa\\n c[1] = floor(128.0 * m);\\n m -= c[1] / 128.0;\\n c[2] = floor(32768.0 * m);\\n m -= c[2] / 32768.0;\\n c[3] = floor(8388608.0 * m);\\n\\n //Unpack exponent\\n float ebias = e + 127.0;\\n c[0] = floor(ebias / 2.0);\\n ebias -= c[0] * 2.0;\\n c[1] += floor(ebias) * 128.0;\\n\\n //Unpack sign bit\\n c[0] += 128.0 * step(0.0, -v);\\n\\n //Scale back to range\\n return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return i(t,a,o,null,l)},r.createPickShader=function(t){return i(t,a,s,null,l)}},{\"gl-shader\":132,glslify:231}],91:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),u=c(new Array(1024),[256,1,4]),p=0;p<1024;++p)u.data[p]=255;var d=a(e,u);d.wrap=e.REPEAT;var m=new v(e,r,o,s,l,d);return m.update(t),m};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"gl-texture2d\"),o=new Uint8Array(4),s=new Float32Array(o.buffer);var l=t(\"binary-search-bounds\"),c=t(\"ndarray\"),u=t(\"./lib/shaders\"),f=u.createShader,h=u.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function m(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var y=v.prototype;y.isTransparent=function(){return this.hasAlpha},y.isOpaque=function(){return!this.hasAlpha},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:m(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:m(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var 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t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=c,t[6]=h,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(a*m+o*g+s*v),t[13]=-(l*m+c*g+u*v),t[14]=-(f*m+h*g+p*v),t[15]=1,t}},{\"./identity\":97}],100:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],m=e[12],g=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*m,t[1]=x*i+b*l+_*h+w*g,t[2]=x*a+b*c+_*p+w*v,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*m,t[5]=x*i+b*l+_*h+w*g,t[6]=x*a+b*c+_*p+w*v,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*m,t[9]=x*i+b*l+_*h+w*g,t[10]=x*a+b*c+_*p+w*v,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*m,t[13]=x*i+b*l+_*h+w*g,t[14]=x*a+b*c+_*p+w*v,t[15]=x*o+b*u+_*d+w*y,t}},{}],101:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t}},{}],102:[function(t,e,r){e.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},{}],103:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,A,M,S,E=n[0],L=n[1],C=n[2],P=Math.sqrt(E*E+L*L+C*C);if(Math.abs(P)<1e-6)return null;E*=P=1/P,L*=P,C*=P,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],c=e[2],u=e[3],f=e[4],h=e[5],p=e[6],d=e[7],m=e[8],g=e[9],v=e[10],y=e[11],x=E*E*o+a,b=L*E*o+C*i,_=C*E*o-L*i,w=E*L*o-C*i,T=L*L*o+a,k=C*L*o+E*i,A=E*C*o+L*i,M=L*C*o-E*i,S=C*C*o+a,t[0]=s*x+f*b+m*_,t[1]=l*x+h*b+g*_,t[2]=c*x+p*b+v*_,t[3]=u*x+d*b+y*_,t[4]=s*w+f*T+m*k,t[5]=l*w+h*T+g*k,t[6]=c*w+p*T+v*k,t[7]=u*w+d*T+y*k,t[8]=s*A+f*M+m*S,t[9]=l*A+h*M+g*S,t[10]=c*A+p*M+v*S,t[11]=u*A+d*M+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],104:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=a*i+c*n,t[5]=o*i+u*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=c*i-a*n,t[9]=u*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},{}],105:[function(t,e,r){e.exports=function(t,e,r){var 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null;return[h,s(t,g),g]}},{barycentric:14,\"polytope-closest-point/lib/closest_point_2d.js\":270}],111:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n , view\\n , projection\\n , inverseModel;\\nuniform vec3 eyePosition\\n , lightPosition;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n gl_Position = project(position);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * vec4(position , 1.0);\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n , fresnel\\n , kambient\\n , kdiffuse\\n , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (f_color.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], f_data)\\n ) discard;\\n\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n }\\n gl_PointSize = pointSize;\\n f_color = color;\\n f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n if(dot(pointR, pointR) > 0.25) {\\n discard;\\n }\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_id = id;\\n f_position = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute float pointSize;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n gl_PointSize = pointSize;\\n }\\n f_id = id;\\n f_position = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:231}],112:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),m=t(\"./lib/closest-point\"),g=d.meshShader,v=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=v,this.edgeIds=m,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,g.vertex,g.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function S(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function E(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function C(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function P(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],m=n[f][1],g=i[f],v=1-g,y=this.positions[d],x=this.positions[m],b=0;b<3;++b)o[s++]=g*y[b]+v*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],c=[],h=[],p=[],d=[],m=[],g=[],v=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,I=t.cellUVs,O=t.cellIntensity,z=1/0,D=-1/0;if(!C&&!I)if(P)if(t.vertexIntensityBounds)z=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];z=Math.min(z,F),D=Math.max(D,F)}else if(O)if(t.cellIntensityBounds)z=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<O.length;++R){F=O[R];z=Math.min(z,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];z=Math.min(z,F),D=Math.max(D,F)}this.intensity=P||(O||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(O||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,H=0,q=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;v.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),q+=1;break;case 2:for(U=0;U<2;++U){j=n[W=G[U]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(U=0;U<2;++U){j=n[W=G[U]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],m.push(Z[0],Z[1]),g.push(R)}H+=1;break;case 3:for(U=0;U<3;++U)for(j=n[W=G[U]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(U=0;U<3;++U){var W,X,Z,J;j=n[W=G[2-U]];i.push(j[0],j[1],j[2]),(X=S?S[W]:E?E[R]:L)?this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],c.push(Z[0],Z[1]),J=w?w[W]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=q,this.edgeCount=H,this.triangleCount=V,this.pointPositions.update(v),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(m),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f,h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],f=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=m(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\");if(!r)throw new Error(\"derivatives not supported\");var n=M(t),s=S(t),l=E(t),c=L(t),f=C(t),h=P(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),m=i(t),g=i(t),v=i(t),y=i(t),x=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:m,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:v,type:t.FLOAT,size:3}]),b=i(t),_=i(t),w=i(t),k=i(t),A=a(t,[{buffer:b,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),I=i(t),O=i(t),z=i(t),D=i(t),R=i(t),F=a(t,[{buffer:I,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:O,type:t.FLOAT,size:4},{buffer:z,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=i(t),N=a(t,[{buffer:B,type:t.FLOAT,size:3}]),j=new T(t,p,n,s,l,c,f,h,d,y,m,g,v,x,b,k,_,w,A,I,R,O,z,D,F,B,N);return j.update(e),j}},{\"./lib/closest-point\":110,\"./lib/shaders\":111,colormap:53,\"gl-buffer\":78,\"gl-mat4/invert\":98,\"gl-mat4/multiply\":100,\"gl-shader\":132,\"gl-texture2d\":146,\"gl-vao\":150,ndarray:259,normals:261,\"simplicial-complex-contour\":291,\"typedarray-pool\":308}],113:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=i(e,a.boxVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,c=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":116,\"gl-buffer\":78,\"gl-shader\":132}],114:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,o.gridVert,o.gridFrag),l=i(e,o.tickVert,o.gridFrag);return new s(t,r,a,l)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,f,h,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,m=0;m<2;++m){var g=a[m],v=a[m+2]-g,y=.5*(o[m+2]+o[m]),x=o[m+2]-o[m];u[m]=2*v/x,c[m]=2*(g-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(m=0;m<2;++m){f[0]=f[1]=0,f[m]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[m]/(s[m+2]-s[m])*d,r.uniforms.color=h[m];var _=6*n[m].length;p[m]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,m=s.viewBox,g=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=m[2]-m[0],_=m[3]-m[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,I=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),O=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),z=0+6*I,D=6*Math.max(0,O-I),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(m[0]-E[1])/y-1,i[1]=(m[3]+m[1])/x-1,o[0]=E[1]*g/y,o[1]=L[1]*g/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(m[2]+m[0])/y-1,i[1]=2*(m[1]-E[0])/x-1,o[0]=L[0]*g/y,o[1]=E[0]*g/x,D&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D)),i[0]=2*(m[2]+E[3])/y-1,i[1]=(m[3]+m[1])/x-1,o[0]=E[3]*g/y,o[1]=L[3]*g/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(m[2]+m[0])/y-1,i[1]=2*(m[3]+E[2])/x-1,o[0]=L[2]*g/y,o[1]=E[2]*g/x,D&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],c=r[o],u=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-c)/(u-c);s.push(d);for(var m=0;m<6;++m)n[i++]=d,n[i++]=h[m],n[i++]=p[m]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":116,\"binary-search-bounds\":31,\"gl-buffer\":78,\"gl-shader\":132}],115:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=i(e,a.lineVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=i*o.pixelRatio,c.uniforms.color=a,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":116,\"gl-buffer\":78,\"gl-shader\":132}],116:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n vec2 delta = normalize(perp(start - end));\\n vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n float dataOffset = textCoordinate.z;\\n vec2 glyphOffset = textCoordinate.xy;\\n mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n glyphMatrix * glyphOffset * textScale + screenOffset;\\n gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:231}],117:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,s.textVert,s.textFrag);return new l(t,r,a)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,f,h,p,d,m=l.prototype;m.drawTicks=(c=[0,0],u=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,m=e.tickPad,g=e.tickColor,v=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];u[1^t]=M*s[1^t]-1,d[t]&&(u[1^t]-=M*p*m[t],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=g[t],r.uniforms.angle=v[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),y[t]&&T&&(u[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),u[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=M*p*m[t+2],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=g[t+2],r.uniforms.angle=v[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),y[t+2]&&T&&(u[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),m.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-a[u])/(a[2+u]-a[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),m.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],f=a[o],m=a[o+2]-f,g=i[o],v=i[o+2]-g;p[o]=2*l/u*m/v,h[o]=2*(s-c)/u*m/v}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),m.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,m=p.text,g=p.font||\"sans-serif\";i=p.fontSize||12;for(var v=1/(c[o+2]-c[o]),y=c[o],x=m.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(g,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-y)*v);u.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=u,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},m.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":116,\"binary-search-bounds\":31,\"gl-buffer\":78,\"gl-shader\":132,\"text-cache\":303}],118:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=i(c),c.text=a(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),i=t(\"./lib/grid\"),a=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var m=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(m,e[1],m,e[3],p[d],h[d]):o.drawLine(e[0],m,e[2],m,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var g=this.borderLineEnable,v=this.borderLineWidth,y=this.borderLineColor;for(g[1]&&o.drawLine(r[0],r[1]-.5*v[1]*i,r[0],r[3]+.5*v[3]*i,v[1],y[1]),g[0]&&o.drawLine(r[0]-.5*v[0]*i,r[1],r[2]+.5*v[2]*i,r[1],v[0],y[0]),g[3]&&o.drawLine(r[2],r[1]-.5*v[1]*i,r[2],r[3]+.5*v[3]*i,v[3],y[3]),g[2]&&o.drawLine(r[0]-.5*v[0]*i,r[3],r[2]+.5*v[2]*i,r[3],v[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var f=c[u].pick(a,o,l);if(f)return f}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":113,\"./lib/grid\":114,\"./lib/line\":115,\"./lib/text\":117,\"gl-select-static\":131}],119:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;c.idle(e-r),c.recalcMatrix(i),c.flush(e-(100+2*r));for(var a=!0,o=c.computedMatrix,s=0;s<16;++s)a=a&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),i=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var a=n();c._active.lookAt(a,r,i,e),c._active.lookAt(a+500,r,i,[0,0,1]),c._active.flush(a)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,h=!!a.control,p=!!a.alt,m=!!a.shift,g=!!(1&e),v=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&g&&!h&&!p&&!m||g&&!h&&!p&&m)&&c.rotate(A,w*k*b,-T*k*_,0),(l&&g&&!h&&!p&&!m||v||g&&h&&!p&&!m)&&c.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),u&&g&&!h&&!p&&!m||y||g&&!h&&p&&!m)){var M=-d.zoomSpeed*_/window.innerHeight*(A-c.lastT())*100;c.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))c.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-c.lastT())/20;c.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),i=t(\"3d-view\"),a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":7,\"has-passive-events\":232,\"mouse-change\":247,\"mouse-event-offset\":248,\"mouse-wheel\":250,\"right-now\":278}],120:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n uv = position;\\n gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":132,glslify:231}],121:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),i=t(\"gl-axes3d\"),a=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),f=t(\"gl-mat4/perspective\"),h=t(\"gl-mat4/ortho\"),p=t(\"./lib/shader\"),d=t(\"is-mobile\")({tablet:!0,featureDetect:!0});function m(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function v(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e){if(e=document.createElement(\"canvas\"),t.container)t.container.appendChild(e);else document.body.appendChild(e)}var r=t.gl;r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!r)throw new Error(\"webgl not supported\");var y=t.bounds||[[-10,-10,-10],[10,10,10]],x=new m,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],I=!0,O=!0,z=new Array(16),D=new Array(16),R={view:null,projection:z,model:D,_ortho:!1},F=(O=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),B=t.cameraObject||n(e,T),N={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:B,axes:A,axesPixels:null,spikes:S,bounds:y,objects:E,shape:F,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:v(t.autoResize),autoBounds:v(t.autoBounds),autoScale:!!t.autoScale,autoCenter:v(t.autoCenter),clipToBounds:v(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:R,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,O=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},j=[r.drawingBufferWidth/N.pixelRatio|0,r.drawingBufferHeight/N.pixelRatio|0];function U(){if(!N._stopped&&N.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*N.pixelRatio),a=0|Math.ceil(n*N.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",I=!0}}}N.autoResize&&U();function V(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,F);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function H(){if(N.contextLost)return!0;r.isContextLost()&&(N.contextLost=!0,N.mouseListener.enabled=!1,N.selection.object=null,N.oncontextloss&&N.oncontextloss())}window.addEventListener(\"resize\",U),N.update=function(t){N._stopped||(t=t||{},I=!0,O=!0)},N.add=function(t){N._stopped||(t.axes=A,E.push(t),L.push(-1),I=!0,O=!0,V())},N.remove=function(t){if(!N._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),I=!0,O=!0,V())}},N.dispose=function(){if(!N._stopped&&(N._stopped=!0,window.removeEventListener(\"resize\",U),e.removeEventListener(\"webglcontextlost\",H),N.mouseListener.enabled=!1,!N.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();b.dispose();for(t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},N._mouseRotating=!1,N._prevButtons=0,N.enableMouseListeners=function(){N.mouseListener=u(e,(function(t,e,r){if(!N._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&N._prevButtons)N._mouseRotating=!0;else{N._mouseRotating&&(O=!0),N._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,j[1]-r-1,N.pickRadius);if(l){if(l.distance>x.distance)continue;for(var c=0;c<i;++c){var u=E[c];if(L[c]===s){var f=u.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=u,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),I=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),I=!0),(o=o||x.object!==a)&&N.onselect&&N.onselect(x),1&t&&!(1&N._prevButtons)&&N.onclick&&N.onclick(x),N._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",H);var q=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],G=[q[0].slice(),q[1].slice()];function Y(){if(!H()){U();var t=N.camera.tick();R.view=N.camera.matrix,I=I||t,O=O||t,A.pixelRatio=N.pixelRatio,S.pixelRatio=N.pixelRatio;var e=E.length,n=q[0],i=q[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=N.pixelRatio,C.axes=N.axes,I=I||!!C.dirty,O=O||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],u[p])}var d=N.bounds;if(N.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var m=.05*(i[p]-n[p]);n[p]=n[p]-m,i[p]=i[p]+m}d[0][p]=n[p],d[1][p]=i[p]}var v=!1;for(p=0;p<3;++p)v=v||G[0][p]!==d[0][p]||G[1][p]!==d[1][p],G[0][p]=d[0][p],G[1][p]=d[1][p];if(O=O||v,I=I||v){if(v){var y=[0,0,0];for(o=0;o<3;++o)y[o]=g((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:y}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;F[0]=T,F[1]=k,j[0]=0|Math.max(T/N.pixelRatio,1),j[1]=0|Math.max(k/N.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,c),n._ortho=!0):(f(i,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var m=0;for(d=0;d<3;++d)m=Math.max(m,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/m,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(N,w);for(o=0;o<e;++o){(C=E[o]).axesBounds=d,N.clipToBounds&&(C.clipBounds=d)}x.object&&(N.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),O&&(O=!1,function(){if(!H()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=j,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(R))}i.end()}}}()),N.axesPixels=a(N.axes,R,T,k),N.onrender&&N.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),N.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;A.enable&&(M=M||A.isTransparent(),A.draw(R)),S.axes=A,x.object&&S.draw(R),r.disable(r.CULL_FACE);for(o=0;o<e;++o){(C=E[o]).axes=A,C.pixelRatio=N.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(R),C.isTransparent&&C.isTransparent()&&(M=!0)}if(M){b.shape=F,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(R)}r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(R)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,c(r),r.disable(r.BLEND)}I=!1;for(o=0;o<e;++o)E[o].dirty=!1}}}return N.enableMouseListeners(),function t(){if(N._stopped||N.contextLost)return;Y(),requestAnimationFrame(t)}(),N.redraw=function(){N._stopped||(I=!0,Y())},N},createCamera:n}},{\"./camera.js\":119,\"./lib/shader\":120,\"a-big-triangle\":8,\"gl-axes3d\":70,\"gl-axes3d/properties\":77,\"gl-fbo\":86,\"gl-mat4/ortho\":101,\"gl-mat4/perspective\":102,\"gl-select-static\":131,\"gl-spikes3d\":141,\"is-mobile\":238,\"mouse-change\":247}],122:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n highp float a = 12.9898;\\n highp float b = 78.233;\\n highp float c = 43758.5453;\\n highp float d = dot(co.xy, vec2(a, b));\\n highp float e = mod(d, 3.14);\\n return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n // if we don't jitter the point size a bit, overall point cloud\\n // saturation 'jumps' on zooming, which is disturbing and confusing\\n gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n if(pointCloud != 0.0) { // pointCloud is truthy\\n // get the same square surface as circle would be\\n gl_PointSize *= 0.886;\\n }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n float radius;\\n vec4 baseColor;\\n if(pointCloud != 0.0) { // pointCloud is truthy\\n if(centerFraction == 1.0) {\\n gl_FragColor = color;\\n } else {\\n gl_FragColor = mix(borderColor, color, centerFraction);\\n }\\n } else {\\n radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n baseColor = mix(borderColor, color, step(radius, centerFraction));\\n gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n gl_PointSize = pointSize;\\n\\n vec4 id = pickId + pickOffset;\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:231}],123:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,a=i(r),l=i(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),f=new s(t,a,l,c,u);return f.update(e),t.addObject(f),f};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),c=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),i||a.free(l),o||a.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":122,\"gl-buffer\":78,\"gl-shader\":132,\"typedarray-pool\":308}],124:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],f=e[2],h=e[3],p=r[0],d=r[1],m=r[2],g=r[3];(a=c*p+u*d+f*m+h*g)<0&&(a=-a,p=-p,d=-d,m=-m,g=-g);1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*f+l*m,t[3]=s*h+l*g,t}},{}],125:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],126:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var a=i[e];a||(a=i[e]={});if(t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=u.positions.length;for(l=0;l<h;++l){var p=u.positions[l];for(c=0;c<2;++c)f[0][c]=Math.min(f[0][c],p[c]),f[1][c]=Math.max(f[1][c],p[c])}return a[t]=[s,u,f]};var i={}},{\"vectorize-text\":311}],127:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = 1.0;\\n if(distance(highlightId, id) < 0.0001) {\\n scale = highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1);\\n vec4 viewPosition = view * worldPosition;\\n viewPosition = viewPosition / viewPosition.w;\\n vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = pixelRatio;\\n if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n scale *= highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1.0);\\n vec4 viewPosition = view * worldPosition;\\n vec4 clipPosition = projection * viewPosition;\\n clipPosition /= clipPosition.w;\\n\\n gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float lscale = pixelRatio * scale;\\n if(distance(highlightId, id) < 0.0001) {\\n lscale *= highlightScale;\\n }\\n\\n vec4 clipCenter = projection * view * model * vec4(position, 1);\\n vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = dataPosition;\\n }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (\\n outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n interpColor.a * opacity == 0.\\n ) discard;\\n gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:u},h={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:a,fragment:c,attributes:u},m={vertex:o,fragment:c,attributes:u},g={vertex:s,fragment:c,attributes:u};function v(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}r.createPerspective=function(t){return v(t,f)},r.createOrtho=function(t){return v(t,h)},r.createProject=function(t){return v(t,p)},r.createPickPerspective=function(t){return v(t,d)},r.createPickOrtho=function(t){return v(t,m)},r.createPickProject=function(t){return v(t,g)}},{\"gl-shader\":132,glslify:231}],128:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function m(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,c,u,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),m=a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new g(e,r,n,o,f,h,p,d,m,s,c,u);return v.update(t),v};var v=g.prototype;v.pickSlots=1,v.setPickBase=function(t){this.pickId=t},v.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},v.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function L(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||f,u=r.view||f,h=r.projection||f,d=e.axesBounds,m=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=h,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=m,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var v=T,L=0;L<16;++L)v[L]=0;for(L=0;L<4;++L)v[5*L]=1;v[5*g]=0,i[g]<0?v[12+g]=d[0][g]:v[12+g]=d[1][g],s(v,c,v),l.model=v;var C=(g+1)%3,P=(g+2)%3,I=M(x),O=M(b);I[C]=1,O[P]=1;var z=p(0,0,0,S(_,I)),D=p(0,0,0,S(w,O));if(Math.abs(z[1])>Math.abs(D[1])){var R=z;z=D,D=R,R=I,I=O,O=R;var F=C;C=P,P=F}z[0]<0&&(I[C]=-1),D[1]>0&&(O[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(c[4*C+L],2),N+=Math.pow(c[4*P+L],2);I[C]/=Math.sqrt(B),O[P]/=Math.sqrt(N),l.axes[0]=I,l.axes[1]=O,l.fragClipBounds[0]=E(k,m[0],g,-1e8),l.fragClipBounds[1]=E(k,m[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var C=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function P(t,e,r,n,i,a,o){var s=r.gl;if((a===r.projectHasAlpha||o)&&L(e,r,n,i),a===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||f,l.view=n.view||f,l.projection=n.projection||f,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=C,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=i,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*i),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function I(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=u(a);var o=!0;n(a)&&(a=\"\\u25bc\",o=!1);var s=c(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}v.draw=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},v.drawTransparent=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},v.drawPick=function(t){P(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},v.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},v.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},v.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in 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i=0|Math.min(Math.max(t-r,0),n[0]),o=0|Math.min(Math.max(t+r,0),n[0]),l=0|Math.min(Math.max(e-r,0),n[1]),c=0|Math.min(Math.max(e+r,0),n[1]);if(o<=i||c<=l)return null;var u=[o-i,c-l],f=a(this.buffer,[u[0],u[1],4],[4,4*n[0],1],4*(i+n[0]*l)),h=function(t,e,r){for(var n=1e8,i=-1,a=-1,o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++){var u=t.get(l,c,0),f=t.get(l,c,1),h=t.get(l,c,2),p=t.get(l,c,3);if(u<255||f<255||h<255||p<255){var d=e-l,m=r-c,g=d*d+m*m;g<n&&(n=g,i=l,a=c)}}return[i,a,n]}(f.hi(u[0],u[1],1),r,r),p=h[0],d=h[1];return p<0||Math.pow(this.radius,2)<h[2]?null:new s(p+i|0,d+l|0,f.get(p,d,0),[f.get(p,d,1),f.get(p,d,2),f.get(p,d,3)],Math.sqrt(h[2]))},c.dispose=function(){this.gl&&(this.fbo.dispose(),i.free(this.buffer),this.gl=null,this._readTimeout&&clearTimeout(this._readTimeout))}},{\"bit-twiddle\":32,\"gl-fbo\":86,ndarray:259,\"typedarray-pool\":308}],132:[function(t,e,r){\"use strict\";var 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w=c[y];if(w.type.indexOf(\"mat\")>=0){for(var T=0|w.type.charAt(w.type.length-1),k=new Array(T),A=0;A<T;++A)k[A]=_.length,b.push(w.name+\"[\"+A+\"]\"),\"number\"==typeof w.location?_.push(w.location+A):Array.isArray(w.location)&&w.location.length===T&&\"number\"==typeof w.location[A]?_.push(0|w.location[A]):_.push(-1);x.push({name:w.name,type:w.type,locations:k})}else x.push({name:w.name,type:w.type,locations:[_.length]}),b.push(w.name),\"number\"==typeof w.location?_.push(0|w.location):_.push(-1)}var M=0;for(y=0;y<_.length;++y)if(_[y]<0){for(;_.indexOf(M)>=0;)M+=1;_[y]=M}var S=new Array(r.length);function E(){h.program=o.program(p,h._vref,h._fref,b,_);for(var t=0;t<r.length;++t)S[t]=p.getUniformLocation(h.program,r[t].name)}E(),h._relink=E,h.types={uniforms:a(r),attributes:a(c)},h.attributes=i(p,h,x,_),Object.defineProperty(h,\"uniforms\",n(p,h,r,S))},e.exports=function(t,e,r,n,i){var a=new c(t);return 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to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * tubePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(tubePosition, 1.0);\\n vec4 t_position = view * tubePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = tubePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n gl_Position = projection * view * tubePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:231}],143:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=t(\"gl-vec4\"),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],f=[],h=[],p=[],d=[],m=0,g=0,v=i.create(),y=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),g=n.length(_)/a,v=i.create(),n.copy(v,_),v[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;c.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(y,v,v,v,y,y),d.push(m,g,g,g,m,m);var A=c.length;u.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=y;y=v,v=S;var E=m;m=g,g=E}return{positions:c,cells:u,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<u.length;s++){var m=u[s],g=f.length;f=f.concat(m.positions),p=p.concat(m.vectors),d=d.concat(m.vertexIntensity);for(c=0;c<m.cells.length;c++){var v=m.cells[c],y=[];h.push(y);for(var x=0;x<v.length;x++)y.push(v[x]+g)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};e.exports=function(t,e){var r=t.startingPositions,i=t.maxLength||1e3,u=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,o=t[0],c=t[1],u=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=s(a[0],o),m=s(a[1],c),g=s(a[2],u),v=d+1,y=m+1,x=g+1;if(d=l(d,0,f-1),v=l(v,0,f-1),m=l(m,0,h-1),y=l(y,0,h-1),g=l(g,0,p-1),x=l(x,0,p-1),d<0||m<0||g<0||v>f-1||y>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][v],E=a[1][m],L=a[1][y],C=a[2][g],P=(o-M)/(S-M),I=(c-E)/(L-E),O=(u-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(I)||(I=.5),isFinite(O)||(O=.5),r.reversedX&&(d=f-1-d,v=f-1-v),r.reversedY&&(m=h-1-m,y=h-1-y),r.reversedZ&&(g=p-1-g,x=p-1-x),r.filled){case 5:k=g,A=x,w=m*p,T=y*p,b=d*p*h,_=v*p*h;break;case 4:k=g,A=x,b=d*p,_=v*p,w=m*p*f,T=y*p*f;break;case 3:w=m,T=y,k=g*h,A=x*h,b=d*h*p,_=v*h*p;break;case 2:w=m,T=y,b=d*h,_=v*h,k=g*h*f,A=x*h*f;break;case 1:b=d,_=v,k=g*f,A=x*f,w=m*f*p,T=y*f*p;break;default:b=d,_=v,w=m*f,T=y*f,k=g*f*h,A=x*f*h}var z=i[b+w+k],D=i[b+w+A],R=i[b+T+k],F=i[b+T+A],B=i[_+w+k],N=i[_+w+A],j=i[_+T+k],U=i[_+T+A],V=n.create(),H=n.create(),q=n.create(),G=n.create();n.lerp(V,z,B,P),n.lerp(H,D,N,P),n.lerp(q,R,j,P),n.lerp(G,F,U,P);var Y=n.create(),W=n.create();n.lerp(Y,V,q,I),n.lerp(W,H,G,I);var X=n.create();return n.lerp(X,Y,W,O),X}(e,t,p)},m=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},g=[],v=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<v||e>b||r<y||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/i,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,l=0;l<s;l++){var u=t[l],f=u[0],h=u[1],p=u[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),m=c(r),g=c(n),v=Math.min(d,m,g);return isFinite(v)?v:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],I=[],O=d(C),z=C;I.push(O);var D=[],R=m(C,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),g.push({points:P,velocities:I,divergences:D});for(var B=0;B<100*i&&P.length<i&&T(C);){B++;var N=n.clone(O),j=n.squaredLength(N);if(0===j)break;if(j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),O=d(N),n.squaredDistance(z,N)-A>-1e-4*A){P.push(N),z=N,I.push(O);R=m(N,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}C=N}}var U=o(g,t.colormap,S,M);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*u*M/S),U};var u=t(\"./lib/shaders\"),f=t(\"gl-cone3d\").createMesh;e.exports.createTubeMesh=function(t,e){return f(t,e,{shaders:u,traceType:\"streamtube\"})}},{\"./lib/shaders\":142,\"gl-cone3d\":79,\"gl-vec3\":169,\"gl-vec4\":205}],144:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n vec3 localCoordinate = vec3(uv.zw, f.x);\\n worldCoordinate = objectOffset + localCoordinate;\\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n vec4 clipPosition = projection * view * worldPosition;\\n gl_Position = clipPosition;\\n kill = f.y;\\n value = f.z;\\n planeCoordinate = uv.xy;\\n\\n vColor = texture2D(colormap, vec2(value, value));\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * worldPosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n lightDirection = lightPosition - cameraCoordinate.xyz;\\n eyeDirection = eyePosition - cameraCoordinate.xyz;\\n surfaceNormal = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness) {\\n return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n if (\\n kill > 0.0 ||\\n vColor.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n ) discard;\\n\\n vec3 N = normalize(surfaceNormal);\\n vec3 V = normalize(eyeDirection);\\n vec3 L = normalize(lightDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n //decide how to interpolate color \\u2014 in vertex or in fragment\\n vec4 surfaceColor =\\n step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n step(.5, vertexColor) * vColor;\\n\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n worldCoordinate = objectOffset + dataCoordinate;\\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n vec4 clipPosition = projection * view * worldPosition;\\n clipPosition.z += zOffset;\\n\\n gl_Position = clipPosition;\\n value = f + objectOffset.z;\\n kill = -1.0;\\n planeCoordinate = uv.zw;\\n\\n vColor = texture2D(colormap, vec2(value, value));\\n\\n //Don't do lighting for contours\\n surfaceNormal = vec3(1,0,0);\\n eyeDirection = vec3(0,1,0);\\n lightDirection = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n float vh = 255.0 * v;\\n float upper = floor(vh);\\n float lower = fract(vh);\\n return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n if ((kill > 0.0) ||\\n (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":132,glslify:231}],145:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=i(e),u=a(e,[{buffer:c,size:4,stride:40,offset:0},{buffer:c,size:3,stride:40,offset:16},{buffer:c,size:3,stride:40,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),m=o(e,1,256,e.RGBA,e.UNSIGNED_BYTE);m.minFilter=e.LINEAR,m.magFilter=e.LINEAR;var g=new M(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,m,s,l,f,h,p,d,[0,0,0]),v={levels:[[],[],[]]};for(var w in t)v[w]=t[w];return v.colormap=v.colormap||\"jet\",g.update(v),g};var n=t(\"bit-twiddle\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),f=t(\"ndarray\"),h=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),m=t(\"binary-search-bounds\"),g=t(\"ndarray-gradient\"),v=t(\"./lib/shaders\"),y=v.createShader,x=v.createContourShader,b=v.createPickShader,_=v.createPickContourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],k=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function A(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=k[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();function M(t,e,r,n,i,a,o,l,c,u,h,p,d,m,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new A([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=m,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var S=M.prototype;S.genColormap=function(t,e){var r=!1,n=u([l({colormap:t,nshades:256,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return c.divseq(n,255),this.hasAlphaScale=r,n},S.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},S.isOpaque=function(){return!this.isTransparent()},S.pickSlots=1,S.setPickBase=function(t){this.pickId=t};var E=[0,0,0],L={showSurface:!1,showContour:!1,projections:[w.slice(),w.slice(),w.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function C(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||E,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=L.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=L.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return L.showSurface=o,L.showContour=s,L}var P={model:w,view:w,projection:w,inverseModel:w.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},I=w.slice(),O=[1,0,0,0,1,0,0,0,1];function z(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=P;n.model=t.model||w,n.view=t.view||w,n.projection=t.projection||w,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=O,n.vertexColor=this.vertexColor;var s=I;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=C(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=k[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=u.projections[i],f.uniforms.clipBounds=u.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=k[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var m=0;m<this.contourLevels[o].length;++m)m===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==m&&m-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][m]&&(f.uniforms.height=this.contourLevels[o][m],h.draw(r.LINES,this._contourCounts[o][m],this._contourOffsets[o][m]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=k[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=u.projections[o],f.uniforms.clipBounds=u.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}S.draw=function(t){return z.call(this,t,!1)},S.drawTransparent=function(t){return z.call(this,t,!0)};var D={model:w,view:w,projection:w,inverseModel:w,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function R(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function F(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function B(t){if(Array.isArray(t)){if(Array.isArray(t))return[F(t[0]),F(t[1]),F(t[2])];var e=F(t);return[e.slice(),e.slice(),e.slice()]}}S.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=D;r.model=t.model||w,r.view=t.view||w,r.projection=t.projection||w,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=O;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=C(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=k[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=k[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(s.uniforms.height=this.contourLevels[a][c],l.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}l.unbind()}},S.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var f=u?a:1-a,h=0;h<2;++h)for(var p=i+u,d=s+h,g=f*(h?l:1-l),v=0;v<3;++v)c[v]+=this._field[v].get(p,d)*g;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=m.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},S.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},S.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=R(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=R(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=R(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=B(t.contourColor)),\"contourProject\"in t&&(this.contourProject=R(t.contourProject,(function(t){return R(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=B(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=R(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=R(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=l[o];for(v=0;v<2;++v)if(c.shape[v]!==a[v])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],c)}}else if(t.ticks){var u=t.ticks;if(!Array.isArray(u)||2!==u.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=u[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var m=[0,0];m[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],m,0)}this._field[0].set(0,0,0);for(var v=0;v<a[0];++v)this._field[0].set(v+1,0,v);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),v=0;v<a[1];++v)this._field[1].set(0,v+1,v);this._field[1].set(0,a[1]+1,a[1]-1)}var y=this._field,x=f(s.mallocFloat(3*y[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)g(x.pick(o),y[o],\"mirror\");var b=f(s.mallocFloat(3*y[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(v=0;v<a[1]+2;++v){var _=x.get(0,o,v,0),w=x.get(0,o,v,1),k=x.get(1,o,v,0),A=x.get(1,o,v,1),M=x.get(2,o,v,0),S=x.get(2,o,v,1),E=k*S-A*M,L=M*w-S*_,C=_*A-w*k,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,v,0,E*P),b.set(o,v,1,L*P),b.set(o,v,2,C*P)}s.free(x.data);var I=[1/0,1/0,1/0],O=[-1/0,-1/0,-1/0],z=1/0,D=-1/0,F=(a[0]-1)*(a[1]-1)*6,N=s.mallocFloat(n.nextPow2(10*F)),j=0,U=0;for(o=0;o<a[0]-1;++o)t:for(v=0;v<a[1]-1;++v){for(var V=0;V<2;++V)for(var H=0;H<2;++H)for(var q=0;q<3;++q){var G=this._field[q].get(1+o+V,1+v+H);if(isNaN(G)||!isFinite(G))continue t}for(q=0;q<6;++q){var Y=o+T[q][0],W=v+T[q][1],X=this._field[0].get(Y+1,W+1),Z=this._field[1].get(Y+1,W+1);G=this._field[2].get(Y+1,W+1),E=b.get(Y+1,W+1,0),L=b.get(Y+1,W+1,1),C=b.get(Y+1,W+1,2),t.intensity&&(J=t.intensity.get(Y,W));var J=t.intensity?t.intensity.get(Y,W):G+this.objectOffset[2];N[j++]=Y,N[j++]=W,N[j++]=X,N[j++]=Z,N[j++]=G,N[j++]=0,N[j++]=J,N[j++]=E,N[j++]=L,N[j++]=C,I[0]=Math.min(I[0],X+this.objectOffset[0]),I[1]=Math.min(I[1],Z+this.objectOffset[1]),I[2]=Math.min(I[2],G+this.objectOffset[2]),z=Math.min(z,J),O[0]=Math.max(O[0],X+this.objectOffset[0]),O[1]=Math.max(O[1],Z+this.objectOffset[1]),O[2]=Math.max(O[2],G+this.objectOffset[2]),D=Math.max(D,J),U+=1}}for(t.intensityBounds&&(z=+t.intensityBounds[0],D=+t.intensityBounds[1]),o=6;o<j;o+=10)N[o]=(N[o]-z)/(D-z);this._vertexCount=U,this._coordinateBuffer.update(N.subarray(0,j)),s.freeFloat(N),s.free(b.data),this.bounds=[I,O],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===z&&this.intensityBounds[1]===D||(r=!0),this.intensityBounds=[z,D]}if(\"levels\"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(v=0;v<K[o].length;++v)K[o][v]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(v=0;v<K[o].length;++v)if(K[o][v]!==this.contourLevels[o][v]){r=!0;break t}}this.contourLevels=K}if(r){y=this._field,a=this.shape;for(var Q=[],$=0;$<3;++$){var tt=this.contourLevels[$],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[$],tt[o]);et.push(Q.length/5|0),U=0;t:for(v=0;v<it.cells.length;++v){var at=it.cells[v];for(q=0;q<2;++q){var ot=it.positions[at[q]],st=ot[0],lt=0|Math.floor(st),ct=st-lt,ut=ot[1],ft=0|Math.floor(ut),ht=ut-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var mt=($+dt+1)%3;for(V=0;V<2;++V){var gt=V?ct:1-ct;for(Y=0|Math.min(Math.max(lt+V,0),a[0]),H=0;H<2;++H){var vt=H?ht:1-ht;if(W=0|Math.min(Math.max(ft+H,0),a[1]),G=dt<2?this._field[mt].get(Y,W):(this.intensity.get(Y,W)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var yt=gt*vt;nt[dt]+=yt*G}}}if(pt){if(q>0){for(var xt=0;xt<5;++xt)Q.pop();U-=1}continue t}Q.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[$]=et,this._contourCounts[$]=rt}var bt=s.mallocFloat(Q.length);for(o=0;o<Q.length;++o)bt[o]=Q[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},S.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},S.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],f=this._field[l],p=this._field[c],d=h(u,r[o]),m=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<m.length;++e)for(var v=m[e],y=0;y<2;++y){var x=g[v[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,L=1-E,C=k*L,P=k*E,I=T*L,O=T*E,z=C*f.get(_,M)+P*f.get(_,S)+I*f.get(w,M)+O*f.get(w,S),D=C*p.get(_,M)+P*p.get(_,S)+I*p.get(w,M)+O*p.get(w,S);if(isNaN(z)||isNaN(D)){y&&(n-=1);break}a[2*n+0]=z,a[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},{\"./lib/shaders\":144,\"binary-search-bounds\":31,\"bit-twiddle\":32,colormap:53,\"gl-buffer\":78,\"gl-mat4/invert\":98,\"gl-mat4/multiply\":100,\"gl-texture2d\":146,\"gl-vao\":150,ndarray:259,\"ndarray-gradient\":252,\"ndarray-ops\":254,\"ndarray-pack\":255,\"surface-nets\":302,\"typedarray-pool\":308}],146:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"ndarray-ops\"),a=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");o||c(t);if(\"number\"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return v(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return y(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return x(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var f=function(t,e){i.muls(t,e,255)};function h(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function p(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var d=p.prototype;function m(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function g(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new p(t,o,e,r,n,i)}function y(t,e,r,n,i,a){var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new p(t,o,r,n,i,a)}function x(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=m(o,e.stride.slice()),c=0;\"float32\"===r?c=t.FLOAT:\"float64\"===r?(c=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?c=t.UNSIGNED_BYTE:(c=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var u,h,d=0;if(2===o.length)d=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])d=t.ALPHA;else if(2===o[2])d=t.LUMINANCE_ALPHA;else if(3===o[2])d=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");d=t.RGBA}}c!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(c=t.UNSIGNED_BYTE,l=!1);var v=e.size;if(l)u=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var y=[o[2],o[2]*o[0],1];h=a.malloc(v,r);var x=n(h,o,y,0);\"float32\"!==r&&\"float64\"!==r||c!==t.UNSIGNED_BYTE?i.assign(x,e):f(x,e),u=h.subarray(0,v)}var b=g(t);return t.texImage2D(t.TEXTURE_2D,0,d,o[0],o[1],0,d,c,u),l||a.free(h),new p(t,b,o[0],o[1],d,c)}Object.defineProperties(d,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=this.gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;e<2;++e)if(l.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return h(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return h(this,t|=0,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t|=0,h(this,this._shape[0],t),t}}}),d.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},d.dispose=function(){this.gl.deleteTexture(this.handle)},d.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},d.setPixels=function(t,e,r,o){var s=this.gl;this.bind(),Array.isArray(e)?(o=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),o=o||0;var l=u(t)?t:t.raw;if(l){this._mipLevels.indexOf(o)<0?(s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,this.type,l),this._mipLevels.push(o)):s.texSubImage2D(s.TEXTURE_2D,o,e,r,this.format,this.type,l)}else{if(!(t.shape&&t.stride&&t.data))throw new Error(\"gl-texture2d: Unsupported data type\");if(t.shape.length<2||e+t.shape[1]>this._shape[1]>>>o||r+t.shape[0]>this._shape[0]>>>o||e<0||r<0)throw new Error(\"gl-texture2d: Texture dimensions are out of bounds\");!function(t,e,r,o,s,l,c,u){var h=u.dtype,p=u.shape.slice();if(p.length<2||p.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var d=0,g=0,v=m(p,u.stride.slice());\"float32\"===h?d=t.FLOAT:\"float64\"===h?(d=t.FLOAT,v=!1,h=\"float32\"):\"uint8\"===h?d=t.UNSIGNED_BYTE:(d=t.UNSIGNED_BYTE,v=!1,h=\"uint8\");if(2===p.length)g=t.LUMINANCE,p=[p[0],p[1],1],u=n(u.data,p,[u.stride[0],u.stride[1],1],u.offset);else{if(3!==p.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===p[2])g=t.ALPHA;else if(2===p[2])g=t.LUMINANCE_ALPHA;else if(3===p[2])g=t.RGB;else{if(4!==p[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}p[2]}g!==t.LUMINANCE&&g!==t.ALPHA||s!==t.LUMINANCE&&s!==t.ALPHA||(g=s);if(g!==s)throw new Error(\"gl-texture2d: Incompatible texture format for setPixels\");var y=u.size,x=c.indexOf(o)<0;x&&c.push(o);if(d===l&&v)0===u.offset&&u.data.length===y?x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,u.data):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,u.data):x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,u.data.subarray(u.offset,u.offset+y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,u.data.subarray(u.offset,u.offset+y));else{var b;b=l===t.FLOAT?a.mallocFloat32(y):a.mallocUint8(y);var _=n(b,p,[p[2],p[2]*p[0],1]);d===t.FLOAT&&l===t.UNSIGNED_BYTE?f(_,u):i.assign(_,u),x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,b.subarray(0,y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,b.subarray(0,y)),l===t.FLOAT?a.freeFloat32(b):a.freeUint8(b)}}(s,e,r,o,this.format,this.type,this._mipLevels,t)}}},{ndarray:259,\"ndarray-ops\":254,\"typedarray-pool\":308}],147:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){e?e.bind():t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null);var n=0|t.getParameter(t.MAX_VERTEX_ATTRIBS);if(r){if(r.length>n)throw new Error(\"gl-vao: Too many vertex attributes\");for(var i=0;i<r.length;++i){var a=r[i];if(a.buffer){var o=a.buffer,s=a.size||4,l=a.type||t.FLOAT,c=!!a.normalized,u=a.stride||0,f=a.offset||0;o.bind(),t.enableVertexAttribArray(i),t.vertexAttribPointer(i,s,l,c,u,f)}else{if(\"number\"==typeof a)t.vertexAttrib1f(i,a);else if(1===a.length)t.vertexAttrib1f(i,a[0]);else if(2===a.length)t.vertexAttrib2f(i,a[0],a[1]);else if(3===a.length)t.vertexAttrib3f(i,a[0],a[1],a[2]);else{if(4!==a.length)throw new Error(\"gl-vao: Invalid vertex attribute\");t.vertexAttrib4f(i,a[0],a[1],a[2],a[3])}t.disableVertexAttribArray(i)}}for(;i<n;++i)t.disableVertexAttribArray(i)}else{t.bindBuffer(t.ARRAY_BUFFER,null);for(i=0;i<n;++i)t.disableVertexAttribArray(i)}}},{}],148:[function(t,e,r){\"use strict\";var n=t(\"./do-bind.js\");function 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+ "/*!\n",
+ " * Determine if an object is a Buffer\n",
+ " *\n",
+ " * @author Feross Aboukhadijeh <https://feross.org>\n",
+ " * @license MIT\n",
+ " */\n",
+ "e.exports=function(t){return null!=t&&(n(t)||function(t){return\"function\"==typeof t.readFloatLE&&\"function\"==typeof t.slice&&n(t.slice(0,0))}(t)||!!t._isBuffer)}},{}],238:[function(t,e,r){\"use strict\";e.exports=a,e.exports.isMobile=a,e.exports.default=a;var n=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,i=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino|android|ipad|playbook|silk/i;function a(t){t||(t={});var 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+ "/*!\n",
+ " * pad-left <https://github.com/jonschlinkert/pad-left>\n",
+ " *\n",
+ " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+ " * Licensed under the MIT license.\n",
+ " */\n",
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m=t[s];i[m[0]]&&i[m[1]]&&d.push([h[m[0]],h[m[1]]])}return[d,p]};var n=t(\"edges-to-adjacency-list\")},{\"edges-to-adjacency-list\":66}],268:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=c(t,e);t=r[0];for(var f=(e=r[1]).length,h=(t.length,n(t,e.length)),p=0;p<f;++p)if(h[p].length%2==1)throw new Error(\"planar-graph-to-polyline: graph must be manifold\");var d=i(t,e);var m=(d=d.filter((function(t){for(var r=t.length,n=[0],i=0;i<r;++i){var a=e[t[i]],l=e[t[(i+1)%r]],c=o(-a[0],a[1]),u=o(-a[0],l[1]),f=o(l[0],a[1]),h=o(l[0],l[1]);n=s(n,s(s(c,u),s(f,h)))}return n[n.length-1]>0}))).length,g=new Array(m),v=new Array(m);for(p=0;p<m;++p){g[p]=p;var y=new Array(m),x=d[p].map((function(t){return e[t]})),b=a([x]),_=0;t:for(var w=0;w<m;++w)if(y[w]=0,p!==w){for(var T=(H=d[w]).length,k=0;k<T;++k){var A=b(e[H[k]]);if(0!==A){A<0&&(y[w]=1,_+=1);continue t}}y[w]=1,_+=1}v[p]=[_,p,y]}v.sort((function(t,e){return e[0]-t[0]}));for(p=0;p<m;++p){var 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e=this.computedUp,r=this.computedRight,n=0,i=0,a=0;a<3;++a)i+=e[a]*r[a],n+=e[a]*e[a];var l=Math.sqrt(n),u=0;for(a=0;a<3;++a)r[a]-=e[a]*i/n,u+=r[a]*r[a],e[a]/=l;var f=Math.sqrt(u);for(a=0;a<3;++a)r[a]/=f;var h=this.computedToward;o(h,e,r),s(h,h);var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],m=this.computedAngle[1],g=Math.cos(d),v=Math.sin(d),y=Math.cos(m),x=Math.sin(m),b=this.computedCenter,_=g*y,w=v*y,T=x,k=-g*x,A=-v*x,M=y,S=this.computedEye,E=this.computedMatrix;for(a=0;a<3;++a){var L=_*r[a]+w*h[a]+T*e[a];E[4*a+1]=k*r[a]+A*h[a]+M*e[a],E[4*a+2]=L,E[4*a+3]=0}var C=E[1],P=E[5],I=E[9],O=E[2],z=E[6],D=E[10],R=P*D-I*z,F=I*O-C*D,B=C*z-P*O,N=c(R,F,B);R/=N,F/=N,B/=N,E[0]=R,E[4]=F,E[8]=B;for(a=0;a<3;++a)S[a]=b[a]+E[2+4*a]*p;for(a=0;a<3;++a){u=0;for(var j=0;j<3;++j)u+=E[a+4*j]*S[j];E[12+a]=-u}E[15]=1},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r};var d=[0,0,0];p.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;d[0]=i[2],d[1]=i[6],d[2]=i[10];for(var o=this.computedUp,s=this.computedRight,l=this.computedToward,c=0;c<3;++c)i[4*c]=o[c],i[4*c+1]=s[c],i[4*c+2]=l[c];a(i,i,n,d);for(c=0;c<3;++c)o[c]=i[4*c],s[c]=i[4*c+1];this.up.set(t,o[0],o[1],o[2]),this.right.set(t,s[0],s[1],s[2])}},p.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=(Math.exp(this.computedRadius[0]),i[1]),o=i[5],s=i[9],l=c(a,o,s);a/=l,o/=l,s/=l;var u=i[0],f=i[4],h=i[8],p=u*a+f*o+h*s,d=c(u-=a*p,f-=o*p,h-=s*p),m=(u/=d)*e+a*r,g=(f/=d)*e+o*r,v=(h/=d)*e+s*r;this.center.move(t,m,g,v);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+n),this.radius.set(t,Math.log(y))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var a=1;\"number\"==typeof r&&(a=0|r),(a<0||a>3)&&(a=1);var o=(a+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[a],l=e[a+4],f=e[a+8];if(n){var h=Math.abs(s),p=Math.abs(l),d=Math.abs(f),m=Math.max(h,p,d);h===m?(s=s<0?-1:1,l=f=0):d===m?(f=f<0?-1:1,s=l=0):(l=l<0?-1:1,s=f=0)}else{var g=c(s,l,f);s/=g,l/=g,f/=g}var v,y,x=e[o],b=e[o+4],_=e[o+8],w=x*s+b*l+_*f,T=c(x-=s*w,b-=l*w,_-=f*w),k=l*(_/=T)-f*(b/=T),A=f*(x/=T)-s*_,M=s*b-l*x,S=c(k,A,M);if(k/=S,A/=S,M/=S,this.center.jump(t,q,G,Y),this.radius.idle(t),this.up.jump(t,s,l,f),this.right.jump(t,x,b,_),2===a){var E=e[1],L=e[5],C=e[9],P=E*x+L*b+C*_,I=E*k+L*A+C*M;v=R<0?-Math.PI/2:Math.PI/2,y=Math.atan2(I,P)}else{var O=e[2],z=e[6],D=e[10],R=O*s+z*l+D*f,F=O*x+z*b+D*_,B=O*k+z*A+D*M;v=Math.asin(u(R)),y=Math.atan2(B,F)}this.angle.jump(t,y,v),this.recalcMatrix(t);var N=e[2],j=e[6],U=e[10],V=this.computedMatrix;i(V,e);var H=V[15],q=V[12]/H,G=V[13]/H,Y=V[14]/H,W=Math.exp(this.computedRadius[0]);this.center.jump(t,q-N*W,G-j*W,Y-U*W)},p.lastT=function(){return 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+ "source": [
+ "#checking BMI values\n",
+ "\n",
+ "ax= px.treemap(df1,path=['BMI'],title=\"BMI counts\")\n",
+ "ax.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
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+ {
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///yjnj17KiIiQpJUokQJNWjQQIUKFVJcXJyuX7+u7du36/79+5LiR5aXK1dOPXv2TLbOZcuWaf/+/ZKkGjVqyNXVVdmyZdO5c+e0detWRUdH6969e+rfv782bNiQZER9wvP/woULkiQ7Ozs1bdpU5cuX18OHD7Vt2zZduXJFY8eOVa5cuZ7FbUkXV1dXI0Cwd+/edB0bFxenXr166ejRo5Ike3t7NWrUSGXLllW2bNkUGBioAwcO6NSpU5Liv4+DBg3SqlWrZG1tecXTl+XZl9iWLVs0aNAgIxBXqlQpNWzYUAUKFFBQUJB8fX11/vx5hYSEaPDgwXr06JExg1CCqKgo9e3b1wgPFClSRI0bN1aRIkUUHh6u8+fPa/v27YqLi9ORI0c0cODAJDPmAAAAAC8TAgQAAAAAnqnTp0/r448/Nv7nfbFixSx2ZJ06dUqTJk2SJGXLlk0TJ05MUm7UqFHy8fHRjBkzFB0draFDh+qvv/5KV4ff3LlzjfBA1apVNW/ePOXOndtiuW+++UaStH37dt2+fduYTrlhw4Zq2LChwsPDjQBBgwYNknQ6pObSpUv69NNPjc76jh07atSoUWbLM4wYMUKLFy/WpEmTFBsbqyVLlqhGjRp68803LdZ5584dSfFrq0+ePNlsivQhQ4bo008/NTotf/rppyQBgtmzZxvtGTt2rDp37my232Qyadq0aUYH5g8//JBigCAsLEzly5fXzJkzVbp0aWP74MGDNXPmTHl7exttef/999M8hXZiCTMjlChRQnPmzFHZsmXNrnnkyJHauHGjoqOjNXbsWK1bt+6JzpMgoUO0VatWmjhxorJnz27su3Hjhvr06aMLFy7owYMHGj9+vH744Qez40NDQ/XRRx8ZHWg9e/bURx99lKRN27dv15AhQxQaGqqZM2eqVq1aRvimfPnyKl++vPbv3290opUvXz5J52vDhg21atUqxcTE6MCBA/Lw8DDbf/PmzSSzNhw8eNBs/fUECQGCrFmzms3kkBHXk2DLli1GeMDR0VHTp09PMmvEp59+qq+//lqLFy9WaGioBg4cqDVr1iT7mR48eFBZsmTRhAkT1KFDB7N9H3zwgbp166Zbt24pNDRUv/32m/r27WuxnqdlMpkUERGhgIAA7dy5U3PmzNHDhw9lZWWlyZMnp3kJhYoVK6p06dK6evVqqssY/PXXX5LiZ31xc3PT9evXM+x6UvPll18av5WOHTvq888/T7IczKNHjzRixAijk3zZsmUpBgj279+v7Nmza+rUqUm+yydPnlSPHj0UGhqqGzduaOPGjWrTpo1ZmR9++MEIDxQvXlw+Pj565ZVXjP1Dhw7VzJkzNWvWLAUHBz/5xWeQxLMBJPzdSquVK1ca4YHixYtr8eLFFpfB+euvvzR06FDFxcXp3LlzOnr0qF599VWLdb5Mzz4p/vk2cuRIRUdHy9raWiNGjFC3bt3MAhIjRozQ77//rrFjxxp/I6pXr272d2Tjxo26ePGipPhQx9y5c5U1a1azc504cULdu3dXeHi4Dhw4oCNHjqhmzZoW7yMAAADworMcKQYAAACAFNy6dUvz5s2z+G/u3Ln67rvvNG7cOHl6eqp9+/bGqL1cuXJpxowZFjv6vv32WyNk8MUXX1gMGWTJkkV9+/Y1Ruo+ePBAixcvTlfbEzrPJWnixIkWwwOS1KtXL7MpmBNGaWak77//3rjm5s2ba/z48WbhAUmysrKSl5eXhg4damybMWOG2fTdjytVqpSmT59uFh6QJBsbG40ZM8bo9Ll69apu3bplVubYsWOS4tdLfzw8kNCejz/+2BhZGhAQkGRa6MSyZ88uHx8fs/BAggEDBqhEiRKSpIcPHxode0/C3t5e8+bNM+v0STj/tGnTVKlSJUnxo2yXL1/+xOdJ4OLioilTpph1oEnxAZkff/zR2L5t27Yk1/Xrr78a65Z36NBBw4cPt/ibaNy4scaNGycpvvN55syZ6W5n48aNjdeWRjAn3pbwfT948KARIkkQGBiokydPSoqfQSTxdWfU9ZhMJk2fPl1S/Pfs+++/t7jkRNasWTV69GhjJomrV69qzZo1ydyBeL17904SHpCkkiVLmi3tkN5R3slxdnZO8q9ChQqqUaOGmjdvrgkTJuju3bsqWrSofvzxR2P0dFolTLOesIyBJdHR0dq0aZNR/vHO+2fp+vXrxhIBBQoU0GeffWbx/Pb29vr888+N5TCuXbumhw8fplj3J598kiQ8IMUHwnr06GG8f/yzDAoK0k8//SRJsrW11axZs8zCA1L835hBgwalOwz2rCRe7ufhw4dJlpVJycqVK43Xn376qcXwgCS1bt1aDRo0MN6n9rfuZXn2SfHLXSQshzRw4ED16NHD4uwKnp6e+vDDDyVJkZGRRkAuwfHjx43X3bt3TxIekKRq1aoZ378sWbIYM+wAAAAALyMCBAAAAADSzd/fX19//bXFf998842+//57/fLLLzp58qTREVmnTh0tW7ZM1apVS1LfnTt3tGvXLknx01wnN7o+QeKp7v/88880tzsqKkoDBgxQ//791atXrxSnPZdktj80NDTN50mLiIgIo3PPyspKw4cPT7F8jx49VKxYMUnxIz0fn3Y+sfbt21vs4JCkHDlyGEstSErS+Z+w/nhYWJjOnz9vsQ4rKystWLBAvr6+Onr0aIojp1u2bJlsx5WVlZXc3NyM94+HGdKjS5cuKlWqlMV9NjY2Zt+Zv//++4nPk2Do0KHJdsgWLVpU7du3N94/3rn9+++/G6/79euX4nneeOMNI3xx8OBBi2vJp6R+/frGuvcpBQhKliyp5s2bS4oP5iSMtk3g6+uruLg4SUmXL8io6zl69KjR4ejq6qpatWqlWFf//v2N16k9B7p06ZLsvsTfwYTp/p+XsLAw7d69W4GBgek6LnHgYMOGDRbL7N69W0FBQUnKPw+2trb6/PPP9d5772nQoEEpzviRL18+5c+f33ifUoAgR44catu2bbL7U/osd+3apaioKEmSh4dHis//QYMGJTuN//P0eCd9wueZFp06ddKHH36ojh07qlGjRimWTXwvUgtwvCzPvqioKOO5YG9vr3fffTfF8u+++65xv9evX298VySZXW/CrA6WdO/eXRs3btTx48fNwiwAAADAy4YlDAAAAAA8M/Xq1ZObm5s8PDySrEucWOIRzwkjxVNSqFAhFStWTDdu3ND169d1584dFSpUKNXj7OzszDo3UnLv3j2zTr30jPxMi6NHjxodFJUqVTJG4ifH2tpazZs3N0bQHjx40BiB/ThLIY3EEi/5kLiTRJJq166tzZs3KzY2Vu+88466desmDw8PVaxY0RglLCnZzvrHpTaFc+KOw6cJaaS0DrwUP5W/ra2toqOjdejQIUVERChbtmxPdK58+fKl2rnduHFjYw3sQ4cOGdsDAgKMGTny5MljhEJS4uLiYhxz+PBhi+uKJydXrlxycXHRgQMHdOHCBd29e9cs8JEQRHFzczP73hw4cMDsN5uwfIFkHiDIyOtJGLEuSZUrV061nqpVqxqf6fHjxxUTE2MEYBIrUqSIChYsmGw9iX8PkZGRqZ43LZILBEVGRurBgwc6c+aMjhw5ouDgYC1YsEAbNmzQ/Pnzk8ygkRwnJyeVK1dOFy9eTHYZg4TlC4oWLfrcp1IvVKhQiqGNxC5duqTY2FjjfUqzq1SsWDHFMEJKn+WePXuM14lH3FtSuHBhVapU6ZnMPJMejz+f0xNqsDSLjyXBwcHG0jdSyvf/ZXr2nT59WuHh4ZKksmXLpvq8t7OzU5UqVXTgwAFFRkbq1KlTxu+mdu3aWrBggaT45Y1u3Lihtm3bys3NzSzk4ejoKEdHxzS3EQAAAHhRESAAAAAAkG6urq5GB4EUP8Xwo0ePdObMGc2ePduYTeD8+fPq3LlziuEBSWajnTdu3JjqzACPu3nzZpoCBJbcv39fV65ckb+/v/z8/HTp0iWdOXMm3etNp1fitcgrVKiQpmMSl/P390+2XGprqSdeJiFhVHmCDz/8UHv27FF4eLiCg4Pl7e0tb29v5cuXT/Xq1VODBg3UsGHDNHeSJO7QsyRxh+/jbUkrW1vbVL8zdnZ2KlGihC5fvqyYmBgFBASoZMmST3S+tHw/Ey9/ce3aNeP1pUuXjNeBgYFP9F1PL3d3dx04cEBSfCdqwgjuS5cuGTNQuLq6qkaNGrKyspLJZNLBgwfVtWtXSfG/b19fX0nxYZfChQs/k+tJ/ByYP3++5s+fn+Z6IiIi9ODBA4tBgcQhFUtS+j08KUvrsT/u3LlzGjJkiC5cuKDbt2+rb9++Wrt2bbKzhzyuZcuW8vb2NpYxSByiiYyM1JYtWyTFzz6QOPyTGUwmk65fvy4/Pz/j34ULF/TPP//o/v37ScomJ7XPMnEn8eOfZcLU+ZLSFNRwcnLK9ABBwvT7CXLlyvXEdQUHB+vKlSvG/b9y5YrOnj2rS5cumd3zlO7/y/TsS/w8OXXq1BOdLyFA4OHhIVdXV+M5un79eq1fv162traqWbOmGjRooEaNGsnJySld5wAAAABeVAQIAAAAADw1KysrZc+eXa+++qp8fHw0adIk/fzzz7p7964++OADTZo0KcU1pYODg5/q/I93sqQmNDRUP//8s1auXJliR3yWLFnMRsZmpMSzG+TOnTtNx+TJk8d4ndI9S8/I+sc7iypUqKCffvpJn3zyiVmHz/3797V69WqtXr1aNjY2eu2119StW7dUp8Z+fFT0s+Dg4GBx5PnjEt/ne/fuPXGAIC2fl4ODg/E68WeVninILXmS30qjRo301VdfSYqfcSAhQJB4SQM3NzflyZNHzs7OOnv2rNlsACdPntSDBw8kJV2+ICOvJyOeA5YCBIkDAi8SZ2dn+fj4qEWLFoqIiJCfn59+//13I7iRmoQAgRTfoZk4QLB9+3aFhYVJSn12jmfJ399fPj4+2rBhQ4qfr7W1dZrCG0/zWSYOKiT+fSYn8fM2syT87qT4Nqc0+4IlUVFRWrp0qZYvX57skjRS2v/WvUzPvqd9niQ+3traWrNmzdKECRP0559/Gn83o6OjtX//fu3fv19TpkxR6dKl1b59e3l5eb2wzx0AAAAgLQgQAAAAAMhQVlZWGjVqlPz9/bV161ZJ0ujRo1WoUCHVq1fP4jGJOy6aNGmiV199NV3nTFgnOS0uXbqk999/32w0qhQ/Er5EiRJycnJStWrVVLduXS1cuFArV65MV1ueRFpHBye+T89yRHGNGjW0du1a7dmzR3///bd27Nih27dvG/tjYmLk6+srX19fdejQQV988UWmjnBOS3hAMr9/tra2z6o5ksyDGYk7/RK3wcnJSW+99Va66k3L1P6PK1u2rEqWLCk/Pz+z0EDC69KlSxszeLi5uens2bO6d++eLl26pLJly5otX9C4cWOzujPyehLX1a5dO7ORzGmR2mwXL6IiRYqoVatWWrFihSRp27ZtaQ4QlC1bVs7Ozjp37lySZQwSli8oU6ZMmpaFeRY2bdqkIUOGJFlKwN7eXmXKlFGFChXk4uKi+vXr65133knyTM5o6X1GPetnRFqcPn3aeJ3ez/Hu3bvq1auXzp49a7bd2tpaxYoVU/ny5VW1alW5ubnJ19dXs2bNypA2vyjPvsTnq1Wrljw8PNJ1fI0aNcze58qVS1999ZUGDBigv/76S1u3btWpU6fMgi9Xr17V1KlTtWzZMi1atChdSy4AAAAALxICBAAAAAAynJWVlSZNmqQ2bdooICBAMTExGjFihFavXm2xky/xiMVy5cqlafrvJxEVFaUPP/zQ6KgqWbKkevTooVq1aumVV15J0mH06NGjZ9IOyXwkZ+LZCFKSuFxaRtA+DWtra9WvX1/169eXFB+82Ldvn3x9fbV7926jU3D58uWqVatWujuDMtLDhw/TVC7xiFJLI9Uz8nyJz5X4s078ueXIkeOZfdcf16hRIy1atEi3bt3S5cuXVbp0aWM6bjc3N6Ocm5ubfv75Z0nSgQMHVLZsWWNJkgIFCqhq1apm9Wbk9SSuq0aNGurYseMT1/UySTy1euKlTdKiVatWOnfunCIjI7Vt2za98cYbCgsL044dOyRl3uwDV65c0dChQ43nhJubmzp27Khq1aqpePHiSTrzn+WzNkH+/Pl14cIFSWkbDR8aGvqMW5S6Y8eOGa8f79BOzdChQ43wQP78+fXuu+/qtddeU/ny5ZMsk5Gw3EVqXqZnX+LzFS5cOMPOV7JkSfXr10/9+vVTcHCwDh48qN27d2vr1q1G0O769esaNWqU8SwFAAAAXjbWmd0AAAAAAP9Ojo6OGj9+vPH+7t27+vzzzy2WLVGihPH6xIkTaao/KCgoxbWaLdm8ebMxLX/hwoWN6cKdnZ0tjjZNPH10es+VmsTT5587dy5Nx5w5c8Z4nfiePQ9ly5ZV165dNXv2bO3cuVOvvfaasW/16tXPtS2PCw8PN5shwZJHjx4Zy1Vkz55d+fLle+Lz+fn5pVom8Wdavnx543Xiz+3s2bOKiopKta6HDx8qJiYmna00l3jmgL179+rcuXPG0h+JAwSurq7KkiWLpPgAQVBQkPGbbNy4cZKO34y8nid5DqQ1fPMis7b+v/81k57lR6T4ZQwSbNy4UVL8LAYRERGS4gMGmWHBggVGG9zd3fXzzz+rdevWKlGiRJLvUExMjNkyNBn9rE1QrFgx43VanrmJl3DJDNevX9e+ffuM96+//nqajz1+/LhxbPbs2bVs2TL16tVLVapUSRIekNL+O3qZnn1P8jwJDg5O01IaCXLnzq2mTZvq888/1/bt2/XJJ58Y+/bt26c7d+6kvcEAAADAC4QAAQAAAIBnxt3d3awD6++//9a2bduSlKtVq5bx+tChQ6n+T/f79++rfv36ql69ulq2bGnW0Z+SxKM5W7RokeJ6zhEREWadDpY6FZ5m2v7q1asboYV//vkn1Y6ZuLg4bd682Xhfs2bNJz53co4cOaK+ffuqWbNmyYY9pPhwyEcffWS8T63z/nlIPM2+Jdu2bTM+w0aNGqV52QNL/Pz8jDBCcv7++2/jdeLvd5kyZZQ/f35J8aGGxJ9pcry8vFStWjV5eHgkuc60fgddXV2VPXt2SdLu3bt16NAhs30JcuXKpYoVK0qS9u/fL19fX+O+ubu7J6k3I68n8X3avHlzqqPSz5w5o9dee00uLi5q3779U4csMkviDtfEndxpUapUKWNq9507d+rRo0fasGGDpPgp78uWLZtxDU2H48ePG687dOiQ4vf08OHDZp9dejpw0yNxiCa17+nDhw/N/l5kBh8fH+NeVKpUKV1LGCRue7169VS8ePFky5pMJmM2Einl+/8yPftcXFyM57yfn1+qIYKoqCi1bNlS1apVU/PmzY3ZG2JjYzVixAi1a9dO9erVSzb4YGVlpe7du5stqUSAAAAAAC8rAgQAAAAAnqlPPvlEuXLlMt5/8cUXSToGy5Ytq2rVqkmSoqOjNXny5BTr/PbbbxUdHa3IyEjlyJEjzWufJ/4f/6mNuJw+fboxglaSxc7JxCOHE6+3nBbZs2c3RpSaTCZNmTIlxfILFy7UrVu3JMWv9V6nTp10nS8t7O3ttW3bNvn5+WnLli0pTuF9//5943WhQoUyvC3pNW/ePLPPK7GoqCjNnj3beJ8Ro7K//fbbZPedO3dOa9askRS/jnrbtm3N9ide7mHGjBkp3ue1a9fqzJkzio2N1b1795IsIZDW76CdnZ3q1q0rKX5mgf3790uK/+0VKFDArGzCjAT379/XTz/9JEnKmjWrcfzjMup66tSpo8KFC0uKn2Hk+++/T7YeSZo6daqk+Bkoihcv/lShkMxy7949o8NfUrrXaZf+bxaCiIgIbdiwwVhyIrNmH5DS/qyNiYlJ8ux7VkGQBg0aGH+L9u7dqz179iRbdu7cuc9lWYXkbN68WUuXLjXeDxkyJF3Hp+dv3aJFi8yWzkjt/r8sz74cOXKoWbNmxvtJkyal+Iz86aefdP/+fUVHRys8PFzlypWTJGXJkkVnz57V6dOnde/evRSXe4iLizNbHuNF+NsIAAAAPAkCBAAAAACeqQIFCmjw4MHG+xs3bmjmzJlJyg0cONAYUbhu3Tp9/vnnSTqEY2Nj5ePjo2XLlhnbPvzwwzS3pUKFCsbrDRs2WBxhGh4ergkTJmjBggVm2y11JuXMmdN4fePGjTS3I0GfPn1kZ2cnKX768TFjxiQ5j8lk0q+//qqvv/7a2DZixAjjuIxUsWJFY5Tr3bt3NXToULOpxRPcu3dP33zzjfG+efPmGd6W9Lp69aoGDhyYpL0PHz7UwIEDdf78eUnxo+0Tdyo9qTVr1mjGjBlJpls/e/as+vTpo+joaElS586dk3Qi9ejRQ46OjpKka9euqVevXhZHqu7cudNsJoh33nlHefLkMSuTnu9gwgjshw8fauvWrZLMZx9IkHhJg1OnTkmK79y3t7e3WG9GXY+tra369+9vvPfx8dHMmTOTdGhGRkZqwoQJRke5jY2N+vXrl+x1v6ju3LmjDz74wOhELVy4sNmSBGmV+JipU6cqIiJCVlZWmRogSPys9fHxsThLzK1bt/Tuu+8mGRmeXBDoaWXLls34W2QymfTRRx+ZjbxPsGTJEv3444/PpA2pCQsL05w5c8xmePH09FT9+vXTVU/i+3/48GFt2rQpSZmoqCj98MMPSQJ7qQUnXqZnX79+/Yy/lUeOHNHAgQMVHBycpNyqVavk7e1tdlziQFL79u2N12PHjtXJkyeT1GEymTR58mQjQFC9enUCBAAAAHhpvXzxfAAAAAAvnc6dO2vFihVGZ+SCBQvUtm1bOTk5GWUaNGigvn37GiPFly5dqi1btsjDw0NFihTR3bt3tXv3bl29etU45p133lGjRo3S3I7WrVvru+++0/379xUZGakuXbrIw8ND5cqVk5WVlfz8/LRt2zaFhYVJiu/QTOgMSTyqMEHiaaHnz5+vqKgo5cqVS7Vr1zabujk5Tk5OGjNmjEaPHi2TyaRly5Zp69at8vDwUNGiRRUcHKxdu3bpwoULxjHt27c3G8WZ0T799FN169ZNsbGx2rZtm5o0aSJ3d3djhPfVq1fNZieoUqWKWedKZrG1tdWOHTvUvHlzvf766ypSpIhu3bqljRs3GiNw8+XLp/Hjxz/V0hNS/Od++/ZtzZ49Wxs2bJC7u7ty5cqls2fPauvWrcZ3plq1aho2bFiS4wsUKKCvv/5aAwYMUHR0tI4eParXX39d7u7uKleunMLCwnT8+HGzZQaqVKmiQYMGJamrWLFisrKykslk0uHDhzVs2DCVL19eBQsWTPI9adSokVE2YSRu4rBAglq1asnGxsas497S8gXP4no6duyoQ4cOafXq1ZIkb29vrVq1So0bN1a+fPl069Ytbdu2TQEBAcYxQ4YMMeswfRHMmzfP4vbY2FiFh4fr/Pnz8vX1VWRkpKT4EMQXX3xhLDORHsWLF1e1atV04sQJ3b17V5JUo0aNdC+HkJHeeecdrVu3TiaTSVevXlWzZs3UvHlzFS9eXGFhYTp//rz27NljfA8TP2tTGzH/NDp37qzt27dr586dCg4OVrdu3dSgQQNVr15d0dHR2rVrl06fPi1JKl26tNnfm6d19OhRi9+LmJgYBQUF6cqVKzp48KDZqHwPDw+NHTs23eeqW7euypcvrwsXLshkMumDDz5Q/fr1ValSJWXNmlU3btzQtm3bjHud2t+6BC/bs8/Z2dnsb+zmzZt14MABNWnSRKVKlVJgYKAOHjyof/75x6jX3d1dXbp0MTtXp06d9Pvvv+vcuXMKCgpShw4dVLduXTk5OSlv3ry6f/++fH19dfHiRUnxM76MHDkyDZ8UAAAA8GIiQAAAAADgmbO2tta4cePUoUMHxcXFKSYmRp9//rl++eUXs87cjz76SPny5dPUqVP16NEj3b1712y2gQRZsmRRr169zGY2SItcuXJp5sy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+ "text/plain": [
+ "<Figure size 2500x1700 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Suppress warnings\n",
+ "warnings.filterwarnings('ignore')\n",
+ "\n",
+ "# Set the style and context for the plot\n",
+ "sns.set(style=\"whitegrid\")\n",
+ "plt.figure(figsize=(25, 17))\n",
+ "\n",
+ "# Plot the BMI countplot for both categories\n",
+ "sns.countplot(x='BMI', hue='Diabetes_binary', data=df1, palette=[\"r\", \"g\"])\n",
+ "\n",
+ "# Add titles and labels\n",
+ "plt.title(\"Relationship between BMI and Diabetes\", fontsize=24)\n",
+ "plt.xlabel(\"BMI\", fontsize=20)\n",
+ "plt.ylabel(\"Count\", fontsize=20)\n",
+ "plt.legend(title='Diabetes Status', labels=[\"No Diabetes\", \"Diabetes\"], fontsize=16)\n",
+ "plt.xticks(fontsize=14)\n",
+ "plt.yticks(fontsize=14)\n",
+ "\n",
+ "# Show the plot\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 423
+ },
+ "id": "d6iKooqEGGpY",
+ "outputId": "a96b59d7-33c8-4dd2-dae5-aab106321e6c"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<Axes: >"
+ ]
+ },
+ "execution_count": 25,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# checking the outliers in BMI continuous feature\n",
+ "\n",
+ "sns.boxplot(df1[\"BMI\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "4LoTbDkRGJ1d",
+ "outputId": "7b987190-b5b4-4598-ef54-fc8493e9c19f"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "0.0 11650\n",
+ "1.0 545\n",
+ "Name: Diabetes_binary, dtype: int64"
+ ]
+ },
+ "execution_count": 26,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#checking Diabetic patient with BMI less than 20\n",
+ "\n",
+ "df1[(df1[\"BMI\"]<=20)][\"Diabetes_binary\"].value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "jX3GPH9JGOxn",
+ "outputId": "aa08537e-dc32-4cbd-c47b-f07b949eb135"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "len of BMI_2 : 215104\n"
+ ]
+ }
+ ],
+ "source": [
+ "#seconed groups BMI is greater than 20 and less than equal to 50\n",
+ "\n",
+ "BMI_2 = df1.iloc[np.where((df1[\"BMI\"]>20)&(df1[\"BMI\"]<=50))]\n",
+ "\n",
+ "print(\"len of BMI_2 : \", len(BMI_2))\n",
+ "\n",
+ "BMI_2 = pd.DataFrame(BMI_2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "wanB--QiGR04",
+ "outputId": "6c71cee2-7469-40af-f9e6-95037e073040"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "NOn-Diabetic 181255\n",
+ "Diabetic 33849\n",
+ "Name: Diabetes_binary_str, dtype: int64"
+ ]
+ },
+ "execution_count": 28,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#checking Diabetic patient with BMI (BMI>20 and BMI<=50)\n",
+ "\n",
+ "\n",
+ "df1[(df1[\"BMI\"]>20) & (df1[\"BMI\"]<=50)][\"Diabetes_binary_str\"].value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 704
+ },
+ "id": "ewDjKRNlGUd3",
+ "outputId": "446c8188-ec42-45cb-c2ca-b1f2c39f5cfa"
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1000x800 with 3 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# checking outliers in ontinuous feature variable GenHlth , MentHlth and PhysHlth\n",
+ "\n",
+ "plt.figure(figsize = (10,8))\n",
+ "for i,col in enumerate(['GenHlth', 'MentHlth', 'PhysHlth']):\n",
+ " plt.subplot(2,2,i+1)\n",
+ " sns.boxplot(x = col, data = df1)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "S9FLs0CkGj54"
+ },
+ "source": [
+ "# Preprocessing"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Handling Outliers"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "numeric_cols, categorical_cols = categorize_data(df1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#Box plots for numeric columns\n",
+ "for i in range (len(numeric_cols)):\n",
+ " plt.figure()\n",
+ " plt.title(numeric_cols[i])\n",
+ " sns.boxplot(x=df1[numeric_cols[i]], data=df1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Diabetes_binary 35097\n",
+ "HighBP 0\n",
+ "HighChol 0\n",
+ "CholCheck 9298\n",
+ "BMI 5638\n",
+ "Smoker 0\n",
+ "Stroke 10284\n",
+ "HeartDiseaseorAttack 23713\n",
+ "PhysActivity 0\n",
+ "Fruits 0\n",
+ "Veggies 47137\n",
+ "HvyAlcoholConsump 13950\n",
+ "AnyHealthcare 12389\n",
+ "NoDocbcCost 21323\n",
+ "GenHlth 12078\n",
+ "MentHlth 36162\n",
+ "PhysHlth 34346\n",
+ "DiffWalk 42625\n",
+ "Sex 0\n",
+ "Age 0\n",
+ "Education 0\n",
+ "Income 0\n"
+ ]
+ }
+ ],
+ "source": [
+ "# More insights into outliers\n",
+ "outliers = outliers_check(df1, numeric_cols)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Diabetes_binary</th>\n",
+ " <th>HighBP</th>\n",
+ " <th>HighChol</th>\n",
+ " <th>CholCheck</th>\n",
+ " <th>BMI</th>\n",
+ " <th>Smoker</th>\n",
+ " <th>Stroke</th>\n",
+ " <th>HeartDiseaseorAttack</th>\n",
+ " <th>PhysActivity</th>\n",
+ " <th>Fruits</th>\n",
+ " <th>Veggies</th>\n",
+ " <th>HvyAlcoholConsump</th>\n",
+ " <th>AnyHealthcare</th>\n",
+ " <th>NoDocbcCost</th>\n",
+ " <th>GenHlth</th>\n",
+ " <th>MentHlth</th>\n",
+ " <th>PhysHlth</th>\n",
+ " <th>DiffWalk</th>\n",
+ " <th>Sex</th>\n",
+ " <th>Age</th>\n",
+ " <th>Education</th>\n",
+ " <th>Income</th>\n",
+ " <th>Diabetes_binary_str</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>40.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>9.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>NOn-Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>25.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>7.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>NOn-Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>28.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>9.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>8.0</td>\n",
+ " <td>NOn-Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>27.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>11.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>NOn-Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>24.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>11.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>NOn-Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253675</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>45.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>7.0</td>\n",
+ " <td>NOn-Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253676</th>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>18.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>11.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253677</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>28.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>NOn-Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253678</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>23.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>7.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>NOn-Diabetic</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253679</th>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>25.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>9.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>Diabetic</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>229474 rows × 23 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Diabetes_binary HighBP HighChol CholCheck BMI Smoker Stroke \\\n",
+ "0 0.0 1.0 1.0 1.0 40.0 1.0 0.0 \n",
+ "1 0.0 0.0 0.0 0.0 25.0 1.0 0.0 \n",
+ "2 0.0 1.0 1.0 1.0 28.0 0.0 0.0 \n",
+ "3 0.0 1.0 0.0 1.0 27.0 0.0 0.0 \n",
+ "4 0.0 1.0 1.0 1.0 24.0 0.0 0.0 \n",
+ "... ... ... ... ... ... ... ... \n",
+ "253675 0.0 1.0 1.0 1.0 45.0 0.0 0.0 \n",
+ "253676 1.0 1.0 1.0 1.0 18.0 0.0 0.0 \n",
+ "253677 0.0 0.0 0.0 1.0 28.0 0.0 0.0 \n",
+ "253678 0.0 1.0 0.0 1.0 23.0 0.0 0.0 \n",
+ "253679 1.0 1.0 1.0 1.0 25.0 0.0 0.0 \n",
+ "\n",
+ " HeartDiseaseorAttack PhysActivity Fruits Veggies \\\n",
+ "0 0.0 0.0 0.0 1.0 \n",
+ "1 0.0 1.0 0.0 0.0 \n",
+ "2 0.0 0.0 1.0 0.0 \n",
+ "3 0.0 1.0 1.0 1.0 \n",
+ "4 0.0 1.0 1.0 1.0 \n",
+ "... ... ... ... ... \n",
+ "253675 0.0 0.0 1.0 1.0 \n",
+ "253676 0.0 0.0 0.0 0.0 \n",
+ "253677 0.0 1.0 1.0 0.0 \n",
+ "253678 0.0 0.0 1.0 1.0 \n",
+ "253679 1.0 1.0 1.0 0.0 \n",
+ "\n",
+ " HvyAlcoholConsump AnyHealthcare NoDocbcCost GenHlth MentHlth \\\n",
+ "0 0.0 1.0 0.0 5.0 0.0 \n",
+ "1 0.0 0.0 1.0 3.0 0.0 \n",
+ "2 0.0 1.0 1.0 5.0 0.0 \n",
+ "3 0.0 1.0 0.0 2.0 0.0 \n",
+ "4 0.0 1.0 0.0 2.0 3.0 \n",
+ "... ... ... ... ... ... \n",
+ "253675 0.0 1.0 0.0 3.0 0.0 \n",
+ "253676 0.0 1.0 0.0 4.0 0.0 \n",
+ "253677 0.0 1.0 0.0 1.0 0.0 \n",
+ "253678 0.0 1.0 0.0 3.0 0.0 \n",
+ "253679 0.0 1.0 0.0 2.0 0.0 \n",
+ "\n",
+ " PhysHlth DiffWalk Sex Age Education Income Diabetes_binary_str \n",
+ "0 0.0 1.0 0.0 9.0 4.0 3.0 NOn-Diabetic \n",
+ "1 0.0 0.0 0.0 7.0 6.0 1.0 NOn-Diabetic \n",
+ "2 0.0 1.0 0.0 9.0 4.0 8.0 NOn-Diabetic \n",
+ "3 0.0 0.0 0.0 11.0 3.0 6.0 NOn-Diabetic \n",
+ "4 0.0 0.0 0.0 11.0 5.0 4.0 NOn-Diabetic \n",
+ "... ... ... ... ... ... ... ... \n",
+ "253675 5.0 0.0 1.0 5.0 6.0 7.0 NOn-Diabetic \n",
+ "253676 0.0 1.0 0.0 11.0 2.0 4.0 Diabetic \n",
+ "253677 0.0 0.0 0.0 2.0 5.0 2.0 NOn-Diabetic \n",
+ "253678 0.0 0.0 1.0 7.0 5.0 1.0 NOn-Diabetic \n",
+ "253679 0.0 0.0 0.0 9.0 6.0 2.0 Diabetic \n",
+ "\n",
+ "[229474 rows x 23 columns]"
+ ]
+ },
+ "execution_count": 33,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#remove outliers\n",
+ "removed_outliers=remove_outliers(df1, ['MentHlth', 'PhysHlth'])\n",
+ "(removed_outliers)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_before_split = removed_outliers.drop(\"Diabetes_binary_str\", axis=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Diabetes_binary</th>\n",
+ " <th>HighBP</th>\n",
+ " <th>HighChol</th>\n",
+ " <th>CholCheck</th>\n",
+ " <th>BMI</th>\n",
+ " <th>Smoker</th>\n",
+ " <th>Stroke</th>\n",
+ " <th>HeartDiseaseorAttack</th>\n",
+ " <th>PhysActivity</th>\n",
+ " <th>Fruits</th>\n",
+ " <th>Veggies</th>\n",
+ " <th>HvyAlcoholConsump</th>\n",
+ " <th>AnyHealthcare</th>\n",
+ " <th>NoDocbcCost</th>\n",
+ " <th>GenHlth</th>\n",
+ " <th>MentHlth</th>\n",
+ " <th>PhysHlth</th>\n",
+ " <th>DiffWalk</th>\n",
+ " <th>Sex</th>\n",
+ " <th>Age</th>\n",
+ " <th>Education</th>\n",
+ " <th>Income</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>40.0</td>\n",
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+ " <td>1.0</td>\n",
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+ " <td>0.0</td>\n",
+ " <td>9.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>3.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>25.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>3.0</td>\n",
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+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>7.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>1.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>28.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>9.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>8.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>27.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>11.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>6.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>24.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>11.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>4.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
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+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253675</th>\n",
+ " <td>0.0</td>\n",
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+ " <td>1.0</td>\n",
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+ " <td>45.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>7.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253676</th>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
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+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>11.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>4.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253677</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>28.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>2.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253678</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>23.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>7.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>1.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>253679</th>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>25.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>9.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>2.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>229474 rows × 22 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Diabetes_binary HighBP HighChol CholCheck BMI Smoker Stroke \\\n",
+ "0 0.0 1.0 1.0 1.0 40.0 1.0 0.0 \n",
+ "1 0.0 0.0 0.0 0.0 25.0 1.0 0.0 \n",
+ "2 0.0 1.0 1.0 1.0 28.0 0.0 0.0 \n",
+ "3 0.0 1.0 0.0 1.0 27.0 0.0 0.0 \n",
+ "4 0.0 1.0 1.0 1.0 24.0 0.0 0.0 \n",
+ "... ... ... ... ... ... ... ... \n",
+ "253675 0.0 1.0 1.0 1.0 45.0 0.0 0.0 \n",
+ "253676 1.0 1.0 1.0 1.0 18.0 0.0 0.0 \n",
+ "253677 0.0 0.0 0.0 1.0 28.0 0.0 0.0 \n",
+ "253678 0.0 1.0 0.0 1.0 23.0 0.0 0.0 \n",
+ "253679 1.0 1.0 1.0 1.0 25.0 0.0 0.0 \n",
+ "\n",
+ " HeartDiseaseorAttack PhysActivity Fruits Veggies \\\n",
+ "0 0.0 0.0 0.0 1.0 \n",
+ "1 0.0 1.0 0.0 0.0 \n",
+ "2 0.0 0.0 1.0 0.0 \n",
+ "3 0.0 1.0 1.0 1.0 \n",
+ "4 0.0 1.0 1.0 1.0 \n",
+ "... ... ... ... ... \n",
+ "253675 0.0 0.0 1.0 1.0 \n",
+ "253676 0.0 0.0 0.0 0.0 \n",
+ "253677 0.0 1.0 1.0 0.0 \n",
+ "253678 0.0 0.0 1.0 1.0 \n",
+ "253679 1.0 1.0 1.0 0.0 \n",
+ "\n",
+ " HvyAlcoholConsump AnyHealthcare NoDocbcCost GenHlth MentHlth \\\n",
+ "0 0.0 1.0 0.0 5.0 0.0 \n",
+ "1 0.0 0.0 1.0 3.0 0.0 \n",
+ "2 0.0 1.0 1.0 5.0 0.0 \n",
+ "3 0.0 1.0 0.0 2.0 0.0 \n",
+ "4 0.0 1.0 0.0 2.0 3.0 \n",
+ "... ... ... ... ... ... \n",
+ "253675 0.0 1.0 0.0 3.0 0.0 \n",
+ "253676 0.0 1.0 0.0 4.0 0.0 \n",
+ "253677 0.0 1.0 0.0 1.0 0.0 \n",
+ "253678 0.0 1.0 0.0 3.0 0.0 \n",
+ "253679 0.0 1.0 0.0 2.0 0.0 \n",
+ "\n",
+ " PhysHlth DiffWalk Sex Age Education Income \n",
+ "0 0.0 1.0 0.0 9.0 4.0 3.0 \n",
+ "1 0.0 0.0 0.0 7.0 6.0 1.0 \n",
+ "2 0.0 1.0 0.0 9.0 4.0 8.0 \n",
+ "3 0.0 0.0 0.0 11.0 3.0 6.0 \n",
+ "4 0.0 0.0 0.0 11.0 5.0 4.0 \n",
+ "... ... ... ... ... ... ... \n",
+ "253675 5.0 0.0 1.0 5.0 6.0 7.0 \n",
+ "253676 0.0 1.0 0.0 11.0 2.0 4.0 \n",
+ "253677 0.0 0.0 0.0 2.0 5.0 2.0 \n",
+ "253678 0.0 0.0 1.0 7.0 5.0 1.0 \n",
+ "253679 0.0 0.0 0.0 9.0 6.0 2.0 \n",
+ "\n",
+ "[229474 rows x 22 columns]"
+ ]
+ },
+ "execution_count": 35,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_before_split"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
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+ " .dataframe thead th {\n",
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+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>HighBP</th>\n",
+ " <th>HighChol</th>\n",
+ " <th>CholCheck</th>\n",
+ " <th>BMI</th>\n",
+ " <th>Smoker</th>\n",
+ " <th>Stroke</th>\n",
+ " <th>HeartDiseaseorAttack</th>\n",
+ " <th>PhysActivity</th>\n",
+ " <th>Fruits</th>\n",
+ " <th>Veggies</th>\n",
+ " <th>HvyAlcoholConsump</th>\n",
+ " <th>AnyHealthcare</th>\n",
+ " <th>NoDocbcCost</th>\n",
+ " <th>GenHlth</th>\n",
+ " <th>MentHlth</th>\n",
+ " <th>PhysHlth</th>\n",
+ " <th>DiffWalk</th>\n",
+ " <th>Sex</th>\n",
+ " <th>Age</th>\n",
+ " <th>Education</th>\n",
+ " <th>Income</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>218137</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>24.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>10.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>10.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>8.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>234092</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>22.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>13.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>4.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>220499</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>25.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>10.0</td>\n",
+ " <td>4.0</td>\n",
+ " <td>4.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>133305</th>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>24.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>10.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>1.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1394</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>28.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>12.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>2.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " HighBP HighChol CholCheck BMI Smoker Stroke \\\n",
+ "218137 0.0 0.0 1.0 24.0 0.0 0.0 \n",
+ "234092 0.0 0.0 1.0 22.0 0.0 0.0 \n",
+ "220499 0.0 0.0 1.0 25.0 0.0 0.0 \n",
+ "133305 1.0 1.0 1.0 24.0 1.0 0.0 \n",
+ "1394 0.0 1.0 1.0 28.0 0.0 0.0 \n",
+ "\n",
+ " HeartDiseaseorAttack PhysActivity Fruits Veggies \\\n",
+ "218137 0.0 1.0 1.0 1.0 \n",
+ "234092 0.0 1.0 1.0 1.0 \n",
+ "220499 0.0 1.0 1.0 1.0 \n",
+ "133305 1.0 0.0 0.0 0.0 \n",
+ "1394 0.0 0.0 0.0 0.0 \n",
+ "\n",
+ " HvyAlcoholConsump AnyHealthcare NoDocbcCost GenHlth MentHlth \\\n",
+ "218137 0.0 1.0 0.0 2.0 2.0 \n",
+ "234092 0.0 1.0 0.0 1.0 0.0 \n",
+ "220499 0.0 1.0 0.0 2.0 0.0 \n",
+ "133305 0.0 1.0 0.0 5.0 0.0 \n",
+ "1394 0.0 1.0 0.0 3.0 0.0 \n",
+ "\n",
+ " PhysHlth DiffWalk Sex Age Education Income \n",
+ "218137 10.0 0.0 0.0 10.0 6.0 8.0 \n",
+ "234092 0.0 0.0 0.0 13.0 5.0 4.0 \n",
+ "220499 0.0 0.0 1.0 10.0 4.0 4.0 \n",
+ "133305 0.0 1.0 0.0 10.0 3.0 1.0 \n",
+ "1394 0.0 0.0 0.0 12.0 3.0 2.0 "
+ ]
+ },
+ "execution_count": 36,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#Randomise the dataset\n",
+ "\n",
+ "data_randomized = data_before_split.sample(n=15000, random_state=42)\n",
+ "\n",
+ "#All features except the target are assigned to 'X'\n",
+ "#categorical_cols.remove('deposit')\n",
+ "X = data_randomized.drop(\"Diabetes_binary\", axis=1)\n",
+ "\n",
+ "#Target feature is assigned to 'Y'\n",
+ "Y = data_randomized[\"Diabetes_binary\"]\n",
+ "\n",
+ "X.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Rebalancing"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#split into train and test, then perform rebalancing on taining data\n",
+ "\n",
+ "x, xtest, y, ytest = train_test_split(X, Y, test_size=0.2, random_state=None)\n",
+ "xtrain, xval, ytrain, yval = train_test_split(x, y, test_size=0.3, random_state=None)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "0.0 12639\n",
+ "1.0 2361\n",
+ "Name: Diabetes_binary, dtype: int64"
+ ]
+ },
+ "execution_count": 38,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "Y.value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(2666, 21)"
+ ]
+ },
+ "execution_count": 39,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#Undersampling\n",
+ "\n",
+ "undersampling = RandomUnderSampler(random_state=42)\n",
+ "\n",
+ "xtrain_undersampled, ytrain_undersampled = undersampling.fit_resample(xtrain, ytrain)\n",
+ "\n",
+ "xtrain_undersampled.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(14134, 21)"
+ ]
+ },
+ "execution_count": 40,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#Oversampling\n",
+ "\n",
+ "oversampling = RandomOverSampler(random_state=42)\n",
+ "\n",
+ "xtrain_oversampled, ytrain_oversampled = oversampling.fit_resample(xtrain, ytrain)\n",
+ "\n",
+ "xtrain_oversampled.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled:\n",
+ " 0.0 1333\n",
+ "1.0 1333\n",
+ "Name: Diabetes_binary, dtype: int64\n",
+ "\n",
+ "Oversampled:\n",
+ " 0.0 7067\n",
+ "1.0 7067\n",
+ "Name: Diabetes_binary, dtype: int64\n"
+ ]
+ }
+ ],
+ "source": [
+ "#Target column is now balanced\n",
+ "\n",
+ "print(\"Undersampled:\\n\", ytrain_undersampled.value_counts())\n",
+ "\n",
+ "print(\"\\nOversampled:\\n\", ytrain_oversampled.value_counts())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Scaling"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(14134, 21)"
+ ]
+ },
+ "execution_count": 42,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#Scaling the data - oversampled dataset & undersampled\n",
+ "\n",
+ "cols_to_scale = [\"BMI\", \"Age\"]\n",
+ "\n",
+ "scaler = StandardScaler()\n",
+ "xtrain_oversampled[cols_to_scale] = scaler.fit_transform(xtrain_oversampled[cols_to_scale])\n",
+ "xtrain_undersampled[cols_to_scale] = scaler.fit_transform(xtrain_undersampled[cols_to_scale])\n",
+ "\n",
+ "\n",
+ "xtest[cols_to_scale] = scaler.transform(xtest[cols_to_scale])\n",
+ "xval[cols_to_scale] = scaler.transform(xval[cols_to_scale])\n",
+ "\n",
+ "\n",
+ "\n",
+ "xtrain_oversampled.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>HighBP</th>\n",
+ " <th>HighChol</th>\n",
+ " <th>CholCheck</th>\n",
+ " <th>BMI</th>\n",
+ " <th>Smoker</th>\n",
+ " <th>Stroke</th>\n",
+ " <th>HeartDiseaseorAttack</th>\n",
+ " <th>PhysActivity</th>\n",
+ " <th>Fruits</th>\n",
+ " <th>Veggies</th>\n",
+ " <th>HvyAlcoholConsump</th>\n",
+ " <th>AnyHealthcare</th>\n",
+ " <th>NoDocbcCost</th>\n",
+ " <th>GenHlth</th>\n",
+ " <th>MentHlth</th>\n",
+ " <th>PhysHlth</th>\n",
+ " <th>DiffWalk</th>\n",
+ " <th>Sex</th>\n",
+ " <th>Age</th>\n",
+ " <th>Education</th>\n",
+ " <th>Income</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.404203</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.511007</td>\n",
+ " <td>6.0</td>\n",
+ " <td>6.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.829915</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.579529</td>\n",
+ " <td>5.0</td>\n",
+ " <td>7.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.692791</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>-0.579529</td>\n",
+ " <td>6.0</td>\n",
+ " <td>8.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.404203</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.162584</td>\n",
+ " <td>5.0</td>\n",
+ " <td>1.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.267079</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.231107</td>\n",
+ " <td>6.0</td>\n",
+ " <td>7.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>14129</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.267079</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.814161</td>\n",
+ " <td>6.0</td>\n",
+ " <td>3.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>14130</th>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.104163</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>-1.624797</td>\n",
+ " <td>5.0</td>\n",
+ " <td>6.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>14131</th>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.418542</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>2.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.231107</td>\n",
+ " <td>4.0</td>\n",
+ " <td>7.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>14132</th>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.952700</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>3.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.465739</td>\n",
+ " <td>3.0</td>\n",
+ " <td>2.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>14133</th>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>-0.129955</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>5.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>6.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.162584</td>\n",
+ " <td>4.0</td>\n",
+ " <td>6.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>14134 rows × 21 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " HighBP HighChol CholCheck BMI Smoker Stroke \\\n",
+ "0 1.0 1.0 1.0 -0.404203 1.0 0.0 \n",
+ "1 1.0 0.0 1.0 0.829915 1.0 0.0 \n",
+ "2 0.0 0.0 1.0 0.692791 1.0 0.0 \n",
+ "3 1.0 0.0 1.0 -0.404203 1.0 0.0 \n",
+ "4 1.0 1.0 1.0 -0.267079 1.0 0.0 \n",
+ "... ... ... ... ... ... ... \n",
+ "14129 0.0 0.0 1.0 -0.267079 1.0 0.0 \n",
+ "14130 1.0 0.0 1.0 1.104163 0.0 0.0 \n",
+ "14131 1.0 1.0 1.0 0.418542 1.0 0.0 \n",
+ "14132 1.0 0.0 1.0 -0.952700 1.0 0.0 \n",
+ "14133 1.0 0.0 1.0 -0.129955 0.0 0.0 \n",
+ "\n",
+ " HeartDiseaseorAttack PhysActivity Fruits Veggies HvyAlcoholConsump \\\n",
+ "0 0.0 1.0 1.0 1.0 0.0 \n",
+ "1 0.0 1.0 0.0 1.0 0.0 \n",
+ "2 0.0 1.0 1.0 1.0 1.0 \n",
+ "3 1.0 0.0 0.0 0.0 0.0 \n",
+ "4 0.0 1.0 1.0 1.0 0.0 \n",
+ "... ... ... ... ... ... \n",
+ "14129 1.0 1.0 1.0 1.0 0.0 \n",
+ "14130 0.0 1.0 0.0 0.0 0.0 \n",
+ "14131 0.0 1.0 0.0 1.0 0.0 \n",
+ "14132 0.0 1.0 1.0 1.0 0.0 \n",
+ "14133 1.0 1.0 1.0 1.0 0.0 \n",
+ "\n",
+ " AnyHealthcare NoDocbcCost GenHlth MentHlth PhysHlth DiffWalk Sex \\\n",
+ "0 1.0 0.0 2.0 0.0 0.0 0.0 0.0 \n",
+ "1 1.0 0.0 3.0 0.0 0.0 0.0 1.0 \n",
+ "2 1.0 0.0 3.0 0.0 0.0 0.0 0.0 \n",
+ "3 1.0 0.0 5.0 0.0 0.0 1.0 0.0 \n",
+ "4 1.0 0.0 3.0 0.0 0.0 1.0 1.0 \n",
+ "... ... ... ... ... ... ... ... \n",
+ "14129 1.0 0.0 3.0 0.0 0.0 0.0 1.0 \n",
+ "14130 1.0 0.0 3.0 0.0 2.0 0.0 0.0 \n",
+ "14131 1.0 0.0 2.0 0.0 0.0 0.0 1.0 \n",
+ "14132 1.0 0.0 3.0 0.0 0.0 0.0 0.0 \n",
+ "14133 1.0 1.0 5.0 0.0 6.0 1.0 0.0 \n",
+ "\n",
+ " Age Education Income \n",
+ "0 1.511007 6.0 6.0 \n",
+ "1 -0.579529 5.0 7.0 \n",
+ "2 -0.579529 6.0 8.0 \n",
+ "3 1.162584 5.0 1.0 \n",
+ "4 -0.231107 6.0 7.0 \n",
+ "... ... ... ... \n",
+ "14129 0.814161 6.0 3.0 \n",
+ "14130 -1.624797 5.0 6.0 \n",
+ "14131 -0.231107 4.0 7.0 \n",
+ "14132 0.465739 3.0 2.0 \n",
+ "14133 1.162584 4.0 6.0 \n",
+ "\n",
+ "[14134 rows x 21 columns]"
+ ]
+ },
+ "execution_count": 43,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "xtrain_oversampled"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Dimensionality Reduction: Principal Compoent Analysis (PCA)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "num_components = len(xtrain.columns) - 4"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 45,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#PCA - oversampled dataset\n",
+ "\n",
+ "pca_undersampled = PCA(n_components=num_components)\n",
+ "\n",
+ "# Fit PCA on the training data\n",
+ "pca_undersampled.fit(xtrain_undersampled)\n",
+ "\n",
+ "# Transform training, validation and testing data\n",
+ "xtrain_pca_undersampled = pca_undersampled.transform(xtrain_undersampled)\n",
+ "xval_pca_undersampled = pca_undersampled.transform(xval)\n",
+ "xtest_pca_undersampled = pca_undersampled.transform(xtest)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 46,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Shape of xtrain_pca_undersampled: (14134, 17)\n",
+ "Shape of ytrain: (14134,)\n",
+ "Unique labels in ytrain: [0. 1.]\n",
+ "Number of unique labels: 2\n"
+ ]
+ }
+ ],
+ "source": [
+ "#PCA - oversampled dataset\n",
+ "\n",
+ "pca = PCA(n_components=num_components)\n",
+ "\n",
+ "# Fit PCA on the training data\n",
+ "pca.fit(xtrain_oversampled)\n",
+ "\n",
+ "# Transform training, validation and testing data\n",
+ "xtrain_pca_oversampled = pca.transform(xtrain_oversampled)\n",
+ "xval_pca_oversampled = pca.transform(xval)\n",
+ "xtest_pca_oversampled = pca.transform(xtest)\n",
+ "\n",
+ "print(\"Shape of xtrain_pca_undersampled:\", xtrain_pca_oversampled.shape)\n",
+ "print(\"Shape of ytrain:\", ytrain_oversampled.shape)\n",
+ "\n",
+ "# Print unique labels and their counts\n",
+ "print(\"Unique labels in ytrain:\", np.unique(ytrain))\n",
+ "print(\"Number of unique labels:\", len(np.unique(ytrain)))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Modelling"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Decision Tree"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 107,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "DT_models = []\n",
+ "DT_name = []\n",
+ "x_val_list = []\n",
+ "x_test_list = []"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 63,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ccp_alpha = 0.05\n",
+ "txt = \"ccp_alpha: 0.05\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 64,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<style>#sk-container-id-9 {\n",
+ " /* Definition of color scheme common for light and dark mode */\n",
+ " --sklearn-color-text: black;\n",
+ " --sklearn-color-line: gray;\n",
+ " /* Definition of color scheme for unfitted estimators */\n",
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
+ " /* Definition of color scheme for fitted estimators */\n",
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
+ "\n",
+ " /* Specific color for light theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-icon: #696969;\n",
+ "\n",
+ " @media (prefers-color-scheme: dark) {\n",
+ " /* Redefinition of color scheme for dark theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-icon: #878787;\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 pre {\n",
+ " padding: 0;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 input.sk-hidden--visually {\n",
+ " border: 0;\n",
+ " clip: rect(1px 1px 1px 1px);\n",
+ " clip: rect(1px, 1px, 1px, 1px);\n",
+ " height: 1px;\n",
+ " margin: -1px;\n",
+ " overflow: hidden;\n",
+ " padding: 0;\n",
+ " position: absolute;\n",
+ " width: 1px;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-dashed-wrapped {\n",
+ " border: 1px dashed var(--sklearn-color-line);\n",
+ " margin: 0 0.4em 0.5em 0.4em;\n",
+ " box-sizing: border-box;\n",
+ " padding-bottom: 0.4em;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-container {\n",
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+ " so we also need the `!important` here to be able to override the\n",
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+ " display: inline-block !important;\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-text-repr-fallback {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-parallel-item,\n",
+ "div.sk-serial,\n",
+ "div.sk-item {\n",
+ " /* draw centered vertical line to link estimators */\n",
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+ " background-size: 2px 100%;\n",
+ " background-repeat: no-repeat;\n",
+ " background-position: center center;\n",
+ "}\n",
+ "\n",
+ "/* Parallel-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-9 div.sk-parallel-item::after {\n",
+ " content: \"\";\n",
+ " width: 100%;\n",
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+ " flex-grow: 1;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-parallel {\n",
+ " display: flex;\n",
+ " align-items: stretch;\n",
+ " justify-content: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-parallel-item {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-parallel-item:first-child::after {\n",
+ " align-self: flex-end;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-parallel-item:last-child::after {\n",
+ " align-self: flex-start;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-parallel-item:only-child::after {\n",
+ " width: 0;\n",
+ "}\n",
+ "\n",
+ "/* Serial-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-9 div.sk-serial {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ " align-items: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " padding-right: 1em;\n",
+ " padding-left: 1em;\n",
+ "}\n",
+ "\n",
+ "\n",
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+ "clickable and can be expanded/collapsed.\n",
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+ "*/\n",
+ "\n",
+ "/* Pipeline and ColumnTransformer style (default) */\n",
+ "\n",
+ "#sk-container-id-9 div.sk-toggleable {\n",
+ " /* Default theme specific background. It is overwritten whether we have a\n",
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable label */\n",
+ "#sk-container-id-9 label.sk-toggleable__label {\n",
+ " cursor: pointer;\n",
+ " display: block;\n",
+ " width: 100%;\n",
+ " margin-bottom: 0;\n",
+ " padding: 0.5em;\n",
+ " box-sizing: border-box;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 label.sk-toggleable__label-arrow:before {\n",
+ " /* Arrow on the left of the label */\n",
+ " content: \"â–¸\";\n",
+ " float: left;\n",
+ " margin-right: 0.25em;\n",
+ " color: var(--sklearn-color-icon);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 label.sk-toggleable__label-arrow:hover:before {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable content - dropdown */\n",
+ "\n",
+ "#sk-container-id-9 div.sk-toggleable__content {\n",
+ " max-height: 0;\n",
+ " max-width: 0;\n",
+ " overflow: hidden;\n",
+ " text-align: left;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-toggleable__content.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-toggleable__content pre {\n",
+ " margin: 0.2em;\n",
+ " border-radius: 0.25em;\n",
+ " color: var(--sklearn-color-text);\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-toggleable__content.fitted pre {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+ " /* Expand drop-down */\n",
+ " max-height: 200px;\n",
+ " max-width: 100%;\n",
+ " overflow: auto;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+ " content: \"â–¾\";\n",
+ "}\n",
+ "\n",
+ "/* Pipeline/ColumnTransformer-specific style */\n",
+ "\n",
+ "#sk-container-id-9 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific style */\n",
+ "\n",
+ "/* Colorize estimator box */\n",
+ "#sk-container-id-9 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-label label.sk-toggleable__label,\n",
+ "#sk-container-id-9 div.sk-label label {\n",
+ " /* The background is the default theme color */\n",
+ " color: var(--sklearn-color-text-on-default-background);\n",
+ "}\n",
+ "\n",
+ "/* On hover, darken the color of the background */\n",
+ "#sk-container-id-9 div.sk-label:hover label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Label box, darken color on hover, fitted */\n",
+ "#sk-container-id-9 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator label */\n",
+ "\n",
+ "#sk-container-id-9 div.sk-label label {\n",
+ " font-family: monospace;\n",
+ " font-weight: bold;\n",
+ " display: inline-block;\n",
+ " line-height: 1.2em;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-label-container {\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific */\n",
+ "#sk-container-id-9 div.sk-estimator {\n",
+ " font-family: monospace;\n",
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
+ " border-radius: 0.25em;\n",
+ " box-sizing: border-box;\n",
+ " margin-bottom: 0.5em;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-estimator.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "/* on hover */\n",
+ "#sk-container-id-9 div.sk-estimator:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 div.sk-estimator.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+ "\n",
+ "/* Common style for \"i\" and \"?\" */\n",
+ "\n",
+ ".sk-estimator-doc-link,\n",
+ "a:link.sk-estimator-doc-link,\n",
+ "a:visited.sk-estimator-doc-link {\n",
+ " float: right;\n",
+ " font-size: smaller;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1em;\n",
+ " height: 1em;\n",
+ " width: 1em;\n",
+ " text-decoration: none !important;\n",
+ " margin-left: 1ex;\n",
+ " /* unfitted */\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted,\n",
+ "a:link.sk-estimator-doc-link.fitted,\n",
+ "a:visited.sk-estimator-doc-link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "/* Span, style for the box shown on hovering the info icon */\n",
+ ".sk-estimator-doc-link span {\n",
+ " display: none;\n",
+ " z-index: 9999;\n",
+ " position: relative;\n",
+ " font-weight: normal;\n",
+ " right: .2ex;\n",
+ " padding: .5ex;\n",
+ " margin: .5ex;\n",
+ " width: min-content;\n",
+ " min-width: 20ex;\n",
+ " max-width: 50ex;\n",
+ " color: var(--sklearn-color-text);\n",
+ " box-shadow: 2pt 2pt 4pt #999;\n",
+ " /* unfitted */\n",
+ " background: var(--sklearn-color-unfitted-level-0);\n",
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted span {\n",
+ " /* fitted */\n",
+ " background: var(--sklearn-color-fitted-level-0);\n",
+ " border: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link:hover span {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+ "\n",
+ "#sk-container-id-9 a.estimator_doc_link {\n",
+ " float: right;\n",
+ " font-size: 1rem;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1rem;\n",
+ " height: 1rem;\n",
+ " width: 1rem;\n",
+ " text-decoration: none;\n",
+ " /* unfitted */\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 a.estimator_doc_link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "#sk-container-id-9 a.estimator_doc_link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-9 a.estimator_doc_link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "</style><div id=\"sk-container-id-9\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(ccp_alpha=0.05)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" checked><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(ccp_alpha=0.05)</pre></div> </div></div></div></div>"
+ ],
+ "text/plain": [
+ "DecisionTreeClassifier(ccp_alpha=0.05)"
+ ]
+ },
+ "execution_count": 64,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#DecsionTree model - oversampled dataset\n",
+ "\n",
+ "# Initialize the decision tree classifier\n",
+ "clf_oversampled = DecisionTreeClassifier(ccp_alpha=ccp_alpha)\n",
+ "DT_models.append(clf_oversampled)\n",
+ "DT_name.append(f\"Oversampled dataset(No PCA), {txt}\")\n",
+ "x_val_list.append(xval)\n",
+ "x_test_list.append(xtest)\n",
+ "# Fit the classifier to the training data\n",
+ "clf_oversampled.fit(xtrain_oversampled, ytrain_oversampled)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 65,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<style>#sk-container-id-10 {\n",
+ " /* Definition of color scheme common for light and dark mode */\n",
+ " --sklearn-color-text: black;\n",
+ " --sklearn-color-line: gray;\n",
+ " /* Definition of color scheme for unfitted estimators */\n",
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
+ " /* Definition of color scheme for fitted estimators */\n",
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
+ "\n",
+ " /* Specific color for light theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-icon: #696969;\n",
+ "\n",
+ " @media (prefers-color-scheme: dark) {\n",
+ " /* Redefinition of color scheme for dark theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-icon: #878787;\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 pre {\n",
+ " padding: 0;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 input.sk-hidden--visually {\n",
+ " border: 0;\n",
+ " clip: rect(1px 1px 1px 1px);\n",
+ " clip: rect(1px, 1px, 1px, 1px);\n",
+ " height: 1px;\n",
+ " margin: -1px;\n",
+ " overflow: hidden;\n",
+ " padding: 0;\n",
+ " position: absolute;\n",
+ " width: 1px;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-dashed-wrapped {\n",
+ " border: 1px dashed var(--sklearn-color-line);\n",
+ " margin: 0 0.4em 0.5em 0.4em;\n",
+ " box-sizing: border-box;\n",
+ " padding-bottom: 0.4em;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-container {\n",
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+ " so we also need the `!important` here to be able to override the\n",
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+ " display: inline-block !important;\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-text-repr-fallback {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-parallel-item,\n",
+ "div.sk-serial,\n",
+ "div.sk-item {\n",
+ " /* draw centered vertical line to link estimators */\n",
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+ " background-size: 2px 100%;\n",
+ " background-repeat: no-repeat;\n",
+ " background-position: center center;\n",
+ "}\n",
+ "\n",
+ "/* Parallel-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-10 div.sk-parallel-item::after {\n",
+ " content: \"\";\n",
+ " width: 100%;\n",
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+ " flex-grow: 1;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-parallel {\n",
+ " display: flex;\n",
+ " align-items: stretch;\n",
+ " justify-content: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-parallel-item {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-parallel-item:first-child::after {\n",
+ " align-self: flex-end;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-parallel-item:last-child::after {\n",
+ " align-self: flex-start;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-parallel-item:only-child::after {\n",
+ " width: 0;\n",
+ "}\n",
+ "\n",
+ "/* Serial-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-10 div.sk-serial {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ " align-items: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " padding-right: 1em;\n",
+ " padding-left: 1em;\n",
+ "}\n",
+ "\n",
+ "\n",
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+ "clickable and can be expanded/collapsed.\n",
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+ "*/\n",
+ "\n",
+ "/* Pipeline and ColumnTransformer style (default) */\n",
+ "\n",
+ "#sk-container-id-10 div.sk-toggleable {\n",
+ " /* Default theme specific background. It is overwritten whether we have a\n",
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable label */\n",
+ "#sk-container-id-10 label.sk-toggleable__label {\n",
+ " cursor: pointer;\n",
+ " display: block;\n",
+ " width: 100%;\n",
+ " margin-bottom: 0;\n",
+ " padding: 0.5em;\n",
+ " box-sizing: border-box;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 label.sk-toggleable__label-arrow:before {\n",
+ " /* Arrow on the left of the label */\n",
+ " content: \"â–¸\";\n",
+ " float: left;\n",
+ " margin-right: 0.25em;\n",
+ " color: var(--sklearn-color-icon);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 label.sk-toggleable__label-arrow:hover:before {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable content - dropdown */\n",
+ "\n",
+ "#sk-container-id-10 div.sk-toggleable__content {\n",
+ " max-height: 0;\n",
+ " max-width: 0;\n",
+ " overflow: hidden;\n",
+ " text-align: left;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-toggleable__content.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-toggleable__content pre {\n",
+ " margin: 0.2em;\n",
+ " border-radius: 0.25em;\n",
+ " color: var(--sklearn-color-text);\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-toggleable__content.fitted pre {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+ " /* Expand drop-down */\n",
+ " max-height: 200px;\n",
+ " max-width: 100%;\n",
+ " overflow: auto;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+ " content: \"â–¾\";\n",
+ "}\n",
+ "\n",
+ "/* Pipeline/ColumnTransformer-specific style */\n",
+ "\n",
+ "#sk-container-id-10 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific style */\n",
+ "\n",
+ "/* Colorize estimator box */\n",
+ "#sk-container-id-10 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-label label.sk-toggleable__label,\n",
+ "#sk-container-id-10 div.sk-label label {\n",
+ " /* The background is the default theme color */\n",
+ " color: var(--sklearn-color-text-on-default-background);\n",
+ "}\n",
+ "\n",
+ "/* On hover, darken the color of the background */\n",
+ "#sk-container-id-10 div.sk-label:hover label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Label box, darken color on hover, fitted */\n",
+ "#sk-container-id-10 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator label */\n",
+ "\n",
+ "#sk-container-id-10 div.sk-label label {\n",
+ " font-family: monospace;\n",
+ " font-weight: bold;\n",
+ " display: inline-block;\n",
+ " line-height: 1.2em;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-label-container {\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific */\n",
+ "#sk-container-id-10 div.sk-estimator {\n",
+ " font-family: monospace;\n",
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
+ " border-radius: 0.25em;\n",
+ " box-sizing: border-box;\n",
+ " margin-bottom: 0.5em;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-estimator.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "/* on hover */\n",
+ "#sk-container-id-10 div.sk-estimator:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 div.sk-estimator.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+ "\n",
+ "/* Common style for \"i\" and \"?\" */\n",
+ "\n",
+ ".sk-estimator-doc-link,\n",
+ "a:link.sk-estimator-doc-link,\n",
+ "a:visited.sk-estimator-doc-link {\n",
+ " float: right;\n",
+ " font-size: smaller;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1em;\n",
+ " height: 1em;\n",
+ " width: 1em;\n",
+ " text-decoration: none !important;\n",
+ " margin-left: 1ex;\n",
+ " /* unfitted */\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted,\n",
+ "a:link.sk-estimator-doc-link.fitted,\n",
+ "a:visited.sk-estimator-doc-link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "/* Span, style for the box shown on hovering the info icon */\n",
+ ".sk-estimator-doc-link span {\n",
+ " display: none;\n",
+ " z-index: 9999;\n",
+ " position: relative;\n",
+ " font-weight: normal;\n",
+ " right: .2ex;\n",
+ " padding: .5ex;\n",
+ " margin: .5ex;\n",
+ " width: min-content;\n",
+ " min-width: 20ex;\n",
+ " max-width: 50ex;\n",
+ " color: var(--sklearn-color-text);\n",
+ " box-shadow: 2pt 2pt 4pt #999;\n",
+ " /* unfitted */\n",
+ " background: var(--sklearn-color-unfitted-level-0);\n",
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted span {\n",
+ " /* fitted */\n",
+ " background: var(--sklearn-color-fitted-level-0);\n",
+ " border: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link:hover span {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+ "\n",
+ "#sk-container-id-10 a.estimator_doc_link {\n",
+ " float: right;\n",
+ " font-size: 1rem;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1rem;\n",
+ " height: 1rem;\n",
+ " width: 1rem;\n",
+ " text-decoration: none;\n",
+ " /* unfitted */\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 a.estimator_doc_link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "#sk-container-id-10 a.estimator_doc_link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-10 a.estimator_doc_link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "</style><div id=\"sk-container-id-10\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(ccp_alpha=0.05)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" checked><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(ccp_alpha=0.05)</pre></div> </div></div></div></div>"
+ ],
+ "text/plain": [
+ "DecisionTreeClassifier(ccp_alpha=0.05)"
+ ]
+ },
+ "execution_count": 65,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#DecsionTree model - undersampled dataset\n",
+ "\n",
+ "# Initialize the decision tree classifier\n",
+ "clf_undersampled = DecisionTreeClassifier(ccp_alpha=ccp_alpha)\n",
+ "\n",
+ "DT_models.append(clf_undersampled)\n",
+ "DT_name.append(f\"Undersampled dataset(No PCA),{txt}\")\n",
+ "x_val_list.append(xval)\n",
+ "x_test_list.append(xtest)\n",
+ "\n",
+ "# Fit the classifier to the training data\n",
+ "clf_undersampled.fit(xtrain_undersampled, ytrain_undersampled)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<style>#sk-container-id-11 {\n",
+ " /* Definition of color scheme common for light and dark mode */\n",
+ " --sklearn-color-text: black;\n",
+ " --sklearn-color-line: gray;\n",
+ " /* Definition of color scheme for unfitted estimators */\n",
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
+ " /* Definition of color scheme for fitted estimators */\n",
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
+ "\n",
+ " /* Specific color for light theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-icon: #696969;\n",
+ "\n",
+ " @media (prefers-color-scheme: dark) {\n",
+ " /* Redefinition of color scheme for dark theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-icon: #878787;\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 pre {\n",
+ " padding: 0;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 input.sk-hidden--visually {\n",
+ " border: 0;\n",
+ " clip: rect(1px 1px 1px 1px);\n",
+ " clip: rect(1px, 1px, 1px, 1px);\n",
+ " height: 1px;\n",
+ " margin: -1px;\n",
+ " overflow: hidden;\n",
+ " padding: 0;\n",
+ " position: absolute;\n",
+ " width: 1px;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-dashed-wrapped {\n",
+ " border: 1px dashed var(--sklearn-color-line);\n",
+ " margin: 0 0.4em 0.5em 0.4em;\n",
+ " box-sizing: border-box;\n",
+ " padding-bottom: 0.4em;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-container {\n",
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+ " so we also need the `!important` here to be able to override the\n",
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+ " display: inline-block !important;\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-text-repr-fallback {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-parallel-item,\n",
+ "div.sk-serial,\n",
+ "div.sk-item {\n",
+ " /* draw centered vertical line to link estimators */\n",
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+ " background-size: 2px 100%;\n",
+ " background-repeat: no-repeat;\n",
+ " background-position: center center;\n",
+ "}\n",
+ "\n",
+ "/* Parallel-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-11 div.sk-parallel-item::after {\n",
+ " content: \"\";\n",
+ " width: 100%;\n",
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+ " flex-grow: 1;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-parallel {\n",
+ " display: flex;\n",
+ " align-items: stretch;\n",
+ " justify-content: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-parallel-item {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-parallel-item:first-child::after {\n",
+ " align-self: flex-end;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-parallel-item:last-child::after {\n",
+ " align-self: flex-start;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-parallel-item:only-child::after {\n",
+ " width: 0;\n",
+ "}\n",
+ "\n",
+ "/* Serial-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-11 div.sk-serial {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ " align-items: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " padding-right: 1em;\n",
+ " padding-left: 1em;\n",
+ "}\n",
+ "\n",
+ "\n",
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+ "clickable and can be expanded/collapsed.\n",
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+ "*/\n",
+ "\n",
+ "/* Pipeline and ColumnTransformer style (default) */\n",
+ "\n",
+ "#sk-container-id-11 div.sk-toggleable {\n",
+ " /* Default theme specific background. It is overwritten whether we have a\n",
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable label */\n",
+ "#sk-container-id-11 label.sk-toggleable__label {\n",
+ " cursor: pointer;\n",
+ " display: block;\n",
+ " width: 100%;\n",
+ " margin-bottom: 0;\n",
+ " padding: 0.5em;\n",
+ " box-sizing: border-box;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 label.sk-toggleable__label-arrow:before {\n",
+ " /* Arrow on the left of the label */\n",
+ " content: \"â–¸\";\n",
+ " float: left;\n",
+ " margin-right: 0.25em;\n",
+ " color: var(--sklearn-color-icon);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 label.sk-toggleable__label-arrow:hover:before {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable content - dropdown */\n",
+ "\n",
+ "#sk-container-id-11 div.sk-toggleable__content {\n",
+ " max-height: 0;\n",
+ " max-width: 0;\n",
+ " overflow: hidden;\n",
+ " text-align: left;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-toggleable__content.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-toggleable__content pre {\n",
+ " margin: 0.2em;\n",
+ " border-radius: 0.25em;\n",
+ " color: var(--sklearn-color-text);\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-toggleable__content.fitted pre {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+ " /* Expand drop-down */\n",
+ " max-height: 200px;\n",
+ " max-width: 100%;\n",
+ " overflow: auto;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+ " content: \"â–¾\";\n",
+ "}\n",
+ "\n",
+ "/* Pipeline/ColumnTransformer-specific style */\n",
+ "\n",
+ "#sk-container-id-11 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific style */\n",
+ "\n",
+ "/* Colorize estimator box */\n",
+ "#sk-container-id-11 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-label label.sk-toggleable__label,\n",
+ "#sk-container-id-11 div.sk-label label {\n",
+ " /* The background is the default theme color */\n",
+ " color: var(--sklearn-color-text-on-default-background);\n",
+ "}\n",
+ "\n",
+ "/* On hover, darken the color of the background */\n",
+ "#sk-container-id-11 div.sk-label:hover label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Label box, darken color on hover, fitted */\n",
+ "#sk-container-id-11 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator label */\n",
+ "\n",
+ "#sk-container-id-11 div.sk-label label {\n",
+ " font-family: monospace;\n",
+ " font-weight: bold;\n",
+ " display: inline-block;\n",
+ " line-height: 1.2em;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-label-container {\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific */\n",
+ "#sk-container-id-11 div.sk-estimator {\n",
+ " font-family: monospace;\n",
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
+ " border-radius: 0.25em;\n",
+ " box-sizing: border-box;\n",
+ " margin-bottom: 0.5em;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-estimator.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "/* on hover */\n",
+ "#sk-container-id-11 div.sk-estimator:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 div.sk-estimator.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+ "\n",
+ "/* Common style for \"i\" and \"?\" */\n",
+ "\n",
+ ".sk-estimator-doc-link,\n",
+ "a:link.sk-estimator-doc-link,\n",
+ "a:visited.sk-estimator-doc-link {\n",
+ " float: right;\n",
+ " font-size: smaller;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1em;\n",
+ " height: 1em;\n",
+ " width: 1em;\n",
+ " text-decoration: none !important;\n",
+ " margin-left: 1ex;\n",
+ " /* unfitted */\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted,\n",
+ "a:link.sk-estimator-doc-link.fitted,\n",
+ "a:visited.sk-estimator-doc-link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "/* Span, style for the box shown on hovering the info icon */\n",
+ ".sk-estimator-doc-link span {\n",
+ " display: none;\n",
+ " z-index: 9999;\n",
+ " position: relative;\n",
+ " font-weight: normal;\n",
+ " right: .2ex;\n",
+ " padding: .5ex;\n",
+ " margin: .5ex;\n",
+ " width: min-content;\n",
+ " min-width: 20ex;\n",
+ " max-width: 50ex;\n",
+ " color: var(--sklearn-color-text);\n",
+ " box-shadow: 2pt 2pt 4pt #999;\n",
+ " /* unfitted */\n",
+ " background: var(--sklearn-color-unfitted-level-0);\n",
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted span {\n",
+ " /* fitted */\n",
+ " background: var(--sklearn-color-fitted-level-0);\n",
+ " border: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link:hover span {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+ "\n",
+ "#sk-container-id-11 a.estimator_doc_link {\n",
+ " float: right;\n",
+ " font-size: 1rem;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1rem;\n",
+ " height: 1rem;\n",
+ " width: 1rem;\n",
+ " text-decoration: none;\n",
+ " /* unfitted */\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 a.estimator_doc_link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "#sk-container-id-11 a.estimator_doc_link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-11 a.estimator_doc_link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "</style><div id=\"sk-container-id-11\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(ccp_alpha=0.05)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" checked><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(ccp_alpha=0.05)</pre></div> </div></div></div></div>"
+ ],
+ "text/plain": [
+ "DecisionTreeClassifier(ccp_alpha=0.05)"
+ ]
+ },
+ "execution_count": 66,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#DecsionTree model - oversampled dataset\n",
+ "\n",
+ "# Initialize the decision tree classifier\n",
+ "clf_oversampled_pca = DecisionTreeClassifier(ccp_alpha=ccp_alpha)\n",
+ "\n",
+ "DT_models.append(clf_oversampled_pca)\n",
+ "DT_name.append(f\"Oversampled dataset(PCA), {txt}\")\n",
+ "x_val_list.append(xval_pca_oversampled)\n",
+ "x_test_list.append(xtest_pca_oversampled)\n",
+ "\n",
+ "# Fit the classifier to the training data\n",
+ "clf_oversampled_pca.fit(xtrain_pca_oversampled, ytrain_oversampled)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<style>#sk-container-id-12 {\n",
+ " /* Definition of color scheme common for light and dark mode */\n",
+ " --sklearn-color-text: black;\n",
+ " --sklearn-color-line: gray;\n",
+ " /* Definition of color scheme for unfitted estimators */\n",
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
+ " /* Definition of color scheme for fitted estimators */\n",
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
+ "\n",
+ " /* Specific color for light theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-icon: #696969;\n",
+ "\n",
+ " @media (prefers-color-scheme: dark) {\n",
+ " /* Redefinition of color scheme for dark theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-icon: #878787;\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 pre {\n",
+ " padding: 0;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 input.sk-hidden--visually {\n",
+ " border: 0;\n",
+ " clip: rect(1px 1px 1px 1px);\n",
+ " clip: rect(1px, 1px, 1px, 1px);\n",
+ " height: 1px;\n",
+ " margin: -1px;\n",
+ " overflow: hidden;\n",
+ " padding: 0;\n",
+ " position: absolute;\n",
+ " width: 1px;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-dashed-wrapped {\n",
+ " border: 1px dashed var(--sklearn-color-line);\n",
+ " margin: 0 0.4em 0.5em 0.4em;\n",
+ " box-sizing: border-box;\n",
+ " padding-bottom: 0.4em;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-container {\n",
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+ " so we also need the `!important` here to be able to override the\n",
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+ " display: inline-block !important;\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-text-repr-fallback {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-parallel-item,\n",
+ "div.sk-serial,\n",
+ "div.sk-item {\n",
+ " /* draw centered vertical line to link estimators */\n",
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+ " background-size: 2px 100%;\n",
+ " background-repeat: no-repeat;\n",
+ " background-position: center center;\n",
+ "}\n",
+ "\n",
+ "/* Parallel-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-12 div.sk-parallel-item::after {\n",
+ " content: \"\";\n",
+ " width: 100%;\n",
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+ " flex-grow: 1;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-parallel {\n",
+ " display: flex;\n",
+ " align-items: stretch;\n",
+ " justify-content: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-parallel-item {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-parallel-item:first-child::after {\n",
+ " align-self: flex-end;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-parallel-item:last-child::after {\n",
+ " align-self: flex-start;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-parallel-item:only-child::after {\n",
+ " width: 0;\n",
+ "}\n",
+ "\n",
+ "/* Serial-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-12 div.sk-serial {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ " align-items: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " padding-right: 1em;\n",
+ " padding-left: 1em;\n",
+ "}\n",
+ "\n",
+ "\n",
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+ "clickable and can be expanded/collapsed.\n",
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+ "*/\n",
+ "\n",
+ "/* Pipeline and ColumnTransformer style (default) */\n",
+ "\n",
+ "#sk-container-id-12 div.sk-toggleable {\n",
+ " /* Default theme specific background. It is overwritten whether we have a\n",
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable label */\n",
+ "#sk-container-id-12 label.sk-toggleable__label {\n",
+ " cursor: pointer;\n",
+ " display: block;\n",
+ " width: 100%;\n",
+ " margin-bottom: 0;\n",
+ " padding: 0.5em;\n",
+ " box-sizing: border-box;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 label.sk-toggleable__label-arrow:before {\n",
+ " /* Arrow on the left of the label */\n",
+ " content: \"â–¸\";\n",
+ " float: left;\n",
+ " margin-right: 0.25em;\n",
+ " color: var(--sklearn-color-icon);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 label.sk-toggleable__label-arrow:hover:before {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable content - dropdown */\n",
+ "\n",
+ "#sk-container-id-12 div.sk-toggleable__content {\n",
+ " max-height: 0;\n",
+ " max-width: 0;\n",
+ " overflow: hidden;\n",
+ " text-align: left;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-toggleable__content.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-toggleable__content pre {\n",
+ " margin: 0.2em;\n",
+ " border-radius: 0.25em;\n",
+ " color: var(--sklearn-color-text);\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-toggleable__content.fitted pre {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+ " /* Expand drop-down */\n",
+ " max-height: 200px;\n",
+ " max-width: 100%;\n",
+ " overflow: auto;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+ " content: \"â–¾\";\n",
+ "}\n",
+ "\n",
+ "/* Pipeline/ColumnTransformer-specific style */\n",
+ "\n",
+ "#sk-container-id-12 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific style */\n",
+ "\n",
+ "/* Colorize estimator box */\n",
+ "#sk-container-id-12 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-label label.sk-toggleable__label,\n",
+ "#sk-container-id-12 div.sk-label label {\n",
+ " /* The background is the default theme color */\n",
+ " color: var(--sklearn-color-text-on-default-background);\n",
+ "}\n",
+ "\n",
+ "/* On hover, darken the color of the background */\n",
+ "#sk-container-id-12 div.sk-label:hover label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Label box, darken color on hover, fitted */\n",
+ "#sk-container-id-12 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator label */\n",
+ "\n",
+ "#sk-container-id-12 div.sk-label label {\n",
+ " font-family: monospace;\n",
+ " font-weight: bold;\n",
+ " display: inline-block;\n",
+ " line-height: 1.2em;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-label-container {\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific */\n",
+ "#sk-container-id-12 div.sk-estimator {\n",
+ " font-family: monospace;\n",
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
+ " border-radius: 0.25em;\n",
+ " box-sizing: border-box;\n",
+ " margin-bottom: 0.5em;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-estimator.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "/* on hover */\n",
+ "#sk-container-id-12 div.sk-estimator:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 div.sk-estimator.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+ "\n",
+ "/* Common style for \"i\" and \"?\" */\n",
+ "\n",
+ ".sk-estimator-doc-link,\n",
+ "a:link.sk-estimator-doc-link,\n",
+ "a:visited.sk-estimator-doc-link {\n",
+ " float: right;\n",
+ " font-size: smaller;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1em;\n",
+ " height: 1em;\n",
+ " width: 1em;\n",
+ " text-decoration: none !important;\n",
+ " margin-left: 1ex;\n",
+ " /* unfitted */\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted,\n",
+ "a:link.sk-estimator-doc-link.fitted,\n",
+ "a:visited.sk-estimator-doc-link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "/* Span, style for the box shown on hovering the info icon */\n",
+ ".sk-estimator-doc-link span {\n",
+ " display: none;\n",
+ " z-index: 9999;\n",
+ " position: relative;\n",
+ " font-weight: normal;\n",
+ " right: .2ex;\n",
+ " padding: .5ex;\n",
+ " margin: .5ex;\n",
+ " width: min-content;\n",
+ " min-width: 20ex;\n",
+ " max-width: 50ex;\n",
+ " color: var(--sklearn-color-text);\n",
+ " box-shadow: 2pt 2pt 4pt #999;\n",
+ " /* unfitted */\n",
+ " background: var(--sklearn-color-unfitted-level-0);\n",
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted span {\n",
+ " /* fitted */\n",
+ " background: var(--sklearn-color-fitted-level-0);\n",
+ " border: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link:hover span {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+ "\n",
+ "#sk-container-id-12 a.estimator_doc_link {\n",
+ " float: right;\n",
+ " font-size: 1rem;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1rem;\n",
+ " height: 1rem;\n",
+ " width: 1rem;\n",
+ " text-decoration: none;\n",
+ " /* unfitted */\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 a.estimator_doc_link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "#sk-container-id-12 a.estimator_doc_link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-12 a.estimator_doc_link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "</style><div id=\"sk-container-id-12\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(ccp_alpha=0.05)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-12\" type=\"checkbox\" checked><label for=\"sk-estimator-id-12\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(ccp_alpha=0.05)</pre></div> </div></div></div></div>"
+ ],
+ "text/plain": [
+ "DecisionTreeClassifier(ccp_alpha=0.05)"
+ ]
+ },
+ "execution_count": 67,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#DecsionTree model - undersampled dataset\n",
+ "\n",
+ "# Initialize the decision tree classifier\n",
+ "clf_undersampled_pca = DecisionTreeClassifier(ccp_alpha=ccp_alpha)\n",
+ "\n",
+ "DT_models.append(clf_undersampled_pca)\n",
+ "DT_name.append(f\"Undersampled dataset(PCA), {txt}\")\n",
+ "x_val_list.append(xval_pca_undersampled)\n",
+ "x_test_list.append(xtest_pca_undersampled)\n",
+ "\n",
+ "# Fit the classifier to the training data\n",
+ "clf_undersampled_pca.fit(xtrain_pca_undersampled, ytrain_undersampled)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 130,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def predict(models, names, x_list, Y, eval_type):\n",
+ " \n",
+ " print(f\"\\033[1mEvaluating {eval_type} data\\033[0m \\n\")\n",
+ " \n",
+ " fpr_list, tpr_list, roc_auc_list = [], [], []\n",
+ " \n",
+ " for model, name, X in zip(models, names, x_list):\n",
+ " print(f\"\\033[1mEvaluating {name}...\\033[0m\")\n",
+ " y_pred = model.predict(X)\n",
+ " accuracy = accuracy_score(Y, y_pred)\n",
+ " report = classification_report(Y, y_pred)\n",
+ " print(f\"{name} Accuracy:\", accuracy)\n",
+ " \n",
+ " \n",
+ " conf_matrix = confusion_matrix(Y, y_pred)\n",
+ " plt.figure(figsize=(3, 2))\n",
+ " sns.heatmap(conf_matrix, annot=True, fmt='d', cmap='Blues')\n",
+ " plt.title('Confusion Matrix')\n",
+ " plt.xlabel('Predicted')\n",
+ " plt.ylabel('Actual')\n",
+ " plt.show()\n",
+ " print(f\"{name} Classification report:\\n\", report)\n",
+ "\n",
+ " \n",
+ " y_prob = model.predict_proba(X)[:, 1]\n",
+ " fpr, tpr, _ = roc_curve(Y, y_prob)\n",
+ " fpr_list.append(fpr)\n",
+ " tpr_list.append(tpr)\n",
+ " \n",
+ " roc_auc = auc(fpr, tpr)\n",
+ " #print(f\"{name} AUC = {roc_auc}\")\n",
+ " roc_auc_list.append(roc_auc)\n",
+ " \n",
+ " cmap = plt.colormaps['tab10']\n",
+ " colors = cmap.colors[:len(names)]\n",
+ " plt.figure(figsize=(9,5))\n",
+ " for i, (fpr, tpr, roc_auc, name) in enumerate(zip(fpr_list, tpr_list, roc_auc_list, names)):\n",
+ " plt.plot(fpr, tpr, color=colors[i], lw=2, label=f'{name} (area = {roc_auc:.2f})')\n",
+ " plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
+ " plt.xlim([0.0, 1.0])\n",
+ " plt.ylim([0.0, 1.05])\n",
+ " plt.xlabel('False Positive Rate')\n",
+ " plt.ylabel('True Positive Rate')\n",
+ " plt.title('Receiver Operating Characteristic (ROC) SVM on Dataset 2')\n",
+ " plt.legend(loc='lower right')\n",
+ " plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\u001b[1mEvaluating validation data\u001b[0m \n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), ccp_alpha: 0.01...\u001b[0m\n",
+ "Oversampled dataset(No PCA), ccp_alpha: 0.01 Accuracy: 0.7455555555555555\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.91 0.77 0.84 3043\n",
+ " 1.0 0.32 0.59 0.42 557\n",
+ "\n",
+ " accuracy 0.75 3600\n",
+ " macro avg 0.62 0.68 0.63 3600\n",
+ "weighted avg 0.82 0.75 0.77 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(No PCA),ccp_alpha: 0.01...\u001b[0m\n",
+ "Undersampled dataset(No PCA),ccp_alpha: 0.01 Accuracy: 0.7455555555555555\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(No PCA),ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.91 0.77 0.84 3043\n",
+ " 1.0 0.32 0.59 0.42 557\n",
+ "\n",
+ " accuracy 0.75 3600\n",
+ " macro avg 0.62 0.68 0.63 3600\n",
+ "weighted avg 0.82 0.75 0.77 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(PCA), ccp_alpha: 0.01...\u001b[0m\n",
+ "Oversampled dataset(PCA), ccp_alpha: 0.01 Accuracy: 0.6380555555555556\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(PCA), ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.62 0.74 3043\n",
+ " 1.0 0.26 0.73 0.38 557\n",
+ "\n",
+ " accuracy 0.64 3600\n",
+ " macro avg 0.59 0.67 0.56 3600\n",
+ "weighted avg 0.82 0.64 0.69 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(PCA), ccp_alpha: 0.01...\u001b[0m\n",
+ "Undersampled dataset(PCA), ccp_alpha: 0.01 Accuracy: 0.6533333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(PCA), ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.92 0.65 0.76 3043\n",
+ " 1.0 0.26 0.68 0.38 557\n",
+ "\n",
+ " accuracy 0.65 3600\n",
+ " macro avg 0.59 0.66 0.57 3600\n",
+ "weighted avg 0.82 0.65 0.70 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), ccp_alpha: 0.05...\u001b[0m\n",
+ "Oversampled dataset(No PCA), ccp_alpha: 0.05 Accuracy: 0.6366666666666667\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.62 0.74 3043\n",
+ " 1.0 0.26 0.74 0.39 557\n",
+ "\n",
+ " accuracy 0.64 3600\n",
+ " macro avg 0.60 0.68 0.56 3600\n",
+ "weighted avg 0.83 0.64 0.69 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(No PCA),ccp_alpha: 0.05...\u001b[0m\n",
+ "Undersampled dataset(No PCA),ccp_alpha: 0.05 Accuracy: 0.6366666666666667\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(No PCA),ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.62 0.74 3043\n",
+ " 1.0 0.26 0.74 0.39 557\n",
+ "\n",
+ " accuracy 0.64 3600\n",
+ " macro avg 0.60 0.68 0.56 3600\n",
+ "weighted avg 0.83 0.64 0.69 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(PCA), ccp_alpha: 0.05...\u001b[0m\n",
+ "Oversampled dataset(PCA), ccp_alpha: 0.05 Accuracy: 0.6380555555555556\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(PCA), ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.62 0.74 3043\n",
+ " 1.0 0.26 0.73 0.38 557\n",
+ "\n",
+ " accuracy 0.64 3600\n",
+ " macro avg 0.59 0.67 0.56 3600\n",
+ "weighted avg 0.82 0.64 0.69 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(PCA), ccp_alpha: 0.05...\u001b[0m\n",
+ "Undersampled dataset(PCA), ccp_alpha: 0.05 Accuracy: 0.6533333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(PCA), ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.92 0.65 0.76 3043\n",
+ " 1.0 0.26 0.68 0.38 557\n",
+ "\n",
+ " accuracy 0.65 3600\n",
+ " macro avg 0.59 0.66 0.57 3600\n",
+ "weighted avg 0.82 0.65 0.70 3600\n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 900x500 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "predict(DT_models, DT_name, x_val_list, yval, \"validation\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\u001b[1mEvaluating testing data\u001b[0m \n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), ccp_alpha: 0.01...\u001b[0m\n",
+ "Oversampled dataset(No PCA), ccp_alpha: 0.01 Accuracy: 0.7623333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.92 0.78 0.85 2529\n",
+ " 1.0 0.36 0.64 0.46 471\n",
+ "\n",
+ " accuracy 0.76 3000\n",
+ " macro avg 0.64 0.71 0.65 3000\n",
+ "weighted avg 0.83 0.76 0.79 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(No PCA),ccp_alpha: 0.01...\u001b[0m\n",
+ "Undersampled dataset(No PCA),ccp_alpha: 0.01 Accuracy: 0.7623333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(No PCA),ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.92 0.78 0.85 2529\n",
+ " 1.0 0.36 0.64 0.46 471\n",
+ "\n",
+ " accuracy 0.76 3000\n",
+ " macro avg 0.64 0.71 0.65 3000\n",
+ "weighted avg 0.83 0.76 0.79 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(PCA), ccp_alpha: 0.01...\u001b[0m\n",
+ "Oversampled dataset(PCA), ccp_alpha: 0.01 Accuracy: 0.6703333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(PCA), ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.94 0.65 0.77 2529\n",
+ " 1.0 0.29 0.77 0.42 471\n",
+ "\n",
+ " accuracy 0.67 3000\n",
+ " macro avg 0.61 0.71 0.60 3000\n",
+ "weighted avg 0.84 0.67 0.71 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(PCA), ccp_alpha: 0.01...\u001b[0m\n",
+ "Undersampled dataset(PCA), ccp_alpha: 0.01 Accuracy: 0.6826666666666666\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(PCA), ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.68 0.78 2529\n",
+ " 1.0 0.29 0.72 0.42 471\n",
+ "\n",
+ " accuracy 0.68 3000\n",
+ " macro avg 0.61 0.70 0.60 3000\n",
+ "weighted avg 0.83 0.68 0.72 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), ccp_alpha: 0.05...\u001b[0m\n",
+ "Oversampled dataset(No PCA), ccp_alpha: 0.05 Accuracy: 0.635\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.61 0.74 2529\n",
+ " 1.0 0.27 0.76 0.39 471\n",
+ "\n",
+ " accuracy 0.64 3000\n",
+ " macro avg 0.60 0.69 0.57 3000\n",
+ "weighted avg 0.83 0.64 0.68 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(No PCA),ccp_alpha: 0.05...\u001b[0m\n",
+ "Undersampled dataset(No PCA),ccp_alpha: 0.05 Accuracy: 0.635\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(No PCA),ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.61 0.74 2529\n",
+ " 1.0 0.27 0.76 0.39 471\n",
+ "\n",
+ " accuracy 0.64 3000\n",
+ " macro avg 0.60 0.69 0.57 3000\n",
+ "weighted avg 0.83 0.64 0.68 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(PCA), ccp_alpha: 0.05...\u001b[0m\n",
+ "Oversampled dataset(PCA), ccp_alpha: 0.05 Accuracy: 0.6703333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(PCA), ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.94 0.65 0.77 2529\n",
+ " 1.0 0.29 0.77 0.42 471\n",
+ "\n",
+ " accuracy 0.67 3000\n",
+ " macro avg 0.61 0.71 0.60 3000\n",
+ "weighted avg 0.84 0.67 0.71 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(PCA), ccp_alpha: 0.05...\u001b[0m\n",
+ "Undersampled dataset(PCA), ccp_alpha: 0.05 Accuracy: 0.6826666666666666\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(PCA), ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.68 0.78 2529\n",
+ " 1.0 0.29 0.72 0.42 471\n",
+ "\n",
+ " accuracy 0.68 3000\n",
+ " macro avg 0.61 0.70 0.60 3000\n",
+ "weighted avg 0.83 0.68 0.72 3000\n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 900x500 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "predict(DT_models, DT_name, x_test_list, ytest, \"testing\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Using the oversampled dataset with PCA for hyperparameter tuning because of its high performance"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 109,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Accuracy Score on train data: 0.6917362388566577\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1000x1000 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Create a DecisionTreeClassifier with specified hyperparameters\n",
+ "clf_oversampled_pca = DecisionTreeClassifier(random_state=0, ccp_alpha=0.005)\n",
+ "\n",
+ "# Fit the classifier on the PCA-transformed oversampled training data\n",
+ "clf_oversampled_pca.fit(xtrain_oversampled, ytrain_oversampled)\n",
+ "\n",
+ "# Evaluate the model on the PCA-transformed test data\n",
+ "y_pred_test_dt_pca = clf_oversampled_pca.predict(xtest)\n",
+ "\n",
+ "print('Accuracy Score on train data: ', accuracy_score(y_true=ytrain_oversampled, y_pred=clf_oversampled_pca.predict(xtrain_oversampled)))\n",
+ "\n",
+ "DT_models.append(clf_oversampled_pca)\n",
+ "DT_name.append(\"Oversampled Dataset (No PCA) ccp_alpha: 0.005\")\n",
+ "x_test_list.append(xtest)\n",
+ "\n",
+ "plt.figure(figsize=(10,10))\n",
+ "plot_tree(clf_oversampled_pca, filled=True)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 113,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Accuracy Score on train data: 0.6824678081222584\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 500x500 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Create a DecisionTreeClassifier with specified hyperparameters\n",
+ "clf_oversampled_pca = DecisionTreeClassifier(random_state=0, ccp_alpha=0.01)\n",
+ "\n",
+ "# Fit the classifier on the PCA-transformed oversampled training data\n",
+ "clf_oversampled_pca.fit(xtrain_oversampled, ytrain_oversampled,)\n",
+ "\n",
+ "# Evaluate the model on the PCA-transformed test data\n",
+ "y_pred_test_dt_pca = clf_oversampled_pca.predict(xtest)\n",
+ "\n",
+ "print('Accuracy Score on train data: ', accuracy_score(y_true=ytrain_oversampled, y_pred=clf_oversampled_pca.predict(xtrain_oversampled)))\n",
+ "\n",
+ "DT_models.append(clf_oversampled_pca)\n",
+ "DT_name.append(\"Oversampled Dataset ccp_alpha: 0.01\")\n",
+ "x_test_list.append(xtest)\n",
+ "\n",
+ "plt.figure(figsize=(5,5))\n",
+ "plot_tree(clf_oversampled_pca, filled=True)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 128,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\u001b[1mEvaluating testing data\u001b[0m \n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled Dataset (No PCA) ccp_alpha: 0.001...\u001b[0m\n",
+ "Oversampled Dataset (No PCA) ccp_alpha: 0.001 Accuracy: 0.7096666666666667\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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KREQEERERmJqa0rNnT8aNG6fuM3bsWHJycpg+fToZGRm4ubkRGRmpXvioUaMGa9euZc6cOfTu3RtLS0smTpxI7969S1SLKj8/P78s31xFVaXlaF2XgJ21BbHbpvLm+DUcPXMFgPRflz+z/5HYy3R9P4zv13xIh9aNn9mvsPdmYmzIme3TOBJ7mfdnbi598S8gLGKCTl73725e/D++mvfsOtr1DqRd70C2BI/l7rVLBdrfmRFK7UZNAfhpaySn9mwt0MerfxDuPd8qu6JLYZh7vWL3tRm2vcj2+DX9SltOhScjwHJSt1Y1dq0YhYWp5gqV97shBfr+w9eFjwZ1JnLHcQA+nLcVs6pGGn0a2NVk7T/fJTL6eKGvt+CTvtStVb2Mqn95WddvxDszQgtsP7Z9PfHXf8fRoyP5eXnc+/M6bt3707i1p0a/mnb11T8n3rxGXaeWePYbpNHHrIaVNkrXOl2tAlckEoBaplKpCOjpzrzxhQ/NT/12Q+PfdWyqEdS3PRFRR9j2/RkALv0Rr9FHX1+PxZP6c+7ybT5ZUPCveBdPJ/p2bknyo8dl8yZeYoZVqqpHcE9dPXOCmxd+pefo6VSvZceDOzfJycqkgat7gb5/l3jzGq6+PYrs8zLR1RS4IpE/AVrWvHFtwqYOYMu3MQz5dMNz+8//uA/pGdnMWL77mX2G9fPE1bEOY+dEkZ2Tq9FmYVqF8E/fYVroN6Q8Si91/a+a7KxMDm1aQQMXdxzaPLn7yL2b1wCwrNPgmc9LS0nicUoSVnULv3zrZaSrVeCKREaAWvZnfBLNegVzOzEZr9eefRwPwMPFnt6dWjJsxiYepWUU2qdqFQOmj/Dniz2nOH0+rkD74kn9uXQ9nrXbj/HJ4M5l8h5eJWe+i+av5Ae8OWWBelti3B8YGlfl8JaVXPv1Z7KzMqjb1JWOA0dQvVad//S5CsDVX05yaHM4ackPqGlbH8/+g2ng0kYn76W0ZASo4wDMyclh//79nD59mjt37pCVlUWVKlWwsbGhdevWdO7cWeNi55dRUupjklKLNxUd/24nbty+z5d7Y5/ZZ9Ab7bAwrcKCyP0F2np1bEEPnxa07j/3het9leXmZPPLga9x9PChmrWtenvizWtkPk6jiqk5b4ybRer9BE58vZkvZ3/Ee7MjMKlWg8S4J6PEx6nJdBkyntzsbH498A07F8+gz8ezsW/RWldv64XJMUAdBuDNmzcZNmwYCQkJODk5YWVlhbm5OZmZmVy8eJEdO3awbNky1q5dS+3atXVVZrmxs7bA37s5kxZFk5ub98x+wwd0YM+R37h6U/Ms+JrVTAib9hZTl37NzbsPtV3uS+n3Uz/xOCUJt+79NbZ3eHMIbf8xENsmzk82ODSndmNnPp88lDP7d+I9YCiObTtiWbcB9s1bq28WWr95azZMH8Hx6A0vZQAqZZpbFJ0FYHBwMHZ2dmzfvh1TU9MC7ampqYwfP57PPvuMiIgIHVRYvv7h60p+fr564aMwzZvY0rieFTOX7yrQFjZ1AJf+iGf91yfQ1//vX3aVSoW+vl6RoaoUl2OPUsO2XoHjeFb1Ch7Xs7CqRfXadbh38w8AzGtaY15T8xIr/UqVqN/sNc4d3qO9orVIpsA6DMAzZ86wdevWQsMPntz/a8KECQwcOLCcK9ONbh2aceyXqyQ+fPTsPl7NSEvPZN/R8wXaendqCcCjWM2779arXYOAnu68PjRUfe6hEuXm5HDjtzO06TGgwPaLJ3+geq06BVZ3c7KyqGL65JrVa2djyM3Opomb5mkyOdmZGJloXtf6spApsA4D0MzMjMTERBwcHJ7Z586dOxp3g3iVveZcl5VRR4rs49a8Pmcv/klGZnaBtvYDFxTYtn3pcH65cJO5q/dx+UZCmdX6Mrp/6zo5WZnYNnbW2K5fqRLHozdiXtOKt6YtVm9PuHGF5IQ76uny7zFHuPrLCeo6uWBU9ckf7azMdP44e4o6TVuU3xspQzID1mEA9uvXjylTpjB27Fjc3d2pVasWBgYGZGVlkZCQwKlTpwgJCaFfv1f/bPS6taphYWpc4Hy//9WsUS0Onix4tQLALxduFtiWlZ3Dw5S0QtuU5t6f1wGoYVu3QFu7NwL4PnIx+1YvpGk7X1LvJXA8eiOWdexp5vU6AG7+/bkce5QdIdNx7/kWebm5nNqzlezMdNr3frdc30tZ0ZMpsO4CcMyYMejp6TF//nwePy64Slq1alUGDhzIhx9+qIPqypdV9SdTqOetFltVN5OTm1/Q49RkAIyMCx5yae7dlcqGhsTu3cbXS2dR2dCIxq3b49U/CD39J9+da2lnz1tTF3Fs++d8tyaE3Nwc7Bya02XoR1hYv5yLdBKAFeBa4OzsbC5evEhCQgLp6ekYGRlhY2ODo6NjgTu+lkZFuBZYaSrCtcBKU5JrgZ2mFjyV6u8uzH29tOVUeDo/ya5y5cq0aPFyHkMR4mUmI8AKEIBCCN2QAJQAFEKx5ERoCUAhFEtGgBKAQiiWBKAEoBCKJTNgCUAhFEtGgBKAQiiWBKAEoBCKJavAEoBCKJaMACUAhVAsCUAJQCEUS6bAxQzA2Nhnf0dFYdzc3F6oGCFE+ZERYDEDMDAwsFh/LfLz81GpVFy8eLHUhQkhtEsCsJgBuHHjRm3XIYQoZzIDLmYAtmnzcn7vqRDi2fRlBPhiiyBnz57l1KlTZGdn8/R+qvn5+Tx+/JgzZ87w1VdflWmRQoiyJwH4AgG4ZcsWZs+eTWE3ktbT08PT07OQZwkhKhpZBYYSfy/e5s2b8fT0JCYmhiFDhvDmm29y9uxZQkNDMTQ0pFevXtqoUwhRxvRUqiIfSlDiALx16xYBAQGYm5vTvHlzzpw5g5GREV26dGH48OGyYCLES0JfT1XkQwlKHICVK1dWf1dv/fr1iYuLIzv7yffUtmrVihs3bpRpgUII7VCpin4oQYkDsGnTphw+fBiAevXqkZeXx9mzZwGIjy/6e22FEBWHjABfYBFk8ODBjB49mpSUFObNm4efnx8TJ06kS5cu7N69m9dee00bdQohypicCP0CI8BOnToRERFBo0aNAPjss8+wt7cnKiqKBg0aMGPGjDIvUghR9sprESQ8PJzAwECNbRcvXiQgIABXV1d8fHyIjIzUaM/LyyMsLAwvLy9cXFwICgoiLi6uRPsojhIHIICPjw9DhgwBoFq1aqxbt46zZ8+yadMmatWq9SK7FEKUs/IIwPXr1xMWFqaxLSkpicGDB1O/fn127NjBmDFjCA0NZceOHeo+4eHhREVFMXv2bLZu3YpKpWLYsGFkZWUVex/FUeIp8J07d57bp3bt2iXdrRCinGnzOF9CQgLTpk3jzJkz2Nvba7R99dVXGBgYMGvWLCpVqkTDhg2Ji4tjzZo19O3bl6ysLNatW8eECRPw9vYGYMmSJXh5eXHgwAH8/f2fu4/iKnEA+vr6PvcESrkZghAVnzZXes+fP4+5uTm7du1ixYoV3L59W912+vRp3NzcqFTpv/Hj4eHBqlWrePDgAbdv3yYtLQ0PDw91u5mZGU5OTsTGxuLv7//cfdSoUaNYdZY4AOfOnVsgAJ9eAvfzzz8zd+7cku5SCKEDzxsB+vn5Fdl+6NChZ7b5+vri6+tbaFt8fDxNmjTR2GZlZQU8mWE+PZvkfw+nWVlZcffu3WLtQ2sB2KdPn0K3Dxw4kPnz57N79258fHxKulshRDnT1dUeGRkZGBgYaGwzNDQEIDMzk/T0dIBC+6SkpBRrH8VVpneE9vHxYeTIkWW5SyGEljwvAIsa4ZWGkZGRejHjqaehZWxsrL7QIisrS/3z0z5VqlQp1j6K64VWgZ/l7NmzGnNyIUTFpaenKvKhLTY2NiQmJmpse/pva2tr9dS3sD42NjbF2kdxlTitpkyZUmBbXl4ed+/e5fTp0/Tr16+kuxRC6ICurvZwc3MjKiqK3Nxc9PX1ATh58iT29vbUqFEDU1NTTExMiImJoW7dugCkpqZy4cIFAgICirWP4ipxAMbExBTYplKpMDExYdiwYYwYMaKkuxRC6ICurvft27cva9euZdq0aQwdOpRz586xYcMGgoODgSfH/gICAggJCaF69erY2tqycOFCbGxs6Ny5c7H2UVwlDsAffvihpE+pEJJil+u6BMW59TBd1yWIIujrKAFr1KjB2rVrmTNnDr1798bS0pKJEyfSu3dvdZ+xY8eSk5PD9OnTycjIwM3NjcjISPXCR3H2URyq/MLubFqEKVOmMHLkSOrUqVOg7Y8//mDBggVERESUqIjykJGj6wqURwKw/DWyqlLsvuO+uVRk+9J/OJa2nAqvWCPAv1/9sXPnTjp16qSed//dTz/9xIkTJ8quOiGE1si9EIoZgJ999hlHjhwBnhzvGz16dKH98vPzad++fdlVJ4TQGqXc8qooxQrA4OBgTpw4QX5+PlOnTuWDDz5Qr848paenh5mZGe7u7lopVAhRtiQAixmA1tbW6oOLKpUKHx8fTExMqFy5MgDp6elkZmZiYWGhtUKFEGWrTE8CfkmV+DPw9/dn0aJFvPnmm+ptv/76K56ensyZM4fc3NwyLVAIoR1yR+gXCMCwsDD27t3LG2+8od7m7OzMpEmT2LlzJ2vWrCnL+oQQWqKvV/RDCUp8HuCePXuYNGkSAwYMUG8zNzcnMDAQPT091q9fLydDC/ESUMpXXxalxAGYlJSEnZ1doW329vYkJCSUuighhPYpZZRXlBJ/BA0bNuT7778vtO3AgQPUq1ev1EUJIbRPX6Uq8qEEJR4BBgUF8fHHH5OcnEynTp2oUaMGDx8+5ODBg+zfv5958+Zpo04hRBlTyDpHkUocgP7+/jx69Ijly5ezf/9+9fZq1aoxY8YMevToUaYFCiG0QykrvUV5oZv3vfXWWwwYMIDr16+TnJyMmZkZhoaGbNu2DR8fH44dO1bWdQohypgEYCnuCK1SqbC3t+fw4cNERERw/PhxcnNzadCgQVnWJ4TQEsm/FwzAxMREtm3bxvbt24mPj8fMzIwBAwbwxhtv0KJFi7KuUQihBUpZ6ChKiQLw+PHjREVFcfjwYfLz83F3dyc+Pp7ly5fj5uamrRqFEFogp8EUMwDXrl3LV199xc2bN7G3t2fs2LH07t0bQ0ND2rRpo+0ahRBaICdCFzMAQ0JCcHBwYNOmTRojvUePHmmtMCGEdskiSDFPhO7Vqxc3b95k6NChDB8+nH379hX4SjohxMtFpSr6oQTFGgEuWLCAtLQ0vv32W6Kjoxk/fjzm5ub4+fmhUqlQKeXTEuIVIosgL/CdIADXrl1j+/bt7N69m/v372Nra0uPHj3w9/enSZMm2qiz1OQ7QcqffCdI+SvJd4JsPnOryPaA1wq/5v9V8kIB+FRubi6HDx9m+/btHDt2jNzcXBo3bsyuXbvKssYyIQFY/iQAy19JAnDLcwJwoAIC8IVPhAbQ19enU6dOdOrUiQcPHhAdHc3XX39dRqUJIbRJTxZBSjcCfJnICLD8yQiw/JVkBPjV2TtFtr/pWru05VR4pRoBCiFeXjL+kwAUQrFkFVgCUAjFkitBJACFUCzJPwlAIRRLpsASgEIolkyBJQB1Lv7uXfr17smSsBW4tXEvdltCQgJLFy3g+LFj5ORk06x5C8Z/MpGmTZ3Ks/yXQm5uLju+3MD+b3fy4F4itnXq0eft9/Dt4q/u89HwQH6/8FuB5y6K2Iij85N7XH4eEcr2LZ8X6PPe8LG8GRCkvTegJXqyDiwBqEt37tzmg/eHFHpXnaLa0tL+Iui9gVSuXJlPZwZjYGjI6ohwRgwdzPavd2NpaVUe5b80NqxexjdfbSZg6CgaOzhx+udjLJo9DT09FT6du5OXl8eNP67Q9+33aOftp/HcevaN1D//ceV3XF5z591hozT6WFrblMv7KGt6cj9ACUBdyMvLY9c3O1m8cEGJ2p7atGE9yUlJfP3tPnXYOTs34603+3D61Cm6+csXUz2V/vgx3+6I4h9vBtB/4GAAXFu7c/X3C+zeEYVP5+7c/jOOzIwM3Np6qUd7hfnj6u/4v9G/yD4vEzkGKAGoE5d//505n83izbfewaNtO0Z/8H6x2p46dGA/nV7vojHSq2lpycHDR8uh+peLgYEBIREbqFa9psb2SpUr8zgtDXgysgOwb/TsG3kkPXxA8sMH2Ddy0F6x5UwlU2AJQF2oVasW3+47gLWNDbGnYordBpCdnc0ff1zDv2cvloctZeeO7SQnJ+Hi2pIp0z6lcZNX5xe0LOhXqkSD/4RWfn4+SQ8fcHDvN5w9HcOYiTOAJyO7qiYmrA5byKkTP5GRkY5LKzeGjZmAXd36AFy7cgmAmGM/sip0AQ/v36Neg4a89/4YWnt46uS9lZYsghTzhqiibJlbWGBtU/hxo6LaAFJTU8nJyWHzxvXEnoph5mezmR+yhOTkZIYMepeEhARtlf3S+/HAXgLf6MSG1ct4zb09HXy7AE9GgGl//YW5RTWmz13C2IkzuXPrJhNHDebB/UR1H4DkpId8OGkG0+csxsKiOsGTxnIm5oTO3lNp6KtURT5K4/bt2zg4OBR4bNu2DYCLFy8SEBCAq6srPj4+REZGajw/Ly+PsLAwvLy8cHFxISgoiLi4uFLVVBgZAb5kcrKz1T+vXLUW46pVgSfHAHt2f52oLzbz4fiPdVVehebg1Jz5yyK5dfMGmyNX8skH77Fk9WYGjRjL2+8Nw6lFyycdXaBpcxdGBPTmm21fEPTBOHw6daVBoya0atMOvf+sHrRyb8voQQPYHBnOa+7tdPjOXow2B4C///47hoaGHDx4UOOGyaampiQlJTF48GA6depEcHAwZ8+eJTg4GAsLC/r27QtAeHg4UVFRzJs3D2traxYuXMiwYcP49ttvMTAwKLM6JQBfMk8Dr7Wbu/pngFq1a9OgQUN+v3RRV6VVeLXt6lLbri7NXF+jlm0dpo57n+NHDtLxdf8CfWvVtqNOPXuuX70MgJVNbaxsNO+OUqlSZVq18WDfNzvKpf6yps1FkMuXL2Nvb4+VVcEzEjZs2ICBgQGzZs2iUqVKNGzYkLi4ONasWUPfvn3Jyspi3bp1TJgwAW9vbwCWLFmCl5cXBw4cwN+/4P9fL0qnARgYGFjs2+lv3LhRy9W8HExNTaleo0ah38mSnZODoZGRDqqquJKTHnL652O09vDEolp19fbGTZ0BiL9zmwN7v6FOPfsCq7tZmZmYmVsAcOrET2RnZ9P+f06TyczMxNTcXLtvQku0PQJs1KhRoW2nT5/Gzc2NSpX+Gz8eHh6sWrWKBw8ecPv2bdLS0vDw8FC3m5mZ4eTkRGxsbJkGoE6PAbZt25bY2FgePHiAra1tkQ/xX56eHYj5+QRJSQ/V225c/4O4G9dp1aq1DiureNLTH7Nk7gy+3x2tsf1MzHEAGjs6sWVdBOtWLtVov/r7Re7e/pMWLZ98nkd/2M/SeTN59ChV3ScjPZ3Yk0dp7vpyfuaq5/yvNC5fvsyDBw945513aNeuHW+//TZHjz45SyE+Ph6b/znO/XSkeOfOHeLj44EnC4L/2+fu3bulqut/6XQEOHLkSIyNjQkLC2PVqlXY2b36t+AuC8M/GMXhHw4yYtgQhn8wipycbJYtXYK1jQ19+vXTdXkVSq3advh17cGXG1ajp69PE0dnrlw6T9TGtbRq047X3NvzzuDhhP5rFovnfErH17uTcPcOmyNXUr9hYzp16wVA33cGcfzHg8yaMJr+AUHk5uayfcvnZKQ/JmDIBzp+ly/meTeE9vPzK7L90KFDhW7Pysrixo0bVKlShYkTJ2JsbMyuXbsYNmwYn3/+ORkZGQWO4xkaGgJPRtTp6U9upFtYn5SUlKKLLiGdHwMcNGgQx44dY+nSpYSEhOi6nJeCXZ06bNgcxdLFIUybPAF9fX082rZjwqSpVK1qouvyKpwxE2ZQu049Duz5mi3rVlK9Rk3+0f8d3np3GCqVitf938DQ0IgdX27gn1PHY2RUhbYdfBk0fCz6/5mm1W/QiPnLI9m4ejlL580kJzsbZ5dWfDh5PbVs6+j4Hb4YbX2bo4GBAbGxsVSqVEkdYs2aNePatWtERkZiZGRU4BBOZmYmAMbGxhj95zBOVlaW+uenfapUKf4dr4ujQtwSPyEhgQsXLtCxY0etvYbcEr/8yS3xy19Jbol/5kZqke2v1TcrbTka5s+fz7Fjx7CxscHCwoKFCxeq206cOMHgwYM5ceIEt2/fpn///hw4cIC6deuq+7z99ts4Ojoyc+bMMqupQpwHaG1trdXwE0IUpK0vRr906RItW7bk9OnTGtv//e9/06hRI9zc3Dhz5gy5ubnqtpMnT2Jvb0+NGjVwdHTExMSEmJj/XgiQmprKhQsXaN26bI+3VogAFEKUPz2VqsjHi2rSpAmNGzcmODiY06dPc+3aNebNm8fZs2cZMWIEffv25a+//mLatGlcvXqV6OhoNmzYwPDhw4EnU+iAgABCQkI4dOgQly5dYvz48djY2NC5c+eyevtABZkClweZApc/mQKXv5JMgf/vZsE7Df2dS13TF67j4cOHhISE8NNPP5GamoqTkxOffPKJegR37tw55syZw4ULF7C0tCQoKIiAgAD183Nzc1m8eDHR0dFkZGTg5ubGjBkzynyhVAJQaI0EYPkrSQCe+/OvIttb1Hn1F9R0vgoshNAN+V50CUAhlEsCUAJQCKWS22FJAAqhWJJ/EoBCKJbcEVoCUAjFkkUQCUAhFEtb1wK/TCQAhVAoyT8JQCEUSwJQAlAIxZLTYCQAhVAsiT8JQCEUSxZBJACFUCw5DUYCUAjFkgGgBKAQiiVTYAlAIRRLpsASgEIollwLLAEohGLJDFgCUAjFkhOhJQCFUC7JPwlAIZRKFkEkAIVQLJkCyxejCyEUTEaAQiiUjAAlAIVQLDkGKAEohHJJAEoACqFUMgWWABRCsST/JACFUCy5FhhU+fn5+bouQgghdEHOAxRCKJYEoBBCsSQAhRCKJQEohFAsCUAhhGJJAAohFEsCUAihWBKAQgjFkgAUQiiWBKAQQrEkAIUQiiUBKIRQLAlAIYRiSQBWUHl5eYSFheHl5YWLiwtBQUHExcXpuizFCA8PJzAwUNdlCC2TAKygwsPDiYqKYvbs2WzduhWVSsWwYcPIysrSdWmvvPXr1xMWFqbrMkQ5kACsgLKysli3bh1jxozB29sbR0dHlixZQkJCAgcOHNB1ea+shIQEhg4dSmhoKPb29rouR5QDCcAK6NKlS6SlpeHh4aHeZmZmhpOTE7GxsTqs7NV2/vx5zM3N2bVrFy4uLrouR5QDuSV+BRQfHw9ArVq1NLZbWVlx9+5dXZSkCL6+vvj6+uq6DFGOZARYAaWnpwNgYGCgsd3Q0JDMzExdlCTEK0kCsAIyMjICKLDgkZmZSZUqVXRRkhCvJAnACujp1DcxMVFje2JiIjY2NrooSYhXkgRgBeTo6IiJiQkxMTHqbampqVy4cIHWrVvrsDIhXi2yCFIBGRgYEBAQQEhICNWrV8fW1paFCxdiY2ND586ddV2eEK8MCcAKauzYseTk5DB9+nQyMjJwc3MjMjKywMKIEOLFyRejCyEUS44BCiEUSwJQCKFYEoBCCMWSABRCKJYEoBBCsSQAhRCKJQEoKhw5M0uUFwnAV1BgYCAODg4aj2bNmuHj40NwcDApKSlaed3o6GgcHBy4desWAMuWLcPBwaHYz4+Pj2f48OHcvn271LXcunULBwcHoqOjS70v8eqSK0FeUU5OTsycOVP97+zsbM6fP8/ixYu5ePEiX375JSqVSqs19O/fHy8vr2L3P3HiBD/++COffvqpFqsS4r8kAF9RJiYmuLq6amxzc3MjLS2NsLAw/u///q9Ae1mzsbGRu9eICk2mwArTrFkzAO7cuUNgYCCffPIJY8eOpVWrVrz//vvAk/sOLliwAG9vb5o1a0bPnj3Zu3evxn7y8vIIDw/Hx8cHFxcXRo4cWWBqXdgUeM+ePfTp0wcXFxd8fHxYuHAhWVlZREdHM2XKFAD8/PyYPHmy+jnbtm3D399fPY1ftmwZOTk5Gvvdv38/vXr1okWLFvTu3ZtLly6VzQcmXmkyAlSY69evA1CnTh0A9u3bR9euXVmxYgW5ubnk5+czatQofvnlF8aOHUvDhg05cOAA48ePJysrizfeeAOAhQsXsnHjRkaMGIGrqyvfffcdixYtKvK1o6KimDlzJv369WP8+PHcunWLBQsWkJSUxCeffMIHH3zAypUrWb58uTo4V61axZIlSwgICGDKlClcvHiRZcuWcffuXebOnQvADz/8wNixY/H39+eTTz7h0qVLTJgwQUufoHiVSAC+ovLz8zVGSSkpKZw6dYqVK1fi6uqqHgnq6enxz3/+E2NjYwCOHz/O0aNHWbJkCd27dwfAy8uL9PR0QkJC6NGjB48fP2bTpk28++67jBkzRt0nISGBo0ePFlpPXl4ey5Yto3PnzsyZM0e9PTMzk507d2JiYkLdunUBaNq0KXZ2djx69IiVK1cyYMAApk+fDoCnpycWFhZMnz6dwYMH07hxY1asWIGzs7M6gDt06ADw3EAWQqbAr6jY2FicnZ3Vj3bt2vHRRx/h7OzM4sWL1QsgdnZ26vADOHnyJCqVCm9vb3JyctQPX19f7t27x5UrVzh79izZ2dn4+flpvGa3bt2eWc/169e5f/8+nTp10tg+aNAgvvnmm0Jv8/Xrr7+Snp6Or69vgVrgSVhnZGRw/vz5EtUixFMyAnxFOTs7ExwcDIBKpcLQ0JBatWphYmKi0a9mzZoa/05OTiY/P59WrVoVut/ExERSU1MBqF69ukabpaXlM+tJTk4GoEaNGsV+D0+f8/TYZGG1pKSkkJ+fX6AWKyurYr+OUC4JwFdU1apVad68eYmfZ2pqirGxMRs3biy0vV69epw7dw6ABw8e0KBBA3Xb08AqjJmZGQAPHz7U2J6cnMz58+cLXZF++pyQkBDq169foL1mzZpYWFigp6fH/fv3C+xXiOeRKbDQ0KZNGx4/fkx+fj7NmzdXP65cucKKFSvIycmhZcuWGBkZ8d1332k89/Dhw8/cb4MGDahWrRqHDh3S2L57926GDRtGZmYmenqa/zm6uLhQuXJlEhISNGqpXLkyixYt4tatWxgaGtKyZUv279+vcQXJDz/8UAafhnjVyQhQaPD29sbNzY2RI0cycuRIGjZsyLlz51i2bBmenp7qqebIkSNZunQpVapUwcPDgyNHjhQZgPr6+owZM4bPPvuMWbNm0blzZ27cuMHSpUt5++23qV69unrEd+DAATp06EDDhg0ZOnQooaGh/PXXX7i7u5OQkEBoaCgqlQpHR0cAPvroI9577z1Gjx7NgAEDuHHjBitXrtT+hyVeehKAQoOenh6rV68mNDSUVatW8eDBA6ytrRk0aBCjRo1S9xs+fDjGxsZs2LCBDRs20LJlSyZNmsSsWbOeue+BAwdibGxMZGQk27dvx9ramqCgIPUxPnd3d9q1a8eiRYs4efIkq1evZty4cVhaWvLFF1+wdu1azM3Nadu2LR999BGmpqYAtG7dmjVr1rB48WJGjx6NnZ0dc+fOZcSIEVr9rMTLT74TRAihWHIMUAihWBKAQgjFkgAUQiiWBKAQQrEkAIUQiiUBKIRQLAlAIYRiSQAKIRRLAlAIoVgSgEIIxZIAFEIolgSgEEKx/h9+P9lcpzhz/AAAAABJRU5ErkJggg==",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled Dataset (No PCA) ccp_alpha: 0.001 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.94 0.70 0.80 2529\n",
+ " 1.0 0.32 0.75 0.45 471\n",
+ "\n",
+ " accuracy 0.71 3000\n",
+ " macro avg 0.63 0.73 0.63 3000\n",
+ "weighted avg 0.84 0.71 0.75 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled Dataset (No PCA) ccp_alpha: 0.005...\u001b[0m\n",
+ "Oversampled Dataset (No PCA) ccp_alpha: 0.005 Accuracy: 0.666\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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GPG85ZZ7MAIVQKJVargcoASiEQqnkgqgSgEIolVotx0AlAIVQKFkCSwAKoViyBJYAFEKxZAksASiEYskSWAJQCMWSJbAEoBCKJUtgCUAhFEuWwBKApaqyow0ndkzl9Qlr+OnUFc32Sg7WBI9/jY4tPTAyVHPy3E2mLv6S3y9FFzhOozpV+GHTB4z+z2d8uue/V8zo2LIOu5fn//rZgZ/P82pgeMm/oRdIy+o2+NW0xdbciMT0R/xwLZEfrydq2mvamdHTowLO1iakP8rl9zsP2HPhHpnZuQWOV8XGlIk+1fns9F1+vZVcWm+jRMkSWAKw1FStWJ7dy8dgY6l9sUYLcxMOrhtP1qMcxgZ/TkZmNlOGd+brFYF4vT6XmPspWv2NjQxZMzsAI6P8V+vwdKtMQnIqvcau0Nqe9CC95N/QC6RlNRsGNqrIkWsJnL37AFd7c/p5OmJkoOLQ1QQqWpowtlVVrsWns/74bWzMjHitXgXsyxmx8tf8f4QM1SrealIRgxd8BiVLYAlAnVOpVPj3aM68CQVfpWKsfzvsbCxo2Ps/mrD77fxNfvlsEm2b1mL7N6e0+s8c3Q1rC7MCx2rgVpk/Lt/m+B83SvQ9vOhaVLPmWnwaO87GAnDpXhoVLIxpW6M8h64m4FXFijxg9a9/k5nz+NogahW80agitmaGJKRna43XvY4DZob6uZpySZIlsFwPUOfq16pE6NT+bP06iqEfbcrX/lr7huw6dFprphcb/4CanabnC7/mDVwYNcCH8R9vL/C1GtR25uy/LJuVzFCtIv2R9lI2NTOHcsYGmvac3Dyycv57YaTUrMcX2ixnrD1HcLE1w6dmebb9HqPjqnVPpVIV+lACCUAd+zsmkXo9g5i0MJK09EdabYaGauq4VOTy9VhmjO7GXweCSTm+lANr36WuayWtvqYmRqyZHcAn6w/wx+Xb+V7HzNQI16oVcKniQNS2ySQfX8KlfbMZH1D4jW2U4PtrCdSpUA6vKlaYGqqpU6Eczatac/zvx/vufrmZBEDv+o6UMzagoqUxXdztuZ2cQXRyhmYcI7WKgCYV+fZSPLdTin7jnbJKpVYV+lACvS6Bs7OzOXDgACdPnuTOnTtkZWVhZmaGk5MTTZs2pWPHjlr3/XwRJaakkZiSVmBbeUtzjIwMGOvvx/Xo+4ye/RkmxoZ8NKob3655l2avz+XOvce/pMHvvsrDtEwWrD+AcwWbfGPVr+WMgYEa1yoOzF7xNYkpafTwbUDw+FexsTJn1vI9unybZdrp2w9wc0hmUFNnzbbzsQ/Z+f9L4pgHWXx1Lo7XPZ3wc7UFID41i0U/3eSfF8t8rV4FMrPzOHD5PjZmRqX5FnRC9gHqMQBv3brF8OHDiY2NxcPDgwoVKmBtbU1mZiYXLlzgiy++ICwsjLVr11KpUqWnD/gCMjb678ffc8xyUtMf3+Xqt/O3+OOrGYwc4MOMsN20aVKLIb1b0SZgATk5BR+VvHQ9lp5jlnPq3C0SklMBOHL8MqYmRox/y49Fmw6S8jCjwOe+7EZ4V6aGrRm7/ozlRkIGztYmdK1jz7BmlVkdFc0rte14tW4FfriWwJk7D7AwMaCLuz3jWldl8Y83eZCZQy17c1pVt+GTIzfIfUkuIayUZW5h9BaAQUFBVK5cmZ07d2JpaZmvPSUlhQkTJjB79mxWrlyphwp170Ha40D68eQVTfjB42XzxeuxNHBzppyZMauDBrJw40Eu/BWDgYEaA4PHf7nVahUGBmpycnJJfpjOwV8u5HuNb346x5DerXB3cVLkwREXWzM8HC3Y+ttdzVL3anwa91MfMbplFeo5WdDZzZ7jt5LZ/v8zQoAr99MIesWVDrXs2HfhHv6NK3LwcjwxDzJRqx4fJIHH9w5Sq3ghQ1Epy9zC6C0AT506xbZt2woMPwArKysmTpzIwIEDS7my0pPyMIPY+BRMjPP/32BkaEBGxiMae1SjurM900Z0ZdqIrlp9Vs3yZ9Usf8waBdKoThWa1K3G2p1HtfqYmT5eqt1Peqi7N1KG2Zo/fv/XErR3Q1y9/3iWXNXGFBNDNX/9T/uDzBxiHmRS0dKEquXNsC9nTNc6DnSt46DVz79xJfwbV2LMrvx/fMo6WQLrMQCtrKyIi4vDzc3tX/vcuXNH68bIL6MDP5+nZztP7GzKEZ/0+JeyVrUK1K5WgY27fuH0hVu0GviJ1nOc7K34YulI5qzcx/6f/gSgfm1nwqYN4MrNOH44cVnTt+8rjbl1N4Ebt+NL702VIbEPHh+scLUzJ/bBf2fZNewen48Z8yCTh1nZ1LQz56frSZr2csYGVLAw5mZiCreSMph/+LrWuFamhoxqUYW9F+7xZ8yL+cdFVsB6DMC+ffsyZcoUxo0bR/PmzalYsSLGxsZkZWURGxvL8ePHCQkJoW/fvvoqsVTMXb2fHu0asCc8kHmr92NkaEDQ2B5ExyayYdcvPEzL5Lfzt7SeU7Xi4x31N+/Ea9p2fvsbE97qwPo5bzFr+dfE3E9mQBcvuvnUJ2DSBnJfxDVaCYhOzuT07RT61HfE3MiAG4npVLR8vA/wVmI6Z+48wNLEkNc9ncjIzuX07RTKGRvQqbY9eXlw6Go8mdm53ErS3n/6ZGaZkPYoX9uLQi1LYP0F4NixY1Gr1cyfP5+0tPxHScuVK8fAgQN599139VBd6blxO552gxYxZ9yrrJvzFjm5uXz/60U+DInkYVrRT7VIy8iiy4hQZo3pwczR3bCzseDctbsMeH8te46c1eE7KPs2nLhNZ3d7WrvY0K2OPYnp2fx6M5n9F++Rmwc//JVI2qMc2rva4V3VmtSsHK7Gp7EqKpqEtEdPf4EXlARgGbgt5qNHj7hw4QKxsbGkp6djamqKk5MT7u7umnuAlgS5LWbpk9tilr7i3BbTY+qBQtvPz33lecsp8/R+kp2RkRENGjTQdxlCKI7MAMtAAAoh9EMCUAJQCMWSE6ElAIVQLJkBSgAKoVgSgBKAQiiWrIAlAIVQLJkBSgAKoVgSgBKAQiiWHAWWABRCsWQGKAEohGJJAEoACqFYsgQuYgCeOHGiWIN6eXk9UzFCiNIjM8AiBmBAQECR/lrk5eWhUqm4cOHFuzquEEojAVjEANy8ebOu6xBClDJZARcxAJs1a6brOoQQpcxAZoDPdhDkzJkzHD9+nEePHvHkeqp5eXmkpaVx6tQptm/fXqJFCiFKXmkFYHh4OMeOHWPLli2abRcuXCA4OJg///wTGxsbAgICGDp0qKY9NzeXZcuWsWPHDlJSUmjSpAkzZ86kWrVqRR6jKIodgFu3bmXOnDkUdCFptVpN69atizukEEIPSuMo8MaNGwkNDdU6MJqYmMjgwYPp0KEDQUFBnDlzhqCgIGxsbOjTpw/wODQjIiKYN28ejo6OLFiwgOHDh/P1119jbGxcpDGKotj3xfv0009p3bo1UVFRDB06lNdff50zZ86wdOlSTExM6NmzZ3GHFELogVqlKvTxPGJjYxk2bBhLly7FxcVFq2379u0YGxsza9YsatasSZ8+fRg0aBBr1qwBICsri/Xr1zN27Fh8fHxwd3dn8eLFxMbGcvDgwSKNUeTPoLhvLDo6Gn9/f6ytralfvz6nTp3C1NSUTp06MWLECDlgIsQLwkCtKvTxPM6dO4e1tTW7d+/G09NTq+3kyZN4eXlhaPjfBai3tzfXr18nPj6eixcvkpqaire3t6bdysoKDw8PzSl5TxujqIq9BDYyMtLcq7d69ercvHmTR48eYWRkROPGjVm/fn1xhxRC6MHTJnnt27cvtP3QoUP/2ubn54efn1+BbTExMdSuXVtrW4UKFYDH9wKPiYkBoGLFivn63L17t0hj2NnZFVr7E8WeAdapU4fDhw8DUK1aNXJzczlz5oymKCHEi0GXM8DCZGRk5Lvjo4mJCQCZmZmkp6cDFNgnMzOzSGMUVbFngIMHDyYwMJDk5GTmzZtH+/bt+fDDD+nUqRN79uyhSZMmxR1SCKEHTzsRurAZ3vMwNTUlKytLa9uT0DI3N9esMLOysjT/ftLHzMysSGMUVbFngB06dGDlypW4uroCMHv2bFxcXIiIiKBGjRrMmDGjuEMKIfRAlwdBCuPk5ERcXJzWtic/Ozo6apa+BfVxcnIq0hhF9UznAfr6+uLr6wtA+fLlZb+fEC8gXYZcYby8vIiIiCAnJwcDAwMAjh07houLC3Z2dlhaWmJhYUFUVBRVq1YFICUlhfPnz+Pv71+kMYqq2DPAO3fuPPUhhCj79LUPsE+fPjx8+JBp06Zx9epVIiMj2bRpEyNGjAAe7/vz9/cnJCSEQ4cOcfHiRSZMmICTkxMdO3Ys0hhFVewZoJ+f31NPoJSLIQhR9unru8B2dnasXbuW4OBgevXqhYODAx9++CG9evXS9Bk3bhzZ2dlMnz6djIwMvLy8WLdunebAR1HGKApVXkFf6ShEZGRkvgB88hW4X3/9lblz52qWx2WJWaNAfZegOENmjNF3CYqzvFedIvcd9PnZQts3vtHgecsp84o9A+zdu3eB2wcOHMj8+fPZs2dPmQxAIYQ2fe0DLEuKvQ+wML6+vhw5cqQkhxRC6Ii+jgKXJSV6SfwzZ85ofTVFCFF2yQVRnyEAp0yZkm9bbm4ud+/e5eTJk/Tt27dEChNC6JZcD/AZAjAqKirfNpVKhYWFBcOHD2fkyJElUpgQQrcUssotVLED8Pvvv9dFHTqXeGKZvktQnFv30/RdgiiEgSRg8Q+CTJkyhb///rvAtr/++ktmgEK8IPR1InRZUqQZ4D+/3bFr1y46dOig+frJP/3444/88ssvJVedEEJnFJJxhSpSAM6ePZsffvgBeLy/LzCw4JOK8/LyaNWqVclVJ4TQGaXM8gpTpAAMCgril19+IS8vj6lTpzJq1CjNl5SfUKvVWFlZ0bx5c50UKoQoWRKARQxAR0dHzXfsVCoVvr6+WFhYYGRkBEB6ejqZmZnY2NjorFAhRMkq0W9BvKCK/Rl069aNhQsX8vrrr2u2nT59mtatWxMcHExOTk6JFiiE0A05CPIMARgaGsq+fft47bXXNNvq1q3LpEmT2LVrV7HvyiSE0A8DdeEPJSj2eYB79+5l0qRJ9O/fX7PN2tqagIAA1Go1GzdulFNhhHgBKOX7voUpdgAmJiZSuXLlAttcXFyIjY197qKEELqnlFleYYr9EdSsWZNvv/22wLaDBw9SrVq15y5KCKF7BipVoQ8lKPYMcMiQIbz//vskJSXRoUMH7OzsSEhI4LvvvuPAgQPMmzdPF3UKIUqYQo5zFKrYAditWzcePHjAsmXLOHDggGZ7+fLlmTFjBt27dy/RAoUQuqGUI72FeaaL9w0YMID+/ftz/fp1kpKSsLKywsTEhB07duDr68vRo0dLuk4hRAmTAHyOC6KqVCpcXFw4fPgwK1eu5OeffyYnJ4caNWqUZH1CCB2R/HvGAIyLi2PHjh3s3LmTmJgYrKys6N+/P6+99hoNGrz8N1IR4mWglAMdhSlWAP78889ERERw+PBh8vLyaN68OTExMSxbtgwvLy9d1SiE0AE5DaaIAbh27Vq2b9/OrVu3cHFxYdy4cfTq1QsTExOaNWum6xqFEDogJ0IXMQBDQkJwc3Njy5YtWjO9Bw8e6KwwIYRuyUGQIp4I3bNnT27dusWwYcMYMWIE+/fvJysrS9e1CSF0SKUq/KEERZoBfvLJJ6SmpvL1118TGRnJhAkTsLa2pn379qhUKlRK+bSEeInIQRBQ5eXl5RX3SdeuXWPnzp3s2bOH+/fv4+zsTPfu3enWrRu1a9fWRZ3PLSNb3xUoj9wUqfTVdjIvct9PT0UX2u7fpODv/L9MnikAn8jJyeHw4cPs3LmTo0ePkpOTQ61atdi9e3dJ1lgiJABLnwRg6StOAG59SgAOVEAAPvOJ0AAGBgZ06NCBDh06EB8fT2RkJF9++WUJlSaE0CW1HAR5vhngi0RmgKVPZoClrzgzwO1n7hTa/nrDSs9bTpn3XDNAIcSLS+Z/EoBCKJYcBZYAFEKx5JsgEoBCKJbknwSgEIolS2AJQCEUS5bAEoB6F3P3Ln179WBx6HK8mjUvcttvp04SumQRly9dxNLSCr8OHQgcN55y5SxKs/wXQk5ODpERmzi490vi78VRqUpVeg94m3avdNP0+WDUW1w6/0e+5y4I34R73cfXuLx+7TIbVy7l0vmzqNUGeLVow9sjxmFr51Bq76UkqeU4sASgPt25c5tR7wwt8Ko6hbVduXKZEcMG06hxExYsXEJsbCyLFy4g+u9owsJXlkbpL5Qta5bx1Y5PGTh0NLXcPDj561EWBU9HpVLj27ELubm53PjrCr0HvE2Ltn5az63m4grA/bhYpk0YgXPlqrw/fS6ZGRlsXhPG9PdGErZuGwaGL96vklquBygBqA+5ubns/moXixZ8Uqy2J/bv/RqVSsWS0OWYlysHQHZONsGzZ3Hnzm0qVXLWVekvnPS0NPZERvBqP3/6vjkYAM8mzbl6+QJfR36Ob8cu3P77JpkZGTRt0Voz2/tf3+zZSWZ6OjM+DsXSyhoAa5vyTB0/nN9/O07jZi1L7T2VFF3uA7x9+zZ+fn75ts+ZM4d+/fpx4cIFgoOD+fPPP7GxsSEgIIChQ4dq+uXm5rJs2TJ27NhBSkoKTZo0YebMmSV+210JQD24fOkSwbNn8fqAN/Fu0ZLAUe8Uqe2JrKwsDA0NMTUz02wrb1MegOSkJAnAfzA2NiYkfCM2tvZa2w0NjUhLTQXg+tVLALjUdPvXcXr0eYPmrXw14QdgaPT41+fRoxfz0nAqHS6BL126hImJCd99953W1aIsLS1JTExk8ODBdOjQgaCgIM6cOUNQUBA2Njb06dMHgPDwcCIiIpg3bx6Ojo4sWLCA4cOH8/XXX2NsbFxidUoA6kHFihX5ev9BHJ2cOHE8qshtT/Tq3ZddX+wgZP483hk1mvv377NyxXJq1a5NbTf30ngLLwwDQ0NcXB8HW15eHkkJ8Xy3/yt+PxVF4MSPAPjr6iXKWViwZtkCTvzyIxkZ6TRo5MWwwA+oXLU6ANY2tljb2AKQlZnJX1cusnLxx1SqXJVGTVvo5b09L10eBLl8+TIuLi5UqFAhX9umTZswNjZm1qxZGBoaUrNmTW7evMmaNWvo06cPWVlZrF+/nokTJ+Lj4wPA4sWLadOmDQcPHqRbt275xnxWEoB6YG1jg/UztD1R09WVdye8z7zg/7D1080AVKrkzIbNWzEwMCjRWl8mP3y3n4VzpgHQ1Ls1bdp1AuD61cukPnyItU15ps1ZRFzsXT7fuIrJY4ewdF0Edvbav8SBg/tx9/bfGBubMHn2AoxNTEr9vZQEXS6BL126hKura4FtJ0+exMvLC8N/7Df19vZm1apVxMfHc/v2bVJTU/H29ta0W1lZ4eHhwYkTJ0o0AGU36Ato3ZpVBP8niH7932D1uo3MD1mMmbk5w4cOIv7+fX2XV2bVrlOPeaFrCfzgI65dvsiHYwaRlZnJ2++MY/6yDQwZNYG6no1p90o3ZoeEk5r6kD07P883zqgJU5kdsoIWbf2YM3U8hw/s1cO7eX66vCL05cuXiY+P580336Rly5a88cYb/PTTTwDExMTg5OSk1f/JTPHOnTvExMQAj1dD/9vn7t27z1fY/5AZ4AsmOzub1atW0LV7D6ZOn6HZ7uXVjG6dO7JxwzrenzhJjxWWXZUqV6VS5arU82yCk3Nlpk8YwS8/HsK3Y9d8fZ0qVaZKNReuX7ucr62Rl7fmf+/fi+Xzjau0Tql5UTxtBti+fftC2w8dOlTg9qysLG7cuIGZmRkffvgh5ubm7N69m+HDh7NhwwYyMjLy7ccz+f9ZdGZmJunp6QAF9klOTi60puLSawAGBAQU+XL6mzdv1nE1L4bExAQy0tNp1Kix1nY7e3tcarhw7eoVPVVWNiUlJnAq6ihNmrfGprytZnst97oAxNyJ5rv9u6lctXq+I8BZmZlYWdsA8Ptvx3mUlUlT7zZafWq5ebD3wnbdvgkd0dUK2NjYmBMnTmBoaKgJsXr16nHt2jXWrVuHqalpvnsKZWZmAmBubo6pqSnwOEif/PtJH7N/HPgrCXoNwBYtWhAWFkaNGjXkhupFZGtrh7W1Db+dOsXrA97UbE9MTODmjRvUqyef4z9lpKexZN5MAoYF8nrAf0+z+C3qFwBc3TwIXxRMBceKfBy2XtN+9fIF7t7+m14D3gLg0P7dnIz6mbURX2Nu/vjUo5zsbH7/7TguNcvmbSCe5mlHgf9thlcU5ub5r0tYu3Ztjh49ipOTE3FxcVptT352dHQkOztbs61q1apafdzdS/Ygn14DcPTo0ZibmxMaGsqqVauoXPnlvwT38zIwMGDUmLF8PPc/lLMoxyudupCYmMj6NatQGxjw1qAh+i6xTHGqVBm/Tt2J2LwatYGaWu51uXrxPNu2rKVxs5Y0ad6KN94eQegnQSyeNwPfDl2Ji7nD1vUrqF6jFh069wSgzxuD+OXHQwR9OJY+b7xNHnns+eJz/r7xF7MXrtDzu3w2urog9MWLF3njjTdYs2YNTZs21Wz/888/cXV1pU6dOkRERJCTk6M5aHfs2DFcXFyws7PD0tISCwsLoqKiNAGYkpLC+fPn8ff3L9Fa9b4PcNCgQRw9epQlS5YQEhKi73JeCG8M9MfSypLNGzfw1a5IbMqXp3GTpiwOW46zs/wR+V+BH3xEpSrV+G7fV3y2YSXlbe3p2fcN+gcMR6VS0bHba5iYmhIZsZng6RMwNTXDu40fb78zVvMNj2o1XPk4bD1b1ixjycczefQoC/e6nswLXfevJ0+Xdbq6m2Pt2rWpVasWQUFBzJw5k/Lly7N9+3bOnDnDzp07sbe3Z+3atUybNo1hw4Zx9uxZNm3aRFBQEPB4Ce3v709ISAi2trY4OzuzYMECnJyc6NixY4nWWiYuiR8bG8v58+dp166dzl5DLolf+uSS+KWvOJfEP3UjpdD2JtWtnrmOhIQEQkJC+PHHH0lJScHDw4MPPvhAMyM8e/YswcHBnD9/HgcHB4YMGaI1u8vJyWHRokVERkaSkZGBl5cXM2bMKPFVYpkIwNIgAVj6JABLX3EC8LebhQdg42rPHoAvCr0vgYUQ+iGXw5IAFEKxJP4kAIVQLF0dBHmRSAAKoVByX3QJQCGUSwJQAlAIpZKDIBKAQiiW5J8EoBCKpcsrQr8oJACFUCg5CCIBKIRiyWkwEoBCKJbknwSgEIolASgBKIRiyWkwEoBCKJbEnwSgEIolB0EkAIVQLDkNRgJQCMWSCaAEoBCKJUtgCUAhFEuWwBKAQiiWfBdYAlAIxZIVsASgEIolJ0JLAAqhXJJ/EoBCKJUcBJEAFEKxZAkMan0XIIQQ+iIzQCEUSmaAEoBCKJbsA5QAFEK5JAAlAIVQKlkCSwAKoViSfxKAQiiWfBcYVHl5eXn6LkIIIfRBzgMUQiiWBKAQQrEkAIUQiiUBKIRQLAlAIYRiSQAKIRRLAlAIoVgSgEIIxZIAFEIolgSgEEKxJACFEIolASiEUCwJQCGEYkkAllG5ubmEhobSpk0bPD09GTJkCDdv3tR3WYoRHh5OQECAvssQOiYBWEaFh4cTERHBnDlz2LZtGyqViuHDh5OVlaXv0l56GzduJDQ0VN9liFIgAVgGZWVlsX79esaOHYuPjw/u7u4sXryY2NhYDh48qO/yXlqxsbEMGzaMpUuX4uLiou9yRCmQACyDLl68SGpqKt7e3pptVlZWeHh4cOLECT1W9nI7d+4c1tbW7N69G09PT32XI0qBXBK/DIqJiQGgYsWKWtsrVKjA3bt39VGSIvj5+eHn56fvMkQpkhlgGZSeng6AsbGx1nYTExMyMzP1UZIQLyUJwDLI1NQUIN8Bj8zMTMzMzPRRkhAvJQnAMujJ0jcuLk5re1xcHE5OTvooSYiXkgRgGeTu7o6FhQVRUVGabSkpKZw/f56mTZvqsTIhXi5yEKQMMjY2xt/fn5CQEGxtbXF2dmbBggU4OTnRsWNHfZcnxEtDArCMGjduHNnZ2UyfPp2MjAy8vLxYt25dvgMjQohnJzdGF0IoluwDFEIolgSgEEKxJACFEIolASiEUCwJQCGEYkkACiEUSwJQlDlyZpYoLRKAL6GAgADc3Ny0HvXq1cPX15egoCCSk5N18rqRkZG4ubkRHR0NQFhYGG5ubkV+fkxMDCNGjOD27dvPXUt0dDRubm5ERkY+91ji5SXfBHlJeXh4MHPmTM3Pjx494ty5cyxatIgLFy7w+eefo1KpdFpDv379aNOmTZH7//LLLxw5coSPPvpIh1UJ8V8SgC8pCwsLGjZsqLXNy8uL1NRUQkND+f333/O1lzQnJye5eo0o02QJrDD16tUD4M6dOwQEBPDBBx8wbtw4GjduzDvvvAM8vu7gJ598go+PD/Xq1aNHjx7s27dPa5zc3FzCw8Px9fXF09OT0aNH51taF7QE3rt3L71798bT0xNfX18WLFhAVlYWkZGRTJkyBYD27dszefJkzXN27NhBt27dNMv4sLAwsrOztcY9cOAAPXv2pEGDBvTq1YuLFy+WzAcmXmoyA1SY69evA1ClShUA9u/fT+fOnVm+fDk5OTnk5eUxZswYfvvtN8aNG0fNmjU5ePAgEyZMICsri9deew2ABQsWsHnzZkaOHEnDhg355ptvWLhwYaGvHRERwcyZM+nbty8TJkwgOjqaTz75hMTERD744ANGjRrFihUrWLZsmSY4V61axeLFi/H392fKlClcuHCBsLAw7t69y9y5cwH4/vvvGTduHN26deODDz7g4sWLTJw4UUefoHiZSAC+pPLy8rRmScnJyRw/fpwVK1bQsGFDzUxQrVbzn//8B3NzcwB+/vlnfvrpJxYvXkzXrl0BaNOmDenp6YSEhNC9e3fS0tLYsmULb731FmPHjtX0iY2N5aeffiqwntzcXMLCwujYsSPBwcGa7ZmZmezatQsLCwuqVq0KQJ06dahcuTIPHjxgxYoV9O/fn+nTpwPQunVrbGxsmD59OoMHD6ZWrVosX76cunXragK4bdu2AE8NZCFkCfySOnHiBHXr1tU8WrZsyXvvvUfdunVZtGiR5gBI5cqVNeEHcOzYMVQqFT4+PmRnZ2sefn5+3Lt3jytXrnDmzBkePXpE+/bttV6zS5cu/1rP9evXuX//Ph06dNDaPmjQIL766qsCL/N1+vRp0tPT8fPzy1cLPA7rjIwMzp07V6xahHhCZoAvqbp16xIUFASASqXCxMSEihUrYmFhodXP3t5e6+ekpCTy8vJo3LhxgePGxcWRkpICgK2trVabg4PDv9aTlJQEgJ2dXZHfw5PnPNk3WVAtycnJ5OXl5aulQoUKRX4doVwSgC+pcuXKUb9+/WI/z9LSEnNzczZv3lxge7Vq1Th79iwA8fHx1KhRQ9P2JLAKYmVlBUBCQoLW9qSkJM6dO1fgEeknzwkJCaF69er52u3t7bGxsUGtVnP//v184wrxNLIEFlqaNWtGWloaeXl51K9fX/O4cuUKy5cvJzs7m0aNGmFqaso333yj9dzDhw//67g1atSgfPnyHDp0SGv7nj17GD58OJmZmajV2v85enp6YmRkRGxsrFYtRkZGLFy4kOjoaExMTGjUqBEHDhzQ+gbJ999/XwKfhnjZyQxQaPHx8cHLy4vRo0czevRoatasydmzZwkLC6N169aapebo0aNZsmQJZmZmeHt788MPPxQagAYGBowdO5bZs2cza9YsOnbsyI0bN1iyZAlvvPEGtra2mhnfwYMHadu2LTVr1mTYsGEsXbqUhw8f0rx5c2JjY1m6dCkqlQp3d3cA3nvvPd5++20CAwPp378/N27cYMWKFbr/sMQLTwJQaFGr1axevZqlS5eyatUq4uPjcXR0ZNCgQYwZM0bTb8SIEZibm7Np0yY2bdpEo0aNmDRpErNmzfrXsQcOHIi5uTnr1q1j586dODo6MmTIEM0+vubNm9OyZUsWLlzIsWPHWL16NePHj8fBwYHPPvuMtWvXYm1tTYsWLXjvvfewtLQEoGnTpqxZs4ZFixYRGBhI5cqVmTt3LiNHjtTpZyVefHJPECGEYsk+QCGEYkkACiEUSwJQCKFYEoBCCMWSABRCKJYEoBBCsSQAhRCKJQEohFAsCUAhhGJJAAohFEsCUAihWBKAQgjF+j/siJ1KlEkOdwAAAABJRU5ErkJggg==",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled Dataset (No PCA) ccp_alpha: 0.005 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.65 0.77 2529\n",
+ " 1.0 0.29 0.75 0.41 471\n",
+ "\n",
+ " accuracy 0.67 3000\n",
+ " macro avg 0.61 0.70 0.59 3000\n",
+ "weighted avg 0.83 0.67 0.71 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled Dataset ccp_alpha: 0.05...\u001b[0m\n",
+ "Oversampled Dataset ccp_alpha: 0.05 Accuracy: 0.635\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled Dataset ccp_alpha: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.61 0.74 2529\n",
+ " 1.0 0.27 0.76 0.39 471\n",
+ "\n",
+ " accuracy 0.64 3000\n",
+ " macro avg 0.60 0.69 0.57 3000\n",
+ "weighted avg 0.83 0.64 0.68 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled Dataset ccp_alpha: 0.01...\u001b[0m\n",
+ "Oversampled Dataset ccp_alpha: 0.01 Accuracy: 0.7623333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled Dataset ccp_alpha: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.92 0.78 0.85 2529\n",
+ " 1.0 0.36 0.64 0.46 471\n",
+ "\n",
+ " accuracy 0.76 3000\n",
+ " macro avg 0.64 0.71 0.65 3000\n",
+ "weighted avg 0.83 0.76 0.79 3000\n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 900x500 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "predict(DT_models, DT_name, x_test_list, ytest, \"testing\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Support Vector Machine (SVM)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 117,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SVM_models = []\n",
+ "SVM_name = []\n",
+ "x_val_list = []\n",
+ "x_test_list = []"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 124,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "gamma=0.05\n",
+ "txt = \"gamma: 0.05\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 125,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<style>#sk-container-id-20 {\n",
+ " /* Definition of color scheme common for light and dark mode */\n",
+ " --sklearn-color-text: black;\n",
+ " --sklearn-color-line: gray;\n",
+ " /* Definition of color scheme for unfitted estimators */\n",
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
+ " /* Definition of color scheme for fitted estimators */\n",
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
+ "\n",
+ " /* Specific color for light theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-icon: #696969;\n",
+ "\n",
+ " @media (prefers-color-scheme: dark) {\n",
+ " /* Redefinition of color scheme for dark theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-icon: #878787;\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 pre {\n",
+ " padding: 0;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 input.sk-hidden--visually {\n",
+ " border: 0;\n",
+ " clip: rect(1px 1px 1px 1px);\n",
+ " clip: rect(1px, 1px, 1px, 1px);\n",
+ " height: 1px;\n",
+ " margin: -1px;\n",
+ " overflow: hidden;\n",
+ " padding: 0;\n",
+ " position: absolute;\n",
+ " width: 1px;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-dashed-wrapped {\n",
+ " border: 1px dashed var(--sklearn-color-line);\n",
+ " margin: 0 0.4em 0.5em 0.4em;\n",
+ " box-sizing: border-box;\n",
+ " padding-bottom: 0.4em;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-container {\n",
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+ " so we also need the `!important` here to be able to override the\n",
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+ " display: inline-block !important;\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-text-repr-fallback {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-parallel-item,\n",
+ "div.sk-serial,\n",
+ "div.sk-item {\n",
+ " /* draw centered vertical line to link estimators */\n",
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+ " background-size: 2px 100%;\n",
+ " background-repeat: no-repeat;\n",
+ " background-position: center center;\n",
+ "}\n",
+ "\n",
+ "/* Parallel-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-20 div.sk-parallel-item::after {\n",
+ " content: \"\";\n",
+ " width: 100%;\n",
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+ " flex-grow: 1;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-parallel {\n",
+ " display: flex;\n",
+ " align-items: stretch;\n",
+ " justify-content: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-parallel-item {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-parallel-item:first-child::after {\n",
+ " align-self: flex-end;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-parallel-item:last-child::after {\n",
+ " align-self: flex-start;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-parallel-item:only-child::after {\n",
+ " width: 0;\n",
+ "}\n",
+ "\n",
+ "/* Serial-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-20 div.sk-serial {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ " align-items: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " padding-right: 1em;\n",
+ " padding-left: 1em;\n",
+ "}\n",
+ "\n",
+ "\n",
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+ "clickable and can be expanded/collapsed.\n",
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+ "*/\n",
+ "\n",
+ "/* Pipeline and ColumnTransformer style (default) */\n",
+ "\n",
+ "#sk-container-id-20 div.sk-toggleable {\n",
+ " /* Default theme specific background. It is overwritten whether we have a\n",
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable label */\n",
+ "#sk-container-id-20 label.sk-toggleable__label {\n",
+ " cursor: pointer;\n",
+ " display: block;\n",
+ " width: 100%;\n",
+ " margin-bottom: 0;\n",
+ " padding: 0.5em;\n",
+ " box-sizing: border-box;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 label.sk-toggleable__label-arrow:before {\n",
+ " /* Arrow on the left of the label */\n",
+ " content: \"â–¸\";\n",
+ " float: left;\n",
+ " margin-right: 0.25em;\n",
+ " color: var(--sklearn-color-icon);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 label.sk-toggleable__label-arrow:hover:before {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable content - dropdown */\n",
+ "\n",
+ "#sk-container-id-20 div.sk-toggleable__content {\n",
+ " max-height: 0;\n",
+ " max-width: 0;\n",
+ " overflow: hidden;\n",
+ " text-align: left;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-toggleable__content.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-toggleable__content pre {\n",
+ " margin: 0.2em;\n",
+ " border-radius: 0.25em;\n",
+ " color: var(--sklearn-color-text);\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-toggleable__content.fitted pre {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+ " /* Expand drop-down */\n",
+ " max-height: 200px;\n",
+ " max-width: 100%;\n",
+ " overflow: auto;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+ " content: \"â–¾\";\n",
+ "}\n",
+ "\n",
+ "/* Pipeline/ColumnTransformer-specific style */\n",
+ "\n",
+ "#sk-container-id-20 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific style */\n",
+ "\n",
+ "/* Colorize estimator box */\n",
+ "#sk-container-id-20 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-label label.sk-toggleable__label,\n",
+ "#sk-container-id-20 div.sk-label label {\n",
+ " /* The background is the default theme color */\n",
+ " color: var(--sklearn-color-text-on-default-background);\n",
+ "}\n",
+ "\n",
+ "/* On hover, darken the color of the background */\n",
+ "#sk-container-id-20 div.sk-label:hover label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Label box, darken color on hover, fitted */\n",
+ "#sk-container-id-20 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator label */\n",
+ "\n",
+ "#sk-container-id-20 div.sk-label label {\n",
+ " font-family: monospace;\n",
+ " font-weight: bold;\n",
+ " display: inline-block;\n",
+ " line-height: 1.2em;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-label-container {\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific */\n",
+ "#sk-container-id-20 div.sk-estimator {\n",
+ " font-family: monospace;\n",
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
+ " border-radius: 0.25em;\n",
+ " box-sizing: border-box;\n",
+ " margin-bottom: 0.5em;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-estimator.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "/* on hover */\n",
+ "#sk-container-id-20 div.sk-estimator:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 div.sk-estimator.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+ "\n",
+ "/* Common style for \"i\" and \"?\" */\n",
+ "\n",
+ ".sk-estimator-doc-link,\n",
+ "a:link.sk-estimator-doc-link,\n",
+ "a:visited.sk-estimator-doc-link {\n",
+ " float: right;\n",
+ " font-size: smaller;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1em;\n",
+ " height: 1em;\n",
+ " width: 1em;\n",
+ " text-decoration: none !important;\n",
+ " margin-left: 1ex;\n",
+ " /* unfitted */\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted,\n",
+ "a:link.sk-estimator-doc-link.fitted,\n",
+ "a:visited.sk-estimator-doc-link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "/* Span, style for the box shown on hovering the info icon */\n",
+ ".sk-estimator-doc-link span {\n",
+ " display: none;\n",
+ " z-index: 9999;\n",
+ " position: relative;\n",
+ " font-weight: normal;\n",
+ " right: .2ex;\n",
+ " padding: .5ex;\n",
+ " margin: .5ex;\n",
+ " width: min-content;\n",
+ " min-width: 20ex;\n",
+ " max-width: 50ex;\n",
+ " color: var(--sklearn-color-text);\n",
+ " box-shadow: 2pt 2pt 4pt #999;\n",
+ " /* unfitted */\n",
+ " background: var(--sklearn-color-unfitted-level-0);\n",
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted span {\n",
+ " /* fitted */\n",
+ " background: var(--sklearn-color-fitted-level-0);\n",
+ " border: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link:hover span {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+ "\n",
+ "#sk-container-id-20 a.estimator_doc_link {\n",
+ " float: right;\n",
+ " font-size: 1rem;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1rem;\n",
+ " height: 1rem;\n",
+ " width: 1rem;\n",
+ " text-decoration: none;\n",
+ " /* unfitted */\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 a.estimator_doc_link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "#sk-container-id-20 a.estimator_doc_link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-20 a.estimator_doc_link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "</style><div id=\"sk-container-id-20\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVC(gamma=0.05, probability=True, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-20\" type=\"checkbox\" checked><label for=\"sk-estimator-id-20\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> SVC<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.svm.SVC.html\">?<span>Documentation for SVC</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>SVC(gamma=0.05, probability=True, random_state=42)</pre></div> </div></div></div></div>"
+ ],
+ "text/plain": [
+ "SVC(gamma=0.05, probability=True, random_state=42)"
+ ]
+ },
+ "execution_count": 125,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#SVM model - oversampled dataset\n",
+ "\n",
+ "# Initialize the SVM classifier\n",
+ "svm_oversampled = svm.SVC(probability=True, random_state=42, gamma=gamma)\n",
+ "SVM_models.append(svm_oversampled)\n",
+ "SVM_name.append(f\"Oversampled dataset(No PCA), {txt}\")\n",
+ "x_val_list.append(xval)\n",
+ "x_test_list.append(xtest)\n",
+ "\n",
+ "# Fit the classifier to the training data\n",
+ "svm_oversampled.fit(xtrain_oversampled, ytrain_oversampled)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 85,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<style>#sk-container-id-14 {\n",
+ " /* Definition of color scheme common for light and dark mode */\n",
+ " --sklearn-color-text: black;\n",
+ " --sklearn-color-line: gray;\n",
+ " /* Definition of color scheme for unfitted estimators */\n",
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
+ " /* Definition of color scheme for fitted estimators */\n",
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
+ "\n",
+ " /* Specific color for light theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-icon: #696969;\n",
+ "\n",
+ " @media (prefers-color-scheme: dark) {\n",
+ " /* Redefinition of color scheme for dark theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-icon: #878787;\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 pre {\n",
+ " padding: 0;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 input.sk-hidden--visually {\n",
+ " border: 0;\n",
+ " clip: rect(1px 1px 1px 1px);\n",
+ " clip: rect(1px, 1px, 1px, 1px);\n",
+ " height: 1px;\n",
+ " margin: -1px;\n",
+ " overflow: hidden;\n",
+ " padding: 0;\n",
+ " position: absolute;\n",
+ " width: 1px;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-dashed-wrapped {\n",
+ " border: 1px dashed var(--sklearn-color-line);\n",
+ " margin: 0 0.4em 0.5em 0.4em;\n",
+ " box-sizing: border-box;\n",
+ " padding-bottom: 0.4em;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-container {\n",
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+ " so we also need the `!important` here to be able to override the\n",
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+ " display: inline-block !important;\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-text-repr-fallback {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-parallel-item,\n",
+ "div.sk-serial,\n",
+ "div.sk-item {\n",
+ " /* draw centered vertical line to link estimators */\n",
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+ " background-size: 2px 100%;\n",
+ " background-repeat: no-repeat;\n",
+ " background-position: center center;\n",
+ "}\n",
+ "\n",
+ "/* Parallel-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-14 div.sk-parallel-item::after {\n",
+ " content: \"\";\n",
+ " width: 100%;\n",
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+ " flex-grow: 1;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-parallel {\n",
+ " display: flex;\n",
+ " align-items: stretch;\n",
+ " justify-content: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-parallel-item {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-parallel-item:first-child::after {\n",
+ " align-self: flex-end;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-parallel-item:last-child::after {\n",
+ " align-self: flex-start;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-parallel-item:only-child::after {\n",
+ " width: 0;\n",
+ "}\n",
+ "\n",
+ "/* Serial-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-14 div.sk-serial {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ " align-items: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " padding-right: 1em;\n",
+ " padding-left: 1em;\n",
+ "}\n",
+ "\n",
+ "\n",
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+ "clickable and can be expanded/collapsed.\n",
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+ "*/\n",
+ "\n",
+ "/* Pipeline and ColumnTransformer style (default) */\n",
+ "\n",
+ "#sk-container-id-14 div.sk-toggleable {\n",
+ " /* Default theme specific background. It is overwritten whether we have a\n",
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable label */\n",
+ "#sk-container-id-14 label.sk-toggleable__label {\n",
+ " cursor: pointer;\n",
+ " display: block;\n",
+ " width: 100%;\n",
+ " margin-bottom: 0;\n",
+ " padding: 0.5em;\n",
+ " box-sizing: border-box;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 label.sk-toggleable__label-arrow:before {\n",
+ " /* Arrow on the left of the label */\n",
+ " content: \"â–¸\";\n",
+ " float: left;\n",
+ " margin-right: 0.25em;\n",
+ " color: var(--sklearn-color-icon);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 label.sk-toggleable__label-arrow:hover:before {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable content - dropdown */\n",
+ "\n",
+ "#sk-container-id-14 div.sk-toggleable__content {\n",
+ " max-height: 0;\n",
+ " max-width: 0;\n",
+ " overflow: hidden;\n",
+ " text-align: left;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-toggleable__content.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-toggleable__content pre {\n",
+ " margin: 0.2em;\n",
+ " border-radius: 0.25em;\n",
+ " color: var(--sklearn-color-text);\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-toggleable__content.fitted pre {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+ " /* Expand drop-down */\n",
+ " max-height: 200px;\n",
+ " max-width: 100%;\n",
+ " overflow: auto;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+ " content: \"â–¾\";\n",
+ "}\n",
+ "\n",
+ "/* Pipeline/ColumnTransformer-specific style */\n",
+ "\n",
+ "#sk-container-id-14 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific style */\n",
+ "\n",
+ "/* Colorize estimator box */\n",
+ "#sk-container-id-14 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-label label.sk-toggleable__label,\n",
+ "#sk-container-id-14 div.sk-label label {\n",
+ " /* The background is the default theme color */\n",
+ " color: var(--sklearn-color-text-on-default-background);\n",
+ "}\n",
+ "\n",
+ "/* On hover, darken the color of the background */\n",
+ "#sk-container-id-14 div.sk-label:hover label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Label box, darken color on hover, fitted */\n",
+ "#sk-container-id-14 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator label */\n",
+ "\n",
+ "#sk-container-id-14 div.sk-label label {\n",
+ " font-family: monospace;\n",
+ " font-weight: bold;\n",
+ " display: inline-block;\n",
+ " line-height: 1.2em;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-label-container {\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific */\n",
+ "#sk-container-id-14 div.sk-estimator {\n",
+ " font-family: monospace;\n",
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
+ " border-radius: 0.25em;\n",
+ " box-sizing: border-box;\n",
+ " margin-bottom: 0.5em;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-estimator.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "/* on hover */\n",
+ "#sk-container-id-14 div.sk-estimator:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 div.sk-estimator.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+ "\n",
+ "/* Common style for \"i\" and \"?\" */\n",
+ "\n",
+ ".sk-estimator-doc-link,\n",
+ "a:link.sk-estimator-doc-link,\n",
+ "a:visited.sk-estimator-doc-link {\n",
+ " float: right;\n",
+ " font-size: smaller;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1em;\n",
+ " height: 1em;\n",
+ " width: 1em;\n",
+ " text-decoration: none !important;\n",
+ " margin-left: 1ex;\n",
+ " /* unfitted */\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted,\n",
+ "a:link.sk-estimator-doc-link.fitted,\n",
+ "a:visited.sk-estimator-doc-link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "/* Span, style for the box shown on hovering the info icon */\n",
+ ".sk-estimator-doc-link span {\n",
+ " display: none;\n",
+ " z-index: 9999;\n",
+ " position: relative;\n",
+ " font-weight: normal;\n",
+ " right: .2ex;\n",
+ " padding: .5ex;\n",
+ " margin: .5ex;\n",
+ " width: min-content;\n",
+ " min-width: 20ex;\n",
+ " max-width: 50ex;\n",
+ " color: var(--sklearn-color-text);\n",
+ " box-shadow: 2pt 2pt 4pt #999;\n",
+ " /* unfitted */\n",
+ " background: var(--sklearn-color-unfitted-level-0);\n",
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted span {\n",
+ " /* fitted */\n",
+ " background: var(--sklearn-color-fitted-level-0);\n",
+ " border: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link:hover span {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+ "\n",
+ "#sk-container-id-14 a.estimator_doc_link {\n",
+ " float: right;\n",
+ " font-size: 1rem;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1rem;\n",
+ " height: 1rem;\n",
+ " width: 1rem;\n",
+ " text-decoration: none;\n",
+ " /* unfitted */\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 a.estimator_doc_link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "#sk-container-id-14 a.estimator_doc_link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-14 a.estimator_doc_link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "</style><div id=\"sk-container-id-14\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVC(gamma=0.1, probability=True, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-14\" type=\"checkbox\" checked><label for=\"sk-estimator-id-14\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> SVC<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.svm.SVC.html\">?<span>Documentation for SVC</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>SVC(gamma=0.1, probability=True, random_state=42)</pre></div> </div></div></div></div>"
+ ],
+ "text/plain": [
+ "SVC(gamma=0.1, probability=True, random_state=42)"
+ ]
+ },
+ "execution_count": 85,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#SVM model - undersampled dataset\n",
+ "\n",
+ "# Initialize the SVM classifier\n",
+ "svm_undersampled = svm.SVC(probability=True, random_state=42, gamma=gamma)\n",
+ "\n",
+ "SVM_models.append(svm_undersampled)\n",
+ "SVM_name.append(f\"Undersampled dataset(No PCA), {txt}\")\n",
+ "x_val_list.append(xval)\n",
+ "x_test_list.append(xtest)\n",
+ "\n",
+ "# Fit the classifier to the training data\n",
+ "svm_undersampled.fit(xtrain_undersampled, ytrain_undersampled)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 86,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<style>#sk-container-id-15 {\n",
+ " /* Definition of color scheme common for light and dark mode */\n",
+ " --sklearn-color-text: black;\n",
+ " --sklearn-color-line: gray;\n",
+ " /* Definition of color scheme for unfitted estimators */\n",
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
+ " /* Definition of color scheme for fitted estimators */\n",
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
+ "\n",
+ " /* Specific color for light theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-icon: #696969;\n",
+ "\n",
+ " @media (prefers-color-scheme: dark) {\n",
+ " /* Redefinition of color scheme for dark theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-icon: #878787;\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 pre {\n",
+ " padding: 0;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 input.sk-hidden--visually {\n",
+ " border: 0;\n",
+ " clip: rect(1px 1px 1px 1px);\n",
+ " clip: rect(1px, 1px, 1px, 1px);\n",
+ " height: 1px;\n",
+ " margin: -1px;\n",
+ " overflow: hidden;\n",
+ " padding: 0;\n",
+ " position: absolute;\n",
+ " width: 1px;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-dashed-wrapped {\n",
+ " border: 1px dashed var(--sklearn-color-line);\n",
+ " margin: 0 0.4em 0.5em 0.4em;\n",
+ " box-sizing: border-box;\n",
+ " padding-bottom: 0.4em;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-container {\n",
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+ " so we also need the `!important` here to be able to override the\n",
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+ " display: inline-block !important;\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-text-repr-fallback {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-parallel-item,\n",
+ "div.sk-serial,\n",
+ "div.sk-item {\n",
+ " /* draw centered vertical line to link estimators */\n",
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+ " background-size: 2px 100%;\n",
+ " background-repeat: no-repeat;\n",
+ " background-position: center center;\n",
+ "}\n",
+ "\n",
+ "/* Parallel-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-15 div.sk-parallel-item::after {\n",
+ " content: \"\";\n",
+ " width: 100%;\n",
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+ " flex-grow: 1;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-parallel {\n",
+ " display: flex;\n",
+ " align-items: stretch;\n",
+ " justify-content: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-parallel-item {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-parallel-item:first-child::after {\n",
+ " align-self: flex-end;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-parallel-item:last-child::after {\n",
+ " align-self: flex-start;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-parallel-item:only-child::after {\n",
+ " width: 0;\n",
+ "}\n",
+ "\n",
+ "/* Serial-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-15 div.sk-serial {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ " align-items: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " padding-right: 1em;\n",
+ " padding-left: 1em;\n",
+ "}\n",
+ "\n",
+ "\n",
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+ "clickable and can be expanded/collapsed.\n",
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+ "*/\n",
+ "\n",
+ "/* Pipeline and ColumnTransformer style (default) */\n",
+ "\n",
+ "#sk-container-id-15 div.sk-toggleable {\n",
+ " /* Default theme specific background. It is overwritten whether we have a\n",
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable label */\n",
+ "#sk-container-id-15 label.sk-toggleable__label {\n",
+ " cursor: pointer;\n",
+ " display: block;\n",
+ " width: 100%;\n",
+ " margin-bottom: 0;\n",
+ " padding: 0.5em;\n",
+ " box-sizing: border-box;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 label.sk-toggleable__label-arrow:before {\n",
+ " /* Arrow on the left of the label */\n",
+ " content: \"â–¸\";\n",
+ " float: left;\n",
+ " margin-right: 0.25em;\n",
+ " color: var(--sklearn-color-icon);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 label.sk-toggleable__label-arrow:hover:before {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable content - dropdown */\n",
+ "\n",
+ "#sk-container-id-15 div.sk-toggleable__content {\n",
+ " max-height: 0;\n",
+ " max-width: 0;\n",
+ " overflow: hidden;\n",
+ " text-align: left;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-toggleable__content.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-toggleable__content pre {\n",
+ " margin: 0.2em;\n",
+ " border-radius: 0.25em;\n",
+ " color: var(--sklearn-color-text);\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-toggleable__content.fitted pre {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+ " /* Expand drop-down */\n",
+ " max-height: 200px;\n",
+ " max-width: 100%;\n",
+ " overflow: auto;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+ " content: \"â–¾\";\n",
+ "}\n",
+ "\n",
+ "/* Pipeline/ColumnTransformer-specific style */\n",
+ "\n",
+ "#sk-container-id-15 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific style */\n",
+ "\n",
+ "/* Colorize estimator box */\n",
+ "#sk-container-id-15 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-label label.sk-toggleable__label,\n",
+ "#sk-container-id-15 div.sk-label label {\n",
+ " /* The background is the default theme color */\n",
+ " color: var(--sklearn-color-text-on-default-background);\n",
+ "}\n",
+ "\n",
+ "/* On hover, darken the color of the background */\n",
+ "#sk-container-id-15 div.sk-label:hover label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Label box, darken color on hover, fitted */\n",
+ "#sk-container-id-15 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator label */\n",
+ "\n",
+ "#sk-container-id-15 div.sk-label label {\n",
+ " font-family: monospace;\n",
+ " font-weight: bold;\n",
+ " display: inline-block;\n",
+ " line-height: 1.2em;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-label-container {\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific */\n",
+ "#sk-container-id-15 div.sk-estimator {\n",
+ " font-family: monospace;\n",
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
+ " border-radius: 0.25em;\n",
+ " box-sizing: border-box;\n",
+ " margin-bottom: 0.5em;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-estimator.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "/* on hover */\n",
+ "#sk-container-id-15 div.sk-estimator:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 div.sk-estimator.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+ "\n",
+ "/* Common style for \"i\" and \"?\" */\n",
+ "\n",
+ ".sk-estimator-doc-link,\n",
+ "a:link.sk-estimator-doc-link,\n",
+ "a:visited.sk-estimator-doc-link {\n",
+ " float: right;\n",
+ " font-size: smaller;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1em;\n",
+ " height: 1em;\n",
+ " width: 1em;\n",
+ " text-decoration: none !important;\n",
+ " margin-left: 1ex;\n",
+ " /* unfitted */\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted,\n",
+ "a:link.sk-estimator-doc-link.fitted,\n",
+ "a:visited.sk-estimator-doc-link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "/* Span, style for the box shown on hovering the info icon */\n",
+ ".sk-estimator-doc-link span {\n",
+ " display: none;\n",
+ " z-index: 9999;\n",
+ " position: relative;\n",
+ " font-weight: normal;\n",
+ " right: .2ex;\n",
+ " padding: .5ex;\n",
+ " margin: .5ex;\n",
+ " width: min-content;\n",
+ " min-width: 20ex;\n",
+ " max-width: 50ex;\n",
+ " color: var(--sklearn-color-text);\n",
+ " box-shadow: 2pt 2pt 4pt #999;\n",
+ " /* unfitted */\n",
+ " background: var(--sklearn-color-unfitted-level-0);\n",
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted span {\n",
+ " /* fitted */\n",
+ " background: var(--sklearn-color-fitted-level-0);\n",
+ " border: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link:hover span {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+ "\n",
+ "#sk-container-id-15 a.estimator_doc_link {\n",
+ " float: right;\n",
+ " font-size: 1rem;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1rem;\n",
+ " height: 1rem;\n",
+ " width: 1rem;\n",
+ " text-decoration: none;\n",
+ " /* unfitted */\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 a.estimator_doc_link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "#sk-container-id-15 a.estimator_doc_link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-15 a.estimator_doc_link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "</style><div id=\"sk-container-id-15\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVC(gamma=0.1, probability=True, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-15\" type=\"checkbox\" checked><label for=\"sk-estimator-id-15\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> SVC<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.svm.SVC.html\">?<span>Documentation for SVC</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>SVC(gamma=0.1, probability=True, random_state=42)</pre></div> </div></div></div></div>"
+ ],
+ "text/plain": [
+ "SVC(gamma=0.1, probability=True, random_state=42)"
+ ]
+ },
+ "execution_count": 86,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#SVM model - oversampled dataset\n",
+ "\n",
+ "# Initialize the SVM classifier\n",
+ "svm_oversampled_pca = svm.SVC(probability=True, random_state=42, gamma=gamma)\n",
+ "\n",
+ "SVM_models.append(svm_oversampled_pca)\n",
+ "SVM_name.append(f\"Oversampled dataset(PCA), {txt}\")\n",
+ "x_val_list.append(xval_pca_oversampled)\n",
+ "x_test_list.append(xtest_pca_oversampled)\n",
+ "\n",
+ "# Fit the classifier to the training data\n",
+ "svm_oversampled_pca.fit(xtrain_pca_oversampled, ytrain_oversampled)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 87,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<style>#sk-container-id-16 {\n",
+ " /* Definition of color scheme common for light and dark mode */\n",
+ " --sklearn-color-text: black;\n",
+ " --sklearn-color-line: gray;\n",
+ " /* Definition of color scheme for unfitted estimators */\n",
+ " --sklearn-color-unfitted-level-0: #fff5e6;\n",
+ " --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+ " --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+ " --sklearn-color-unfitted-level-3: chocolate;\n",
+ " /* Definition of color scheme for fitted estimators */\n",
+ " --sklearn-color-fitted-level-0: #f0f8ff;\n",
+ " --sklearn-color-fitted-level-1: #d4ebff;\n",
+ " --sklearn-color-fitted-level-2: #b3dbfd;\n",
+ " --sklearn-color-fitted-level-3: cornflowerblue;\n",
+ "\n",
+ " /* Specific color for light theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+ " --sklearn-color-icon: #696969;\n",
+ "\n",
+ " @media (prefers-color-scheme: dark) {\n",
+ " /* Redefinition of color scheme for dark theme */\n",
+ " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+ " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+ " --sklearn-color-icon: #878787;\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 pre {\n",
+ " padding: 0;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 input.sk-hidden--visually {\n",
+ " border: 0;\n",
+ " clip: rect(1px 1px 1px 1px);\n",
+ " clip: rect(1px, 1px, 1px, 1px);\n",
+ " height: 1px;\n",
+ " margin: -1px;\n",
+ " overflow: hidden;\n",
+ " padding: 0;\n",
+ " position: absolute;\n",
+ " width: 1px;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-dashed-wrapped {\n",
+ " border: 1px dashed var(--sklearn-color-line);\n",
+ " margin: 0 0.4em 0.5em 0.4em;\n",
+ " box-sizing: border-box;\n",
+ " padding-bottom: 0.4em;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-container {\n",
+ " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+ " but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+ " so we also need the `!important` here to be able to override the\n",
+ " default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+ " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+ " display: inline-block !important;\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-text-repr-fallback {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-parallel-item,\n",
+ "div.sk-serial,\n",
+ "div.sk-item {\n",
+ " /* draw centered vertical line to link estimators */\n",
+ " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+ " background-size: 2px 100%;\n",
+ " background-repeat: no-repeat;\n",
+ " background-position: center center;\n",
+ "}\n",
+ "\n",
+ "/* Parallel-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-16 div.sk-parallel-item::after {\n",
+ " content: \"\";\n",
+ " width: 100%;\n",
+ " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+ " flex-grow: 1;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-parallel {\n",
+ " display: flex;\n",
+ " align-items: stretch;\n",
+ " justify-content: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " position: relative;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-parallel-item {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-parallel-item:first-child::after {\n",
+ " align-self: flex-end;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-parallel-item:last-child::after {\n",
+ " align-self: flex-start;\n",
+ " width: 50%;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-parallel-item:only-child::after {\n",
+ " width: 0;\n",
+ "}\n",
+ "\n",
+ "/* Serial-specific style estimator block */\n",
+ "\n",
+ "#sk-container-id-16 div.sk-serial {\n",
+ " display: flex;\n",
+ " flex-direction: column;\n",
+ " align-items: center;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " padding-right: 1em;\n",
+ " padding-left: 1em;\n",
+ "}\n",
+ "\n",
+ "\n",
+ "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+ "clickable and can be expanded/collapsed.\n",
+ "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+ "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+ "*/\n",
+ "\n",
+ "/* Pipeline and ColumnTransformer style (default) */\n",
+ "\n",
+ "#sk-container-id-16 div.sk-toggleable {\n",
+ " /* Default theme specific background. It is overwritten whether we have a\n",
+ " specific estimator or a Pipeline/ColumnTransformer */\n",
+ " background-color: var(--sklearn-color-background);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable label */\n",
+ "#sk-container-id-16 label.sk-toggleable__label {\n",
+ " cursor: pointer;\n",
+ " display: block;\n",
+ " width: 100%;\n",
+ " margin-bottom: 0;\n",
+ " padding: 0.5em;\n",
+ " box-sizing: border-box;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 label.sk-toggleable__label-arrow:before {\n",
+ " /* Arrow on the left of the label */\n",
+ " content: \"â–¸\";\n",
+ " float: left;\n",
+ " margin-right: 0.25em;\n",
+ " color: var(--sklearn-color-icon);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 label.sk-toggleable__label-arrow:hover:before {\n",
+ " color: var(--sklearn-color-text);\n",
+ "}\n",
+ "\n",
+ "/* Toggleable content - dropdown */\n",
+ "\n",
+ "#sk-container-id-16 div.sk-toggleable__content {\n",
+ " max-height: 0;\n",
+ " max-width: 0;\n",
+ " overflow: hidden;\n",
+ " text-align: left;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-toggleable__content.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-toggleable__content pre {\n",
+ " margin: 0.2em;\n",
+ " border-radius: 0.25em;\n",
+ " color: var(--sklearn-color-text);\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-toggleable__content.fitted pre {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+ " /* Expand drop-down */\n",
+ " max-height: 200px;\n",
+ " max-width: 100%;\n",
+ " overflow: auto;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+ " content: \"â–¾\";\n",
+ "}\n",
+ "\n",
+ "/* Pipeline/ColumnTransformer-specific style */\n",
+ "\n",
+ "#sk-container-id-16 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific style */\n",
+ "\n",
+ "/* Colorize estimator box */\n",
+ "#sk-container-id-16 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-label label.sk-toggleable__label,\n",
+ "#sk-container-id-16 div.sk-label label {\n",
+ " /* The background is the default theme color */\n",
+ " color: var(--sklearn-color-text-on-default-background);\n",
+ "}\n",
+ "\n",
+ "/* On hover, darken the color of the background */\n",
+ "#sk-container-id-16 div.sk-label:hover label.sk-toggleable__label {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Label box, darken color on hover, fitted */\n",
+ "#sk-container-id-16 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+ " color: var(--sklearn-color-text);\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Estimator label */\n",
+ "\n",
+ "#sk-container-id-16 div.sk-label label {\n",
+ " font-family: monospace;\n",
+ " font-weight: bold;\n",
+ " display: inline-block;\n",
+ " line-height: 1.2em;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-label-container {\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ "/* Estimator-specific */\n",
+ "#sk-container-id-16 div.sk-estimator {\n",
+ " font-family: monospace;\n",
+ " border: 1px dotted var(--sklearn-color-border-box);\n",
+ " border-radius: 0.25em;\n",
+ " box-sizing: border-box;\n",
+ " margin-bottom: 0.5em;\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-0);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-estimator.fitted {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-0);\n",
+ "}\n",
+ "\n",
+ "/* on hover */\n",
+ "#sk-container-id-16 div.sk-estimator:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-2);\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 div.sk-estimator.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-2);\n",
+ "}\n",
+ "\n",
+ "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+ "\n",
+ "/* Common style for \"i\" and \"?\" */\n",
+ "\n",
+ ".sk-estimator-doc-link,\n",
+ "a:link.sk-estimator-doc-link,\n",
+ "a:visited.sk-estimator-doc-link {\n",
+ " float: right;\n",
+ " font-size: smaller;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1em;\n",
+ " height: 1em;\n",
+ " width: 1em;\n",
+ " text-decoration: none !important;\n",
+ " margin-left: 1ex;\n",
+ " /* unfitted */\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted,\n",
+ "a:link.sk-estimator-doc-link.fitted,\n",
+ "a:visited.sk-estimator-doc-link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+ ".sk-estimator-doc-link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover,\n",
+ "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+ ".sk-estimator-doc-link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "/* Span, style for the box shown on hovering the info icon */\n",
+ ".sk-estimator-doc-link span {\n",
+ " display: none;\n",
+ " z-index: 9999;\n",
+ " position: relative;\n",
+ " font-weight: normal;\n",
+ " right: .2ex;\n",
+ " padding: .5ex;\n",
+ " margin: .5ex;\n",
+ " width: min-content;\n",
+ " min-width: 20ex;\n",
+ " max-width: 50ex;\n",
+ " color: var(--sklearn-color-text);\n",
+ " box-shadow: 2pt 2pt 4pt #999;\n",
+ " /* unfitted */\n",
+ " background: var(--sklearn-color-unfitted-level-0);\n",
+ " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link.fitted span {\n",
+ " /* fitted */\n",
+ " background: var(--sklearn-color-fitted-level-0);\n",
+ " border: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "\n",
+ ".sk-estimator-doc-link:hover span {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+ "\n",
+ "#sk-container-id-16 a.estimator_doc_link {\n",
+ " float: right;\n",
+ " font-size: 1rem;\n",
+ " line-height: 1em;\n",
+ " font-family: monospace;\n",
+ " background-color: var(--sklearn-color-background);\n",
+ " border-radius: 1rem;\n",
+ " height: 1rem;\n",
+ " width: 1rem;\n",
+ " text-decoration: none;\n",
+ " /* unfitted */\n",
+ " color: var(--sklearn-color-unfitted-level-1);\n",
+ " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 a.estimator_doc_link.fitted {\n",
+ " /* fitted */\n",
+ " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+ " color: var(--sklearn-color-fitted-level-1);\n",
+ "}\n",
+ "\n",
+ "/* On hover */\n",
+ "#sk-container-id-16 a.estimator_doc_link:hover {\n",
+ " /* unfitted */\n",
+ " background-color: var(--sklearn-color-unfitted-level-3);\n",
+ " color: var(--sklearn-color-background);\n",
+ " text-decoration: none;\n",
+ "}\n",
+ "\n",
+ "#sk-container-id-16 a.estimator_doc_link.fitted:hover {\n",
+ " /* fitted */\n",
+ " background-color: var(--sklearn-color-fitted-level-3);\n",
+ "}\n",
+ "</style><div id=\"sk-container-id-16\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVC(gamma=0.1, probability=True, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-16\" type=\"checkbox\" checked><label for=\"sk-estimator-id-16\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> SVC<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.svm.SVC.html\">?<span>Documentation for SVC</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>SVC(gamma=0.1, probability=True, random_state=42)</pre></div> </div></div></div></div>"
+ ],
+ "text/plain": [
+ "SVC(gamma=0.1, probability=True, random_state=42)"
+ ]
+ },
+ "execution_count": 87,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#SVM model - undersampled dataset\n",
+ "\n",
+ "# Initialize the SVM classifier\n",
+ "svm_undersampled_pca = svm.SVC(probability=True, random_state=42, gamma=gamma)\n",
+ "\n",
+ "SVM_models.append(clf_undersampled_pca)\n",
+ "SVM_name.append(f\"Undersampled dataset(PCA), {txt}\")\n",
+ "x_val_list.append(xval_pca_undersampled)\n",
+ "x_test_list.append(xtest_pca_undersampled)\n",
+ "\n",
+ "# Fit the classifier to the training data\n",
+ "svm_undersampled_pca.fit(xtrain_pca_undersampled, ytrain_undersampled)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 88,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\u001b[1mEvaluating SVM validation data\u001b[0m \n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), gamma: 0.1...\u001b[0m\n",
+ "Oversampled dataset(No PCA), gamma: 0.1 Accuracy: 0.7397222222222222\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), gamma: 0.1 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.92 0.76 0.83 3043\n",
+ " 1.0 0.33 0.66 0.44 557\n",
+ "\n",
+ " accuracy 0.74 3600\n",
+ " macro avg 0.63 0.71 0.63 3600\n",
+ "weighted avg 0.83 0.74 0.77 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(No PCA), gamma: 0.1...\u001b[0m\n",
+ "Undersampled dataset(No PCA), gamma: 0.1 Accuracy: 0.6869444444444445\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(No PCA), gamma: 0.1 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.94 0.67 0.78 3043\n",
+ " 1.0 0.30 0.76 0.43 557\n",
+ "\n",
+ " accuracy 0.69 3600\n",
+ " macro avg 0.62 0.72 0.61 3600\n",
+ "weighted avg 0.84 0.69 0.73 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(PCA), gamma: 0.1...\u001b[0m\n",
+ "Oversampled dataset(PCA), gamma: 0.1 Accuracy: 0.7338888888888889\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(PCA), gamma: 0.1 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.92 0.75 0.83 3043\n",
+ " 1.0 0.32 0.66 0.43 557\n",
+ "\n",
+ " accuracy 0.73 3600\n",
+ " macro avg 0.62 0.70 0.63 3600\n",
+ "weighted avg 0.83 0.73 0.77 3600\n",
+ "\n",
+ "\u001b[1mEvaluating Undersampled dataset(PCA), gamma: 0.1...\u001b[0m\n",
+ "Undersampled dataset(PCA), gamma: 0.1 Accuracy: 0.6533333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Undersampled dataset(PCA), gamma: 0.1 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.92 0.65 0.76 3043\n",
+ " 1.0 0.26 0.68 0.38 557\n",
+ "\n",
+ " accuracy 0.65 3600\n",
+ " macro avg 0.59 0.66 0.57 3600\n",
+ "weighted avg 0.82 0.65 0.70 3600\n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 900x500 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "predict(SVM_models, SVM_name, x_val_list, yval, \"SVM validation\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 129,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\u001b[1mEvaluating SVM testing data\u001b[0m \n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), gamma: 0.1...\u001b[0m\n",
+ "Oversampled dataset(No PCA), gamma: 0.1 Accuracy: 0.7646666666666667\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), gamma: 0.1 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.93 0.78 0.85 2529\n",
+ " 1.0 0.37 0.69 0.48 471\n",
+ "\n",
+ " accuracy 0.76 3000\n",
+ " macro avg 0.65 0.74 0.66 3000\n",
+ "weighted avg 0.84 0.76 0.79 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), gamma: 0.5...\u001b[0m\n",
+ "Oversampled dataset(No PCA), gamma: 0.5 Accuracy: 0.822\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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wICgoSD2TrFatWqF9aEOVk5OT8/xfufyr2GJUWQ9BceJPBZT1EBSnsqH2oWbx4e4C6+M29nve4ZR7MgMsYT692zOsfwesalfnzr0HHPzhT+asOciDlDQAerg2Z8qQLlhbWZCQlML20F9YuPE7Hmf+79jGp2N6MmHQG3n6/iTga/w35/4NW82sEnNG96Src1MqVzIk/M/rfBLwNWcjb5TOF31BxMbe5p2+b+K/bBWtHFoD0Mqu8VPbv96qNeuCtgK5ZyU3rF3NoYP7SUq8R9169fH5cCgenbuWytiLW3Gd6X2RSQCWoPEfdMJvVA+WbTvK8TMXaVDHnJkjPLFtWBPPYavo7GRL8JIP2Rb6CzMCvsa6vgVzRvfEsropo+Z+qe6neaPaHDsdhd/qAxr9/xObCOT+j7x72UfUe6UaMwK+Jj7hAaMHdOTbDWNxfPczrt64U6rfu7y6HXOLUcOH8PDBA43yzdu/zNP22NEwtm/ZRO++b6vLPpk2iV9+PsHocR9Tp249Dh0IZdrkj6lkbEy79s4lPv7iVlJL4BeJBGAJUalUTPB5g417TzJzZSgAx09f5F5SCjsWD6albV0mDnqDiL+iGe73hbq+mpkxkwd3ZpL/Xh6l5V7n1Ny6Nht2/8SZP6/n+1kuDq/R1r4Bb44K5PDJSABO/naFm8cW8sGbbdWfr1TZ2dkcCP2KFUsX5VvfrLm9xp9jb8ewb+9u+vV/j85dPQH49Ww4R8O+Y/mqtTg5596f2rpNW/755wY/n/jphQzAkroX+EUiAVhCTCoZEnwonN3fntUov3wj91qlV2tXZ8isz9HT1fxbOONxJrq6Kiro5e7VVqNqZSyrm/DHpZtP/awzf1yn48AlhP/1v+2CMh5nkUMOBvryn/jypYt8Ns+Pvm+/S2vHtowbNazA9kv9F2JoaMjIMb7qsmNHwqhVu446/CD3L7lNW78osXGXNFkCSwCWmOSHqYxfmPcg85tudgCcvxLDtZt31eUmxoa4tbFh3PvuBB+KIPlh7u1Adja1Aeju0pwlk/pRs7op56/GMGvVfvVs71FaBr/8fg0AXV0drGpVZ8awbqhQse3rX0r0e74ILGvWZN+B77CwsCQi/EyBbX8/9xvHjhxm1pz5GBsbq8svXbxAw9ca8e2hA2xcv4Z/bkRTu05dRoweh3unvMdnXwQyAyzjAMzMzOTw4cNEREQQExNDRkYGFStWxNLSklatWuHh4aGx28OLztHOio8HehB67Hcu/B2rLn/F3JSrh+cBcO3mXeauO6Sus7PODUDzqpUZ7vcFBvp6DH/HhZAVw3hr9BqOnLqg8RkB0/rj07s9APPWHeL8Fe1vDH9ZmZqaYWqqXdvtW4J45ZVadPXsoVGemJjIjRvRREWeZ/josVSvbs6enV8yZcI4lq1cozEzfFHIMcAyDMAbN24wZMgQ4uLisLW1pUaNGpiampKens6FCxfYu3cvK1euZOPGjbzyyitlNcxi075FA/asGMrfN+8yzG+HRl1KagZdPgrA1NiQSYM7c3LHJNwGLSXq71h2fRvBH5duEfbzBZ5csRR2KpIzO6cyc7hnngDctPckXx4Kx9WhERN93shzQkU8XWzsbX784Ti+Eybn+Yv38ePH3L1zh8+D92DTuAkADq0debffWwStfzEDUJbAZRiAfn5+1K5dmz179lC5cuU89ffv38fX15c5c+awdu3aMhhh8enX+XXW+3lxKTqOniNWk3j/kUZ98sNUfgi/BMCPEZe5cNCP0QM6MvLTL7lxO5EbtxM12mdmZnP0VBSD+7TP81lPLns5cfYKKpWKKR92ZsH6b7gVn1QyX+4lcvxoGCqVije6dMtTZ2RUierm5urwA9DV1aWNY1tC9uwqzWEWG1kCl+GtcGfPnmXSpEn5hh/k7ik2ceJE9QaILyrf993ZMv8Dzvx5HY/By4lLyL0EQ1dXh75vtFQvcZ9IepDK3//cpbZFFQC6ODVRHzf8N0ODCtxLTgGg8auWePd0zNPm7PlodHR0qGVhVszf6uX004/f06JlK6pVq56nrm69ejx+/Jj/3jeQmZmJgYFhaQ2xWJXUfoAvkjL7liYmJnl2c/ivmJgY9dY4L6LBfdoz37cXIWG/0X34Ku4/TFPXZWVlM2/cW8wd+6bGe+pYVsHGypI/L90CoG/nlqyb7YVZ5YrqNkaG+nR1bsKPEZcBcGhWn/V+XjjaWWn05dHOlrT0x1y8FldSX/GlkZOTQ+T5v7Czb5FvfXunDiQnJXH61M/qssePM/j55AnsW75eWsMsVipVwS8lKLMlcN++fZk6dSpjxoyhTZs21KxZE319fTIyMoiLi+PMmTP4+/vTt2/fshric7GoVplFH/chOiaBNcE/0KJxHY36v2/eZe7aQ6z382L1J++y5/Cv1DQ3ZdqQrtxLTmHF9tytiJZuOUIv9xZ8tWoEizcdRk9Xh48HelDJyIBP1+aeLNnz3a+Me9+drQsGMWfNQWLvJNPdtTkf9XNi1uoD6jPK4ulib8fw8MEDrBo0zLe+a7fu7ArewYxpExk1xpcaFpYE79hOfFwsC/2XlfJoi4eOLIHLLgBHjx6Njo4OCxcu5NGjR3nqK1WqxIABAxg7dmwZjO75dXZqglFFfepVrMbRzePz1A+ZuZ3tob+Q8iid8YM86N+1FY/SMjh8MpKZAaHcSXwIQOTV23h8uJzZI3uwbrYX+hV0OfHrFYYN2qG+jOZRWgZdPwpg9qge+I3sTjUzY6KuxTJk1ud8caDgyz5ErifPkTAxMcm3Xq9CBVavC2J1wDICV64g5VEKNja2BK7fpHFc8EUiAVgONkN4/PgxFy5cIC4ujtTUVAwNDbG0tMTGxibPltfPQzZDKH2yGULpK8pmCLbTDhdYHzn/xby+sSjK/CK7ChUq0Lx587IehhCKIzPAchCAQoiyIQEoASiEYsmF0BKAQiiWzAAlAIVQLAlACUAhFEtWwBKAQiiWzAAlAIVQLAlACUAhFEvOAsuD0YVQLB0dVYGv4hIYGIi3t7dG2dSpU7G2ttZ4dejQQV2fnZ1NQEAAzs7O2NnZ4ePjQ3R0tEYfFy5cwMvLC3t7e1xdXQkKCiry2CQAhVCo0gjALVu2EBCQ95bIixcvMmzYME6cOKF+ffXVV+r6wMBAgoODmTt3Ljt37kSlUjFkyBAyMnIfFJaYmMigQYOoX78+e/fuZfTo0axYsYK9e/cWaXyyBBZCoUpyCRwXF8f06dM5e/YsVlaa27RlZWVx5coVRowYgbm5eZ73ZmRksGnTJiZOnIiLS+5O28uWLcPZ2ZmwsDA8PT3ZtWsX+vr6zJ49Gz09PRo0aEB0dDQbNmygT58+Wo9TqwAs6qakDg4ORWovhCh9JXkS5Pz585iamhIaGsrq1au5deuWuu769eukp6fToEGDfN8bFRVFSkoKjo7/2+TXxMQEW1tbwsPD8fT0JCIiAgcHB41HFzg6OrJu3ToSEhKoVq2aVuPUKgC9vb21+tsiJycHlUrFhQsXCm0rhChbJRmAbm5uuLm55Vt36dIlVCoVW7du5ccff0RHRwcXFxfGjRtH5cqViY3NfWBYzZo1Nd5Xo0YNbt++DUBsbCyNGjXKUw+5GykXawBu27ZNq86EEC+OwuY07u7uBdYfPXr0mT738uXLuY9qqFWLtWvXEh0dzcKFC7l06RJbt24lNTV3A9//bodnYGBAcnIyAGlpafnWA6Snp2s9Fq0CsHXr1lp3KIR4MegWMgPMKqHPHT16NAMHDlRvPtuoUSPMzc3p378/f/75p/oxGBkZGRqPxEhPT6dixdxHQxgaGqpPiPy7HsDIyEjrsTzTSZBz585x5swZjYfE5OTk8OjRI86ePcuuXS/mU7KEUJLCAvDwM87wCqNSqfLsvP1kORsbG6te+sbHx1O3bl11m/j4eGxsbACwtLTM80yhJ3+2sLDQeixFDsAdO3Ywd+7cPE/HgtynTDk5ORW1SyFEGSirC6E//vhjkpKSNK7b+/PPPwFo2LAhderUwdjYmNOnT6sD8P79+0RGRuLl5QXknmgNDg4mKysLXV1dAE6dOoWVlZXWx//gGa4D/Pzzz3FycuL06dMMHjyYt99+m3PnzrFixQoMDAzo2bNnUbsUQpQBHZWqwFdJ6d69OydPnmTNmjXcuHGDH374gWnTptG9e3caNGiAvr4+Xl5e+Pv7c/ToUaKiovD19cXS0hIPDw8A+vTpw8OHD5k+fTpXrlwhJCSErVu3MnTo0CKNpcgzwJs3bzJlyhRMTU1p1qwZK1euxNDQkM6dO3Pt2jW2bdtG9+7di9qtEKKUFbYELikdO3ZkxYoVrF27lrVr11K5cmV69OjBuHHj1G3GjBlDZmYmM2bMIC0tDQcHB4KCgtQnPqpVq8bGjRuZN28evXr1wtzcnEmTJtGrV68ijaXIAVihQgX1gcn69esTHR3N48ePqVChAi1btmTTpk1F7VIIUQZKawX82Wef5Snr3LkznTt3fup7dHV1mThxIhMnTnxqm+bNm7Nz587nGluRl8CNGzfm+PHjANSrV4/s7GzOnTsHoL5+RwhR/unqqAp8KUGRZ4CDBg1i1KhRJCcns2DBAtzd3Zk0aRKdO3dm//79vP766yUxTiFEMZPtsJ5hBtipUyfWrl1Lw4YNAZgzZw5WVlYEBwfz6quvMnPmzGIfpBCi+JXVSZDy5JmuA3R1dcXV1RWAKlWqyHE/IV5ASgm5ghQ5AGNiYgpt88orrzzTYIQQpUcpx/kKUuQAdHNzK/QCStkMQYjyTyaAzxCA8+fPzxOAT26B++WXX5g/f36xDU4IUXJkBvgMAdi7d+98ywcMGMDChQvZv3+/+vigEKL8kmOAxbwlvqurK99//31xdimEKCFyFriYt8Q/d+6cxg6tQojyS64DfIYAnDp1ap6y7Oxsbt++TUREBH379i2WgQkhSpYcA3yGADx9+nSeMpVKhbGxMUOGDGHYsGHFMjAhRMlSyCq3QEUOwGPHjpXEOErcxaNLynoIilNBT566Wp7pSgIW/STI1KlT+eeff/Kt+/vvv2UGKMQLQjZD0HIG+O+7P/bt20enTp3Uu7D+248//sjPP/9cfKMTQpQYhWRcgbQKwDlz5vDDDz8Aucf7Ro0alW+7nJwc2rdvX3yjE0KUGKXM8gqiVQD6+fnx888/k5OTw7Rp0xg+fLjGw0og93kgJiYmtGnTpkQGKoQoXhKAWgaghYWFeqtplUqFq6srxsbGVKhQAYDU1FTS09MxMzMrsYEKIYqXnKJ6hp+Bp6cnS5Ys4e2331aX/fbbbzg5OTFv3jyyskrqaaJCiOIkJ0GeIQADAgI4dOgQb731lrqsSZMmTJ48mX379rFhw4biHJ8QooTo6hT8UoIiXwd48OBBJk+eTP/+/dVlpqameHt7o6Ojw5YtW+RSGCFeAEq537cgRQ7AxMREateunW+dlZUVcXFxzz0oIUTJU8osryBF/hE0aNCA7777Lt+6sLAw6tWr99yDEkKUPF2VqsCXEhQ5AH18fNi1axdjxowhNDSUkydPsn//fsaOHUtwcDCDBw8uiXEKIYqZjqrgV3EJDAzE29tbo+zChQt4eXlhb2+Pq6srQUFBGvXZ2dkEBATg7OyMnZ0dPj4+REdHF6kPbRR5Cezp6cmDBw9YtWoVhw8fVpdXqVKFmTNn0r179yIPQghR+krjTO+WLVsICAjAwcFBXZaYmMigQYPo1KkTfn5+nDt3Dj8/P8zMzOjTpw+QG5rBwcEsWLAACwsLFi9ezJAhQzhw4AD6+vpa9aGNZ9q875133qF///5cu3aNpKQkTExMMDAwYPfu3bi6unLixIln6VYIUYpKMgDj4uKYPn06Z8+excrKSqNu165d6OvrM3v2bPT09GjQoAHR0dFs2LCBPn36kJGRwaZNm5g4cSIuLi4ALFu2DGdnZ8LCwvD09Cy0D20982FQlUqFlZUVSUlJLFq0iC5durB+/XpMTEyetUshRCkqySXw+fPnMTU1JTQ0FDs7O426iIgIHBwcNDZPdnR05Nq1ayQkJBAVFUVKSgqOjo7qehMTE2xtbQkPD9eqD2090wwwPj6e3bt3s2fPHmJjYzExMaF///689dZbNG/e/Fm6FEKUssJOdLi7uxdYf/To0afWubm54ebmlm9dbGwsjRo10iirUaMGkLvxSmxsLAA1a9bM0+b27dta9VGtWrUCx/5EkQLw5MmTBAcHc/z4cXJycmjTpg2xsbGsWrVKY40vhCj/yuoymLS0NPT19TXKDAwMAEhPTyc1NRUg3zbJycla9aEtrQJw48aN7Nq1ixs3bmBlZcWYMWPo1asXBgYGtG7dWusPE0KUH4VdCF3QDO95GBoakpGRoVH2JLSMjIwwNDQEICMjQ/3vT9pUrFhRqz60pVUA+vv7Y21tzfbt2zVmeg8ePND6g4QQ5UtZ3e9raWlJfHy8RtmTP1tYWJCZmaku+/euU/Hx8djY2GjVh7a0mgT37NmTGzdu8OGHHzJ06FC++eabPOkrhHixqFQFv0qKg4MDZ8+e1dg45dSpU1hZWVGtWjVsbGwwNjbWeP7Q/fv3iYyMpFWrVlr1oS2tAnDRokWcOHGCadOmkZSUhK+vL87OzixYsACVSoVKIVeNC/EyKas7Qfr06cPDhw+ZPn06V65cISQkhK1btzJ06FAg99ifl5cX/v7+HD16lKioKHx9fbG0tMTDw0OrPrSlysnJySnqF7h69Sp79uxh//793L17l1q1atG9e3c8PT3znJkpL27c0/7AqCgeNUwMynoIimNYhNOan5+9WWC91+v53/NfVFOmTOHWrVts375dXfbHH38wb948IiMjMTc3x8fHBy8vL3V9VlYWS5cuJSQkhLS0NBwcHJg5c6bGPgSF9aGNZwrAfw/y+PHj7NmzhxMnTpCVlcVrr71GaGjos3ZZYiQAS58EYOkrSgDuKCQABxRTAJZnz3Qd4BO6urp06tSJTp06kZCQQEhICF999VUxDU0IUZJ0FLLpaUGeawb4IpEZYOmTGWDpK8oMcNe5mALr37Z/5TlHU/491wxQCPHikvmfBKAQiqWUPf8KIgEohELJlvgSgEIoluSfBKAQiiVLYAlAIRRLlsDycPhSl5WVRfC2ID7o64mniwNDvfty5NsDGm1GfzgAj7bN87wi//pd3SbudgyfTp9Av24u9OnSgVmTxxJz85/S/jovpNjbt3FybEX4mdNFqjt29Ajv9OtNm1b2dOnUkcBVATx+ge+J10FV4EsJZAZYyjatDSAkeDsffDSKRja2nDl1goV+09BRqXDr7El2djbXr17m7QEDae+quSGl1auvAZCWlsrksUPJyspk5Pip6OsbsGX9KiaM9GH953sxriy7cj9NTMwthn80ON+djAqq++nHHxg/dhRv9urNuPETuPb33wQsX8LdO3eY6fdpaQy92OnI9EcCsDSlPnrE17u/pPc73rzj7QNASwdHLkdF8tWeL3Hr7MnNG9GkpaXRul0HbJva5dvPX7//xq1/olkYsJ6WDrnbhteuW5/B777Jzz8e5w3PN0vtO70osrOzCf16H0sXLypS3RNBG9bRtFlz/D6dD4Bj23YkJSWycf1aJkyeWqQ96MoLOQYoAViq9PX1WbFhO1WrVdco16tQgUcpDwG4ejkKgAavPX1TiSfLrkqVjNVlpmZmANy/n1ycQ35pXLp4kXlzZvP2O+/h2LYdo4Z/pFXdE5/O+4ysrEyNsgoVKpCVlaXev+5Fo1LIMrcgEoClSFdPjwavWQOQk5ND4r0EvjvwFb+F/4LvlFkAXL18kUrGlQlcvohfTvxAWloq9q+3ZvjYidSpl/t0rddbt6X+qw3ZsHoZH0/zw8DQkDXLF1HRyIj2HfJ/DoPS1axZkwPfhGFhaZnn+F5BdU/U+dfGnA8ePOD0qZ/ZunkT3br3eGEfBCYnQSQAy8yxw4f4bPZUAFq3c8a1UxcArl6KIuXhA8zMquC3cDlxsbfZHrSW8cMHsmbrbqqb10DfwADfKbP4ZOJo3u/bDYAK+vp8unglNWu9/Dt4PAtTMzNMn6Huv+Li4njDrQMAtWrXZviI0cUyvrIgS2A5C1xmbGybsSRwE75TZnLl4gXGfuRNRno6g0eMY9narXw0+mOa2b9Opy7d+Wz5WlIePmTfrh0A/P5rOBNGDebVho2Y67+K+UsDadWmHbOnjOPPc2fL+Ju93CpWrMj6oC0sXbEKM1Mz3u3fh6tXrpT1sJ5JWe0IXZ7IDLCM1KpTl1p16tK8RStq1qrDpNFD+On7I7h39szTtmat2tSp/yp/X74IwBdbN1LdvAbzlgaqn4z1ept2jB3ixZoViwncHFyq30VJTExMaOPYFgAHh9Z06+zO59u2MGvO3DIeWdHJDLCMA9Db21vr7fS3bdtWwqMpeYn3Egg/dQKHtk5Uqfq/5xZYN24KwO1bN/nu4NfUqVc/zxngjPQ0TM2qABAfG0MjmyYajwXU0dGhqV1LQvfuLIVvoiyZmZkcCTtMvfr1adzYVl1uYmpK7Tp1iY29XYaje3aSf2W8BG7bti3h4eEkJCRQq1atAl8vg7TUVBbP/YRvQkM0ysN/OQlAo8a2bNsYyMbVyzTqL1+MJObmPzRvmftAmDr1rLgY+afGg6lycnKI/OsPLF95OX5W5Ymenh7Llyxm+VJ/jfLbMTFc+/sqjaxtymhkz0dVyD9KUKYzwBEjRmBkZERAQADr1q3T2O//ZVSzVm08uvbg883r0NHVxbpxEy5FneeLzRto1aYdDo5OePsMY8n8WSz6dAbunT2Ju32LrRsCsWrQiM7dcq/vGzBoKL7DPmD6+OH06u+Frq4e3x3Yx4W/fueTef6FjEI8i2EjRzFrxjT8Zs6gc9du3ImPZ92a1ZiamfH+QJ+yHt4zkQ2hy8ExwIEDB3LixAmWL1+Ov//L/8s7bsosatWtx3cH9rFtYyDVqlWn19sDeG/QR6hUKrr06IWBoSG7d2xh9uSxGFasSPsO7vgMH4uuXu5/LuvGTVgSuIkt61ezYNYUKuhV4NXXrFm8Kgi7/58liuL1Vq8+GBkZsTloA4cOHaCioSHtnTswZtzHRXoMY3kiT3MsJ1vix8XFERkZSceOHUvsM2RL/NInW+KXvqJsiX/2+v0C61+v/2Je31gUZT4DhNwnuRflae5CiOcnE0C5DlAIxdJRqQp8PY9bt25hbW2d57V7924ALly4gJeXF/b29ri6uhIUFKTx/uzsbAICAnB2dsbOzg4fHx+io6Ofa0z5KRczQCFE6SvJCeDFixcxMDDgyJEjGscaK1euTGJiIoMGDaJTp074+flx7tw5/Pz8MDMzo0+fPgAEBgYSHBzMggULsLCwYPHixQwZMoQDBw5oXP71vCQAhVCokjwJcunSJaysrKhRo0aeuq1bt6Kvr8/s2bPR09OjQYMGREdHs2HDBvr06UNGRgabNm1i4sSJuLi4ALBs2TKcnZ0JCwvD0zPvzQLPSpbAQiiUjqrg1/O4ePEiDRs2zLcuIiICBwcH9PT+N/9ydHTk2rVrJCQkEBUVRUpKCo6Ojup6ExMTbG1tCQ8Pf76B/YcEoBBKpSrk9RwuXbpEQkIC7733Hu3atePdd9/lp59+AiA2NhZLS0uN9k9mijExMcTGxgK5u/T8t83t28V7140sgYVQqMJOdLi7uxdYf/To0XzLMzIyuH79OhUrVmTSpEkYGRkRGhrKkCFD2Lx5M2lpaXmO4xkY5F4ylZ6eTmpqKkC+bZKTi3e/SwlAIRSqpA4B6uvrEx4ejp6enjrEmjZtytWrVwkKCsLQ0FDjNk7IDT4AIyMjDA0NgdwgffLvT9pUrFixWMcqASiEQhV2v+/TZnjayO8RAY0aNeLEiRNYWloSHx+vUffkzxYWFuodtuPj46n7r41o4+PjsbEp3vuu5RigEApVUidBoqKiaNGiBRERERrlf/31Fw0bNsTBwYGzZ8+SlZWlrjt16hRWVlZUq1YNGxsbjI2NOX36f7tz379/n8jISFq1Kt5bPSUAhVAolUpV4OtZNWrUiNdeew0/Pz8iIiK4evUqCxYs4Ny5cwwbNow+ffrw8OFDpk+fzpUrVwgJCWHr1q0MHToUyF1Ce3l54e/vz9GjR4mKisLX1xdLS0s8PDyK6+sD5eRe4NIg9wKXPrkXuPQV5V7gK/GpBdY3rPHsx9vu3buHv78/P/74I/fv38fW1pYJEyaoZ3B//PEH8+bNIzIyEnNzc3x8fPDy8lK/Pysri6VLlxISEkJaWhoODg7MnDmz2HeMkgAUJUYCsPQVJQCv3ik4ABuYF+8Jh/JIToIIoVDyVDgJQCEUS+JPAlAIxZINUSUAhVAs2RJfAlAIxZIJoASgEIolS2AJQCEUS5bAEoBCKJZSnv1bEAlAIRRKVsASgEIollwILQEohHJJ/kkACqFUchJEAlAIxZIlsOwHKIRQMJkBCqFQMgOUABRCseQYoASgEMolASgBKIRSyRJYAlAIxZL8kwAUQrHkXmAFPRRJCCH+S64DFEIolgSgEEKxJACFEIolASiEUCwJQCGEYkkACiEUSwJQCKFYEoBCCMWSABRCKJYEoBBCsSQAhRCKJQEohFAsCUAhhGJJAJZT2dnZBAQE4OzsjJ2dHT4+PkRHR5f1sBQjMDAQb2/vsh6GKGESgOVUYGAgwcHBzJ07l507d6JSqRgyZAgZGRllPbSX3pYtWwgICCjrYYhSIAFYDmVkZLBp0yZGjx6Ni4sLNjY2LFu2jLi4OMLCwsp6eC+tuLg4PvzwQ1asWIGVlVVZD0eUAgnAcigqKoqUlBQcHR3VZSYmJtja2hIeHl6GI3u5nT9/HlNTU0JDQ7Gzsyvr4YhSIFvil0OxsbEA1KxZU6O8Ro0a3L59uyyGpAhubm64ubmV9TBEKZIZYDmUmpoKgL6+vka5gYEB6enpZTEkIV5KEoDlkKGhIUCeEx7p6elUrFixLIYkxEtJArAcerL0jY+P1yiPj4/H0tKyLIYkxEtJArAcsrGxwdjYmNOnT6vL7t+/T2RkJK1atSrDkQnxcpGTIOWQvr4+Xl5e+Pv7U7VqVWrVqsXixYuxtLTEw8OjrIcnxEtDArCcGjNmDJmZmcyYMYO0tDQcHBwICgrKc2JECPHs5MHoQgjFkmOAQgjFkgAUQiiWBKAQQrEkAIUQiiUBKIRQLAlAIYRiSQCKckeuzBKlRQLwJeTt7Y21tbXGq2nTpri6uuLn50dycnKJfG5ISAjW1tbcvHkTgJUrV2Jtba31+2NjYxk6dCi3bt167rHcvHkTa2trQkJCnrsv8fKSO0FeUra2tsyaNUv958ePH3P+/HmWLl3KhQsX+PLLL1GpVCU6hn79+uHs7Kx1+59//pnvv/+eTz75pARHJcT/SAC+pIyNjbG3t9coc3BwICUlhYCAAH7//fc89cXN0tJSdq8R5ZosgRWmadOmAMTExODt7c2ECRMYM2YMLVu25KOPPgJy9x1ctGgRLi4uNG3alB49enDo0CGNfrKzswkMDMTV1RU7OztGjBiRZ2md3xL44MGD9O7dGzs7O1xdXVm8eDEZGRmEhIQwdepUANzd3ZkyZYr6Pbt378bT01O9jF+5ciWZmZka/R4+fJiePXvSvHlzevXqRVRUVPH8wMRLTWaACnPt2jUA6tSpA8A333xDly5dWL16NVlZWeTk5DBy5Eh+/fVXxowZQ4MGDQgLC8PX15eMjAzeeustABYvXsy2bdsYNmwY9vb2fPvttyxZsqTAzw4ODmbWrFn07dsXX19fbt68yaJFi0hMTGTChAkMHz6cNWvWsGrVKnVwrlu3jmXLluHl5cXUqVO5cOECK1eu5Pbt28yfPx+AY8eOMWbMGDw9PZkwYQJRUVFMnDixhH6C4mUiAfiSysnJ0ZglJScnc+bMGdasWYO9vb16Jqijo8Onn36KkZERACdPnuSnn35i2bJldOvWDQBnZ2dSU1Px9/ene/fuPHr0iO3bt/P+++8zevRodZu4uDh++umnfMeTnZ3NypUr8fDwYN68eery9PR09u3bh7GxMXXr1gWgcePG1K5dmwcPHrBmzRr69+/PjBkzAHBycsLMzIwZM2YwaNAgXnvtNVavXk2TJk3UAdyhQweAQgNZCFkCv6TCw8Np0qSJ+tWuXTvGjx9PkyZNWLp0qfoESO3atdXhB3Dq1ClUKhUuLi5kZmaqX25ubty5c4fLly9z7tw5Hj9+jLu7u8Zndu3a9anjuXbtGnfv3qVTp04a5QMHDuTrr7/Od5uv3377jdTUVNzc3PKMBXLDOi0tjfPnzxdpLEI8ITPAl1STJk3w8/MDQKVSYWBgQM2aNTE2NtZoV716dY0/JyUlkZOTQ8uWLfPtNz4+nvv37wNQtWpVjTpzc/OnjicpKQmAatWqaf0dnrznybHJ/MaSnJxMTk5OnrHUqFFD688RyiUB+JKqVKkSzZo1K/L7KleujJGREdu2bcu3vl69evzxxx8AJCQk8Oqrr6rrngRWfkxMTAC4d++eRnlSUhLnz5/P94z0k/f4+/tTv379PPXVq1fHzMwMHR0d7t69m6dfIQojS2ChoXXr1jx69IicnByaNWumfl2+fJnVq1eTmZlJixYtMDQ05Ntvv9V47/Hjx5/a76uvvkqVKlU4evSoRvn+/fsZMmQI6enp6Oho/u9oZ2dHhQoViIuL0xhLhQoVWLJkCTdv3sTAwIAWLVpw+PBhjTtIjh07Vgw/DfGykxmg0ODi4oKDgwMjRoxgxIgRNGjQgD/++IOVK1fi5OSkXmqOGDGC5cuXU7FiRRwdHfnhhx8KDEBdXV1Gjx7NnDlzmD17Nh4eHly/fp3ly5fz7rvvUrVqVfWMLywsjA4dOtCgQQM+/PBDVqxYwcOHD2nTpg1xcXGsWLEClUqFjY0NAOPHj+eDDz5g1KhR9O/fn+vXr7NmzZqS/2GJF54EoNCgo6PD+vXrWbFiBevWrSMhIQELCwsGDhzIyJEj1e2GDh2KkZERW7duZevWrbRo0YLJkycze/bsp/Y9YMAAjIyMCAoKYs+ePVhYWODj46M+xtemTRvatWvHkiVLOHXqFOvXr2fcuHGYm5vzxRdfsHHjRkxNTWnbti3jx4+ncuXKALRq1YoNGzawdOlSRo0aRe3atZk/fz7Dhg0r0Z+VePHJM0GEEIolxwCFEIolASiEUCwJQCGEYkkACiEUSwJQCKFYEoBCCMWSABRCKJYEoBBCsSQAhRCKJQEohFAsCUAhhGJJAAohFOv/ALbcCVBggQX3AAAAAElFTkSuQmCC",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), gamma: 0.5 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.87 0.93 0.90 2529\n",
+ " 1.0 0.39 0.24 0.30 471\n",
+ "\n",
+ " accuracy 0.82 3000\n",
+ " macro avg 0.63 0.59 0.60 3000\n",
+ "weighted avg 0.79 0.82 0.80 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), gamma: 0.01...\u001b[0m\n",
+ "Oversampled dataset(No PCA), gamma: 0.01 Accuracy: 0.722\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), gamma: 0.01 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.96 0.70 0.81 2529\n",
+ " 1.0 0.34 0.82 0.48 471\n",
+ "\n",
+ " accuracy 0.72 3000\n",
+ " macro avg 0.65 0.76 0.65 3000\n",
+ "weighted avg 0.86 0.72 0.76 3000\n",
+ "\n",
+ "\u001b[1mEvaluating Oversampled dataset(No PCA), gamma: 0.05...\u001b[0m\n",
+ "Oversampled dataset(No PCA), gamma: 0.05 Accuracy: 0.7423333333333333\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 300x200 with 2 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oversampled dataset(No PCA), gamma: 0.05 Classification report:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0.0 0.94 0.74 0.83 2529\n",
+ " 1.0 0.35 0.76 0.48 471\n",
+ "\n",
+ " accuracy 0.74 3000\n",
+ " macro avg 0.65 0.75 0.65 3000\n",
+ "weighted avg 0.85 0.74 0.77 3000\n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 900x500 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "predict(SVM_models, SVM_name, x_test_list, ytest, \"SVM testing\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Multi Layer Perceptron"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Deep Reinforcement Learning"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## ILP"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Cross Validation on Best Performing Datasets"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 132,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Decision Tree: 0.755696 (0.011827)\n",
+ "SVM: 0.738926 (0.014916)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 700x700 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Evaluate each model in turn\n",
+ "models = [\n",
+ " ('Decision Tree', DecisionTreeClassifier(ccp_alpha=0.001)),\n",
+ " ('SVM', svm.SVC(probability=True, random_state=42, gamma=0.01))\n",
+ "]\n",
+ "\n",
+ "\n",
+ "models_list = []\n",
+ "x_val_list = []\n",
+ "x_test_list = []\n",
+ "\n",
+ "results = []\n",
+ "names = []\n",
+ "for name, model in models:\n",
+ " models_list.append(model)\n",
+ " x_test_list.append(xtest_pca_oversampled)\n",
+ " kfold = StratifiedKFold(n_splits=10, random_state=None)\n",
+ " cv_results = cross_val_score(model, xtrain_pca_oversampled, ytrain_oversampled, cv=kfold, scoring='accuracy')\n",
+ " results.append(cv_results)\n",
+ " names.append(name)\n",
+ " print('%s: %f (%f)' % (name, cv_results.mean(), cv_results.std()))\n",
+ "\n",
+ "# Compare Algorithms\n",
+ "plt.figure(figsize=(7,7))\n",
+ "plt.boxplot(results, labels=names)\n",
+ "plt.title('Comparison of Models on Dataset 2')\n",
+ "plt.xlabel('Model')\n",
+ "plt.ylabel('Accuracy')\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "colab": {
+ "provenance": []
+ },
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}