diff --git a/data/processed/SM_Regression_Suraj.csv b/data/processed/SM_Regression_Suraj.csv
deleted file mode 100644
index 1925919c226396c69a490b747795cdb84bf64c5b..0000000000000000000000000000000000000000
--- a/data/processed/SM_Regression_Suraj.csv
+++ /dev/null
@@ -1,1198 +0,0 @@
-date,quarter,department,team,targeted_productivity,smv,wip,over_time,incentive,idle_time,idle_men,no_of_style_change,no_of_workers,day_num,day_sin,day_cos,day_Monday,day_Saturday,day_Sunday,day_Thursday,day_Tuesday,day_Wednesday,department_encoded,team_encoded,quarter_encoded,actual_productivity
-2015-01-01,0,1,8,0.8,26.16,1108.0,7080.0,98.0,0.0,0.0,0,59.0,3,0.43388373911755823,-0.900968867902419,0,0,0,1,0,0,0.7220130317105644,0.6741481065963303,0.75155978095,0.940725424
-2015-01-01,0,0,1,0.75,3.94,1190.4659913169319,960.0,0.0,0.0,0.0,0,8.0,3,0.43388373911755823,-0.900968867902419,0,0,0,1,0,0,0.7529506683241107,0.8210543824666667,0.75155978095,0.8865
-2015-01-01,0,1,11,0.8,11.41,968.0,3660.0,50.0,0.0,0.0,0,30.5,3,0.43388373911755823,-0.900968867902419,0,0,0,1,0,0,0.7220130317105644,0.6819845691931818,0.75155978095,0.800570492
-2015-01-01,0,1,12,0.8,11.41,968.0,3660.0,50.0,0.0,0.0,0,30.5,3,0.43388373911755823,-0.900968867902419,0,0,0,1,0,0,0.7220130317105644,0.7790554071515151,0.75155978095,0.800570492
-2015-01-01,0,1,6,0.8,25.9,1170.0,1920.0,50.0,0.0,0.0,0,56.0,3,0.43388373911755823,-0.900968867902419,0,0,0,1,0,0,0.7220130317105644,0.6853852354148937,0.75155978095,0.800381944
-2015-01-01,0,1,7,0.8,25.9,984.0,6720.0,38.0,0.0,0.0,0,56.0,3,0.43388373911755823,-0.900968867902419,0,0,0,1,0,0,0.7220130317105644,0.6680055056458333,0.75155978095,0.800125
-2015-01-01,0,0,2,0.75,3.94,1190.4659913169319,960.0,0.0,0.0,0.0,0,8.0,3,0.43388373911755823,-0.900968867902419,0,0,0,1,0,0,0.7529506683241107,0.7708551285779817,0.75155978095,0.755166667
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-2015-01-01,0,1,9,0.7,28.08,872.0,6900.0,44.0,0.0,0.0,0,57.5,3,0.43388373911755823,-0.900968867902419,0,0,0,1,0,0,0.7220130317105644,0.7344619130769231,0.75155978095,0.721126957
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-2015-01-03,0,1,12,0.8,26.16,844.0,7080.0,63.0,0.0,0.0,0,59.0,5,-0.9749279121818236,-0.2225209339563146,0,1,0,0,0,0,0.7220130317105644,0.7790554071515151,0.75155978095,0.800318644
-2015-01-03,0,1,11,0.8,11.61,1005.0,7080.0,50.0,0.0,0.0,0,29.5,5,-0.9749279121818236,-0.2225209339563146,0,1,0,0,0,0,0.7220130317105644,0.6819845691931818,0.75155978095,0.800237288
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-2015-01-03,0,1,6,0.8,25.9,1152.0,6720.0,50.0,0.0,0.0,0,56.0,5,-0.9749279121818236,-0.2225209339563146,0,1,0,0,0,0,0.7220130317105644,0.6853852354148937,0.75155978095,0.800125
-2015-01-03,0,1,7,0.8,25.9,1138.0,6720.0,38.0,0.0,0.0,0,56.0,5,-0.9749279121818236,-0.2225209339563146,0,1,0,0,0,0,0.7220130317105644,0.6680055056458333,0.75155978095,0.800125
-2015-01-03,0,1,10,0.75,19.31,1190.4659913169319,6480.0,56.0,0.0,0.0,0,54.0,5,-0.9749279121818236,-0.2225209339563146,0,1,0,0,0,0,0.7220130317105644,0.71973620015,0.75155978095,0.787299691
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-2015-02-23,3,0,10,0.8,3.94,1190.4659913169319,2400.0,0.0,0.0,0.0,0,20.0,0,0.0,1.0,1,0,0,0,0,0,0.7529506683241107,0.71973620015,0.7090671237096774,0.955791667
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-2015-02-23,3,1,10,0.7,21.25,1190.4659913169319,6000.0,0.0,0.0,0.0,1,50.0,0,0.0,1.0,1,0,0,0,0,0,0.7220130317105644,0.71973620015,0.7090671237096774,0.417916667
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-2015-03-11,1,1,9,0.75,18.79,1190.4659913169319,5040.0,45.0,0.0,0.0,0,52.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7220130317105644,0.7344619130769231,0.7437097343044776,0.750347333
-2015-03-11,1,1,2,0.75,16.1,971.0,5400.0,45.0,0.0,0.0,1,45.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7220130317105644,0.7708551285779817,0.7437097343044776,0.750140741
-2015-03-11,1,1,1,0.75,26.82,1322.0,7080.0,45.0,0.0,0.0,0,59.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7220130317105644,0.8210543824666667,0.7437097343044776,0.750050847
-2015-03-11,1,1,4,0.75,26.82,1054.0,7080.0,45.0,0.0,0.0,0,59.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7220130317105644,0.7700348248857143,0.7437097343044776,0.750050847
-2015-03-11,1,1,5,0.7,26.82,992.0,6960.0,30.0,0.0,0.0,1,58.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7220130317105644,0.6979807909032258,0.7437097343044776,0.700556897
-2015-03-11,1,1,8,0.7,30.48,914.0,6840.0,30.0,0.0,0.0,1,57.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7220130317105644,0.6741481065963303,0.7437097343044776,0.700505263
-2015-03-11,1,1,6,0.7,23.41,1128.0,4560.0,40.0,0.0,0.0,1,38.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7220130317105644,0.6853852354148937,0.7437097343044776,0.700246491
-2015-03-11,1,1,7,0.65,30.48,935.0,6840.0,26.0,0.0,0.0,1,57.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7220130317105644,0.6680055056458333,0.7437097343044776,0.650596491
-2015-03-11,1,0,10,0.75,2.9,1190.4659913169319,960.0,0.0,0.0,0.0,0,8.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7529506683241107,0.71973620015,0.7437097343044776,0.628333333
-2015-03-11,1,0,8,0.7,3.9,1190.4659913169319,960.0,0.0,0.0,0.0,0,8.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7529506683241107,0.6741481065963303,0.7437097343044776,0.625625
-2015-03-11,1,0,7,0.65,3.9,1190.4659913169319,960.0,0.0,0.0,0.0,0,8.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7529506683241107,0.6680055056458333,0.7437097343044776,0.625625
-2015-03-11,1,0,9,0.75,2.9,1190.4659913169319,1800.0,0.0,0.0,0.0,0,15.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7529506683241107,0.7344619130769231,0.7437097343044776,0.505888889
-2015-03-11,1,0,6,0.7,2.9,1190.4659913169319,720.0,0.0,0.0,0.0,0,6.0,2,0.9749279121818236,-0.22252093395631434,0,0,0,0,0,1,0.7529506683241107,0.6853852354148937,0.7437097343044776,0.394722222
diff --git a/notebooks/regression/Pre-Processing_Suraj.ipynb b/notebooks/regression/Pre-Processing_Suraj.ipynb
deleted file mode 100644
index 14df5c587e6b95609253775e4c6575e18ae0cf99..0000000000000000000000000000000000000000
--- a/notebooks/regression/Pre-Processing_Suraj.ipynb
+++ /dev/null
@@ -1,2610 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "e974f0e6",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:49.419344Z",
-     "start_time": "2025-04-04T15:19:46.078227Z"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import seaborn as sns\n",
-    "\n",
-    "from sklearn.preprocessing import LabelEncoder\n",
-    "import plotly.express as px\n",
-    "\n",
-    "%matplotlib inline\n",
-    "import warnings\n",
-    "warnings.filterwarnings('ignore')\n",
-    "\n",
-    "plt.rcParams['figure.figsize'] = (10,6)\n",
-    "plt.rcParams['figure.dpi'] = 300\n",
-    "sns.set_style('darkgrid')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "b9b6d9f0",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:49.458818Z",
-     "start_time": "2025-04-04T15:19:49.422127Z"
-    }
-   },
-   "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>date</th>\n",
-       "      <th>quarter</th>\n",
-       "      <th>department</th>\n",
-       "      <th>day</th>\n",
-       "      <th>team</th>\n",
-       "      <th>targeted_productivity</th>\n",
-       "      <th>smv</th>\n",
-       "      <th>wip</th>\n",
-       "      <th>over_time</th>\n",
-       "      <th>incentive</th>\n",
-       "      <th>idle_time</th>\n",
-       "      <th>idle_men</th>\n",
-       "      <th>no_of_style_change</th>\n",
-       "      <th>no_of_workers</th>\n",
-       "      <th>actual_productivity</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1/1/2015</td>\n",
-       "      <td>Quarter1</td>\n",
-       "      <td>sweing</td>\n",
-       "      <td>Thursday</td>\n",
-       "      <td>8</td>\n",
-       "      <td>0.80</td>\n",
-       "      <td>26.16</td>\n",
-       "      <td>1108.0</td>\n",
-       "      <td>7080</td>\n",
-       "      <td>98</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>59.0</td>\n",
-       "      <td>0.940725</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1/1/2015</td>\n",
-       "      <td>Quarter1</td>\n",
-       "      <td>finishing</td>\n",
-       "      <td>Thursday</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.75</td>\n",
-       "      <td>3.94</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>960</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
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-       "      <td>0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>0.886500</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1/1/2015</td>\n",
-       "      <td>Quarter1</td>\n",
-       "      <td>sweing</td>\n",
-       "      <td>Thursday</td>\n",
-       "      <td>11</td>\n",
-       "      <td>0.80</td>\n",
-       "      <td>11.41</td>\n",
-       "      <td>968.0</td>\n",
-       "      <td>3660</td>\n",
-       "      <td>50</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
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-       "      <td>30.5</td>\n",
-       "      <td>0.800570</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1/1/2015</td>\n",
-       "      <td>Quarter1</td>\n",
-       "      <td>sweing</td>\n",
-       "      <td>Thursday</td>\n",
-       "      <td>12</td>\n",
-       "      <td>0.80</td>\n",
-       "      <td>11.41</td>\n",
-       "      <td>968.0</td>\n",
-       "      <td>3660</td>\n",
-       "      <td>50</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>30.5</td>\n",
-       "      <td>0.800570</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1/1/2015</td>\n",
-       "      <td>Quarter1</td>\n",
-       "      <td>sweing</td>\n",
-       "      <td>Thursday</td>\n",
-       "      <td>6</td>\n",
-       "      <td>0.80</td>\n",
-       "      <td>25.90</td>\n",
-       "      <td>1170.0</td>\n",
-       "      <td>1920</td>\n",
-       "      <td>50</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>56.0</td>\n",
-       "      <td>0.800382</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",
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-       "      <td>...</td>\n",
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-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1192</th>\n",
-       "      <td>3/11/2015</td>\n",
-       "      <td>Quarter2</td>\n",
-       "      <td>finishing</td>\n",
-       "      <td>Wednesday</td>\n",
-       "      <td>10</td>\n",
-       "      <td>0.75</td>\n",
-       "      <td>2.90</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>960</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>8.0</td>\n",
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-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1193</th>\n",
-       "      <td>3/11/2015</td>\n",
-       "      <td>Quarter2</td>\n",
-       "      <td>finishing</td>\n",
-       "      <td>Wednesday</td>\n",
-       "      <td>8</td>\n",
-       "      <td>0.70</td>\n",
-       "      <td>3.90</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>960</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>0.625625</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1194</th>\n",
-       "      <td>3/11/2015</td>\n",
-       "      <td>Quarter2</td>\n",
-       "      <td>finishing</td>\n",
-       "      <td>Wednesday</td>\n",
-       "      <td>7</td>\n",
-       "      <td>0.65</td>\n",
-       "      <td>3.90</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>960</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>0.625625</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1195</th>\n",
-       "      <td>3/11/2015</td>\n",
-       "      <td>Quarter2</td>\n",
-       "      <td>finishing</td>\n",
-       "      <td>Wednesday</td>\n",
-       "      <td>9</td>\n",
-       "      <td>0.75</td>\n",
-       "      <td>2.90</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1800</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>0.505889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1196</th>\n",
-       "      <td>3/11/2015</td>\n",
-       "      <td>Quarter2</td>\n",
-       "      <td>finishing</td>\n",
-       "      <td>Wednesday</td>\n",
-       "      <td>6</td>\n",
-       "      <td>0.70</td>\n",
-       "      <td>2.90</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>720</td>\n",
-       "      <td>0</td>\n",
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-       "      <td>6.0</td>\n",
-       "      <td>0.394722</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1197 rows × 15 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "           date   quarter  department        day  team  targeted_productivity  \\\n",
-       "0      1/1/2015  Quarter1      sweing   Thursday     8                   0.80   \n",
-       "1      1/1/2015  Quarter1  finishing    Thursday     1                   0.75   \n",
-       "2      1/1/2015  Quarter1      sweing   Thursday    11                   0.80   \n",
-       "3      1/1/2015  Quarter1      sweing   Thursday    12                   0.80   \n",
-       "4      1/1/2015  Quarter1      sweing   Thursday     6                   0.80   \n",
-       "...         ...       ...         ...        ...   ...                    ...   \n",
-       "1192  3/11/2015  Quarter2   finishing  Wednesday    10                   0.75   \n",
-       "1193  3/11/2015  Quarter2   finishing  Wednesday     8                   0.70   \n",
-       "1194  3/11/2015  Quarter2   finishing  Wednesday     7                   0.65   \n",
-       "1195  3/11/2015  Quarter2   finishing  Wednesday     9                   0.75   \n",
-       "1196  3/11/2015  Quarter2   finishing  Wednesday     6                   0.70   \n",
-       "\n",
-       "        smv     wip  over_time  incentive  idle_time  idle_men  \\\n",
-       "0     26.16  1108.0       7080         98        0.0         0   \n",
-       "1      3.94     NaN        960          0        0.0         0   \n",
-       "2     11.41   968.0       3660         50        0.0         0   \n",
-       "3     11.41   968.0       3660         50        0.0         0   \n",
-       "4     25.90  1170.0       1920         50        0.0         0   \n",
-       "...     ...     ...        ...        ...        ...       ...   \n",
-       "1192   2.90     NaN        960          0        0.0         0   \n",
-       "1193   3.90     NaN        960          0        0.0         0   \n",
-       "1194   3.90     NaN        960          0        0.0         0   \n",
-       "1195   2.90     NaN       1800          0        0.0         0   \n",
-       "1196   2.90     NaN        720          0        0.0         0   \n",
-       "\n",
-       "      no_of_style_change  no_of_workers  actual_productivity  \n",
-       "0                      0           59.0             0.940725  \n",
-       "1                      0            8.0             0.886500  \n",
-       "2                      0           30.5             0.800570  \n",
-       "3                      0           30.5             0.800570  \n",
-       "4                      0           56.0             0.800382  \n",
-       "...                  ...            ...                  ...  \n",
-       "1192                   0            8.0             0.628333  \n",
-       "1193                   0            8.0             0.625625  \n",
-       "1194                   0            8.0             0.625625  \n",
-       "1195                   0           15.0             0.505889  \n",
-       "1196                   0            6.0             0.394722  \n",
-       "\n",
-       "[1197 rows x 15 columns]"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df = pd.read_csv(\"../../data/raw/garments_worker_productivity.csv\")\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "77004e00",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:49.478288Z",
-     "start_time": "2025-04-04T15:19:49.460142Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 1197 entries, 0 to 1196\n",
-      "Data columns (total 15 columns):\n",
-      " #   Column                 Non-Null Count  Dtype  \n",
-      "---  ------                 --------------  -----  \n",
-      " 0   date                   1197 non-null   object \n",
-      " 1   quarter                1197 non-null   object \n",
-      " 2   department             1197 non-null   object \n",
-      " 3   day                    1197 non-null   object \n",
-      " 4   team                   1197 non-null   int64  \n",
-      " 5   targeted_productivity  1197 non-null   float64\n",
-      " 6   smv                    1197 non-null   float64\n",
-      " 7   wip                    691 non-null    float64\n",
-      " 8   over_time              1197 non-null   int64  \n",
-      " 9   incentive              1197 non-null   int64  \n",
-      " 10  idle_time              1197 non-null   float64\n",
-      " 11  idle_men               1197 non-null   int64  \n",
-      " 12  no_of_style_change     1197 non-null   int64  \n",
-      " 13  no_of_workers          1197 non-null   float64\n",
-      " 14  actual_productivity    1197 non-null   float64\n",
-      "dtypes: float64(6), int64(5), object(4)\n",
-      "memory usage: 140.4+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "df.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "58af4933",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:49.522624Z",
-     "start_time": "2025-04-04T15:19:49.478288Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
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-       "    .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>team</th>\n",
-       "      <th>targeted_productivity</th>\n",
-       "      <th>smv</th>\n",
-       "      <th>wip</th>\n",
-       "      <th>over_time</th>\n",
-       "      <th>incentive</th>\n",
-       "      <th>idle_time</th>\n",
-       "      <th>idle_men</th>\n",
-       "      <th>no_of_style_change</th>\n",
-       "      <th>no_of_workers</th>\n",
-       "      <th>actual_productivity</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>691.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "      <td>1197.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>6.426901</td>\n",
-       "      <td>0.729632</td>\n",
-       "      <td>15.062172</td>\n",
-       "      <td>1190.465991</td>\n",
-       "      <td>4567.460317</td>\n",
-       "      <td>38.210526</td>\n",
-       "      <td>0.730159</td>\n",
-       "      <td>0.369256</td>\n",
-       "      <td>0.150376</td>\n",
-       "      <td>34.609858</td>\n",
-       "      <td>0.735091</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>3.463963</td>\n",
-       "      <td>0.097891</td>\n",
-       "      <td>10.943219</td>\n",
-       "      <td>1837.455001</td>\n",
-       "      <td>3348.823563</td>\n",
-       "      <td>160.182643</td>\n",
-       "      <td>12.709757</td>\n",
-       "      <td>3.268987</td>\n",
-       "      <td>0.427848</td>\n",
-       "      <td>22.197687</td>\n",
-       "      <td>0.174488</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.070000</td>\n",
-       "      <td>2.900000</td>\n",
-       "      <td>7.000000</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>2.000000</td>\n",
-       "      <td>0.233705</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>0.700000</td>\n",
-       "      <td>3.940000</td>\n",
-       "      <td>774.500000</td>\n",
-       "      <td>1440.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>0.650307</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>6.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>15.260000</td>\n",
-       "      <td>1039.000000</td>\n",
-       "      <td>3960.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>34.000000</td>\n",
-       "      <td>0.773333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>24.260000</td>\n",
-       "      <td>1252.500000</td>\n",
-       "      <td>6960.000000</td>\n",
-       "      <td>50.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>57.000000</td>\n",
-       "      <td>0.850253</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>12.000000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>54.560000</td>\n",
-       "      <td>23122.000000</td>\n",
-       "      <td>25920.000000</td>\n",
-       "      <td>3600.000000</td>\n",
-       "      <td>300.000000</td>\n",
-       "      <td>45.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>89.000000</td>\n",
-       "      <td>1.120437</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "              team  targeted_productivity          smv           wip  \\\n",
-       "count  1197.000000            1197.000000  1197.000000    691.000000   \n",
-       "mean      6.426901               0.729632    15.062172   1190.465991   \n",
-       "std       3.463963               0.097891    10.943219   1837.455001   \n",
-       "min       1.000000               0.070000     2.900000      7.000000   \n",
-       "25%       3.000000               0.700000     3.940000    774.500000   \n",
-       "50%       6.000000               0.750000    15.260000   1039.000000   \n",
-       "75%       9.000000               0.800000    24.260000   1252.500000   \n",
-       "max      12.000000               0.800000    54.560000  23122.000000   \n",
-       "\n",
-       "          over_time    incentive    idle_time     idle_men  \\\n",
-       "count   1197.000000  1197.000000  1197.000000  1197.000000   \n",
-       "mean    4567.460317    38.210526     0.730159     0.369256   \n",
-       "std     3348.823563   160.182643    12.709757     3.268987   \n",
-       "min        0.000000     0.000000     0.000000     0.000000   \n",
-       "25%     1440.000000     0.000000     0.000000     0.000000   \n",
-       "50%     3960.000000     0.000000     0.000000     0.000000   \n",
-       "75%     6960.000000    50.000000     0.000000     0.000000   \n",
-       "max    25920.000000  3600.000000   300.000000    45.000000   \n",
-       "\n",
-       "       no_of_style_change  no_of_workers  actual_productivity  \n",
-       "count         1197.000000    1197.000000          1197.000000  \n",
-       "mean             0.150376      34.609858             0.735091  \n",
-       "std              0.427848      22.197687             0.174488  \n",
-       "min              0.000000       2.000000             0.233705  \n",
-       "25%              0.000000       9.000000             0.650307  \n",
-       "50%              0.000000      34.000000             0.773333  \n",
-       "75%              0.000000      57.000000             0.850253  \n",
-       "max              2.000000      89.000000             1.120437  "
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.describe()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "72707a27",
-   "metadata": {},
-   "source": [
-    "# Exploratory Data Analysis & Pre-Processing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "75c8358b",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:50.159983Z",
-     "start_time": "2025-04-04T15:19:49.522624Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([16436., 16450., 16467., 16481., 16495.]),\n",
-       " [Text(16436.0, 0, '2015-01-01'),\n",
-       "  Text(16450.0, 0, '2015-01-15'),\n",
-       "  Text(16467.0, 0, '2015-02-01'),\n",
-       "  Text(16481.0, 0, '2015-02-15'),\n",
-       "  Text(16495.0, 0, '2015-03-01')])"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<Figure size 3600x1500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Type Conversion of 'Date' column\n",
-    "df['date'] = pd.to_datetime(df['date'], format='%m/%d/%Y')\n",
-    "\n",
-    "# Time Series Plot of 'Productivity'\n",
-    "plt.figure(figsize=(12,5))\n",
-    "df.groupby('date')['actual_productivity'].mean().plot(marker='o', color='purple')\n",
-    "plt.title('Productivity Trend Over Time')\n",
-    "plt.xlabel('Date')\n",
-    "plt.ylabel('Average Productivity')\n",
-    "plt.xticks(rotation=45)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "70ac0333",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:50.721847Z",
-     "start_time": "2025-04-04T15:19:50.159983Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'Productivity by Day of the Week (Circular View)')"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1800x1800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for 'Productivity' on different 'Days' of the week\n",
-    "day_order = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Saturday']\n",
-    "df_day_avg = df.groupby('day')['actual_productivity'].mean().reindex(day_order)\n",
-    "\n",
-    "angles = np.linspace(0, 2 * np.pi, len(df_day_avg), endpoint=False)\n",
-    "fig, ax = plt.subplots(figsize=(6,6), subplot_kw={'projection': 'polar'})\n",
-    "\n",
-    "ax.bar(angles, df_day_avg, align='center', alpha=0.7, color='teal')\n",
-    "ax.set_xticks(angles)\n",
-    "ax.set_xticklabels(day_order)\n",
-    "ax.set_title('Productivity by Day of the Week (Circular View)')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "c8a8ac14",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:50.730466Z",
-     "start_time": "2025-04-04T15:19:50.721847Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['Quarter1' 'Quarter2' 'Quarter3' 'Quarter4' 'Quarter5']\n",
-      "['sweing' 'finishing ' 'finishing']\n",
-      "['Thursday' 'Saturday' 'Sunday' 'Monday' 'Tuesday' 'Wednesday']\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(df['quarter'].unique())\n",
-    "print(df['department'].unique())\n",
-    "print(df['day'].unique())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "db515443",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:51.519325Z",
-     "start_time": "2025-04-04T15:19:50.733242Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
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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+\"&nbsp;\"+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=\"&#215;\",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. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Dt.workerCount},set workerCount(t){Dt.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return Zi})),r}))},{}],240:[function(t,e,r){\"use strict\";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],241:[function(t,e,r){\"use strict\";e.exports=function(t,e){e||(e=t,t=window);var r=0,i=0,a=0,o={shift:!1,alt:!1,control:!1,meta:!1},s=!1;function l(t){var e=!1;return\"altKey\"in t&&(e=e||t.altKey!==o.alt,o.alt=!!t.altKey),\"shiftKey\"in t&&(e=e||t.shiftKey!==o.shift,o.shift=!!t.shiftKey),\"ctrlKey\"in t&&(e=e||t.ctrlKey!==o.control,o.control=!!t.ctrlKey),\"metaKey\"in t&&(e=e||t.metaKey!==o.meta,o.meta=!!t.metaKey),e}function c(t,s){var c=n.x(s),u=n.y(s);\"buttons\"in s&&(t=0|s.buttons),(t!==r||c!==i||u!==a||l(s))&&(r=0|t,i=c||0,a=u||0,e&&e(r,i,a,o))}function u(t){c(0,t)}function f(){(r||i||a||o.shift||o.alt||o.meta||o.control)&&(i=a=0,r=0,o.shift=o.alt=o.control=o.meta=!1,e&&e(0,0,0,o))}function h(t){l(t)&&e&&e(r,i,a,o)}function p(t){0===n.buttons(t)?c(0,t):c(r,t)}function d(t){c(r|n.buttons(t),t)}function m(t){c(r&~n.buttons(t),t)}function g(){s||(s=!0,t.addEventListener(\"mousemove\",p),t.addEventListener(\"mousedown\",d),t.addEventListener(\"mouseup\",m),t.addEventListener(\"mouseleave\",u),t.addEventListener(\"mouseenter\",u),t.addEventListener(\"mouseout\",u),t.addEventListener(\"mouseover\",u),t.addEventListener(\"blur\",f),t.addEventListener(\"keyup\",h),t.addEventListener(\"keydown\",h),t.addEventListener(\"keypress\",h),t!==window&&(window.addEventListener(\"blur\",f),window.addEventListener(\"keyup\",h),window.addEventListener(\"keydown\",h),window.addEventListener(\"keypress\",h)))}g();var v={element:t};return Object.defineProperties(v,{enabled:{get:function(){return s},set:function(e){e?g():function(){if(!s)return;s=!1,t.removeEventListener(\"mousemove\",p),t.removeEventListener(\"mousedown\",d),t.removeEventListener(\"mouseup\",m),t.removeEventListener(\"mouseleave\",u),t.removeEventListener(\"mouseenter\",u),t.removeEventListener(\"mouseout\",u),t.removeEventListener(\"mouseover\",u),t.removeEventListener(\"blur\",f),t.removeEventListener(\"keyup\",h),t.removeEventListener(\"keydown\",h),t.removeEventListener(\"keypress\",h),t!==window&&(window.removeEventListener(\"blur\",f),window.removeEventListener(\"keyup\",h),window.removeEventListener(\"keydown\",h),window.removeEventListener(\"keypress\",h))}()},enumerable:!0},buttons:{get:function(){return r},enumerable:!0},x:{get:function(){return i},enumerable:!0},y:{get:function(){return a},enumerable:!0},mods:{get:function(){return o},enumerable:!0}}),v};var n=t(\"mouse-event\")},{\"mouse-event\":243}],242:[function(t,e,r){var n={left:0,top:0};e.exports=function(t,e,r){e=e||t.currentTarget||t.srcElement,Array.isArray(r)||(r=[0,0]);var i=t.clientX||0,a=t.clientY||0,o=(s=e,s===window||s===document||s===document.body?n:s.getBoundingClientRect());var s;return r[0]=i-o.left,r[1]=a-o.top,r}},{}],243:[function(t,e,r){\"use strict\";function n(t){return t.target||t.srcElement||window}r.buttons=function(t){if(\"object\"==typeof t){if(\"buttons\"in t)return t.buttons;if(\"which\"in t){if(2===(e=t.which))return 4;if(3===e)return 2;if(e>0)return 1<<e-1}else if(\"button\"in t){var e;if(1===(e=t.button))return 4;if(2===e)return 2;if(e>=0)return 1<<e}}return 0},r.element=n,r.x=function(t){if(\"object\"==typeof t){if(\"offsetX\"in t)return t.offsetX;var e=n(t).getBoundingClientRect();return t.clientX-e.left}return 0},r.y=function(t){if(\"object\"==typeof t){if(\"offsetY\"in t)return t.offsetY;var e=n(t).getBoundingClientRect();return t.clientY-e.top}return 0}},{}],244:[function(t,e,r){\"use strict\";var n=t(\"to-px\");e.exports=function(t,e,r){\"function\"==typeof t&&(r=!!e,e=t,t=window);var i=n(\"ex\",t),a=function(t){r&&t.preventDefault();var n=t.deltaX||0,a=t.deltaY||0,o=t.deltaZ||0,s=1;switch(t.deltaMode){case 1:s=i;break;case 2:s=window.innerHeight}if(a*=s,o*=s,(n*=s)||a||o)return e(n,a,o,t)};return t.addEventListener(\"wheel\",a),a}},{\"to-px\":314}],245:[function(t,e,r){(function(t,r){(function(){\n",
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-       "/*\n",
-       " * @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 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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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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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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 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);\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n    return (\\n        vOutside(p[0], lo[0], hi[0]) ||\\n        vOutside(p[1], lo[1], hi[1]) ||\\n        vOutside(p[2], lo[2], hi[2]) ||\\n        vOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    return mOutside(A, loA, hiA) ||\\n           mOutside(B, loB, hiB) ||\\n           mOutside(C, loC, hiC) ||\\n           mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    mat4 pnts[4];\\n    pnts[0] = A;\\n    pnts[1] = B;\\n    pnts[2] = C;\\n    pnts[3] = D;\\n\\n    for(int i = 0; i < 4; ++i) {\\n        for(int j = 0; j < 4; ++j) {\\n            for(int k = 0; k < 4; ++k) {\\n                if(0 == iMod(\\n                    int(255.0 * texture2D(maskTexture,\\n                        vec2(\\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 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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, 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:\"vec3\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},{glslify:231}],82:[function(t,e,r){e.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORM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t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var m=this,g=[0|e,0|r];Object.defineProperties(g,{0:{get:function(){return m._shape[0]},set:function(t){return m.width=t}},1:{get:function(){return m._shape[1]},set:function(t){return m.height=t}}}),this._shapeVector=g,function(t){var e=c(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,m=t._useDepth,g=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var v=0;v<o;++v)t.color[v]=h(r,i,a,g,r.RGBA,r.COLOR_ATTACHMENT0+v);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var 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 i=[],a=[],o=[],s=0,u=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],m=t.lineWidth||1,g=!1;t:for(e=1;e<h.length;++e){var v,y,x,b=h[e-1],_=h[e];for(a.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);u+=2,g=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(v=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],y=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):v=y=p,3===v.length&&(v=[v[0],v[1],v[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0),x=Array.isArray(m)?m.length>e-1?m[e-1]:m.length>0?m[m.length-1]:[0,0,0,1]:m;var T=s;if(s+=d(b,_),g){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3]);u+=2,g=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,v[0],v[1],v[2],v[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,y[0],y[1],y[2],y[3]),u+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=u,this.points=o,this.arcLength=a,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var A=c(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)A.set(e,0,r,0);1&l.le(k,k[k.length-1]*e/255)?A.set(e,0,0,0):A.set(e,0,0,255)}this.texture.setPixels(A)}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=function(t,e,r,n){return o[0]=n,o[1]=r,o[2]=e,o[3]=t,s[0]}(t.value[0],t.value[1],t.value[2],0),r=l.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new g(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],a=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),c=1-a,u=[0,0,0],f=0;f<3;++f)u[f]=c*n[f]+a*i[f];var h=Math.min(a<.5?r:r+1,this.points.length-1);return new g(e,u,h,this.points[h])}},{\"./lib/shaders\":90,\"binary-search-bounds\":31,\"gl-buffer\":78,\"gl-texture2d\":146,\"gl-vao\":150,ndarray:259}],92:[function(t,e,r){e.exports=function(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}},{}],93:[function(t,e,r){e.exports=function(){var t=new Float32Array(16);return 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t[0]=1-(p+m),t[1]=f+y,t[2]=h-v,t[3]=0,t[4]=f-y,t[5]=1-(u+m),t[6]=d+g,t[7]=0,t[8]=h+v,t[9]=d-g,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],97:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],98:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],m=e[13],g=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*c-a*o,_=n*l-i*s,w=n*c-a*s,T=i*c-a*l,k=u*m-f*d,A=u*g-h*d,M=u*v-p*d,S=f*g-h*m,E=f*v-p*m,L=h*v-p*g,C=y*L-x*E+b*S+_*M-w*A+T*k;if(!C)return null;return C=1/C,t[0]=(s*L-l*E+c*S)*C,t[1]=(i*E-n*L-a*S)*C,t[2]=(m*T-g*w+v*_)*C,t[3]=(h*w-f*T-p*_)*C,t[4]=(l*M-o*L-c*A)*C,t[5]=(r*L-i*M+a*A)*C,t[6]=(g*b-d*T-v*x)*C,t[7]=(u*T-h*b+p*x)*C,t[8]=(o*E-s*M+c*k)*C,t[9]=(n*M-r*E-a*k)*C,t[10]=(d*w-m*b+v*y)*C,t[11]=(f*b-u*w-p*y)*C,t[12]=(s*A-o*S-l*k)*C,t[13]=(r*S-n*A+i*k)*C,t[14]=(m*x-d*_-g*y)*C,t[15]=(u*_-f*x+h*y)*C,t}},{}],99:[function(t,e,r){var n=t(\"./identity\");e.exports=function(t,e,r,i){var a,o,s,l,c,u,f,h,p,d,m=e[0],g=e[1],v=e[2],y=i[0],x=i[1],b=i[2],_=r[0],w=r[1],T=r[2];if(Math.abs(m-_)<1e-6&&Math.abs(g-w)<1e-6&&Math.abs(v-T)<1e-6)return n(t);f=m-_,h=g-w,p=v-T,d=1/Math.sqrt(f*f+h*h+p*p),a=x*(p*=d)-b*(h*=d),o=b*(f*=d)-y*p,s=y*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0);l=h*s-p*o,c=p*a-f*s,u=f*o-h*a,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return 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 n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i-c*n,t[1]=o*i-u*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+c*i,t[9]=o*n+u*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},{}],106:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],f=e[6],h=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i+c*n,t[1]=o*i+u*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=c*i-a*n,t[5]=u*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},{}],107:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],108:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o,s,l,c,u,f,h,p,d,m=r[0],g=r[1],v=r[2];e===t?(t[12]=e[0]*m+e[4]*g+e[8]*v+e[12],t[13]=e[1]*m+e[5]*g+e[9]*v+e[13],t[14]=e[2]*m+e[6]*g+e[10]*v+e[14],t[15]=e[3]*m+e[7]*g+e[11]*v+e[15]):(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],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*m+s*g+f*v+e[12],t[13]=i*m+l*g+h*v+e[13],t[14]=a*m+c*g+p*v+e[14],t[15]=o*m+u*g+d*v+e[15]);return t}},{}],109:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],110:[function(t,e,r){\"use strict\";var n=t(\"barycentric\"),i=t(\"polytope-closest-point/lib/closest_point_2d.js\");function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}e.exports=function(t,e,r,a,l,c){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),f=0;f<t.length;++f)u[f]=o(t[f],r,a,l,c);var h=0,p=1/0;for(f=0;f<u.length;++f){for(var d=0,m=0;m<2;++m)d+=Math.pow(u[f][m]-e[m],2);d<p&&(p=d,h=f)}var g=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),a=Math.sqrt(a),r+a<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(u,e),v=0;for(f=0;f<3;++f){if(g[f]<-.001||g[f]>1.0001)return null;v+=g[f]}if(Math.abs(v-1)>.001)return 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 t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{r=+t.projectOpacity;this.projectOpacity=[r,r,r]}for(var n=0;n<3;++n)this.projectOpacity[n]=m(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=m(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",c=t.alignment||[0,0];if(2===c.length)i=c[0],a=c[1];else{i=[],a=[];for(n=0;n<c.length;++n)i[n]=c[n][0],a[n]=c[n][1]}var u=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,g=t.angle,v=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=I(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;x+=3*k.cells.length,b+=2*A.edges.length}}var S=x+b,E=o.mallocFloat(3*S),L=o.mallocFloat(4*S),C=o.mallocFloat(2*S),P=o.mallocUint32(S);if(S>0){var O=0,z=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(v)&&Array.isArray(v[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T])}k=(N=I(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)D[T]=U[T];D[3]=1}else if(4===U.length){for(T=0;T<4;++T)D[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else D[0]=D[1]=D[2]=0,D[3]=1;else D=[1,1,1,0];if(j)if(Array.isArray(v)){var U;if(3===(U=B?n<v.length?v[n]:[0,0,0,0]:v).length){for(T=0;T<3;++T)R[T]=U[T];R[T]=1}else if(4===U.length){for(T=0;T<4;++T)R[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var V=.5;j?Array.isArray(d)?V=n<d.length?+d[n]:12:d?V=+d:this.useOrtho&&(V=12):V=0;var H=0;Array.isArray(g)?H=n<g.length?+g[n]:0:g&&(H=+g);var q=Math.cos(H),G=Math.sin(H);for(w=s[n],T=0;T<3;++T)f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T]);var Y=i,W=a;Y=0;Array.isArray(i)?Y=n<i.length?i[n]:0:i&&(Y=i);W=0;Array.isArray(a)?W=n<a.length?a[n]:0:a&&(W=a);var X=[Y*=Y>0?1-M[0][0]:Y<0?1+M[1][0]:1,W*=W>0?1-M[0][1]:W<0?1+M[1][1]:1],Z=k.cells||[],J=k.positions||[];for(T=0;T<Z.length;++T)for(var K=Z[T],Q=0;Q<3;++Q){for(var $=0;$<3;++$)E[3*O+$]=w[$];for($=0;$<4;++$)L[4*O+$]=D[$];P[O]=y;var tt=J[K[Q]];C[2*O]=V*(q*tt[0]-G*tt[1]+X[0]),C[2*O+1]=V*(G*tt[0]+q*tt[1]+X[1]),O+=1}for(Z=A.edges,J=A.positions,T=0;T<Z.length;++T)for(K=Z[T],Q=0;Q<2;++Q){for($=0;$<3;++$)E[3*z+$]=w[$];for($=0;$<4;++$)L[4*z+$]=R[$];P[z]=y;tt=J[K[Q]];C[2*z]=V*(q*tt[0]-G*tt[1]+X[0]),C[2*z+1]=V*(G*tt[0]+q*tt[1]+X[1]),z+=1}}}this.bounds=[u,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(C),this.idBuffer.update(P),o.free(E),o.free(L),o.free(C),o.free(P)},v.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/get-simple-string\":125,\"./lib/glyphs\":126,\"./lib/shaders\":127,\"gl-buffer\":78,\"gl-mat4/multiply\":100,\"gl-vao\":150,\"is-string-blank\":239,\"typedarray-pool\":308}],129:[function(t,e,r){\"use strict\";var n=t(\"glslify\");r.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),r.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"])},{glslify:231}],130:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"./lib/shaders\");function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}e.exports=function(t,e){var r=t.gl,s=i(r,[0,0,0,1,1,0,1,1]),l=n(r,a.boxVertex,a.boxFragment),c=new o(t,s,l);return c.update(e),t.addOverlay(c),c};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,c=t.viewBox,u=t.pixelRatio,f=(e[0]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],h=(e[1]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1],p=(e[2]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],d=(e[3]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1];if(f=Math.max(f,c[0]),h=Math.max(h,c[1]),p=Math.min(p,c[2]),d=Math.min(d,c[3]),!(p<f||d<h)){o.bind();var m=s[2]-s[0],g=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,m,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,m,g,i),o.drawBox(p,h,m,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var v=r*u;o.drawBox(f-v,h-v,p+v,h+v,a),o.drawBox(f-v,d-v,p+v,d+v,a),o.drawBox(f-v,h-v,f+v,d+v,a),o.drawBox(p-v,h-v,p+v,d+v,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":129,\"gl-buffer\":78,\"gl-shader\":132}],131:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=e[0],a=e[1],o=n(t,r,a,{}),s=i.mallocUint8(r*a*4);return new l(t,o,s)};var n=t(\"gl-fbo\"),i=t(\"typedarray-pool\"),a=t(\"ndarray\"),o=t(\"bit-twiddle\").nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function l(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}var c=l.prototype;Object.defineProperty(c,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){i.free(this.buffer);for(var n=this.buffer=i.mallocUint8(o(r*e*4)),a=0;a<r*e*4;++a)n[a]=255}return t}}}),c.begin=function(){var t=this.gl;this.shape;t&&(this.fbo.bind(),t.clearColor(1,1,1,1),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT))},c.end=function(){var t=this.gl;t&&(t.bindFramebuffer(t.FRAMEBUFFER,null),this._readTimeout||clearTimeout(this._readTimeout),this._readTimeout=setTimeout(this._readCallback,1))},c.query=function(t,e,r){if(!this.gl)return null;var n=this.fbo.shape.slice();t|=0,e|=0,\"number\"!=typeof r&&(r=1);var 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 n=t(\"./lib/create-uniforms\"),i=t(\"./lib/create-attributes\"),a=t(\"./lib/reflect\"),o=t(\"./lib/shader-cache\"),s=t(\"./lib/runtime-reflect\"),l=t(\"./lib/GLError\");function c(t){this.gl=t,this.gl.lastAttribCount=0,this._vref=this._fref=this._relink=this.vertShader=this.fragShader=this.program=this.attributes=this.uniforms=this.types=null}var u=c.prototype;function f(t,e){return t.name<e.name?-1:1}u.bind=function(){var t;this.program||this._relink();var e=this.gl.getProgramParameter(this.program,this.gl.ACTIVE_ATTRIBUTES),r=this.gl.lastAttribCount;if(e>r)for(t=r;t<e;t++)this.gl.enableVertexAttribArray(t);else if(r>e)for(t=e;t<r;t++)this.gl.disableVertexAttribArray(t);this.gl.lastAttribCount=e,this.gl.useProgram(this.program)},u.dispose=function(){for(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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h=c,p=u,d=0;d<3;++d)i&&i[d]<0?(h[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(h[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,h,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":140,\"gl-buffer\":78,\"gl-vao\":150}],142:[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 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 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 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-       "/*!\n",
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-       " * @license  MIT\n",
-       " */\n",
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l=0;l<3;++l){for(var c=0,f=0;f<3;++f)c+=r[l+4*f]*i[f];r[12+l]=-c}},h.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},h.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},h.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},h.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=i[1],o=i[5],s=i[9],c=l(a,o,s);a/=c,o/=c,s/=c;var u=i[0],f=i[4],h=i[8],p=u*a+f*o+h*s,d=l(u-=a*p,f-=o*p,h-=s*p);u/=d,f/=d,h/=d;var m=i[2],g=i[6],v=i[10],y=m*a+g*o+v*s,x=m*u+g*f+v*h,b=l(m-=y*a+x*u,g-=y*o+x*f,v-=y*s+x*h);m/=b,g/=b,v/=b;var _=u*e+a*r,w=f*e+o*r,T=h*e+s*r;this.center.move(t,_,w,T);var k=Math.exp(this.computedRadius[0]);k=Math.max(1e-4,k+n),this.radius.set(t,Math.log(k))},h.rotate=function(t,e,r,n){this.recalcMatrix(t),e=e||0,r=r||0;var i=this.computedMatrix,a=i[0],o=i[4],s=i[8],u=i[1],f=i[5],h=i[9],p=i[2],d=i[6],m=i[10],g=e*a+r*u,v=e*o+r*f,y=e*s+r*h,x=-(d*y-m*v),b=-(m*g-p*y),_=-(p*v-d*g),w=Math.sqrt(Math.max(0,1-Math.pow(x,2)-Math.pow(b,2)-Math.pow(_,2))),T=c(x,b,_,w);T>1e-6?(x/=T,b/=T,_/=T,w/=T):(x=b=_=0,w=1);var k=this.computedRotation,A=k[0],M=k[1],S=k[2],E=k[3],L=A*w+E*x+M*_-S*b,C=M*w+E*b+S*x-A*_,P=S*w+E*_+A*b-M*x,I=E*w-A*x-M*b-S*_;if(n){x=p,b=d,_=m;var O=Math.sin(n)/l(x,b,_);x*=O,b*=O,_*=O,I=I*(w=Math.cos(e))-(L=L*w+I*x+C*_-P*b)*x-(C=C*w+I*b+P*x-L*_)*b-(P=P*w+I*_+L*b-C*x)*_}var z=c(L,C,P,I);z>1e-6?(L/=z,C/=z,P/=z,I/=z):(L=C=P=0,I=1),this.rotation.set(t,L,C,P,I)},h.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var a=this.computedMatrix;i(a,e,r,n);var o=this.computedRotation;s(o,a[0],a[1],a[2],a[4],a[5],a[6],a[8],a[9],a[10]),u(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var l=0,c=0;c<3;++c)l+=Math.pow(r[c]-e[c],2);this.radius.set(t,.5*Math.log(Math.max(l,1e-6))),this.center.set(t,r[0],r[1],r[2])},h.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},h.setMatrix=function(t,e){var r=this.computedRotation;s(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),u(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;o(n,e);var i=n[15];if(Math.abs(i)>1e-6){var a=n[12]/i,l=n[13]/i,c=n[14]/i;this.recalcMatrix(t);var f=Math.exp(this.computedRadius[0]);this.center.set(t,a-n[2]*f,l-n[6]*f,c-n[10]*f),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},h.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},h.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},h.getDistanceLimits=function(t){var e=this.radius.bounds;return 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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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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": [
-    "# Remove extra spaces\n",
-    "df['department'] = df['department'].str.strip()\n",
-    "\n",
-    "# Plot for 'Productivity' based on 'Departments' & 'Teams'\n",
-    "fig = px.sunburst(df, path=['department', 'team'], values='actual_productivity',\n",
-    "                  title=\"Productivity Breakdown by Department & Team\",\n",
-    "                  color='actual_productivity', color_continuous_scale='RdBu')\n",
-    "fig.show()"
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-  },
-  {
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-   "execution_count": 9,
-   "id": "f30a4473",
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-    "ExecuteTime": {
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-   "outputs": [
-    {
-     "data": {
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-       "Text(0, 0.5, 'Actual Productivity')"
-      ]
-     },
-     "execution_count": 9,
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fXH311ZUGBiJWTvD961//ir333jueeuqpNTpvQ1q4cGFKX/v27TMe/+abb8YZZ5yREhiIWHnF6o033ph2om/evHnx29/+No488sh4/vnnKwwMRKx8HL3//vvxpz/9KQ4++OAabZ/w8MMPx3777RejRo1KGxiIWHk150svvRSHHXZYjBw5strnaEhvvvlmDB48OM4///xKAwMRKycl77nnnjjggAPi4YcfrqcKk+22224pqzrU9PfoySefTGr//Oc/r/GkZnX16NEjZUWb5557LoqKiqp9W+W/j+7du8cOO+ywRvVV5rPPPosDDzww7rzzzgonJIuKiuLll1+OX/7yl3HmmWemfb5Y5ZBDDkn5Xa9sIrYiZWVlKY+FdLfdGK2//vqx5ZZbJvV9++23VU6Qr9JQ7wluvfXWOO644yoMDERELFmyJEaPHh2DBw+OBx98sFq3v2jRojjnnHPi4IMPjlGjRmX08ygrK4tPPvkkzj///Bg2bFjGP8PypkyZEieffHLan+esWbPi//7v/6K4uLhGt12ZsrKyuP322+OII46I1157LW1gIGLl79iTTz4ZhxxySHz++eeJ/kmTJsVBBx0Ut9xyS4W/nxERH3/8cZx00klx++23V6u+WbNmxcknnxwnnHBCvPrqqxUGBiJW3vfPPvtsDB8+PEaMGFHp63VVvvvuuzj88MPj4osvrvQxvnTp0njmmWfioIMOijvvvLPG5wMAWBcIDQAAwP9v5syZ8cYbbyT1DRs2LOW4rbbaKnr37p3U99BDD1U42bzKrrvumjJ5NWbMmGrXWX7Cp3Xr1ilXja5SWloal156afztb3+r9MPgdL777rv49a9/XePJvmeffbbKMEX5q32//vrrOPTQQ+P111+v0TkjVl5h9utf/zqjD+fnz58fRx11VDz//PMZ3/6yZcvioosuiv/85z81qu/OO++M008/PX744YdqjZs/f3786U9/ihtvvLFG521on3zySUpfpsteL168OP785z9XuDJBRPKKIKt88cUXMXTo0HjxxRczL/T/N3ny5DjmmGOq9di47rrr4vzzz894oqOoqCiuvPLKuOOOO6pdX0O4//7744QTTki6ojMTS5cujfPPPz9uu+22OqqsYrm5uXHwwQcn9b322mvVfj6cPn16fPDBB0l9VYW1alv516MFCxbEq6++Wu3bqc+J8i+++CJOPPHEaj1mnn322TjhhBMqvI/SBSjGjh1b7QnZ999/P6munJycOOSQQ6p1Gw1p1113TemrbDI+omHfE9x+++1x3XXXVfleaZXly5fHBRdcENddd11Gx8+dOzcOP/zwGgVIVvniiy/iV7/6VSxevLha44qLi+NPf/pTLF26tMJj9thjj7Qr7qypq666Kq655pqMA0Tz5s2L3/zmN7Fo0aL47LPP4thjj40ZM2ZkNLasrCyuueaaGD9+fEbHT548OQ4//PB47bXXMjp+ldLS0njsscfi+OOPj7lz51ZrbMTKLZ+OOeaYagX/ioqK4oorrljjUCgAwNrM9gQAAPD/e/zxx5Ou0MrLy4uhQ4emPXb48OFJS05/88038cYbb1S6bGtubm4ccsgh8e9//zvR99JLL8VPP/1Urb2cy0/4DBkyJJo3b5722CuvvDJp3+NVfvazn8U+++wTffr0idatW8eCBQvif//7X4wdOzbpQ9bi4uI4//zzo02bNrHffvtlXOOKFSuqXC69d+/esemmmybay5cvj9/97ncpqwS0b98+DjzwwOjfv3907do1WrRoEUuWLImZM2fGBx98EM8880zK5Mdnn30WDzzwQBx33HEVnr+kpCR++9vfplzp36RJk9hnn31in332iZ49e0ZRUVFMnTo1nn322aQww2WXXVbtrSXuvffeuOKKK1L6+/btG/vvv39sueWW0a5du1i4cGF89dVX8dxzzyUtdR6xcvnyVq1axYknnlitczekwsLCePbZZ1P6q1qGfJWbb745Zs+eXekxQ4YMSWrPnDkzTjnllJSVCXJzc2PvvfeOvfbaK7p37x5NmzaNH374If773//G2LFjk1YHWLZsWZx55plxxx13VLkk88MPPxy33nprSn/v3r3j0EMPjS222CJatmwZP/zwQ7z88svxzDPPJMIFV199daW33RiMGzcu7VL4HTt2jAMOOCB23HHHWG+99aK0tDQmT54cjz/+eEycODHp2GuvvTY233zz2GOPPSIiokOHDknPK+VXHtlyyy2T9tHebLPNalT78OHDk4IZRUVFMW7cuDjqqKMyvo3yYa02bdpUGNaqTMuWLZO+51dffTUpZLLpppsmfZ+rb3szePDguOSSS5ImJseMGVPpdgflffDBB/Htt98m2nU9UV5+25xtttkmDjnkkOjdu3fk5+fHtGnTYty4cfHSSy8lHffZZ5/F6aefHvfee2/aQMOwYcPi3XffTbTnzZsX//3vfxOPrUyUv0+333776NGjR8bjG1q6rX0mTZqUEpJZXUO9J5g4cWJSiDA3Nzf222+/2HfffaNbt26xZMmS+Pjjj+Phhx+O6dOnJ4299dZbo3v37nHYYYdVePtlZWXxhz/8IaZOnZrU37JlyxgyZEj87Gc/ix49ekSrVq1i2bJlMXv27Pjoo49izJgxKa8tM2fOjJtuuinOPffcjL+/0aNHx//+979KjxkyZEj8+OOPid/f7777Lj799NOkY8r/TFd//kvnhRdeSFoZoXPnznHkkUdG3759o0uXLjF37tx45ZVXYvTo0UmhgtmzZ8fVV1+deA8aEVFQUBCHHnpo7LTTTrHeeuvFwoUL44MPPohRo0bFvHnzks571VVXxaBBgyoNG3333Xdx3HHHpawa0rZt2xg6dGjssMMOsf7660dJSUnMnDkzXnvttXj22WeTnt8+/vjjOOWUU+LBBx+s1vuts846K2bOnJlo77DDDrHvvvvG5ptvHi1atIgffvghXn/99XjyySdTgh5XX3117LffftGxY8ek/k033TRx/8ybNy/p+SciYvfdd08Khaz+/hYAYG2RU5ZpxBcAANZhZWVlse+++yZNpgwcODDtJGDEyivadt9996QrG/fdd98qrwL/6quvUiY3L7nkkko/DF/d+++/H0cffXRS3+jRo2PbbbdNOXbChAlx2mmnJfV17tw5rrzyyth5550rPMeTTz4ZF1xwQdJEVuvWrePxxx+vcEKl/D67BQUFSVfqbbXVVrHttttGSUlJTJkyJd57770444wz4re//W3imNtvvz2uueaapNvdfffd49prr600VLF48eL429/+FmPHjk3q79u3bzz++OMVjvv3v/+dMlnbtWvXuP7662ObbbZJO+a1116LP/7xjxVeoVnZvuCffvppHHnkkUkf3BcUFMTFF18cBxxwQIV1vvrqq/GXv/wl6UP7/Pz8uP/++yusc02U35M9YuXVgmvi2muvTbnKvFevXhVeEbr6vs75+fnRpEmTxJLGHTt2jF133TU6duwY3333Xbz55pvRvn37pBUBSktL49BDD01agjkiYvPNN48rr7wyZd/oVebNmxcXX3xxjBs3Lqm/ffv28fjjj1e4FP2sWbNi8ODBSZMPOTk5cdZZZ8XJJ58cubm5KWOmT58eZ599doVL/Jffy3p15e+jYcOGVRnSWd2MGTNSJpore+z++OOPMXjw4JSrbw8//PD4y1/+EgUFBWnH3X///XHJJZckhbG6dOkS48ePTzsBVNV+3umU38u6on2kjzjiiKRtXQYMGFCtK0r322+/pMm5I444Im2Iorr3Tab1r/KXv/wlnnjiiUS7efPm8d///rfC+6C8Cy64IGnJ95/97Gdx3333ZTQ2ExX9buXn58cFF1xQ4Wvdm2++GX/4wx9SnlsvuOCClNe8iJXLmO+6665Jv3MHHXRQxgGcwsLC2GWXXZJCQpdeemnKNkJroi6eS1f3+eefp6w+sd9++8UNN9yQ9viGfE+wum7dusX1118fW2+9dcr/rVixIq666qq49957k/pbtmwZ48aNi/XXXz/tbY4dOzbOOuuspL5+/frFrbfeGuutt16F31thYWFcddVVcc899yT1d+jQIV5//fW0z90Rqb+3q7/nadWqVey5556x/vrrxw8//BDvvPNOLFmyJN56661o1qxZYky6n1FVj4/Kfq5HHXVU/PWvf0373Prmm2/GiSeeWOHWBbvssktcffXVSSGlVWbNmhUnnnhifPnll0n99957b4XbmhQVFcWxxx6bspXWYYcdFueee26Fz1ezZs2K8847L2VlguOOOy7OP//8tGMiUu+PVTp37hyXX3552lU5Ila+Dp966qkp39sf/vCHlN+V1b399ttx/PHHJ/W9+OKL0b179wrHAACsDWxPAAAAEfHOO+8kBQYiKl96umPHjrH77rsn9U2YMKHKq6E33XTT6N+/f1JfdfbXLn9l5CabbJI2MFBYWBgXXHBBUl+XLl3ikUceqXRyICLi4IMPjjvvvDNp9YKffvoprr/++ozrXPXhefPmzeOmm26KRx55JM4///y44IIL4r777otx48bFL37xi8TxpaWlKRNX3bt3j//7v/+rchWGgoKCuOqqq1KuQv78889Tro5b/fspvy9v586d47777qt0In633XaL++67L9q2bVtpTelccMEFSYGBVq1axf33319pYCBiZXDi/vvvT7rqraioKC677LJq11DfCgsL45prrkm7LP2pp56a0W0UFRUlAgO/+MUvYvz48XHllVfGX/7yl7jhhhvilVdeSQmbPPPMMymBga233jruu+++Cic1I1ZOFF133XVxxBFHJPXPnz+/0iWyb7vttpSrFc8999z4zW9+U+GkU48ePeKuu+6Kfv36VXi7jcUtt9ySEhg48cQT4x//+Eelk9XHHHNMnHHGGUl9s2bNWqPlw2uq/PP5Bx98kPGS3B9++GHKPue1OblcHeUniZcvXx4vvPBCRmPTrfhRH8vxN2nSJG688cZKw3E///nP4+67746WLVsm9f/f//1f2j3QW7VqFfvuu29S34svvljp8vCrmzBhQlJgoEWLFtW6cr4x6NSpU0rfrFmz0h7b0O8JVtlggw3i3nvvTRsYiIho1qxZnH/++Skr6SxdurTCEGdEpKye0KZNm7jlllsqDQxERDRt2jTOO++8lJVk5s2bV+XKAatb9fy45557xvjx4+Paa6+NP//5z3HttdfGhAkTYuTIkUmBgdp2xBFHxIUXXljh1fg///nPK1w5a+utt45bb701bWAgYuXj5B//+EdKf/ntWlY3evTolMDA7373u7jkkksqfc3o0qVL3HrrrSm/i/fdd198/fXXFY5Lp6CgIO6+++4KAwMRK1+Hb7rppsjPz0/qL7/yCQBAthAaAACAiHj00UeT2u3bt4+BAwdWOqb8pFFxcXFGe/2Wn7x67733MtrfPt2ET0XBhmeeeSYlwHDVVVdVeJVeedttt12ceeaZSX3PPvtsfP/99xmNX+Wf//xn2iW8N95446QP8z/44IOUyY5TTz01ZQKpInl5eWmXZK4oxPHoo48mTRitqrWqpYAjVl4hX9kVb+m88847KcsQn3/++bH55ptnNH6TTTZJmfCZOHFipR/a17eSkpL46aefYvr06TFhwoS48sorY++9904JZ0SsXAa8/IobVdl1113jkksuSXlMtGzZMrbaaqtEu7S0NG666aakY1q1alXlihWr5OTkxN/+9rfo27dvUv8zzzyT9krGpUuXpqxoscMOO8SvfvWrKs9VUFAQV155ZcqERWOyZMmSlO+vX79+cc4552Q0/pRTTkn5vSq/Kkh9KL+NS1lZWcbhhfJhrU033bROVvnIxI477pjy8xwzZkxGY1955ZWkK/lbtGgRgwcPrs3y0vrVr35V5etpxMqVQM4+++ykvgULFqSs/LFK+QDF0qVL48UXX8yopvL36b777pvxag2NRbrXx4pCE43hPUFOTk5cdtllGb3OnnPOObHFFlsk9T3++OMp4aWIiB9++CFlgvqYY46JLl26ZFxbuhBQJu/LVte7d++48cYbUybfmzZtGtttt121bqs62rZtm9HzcUWvuX//+9+rXPp/u+22S7nfvvrqq7THlpaWpoQ4dthhh5QAWUXy8vLi0ksvjc6dOyf6ysrKUrY6qcppp52W0RYBG2+8cUoAqTqBEQCAdYnQAAAAWW/x4sVJS5tHRBx44IFVTuTtscceKR8OP/zww1FSUlLpuPKTV6WlpRlN+rz88stJe8Pm5uZWuHfxAw88kNTefvvtK1x6vCJHHXVU0iRrcXFx0rLYVdl0002rvIp+lWbNmsVxxx0Xe+65Z2y66abRpk2b2H///atVb7oPh5csWZL22PITRltvvXW19sIeOnRotfZXL39/dOvWrdpX+O67776x0UYbJfWVD7vUlT59+lT5r2/fvrH99tvH3nvvHaeddlqMHDky7VWvnTt3juuuuy6aNKnen6NnnHFGpfsnr/K///0v5arwo48+ulp7lefn56dMwhQXFyftyb3KSy+9lDJR95vf/Cbjc2222WZx0EEHZXx8fZswYULK93faaadFXl5eRuPz8vKSwk0tW7aMpUuXRn3vlNi6deuUAFMmz7tFRUUpIYeqtkyoSzk5OSnPHW+99Vb8+OOPVY5tiInyli1bxu9+97uMjz/yyCNTXlcr2mampgGK+fPnpyx/Xj6AsDZYff/0VZYvX5722MbwnmDQoEHx85//PKNj8/LykrYvilj5vY0fPz7l2BUrVsSvfvWrGDRoUPTu3TtatmxZ4XujiqR7/5DpqhWrnHbaaVVOvteFgw8+OKPVj9KFFPv06ZMUuqvMxhtvnNQuH7xc5fXXX09Zuav8fVmVgoKCOOaYY5L6nnrqqSgsLMxofF5eXtJqVlUpv2JXYWFh2oAKAMC6TmgAAICsN3bs2KS9eiMyW3o6Pz8/ZbnXmTNnxssvv1zpuIKCgpSrmjKZ6Cg/4bPrrrumXXp3yZIlKVe177nnnlXefnktWrRI+YD/vffey3j8HnvskdEkb0TEVlttFeeff37cdtttMXbs2Hj33XerPZnVqlWrlL7VtwNYZd68eSlL19dkie7qfCBdfl/r3XffvdqT5jk5OSlX61bn/mgMNtpoo7jnnnuqXDK6vPbt22d8Zfdbb72V0lfZsugV2WWXXVL2Jy5/P0as3Ct6de3bt894YmyV6k5w1afyP8+2bdtW+/nk8MMPj3vuuSdeffXVmDhxYowaNSrj54baVP55/csvv0x5Liiv/NX5lYW16suwYcOSfn4lJSXxzDPPVDpmwYIFKa9N9TFRPnjw4Go9l+fn56dcEf3RRx9FcXFxyrHpAhT//e9/K9yWZpWxY8cmvTZ07do1dtppp4xrbCzSBRTTLYHfWN4THH744dU638CBA6Ndu3ZJfeWfbyMiNtxwwxgxYkT861//ijFjxsTEiRNTJrirkun7h4o0adIkdtttt2qds7b87Gc/y+i49u3bp/SV3y6rMuWDCRWFKt5+++2kdqtWrTKucXV77bVXUnv58uUpj+OKbLrppimPncpssMEGKX3VDY0AAKwLhAYAAMh65a/W3nzzzVOWxa1IuitOH3zwwWqPmzx5cnzxxRcVHr9gwYJ45ZVXqjx3xMr9t8tPJpS/Qj1T5X8OH374YZSWlmY0tjofRq+pL7/8Mu2y1OmuZp44cWJKX/mrzDKR6XLD06ZNizlz5iT11db9MW3atConyBqDzp07x9lnnx1PPvlkbLLJJtUeX5375913301qr7/++rHhhhtW+5w5OTmxww47JPV99NFHKRNJH3/8cVJ7yy23jNzc3Gqdq3///tUeU18++eSTpPaWW25Z7e0U1ltvvdhxxx2rtVx4Xdhpp51Srkx/6qmnKh1T/v932223pGWzG0KPHj1i++23T+qrKng2bty4Bpkor+7V7BGREhBatmxZheGO8gGK4uLiCrczWKV8AO/ggw9ukBDLmkp31XW6gEZjeE+Qn59f7cdbfn5+bLnllkl9H330UbVuIxPTp09PG7rJ9L1OxMoVYzLZ/qYuZPqamm4VhJ49e2Z8nkyf999///2kdvfu3TNemWZ1vXr1Sjlnplsy9enTp1rnSrfVR1WrhgEArIuq/64NAADWIV999VXKXrjVufqyT58+0a9fv/jss88Sfa+//nrMmDEj5Srl1a2avFp9j/Snnnoq/vjHP6Y9vvyVke3atUu5CmuVKVOmpPT95z//yXjf69XNmDEjqb1kyZKYP39+dOzYscqx1Vm+PxNlZWUxe/bsmD59enz77bfx5ZdfxhdffBGffPJJ0pXA5ceUN3Xq1JS+3r17V7ueTIMlX375ZUrfU089lfGH36tLFxCYMWNGynLeDSEnJyfy8/OjdevW0bFjx9hwww1j8803jx122CEGDBiwRpPivXr1yvjYmTNnJrX79u1b4/NuueWWSVsSrFixIubNm5c0+V1+Gebq1LpKs2bNYuONN077WGlo5b+/6k7GNCarrky/+eabE33PPPNM/PnPf0678seiRYvipZdeSupryK0JVjds2LCkgMynn34aU6dOrfAK6/IT5UOHDq2XifJMnydXl+4xNn369Nh6661T+lcFKFb/WYwZMyZlafNVpk2bljLxvDZuTRCxcpuF8tq0aZPS1xjeE2y22WZpV0GoyhZbbBGvv/560vlLSkpq9Hoyd+7cxPuHr776KvH+IZOtPapSk+f92tKpU6caj61O0CHT54vyr2OzZs2KM844o1p1rZKbm5v03rf8468imWzXsLp0oYbqhEYAANYVQgMAAGS1Rx55JKXvsssui8suu6zGt1laWhoPPfRQnH322RUek5OTE8OGDYubbrop0ff000/HOeeck/aD2fJXux500EEV7p27cOHClL7aXMZ+wYIFGYUGqrM0bDqTJ0+Ol156KT7//PP4+uuv49tvv40VK1as0W1GRMyePTup3bJly2pfOR2x8qq9VfuzVyZdoOGzzz5LCpqsiYoCE7Vp8uTJdX6OylRnAqD8z2NNrgpPF8ZYsGBBIjSwaNGilK1N0i0BnYn111+/0YUGFi9eXGvfX2MxbNiw+Ne//pUIFM2ePTveeuut2HnnnVOOHTduXNLV3O3atUvZIqSh7LfffvGPf/wj6f4ZM2ZM2sm5b7/9NmWFlfoKP2TyWlFeusdYZc9zhxxySFJoYOLEiTF9+vTo0aNHyrHlwxPbbbddjVYiaQxmzZqV0pfuubIxvCdIt/x7Jso/FoqKimLhwoVVBuWmT58eL7zwQnz22Wfx5Zdfxrfffluny81Xd5K6NqW7Sj5TNVkBoDIlJSWxePHipL4FCxbEc889Vyu3n+6xnE51t7dKJ13oFABgXWd7AgAAslZxcXGVS1PX1KOPPlrlfrjll1WeOXNmytLqERHffPNNyoRPZVdGZvqhak0tWrQoo+PSXfGYiddffz0OPfTQGDp0aFx33XXx3HPPxZQpU6oMDFQUoiiv/MRBur2MM5XJVXqN5f5Ym61JaGBNJg/S3b+r35/lJ9Qjav54WpPHYV1JN8nWGOusjh49eqTsr13RFdflJ5grC2vVt4KCgth3332T+p5++um0x5Z/navPifKaLNmebsxPP/1U4fGDBw+OFi1aJPWlu0/LyspSfhaNZeWImvjqq69S+tKtmtMYXoNqunR/unHpnndX+fjjj+OXv/xl7L333nHFFVfE008/HZMmTaoyMLCmv9c1fb9TGxrLc1LEysdaXU62Z/p+p7Fu9wMA0NgJDQAAkLVeeeWVlL3ma8ucOXPihRdeqPSY7t27p+z3nC7EUL5v1ZYIFakqrLCm0u2jnE51r2ArKSmJCy+8ME466aT49NNPqzw+Pz8/+vbtG8cff3zcfvvtceutt9aoruXLl1erztVl8rNoLPfH2qw6EwDlJyzWZAIj3Z7GdTUZ0ZgmftZ1hx56aFL7+eefT3kemD59esoWIo1tgrl8eOybb75Ju+d7+deQ+lyOvyZLfKcb07x58wqPTxegSBcaeP/995OWN2/evHnsv//+1a6vsUi3Wk26LRwaw2tQTVbziVgZ7iyvovcWt9xySxx++OHx1ltvVXm7TZo0ic022yyOOOKIuOGGG+KJJ56oUX1V1ZRtGsNjDQCAmvOuFgCArPXoo48mtQsKCmKXXXap0W0VFham7H394IMPxpAhQyodN3z48KQPuJ977rn4+9//njSBWP5q16omrtJdmffxxx/XaD/h+nTRRRfF6NGj0/5f9+7do1+/frHZZpvFxhtvHJtuumlsttlmST+nTCYKIlKvWl+yZEmNay6/DG866e6PsWPHxqabblrj81KxNm3aJO1RvSb3b7qrm1e/ojndstCZPCbSWZM6qyvdRFw66a6erc8668p+++0XF198ceJ7Wbx4cUyYMCHp+frJJ59MCpxsvvnm0bdv33qvtTI77bRTdOvWLb777rtE35gxY2KbbbZJtCdOnBjffPNNot28efMqX5dq0/Lly1NWAahKut+hqlYbGTZsWNJr5ddffx2fffZZUsCufHhi7733rpVlzBvKG2+8kdRu0qRJbLnllinHNYb3BDV93kj3WEi32sltt90W119/fdrbWG+99WLLLbeMXr16Jb1/WP35e/r06TWqj2TpXjNOOeWU+OMf/9gA1QAAUF1CAwAAZKW5c+fGK6+8ktR3wAEHxMUXX1zj2xwyZEjScsFvv/12TJ06NTbeeOMKx+y7775x8cUXJz4YX7RoUbzyyiuxzz77RETEBx98kPRhdn5+fgwdOrTSOtq1a5fSt3DhwlhvvfWq8+3Uq1deeSUlMJCXlxfHHntsHHvssWn3pi6vqu0LVunUqVNSu7S0NL7//vvo2rVr5gVHxI8//pjRVXXp7o9s2FKgobRt2zYpNLD619WVbuzqe3cXFBREy5Ytk5a+njt3bo3OVdny61Wp7tXcma6u0bx582jatGnS1Z3z58+v1rkaoxYtWsSQIUPi4YcfTvSNGTMmaTK9/JXqjW2VgYiInJycOPjgg+Nf//pXom/cuHExYsSIxIoY5bcsqO+J8rlz56bsS1+VdCsAVRUaSBegePrppxOhgaKionj22WeTxtTnigu17eOPP06Z6N56663TTqg3hvcENd0iofxjoU2bNimP30mTJsUNN9yQMvaQQw6Jk08+OXr16lXleTJ9/0DlWrRoEc2aNUv6eXq/AwCw9rA9AQAAWenJJ59Mudr2gAMOWKPbPOSQQ1L6HnzwwUrHrJq8Wt3zzz+f+Lr8xNWee+4ZHTp0qPQ2u3XrltI3bdq0Ssc0tDvvvDOl74orrogRI0ZkFBiIyHyyNt3yzf/73/8yGru6zz//PKPj1sb7Y21W/vGSbgnvTJXfJqN58+ZJE205OTmx0UYbJR1Tk8dSRMSUKVNqNC6i+ktCz5s3L+Njyz9+a1rnTTfdFKNGjYrXX389vvnmmzpfxroq5UMA//3vfxPhj48//jjpdzQ/Pz8OOuig+iwvY8OGDYucnJxEe86cOfHuu+9GxMowyXPPPZdyfH2qyRXc6Z5b+/TpU+mYVQGK1a3+vb/xxhtJE9ddunSJnXfeudq1NRYPPPBASl9F72Eaw2tQTZ83yj+fpgth3nPPPSnv584+++y44oorMgoMRNQ87EWq8gHMqVOnNlAlAABUl9AAAABZ6bHHHktqr7feevGzn/1sjW5z6NCh0aRJ8lvsxx9/vMor2MpPXr388stRXFwcxcXFNboycsCAASl97733XpXj0nnjjTfi0UcfjTfffDOmT59eJxN9P/30U7z99ttJff37948DDzywWrfzxRdfpPSluwK7b9++Kftjl191IhOvvfZaRselO19N74+PP/44HnrooXj99ddj6tSpro5MY7vttktqz5o1q0YTZKWlpSn3U58+fZImaCNWPlZX9+mnn8ayZcuqda5vv/02FixYkPHx5fcHX32lg0x8/fXXGR9b/vv77LPPoqSkpFrnmzt3btx4441x0UUXxUknnRT77rtvjB8/vlq3Udu22267pMDHihUr4tVXX42IiGeeeSbp2EzCWg2lZ8+eKc/548aNi4iVK9WsvlpGQ0yUf/jhh9Ue88477yS1u3Tpknbiu7zyAYrvvvsuPvroo4iIlPDEwQcfnPJ6vbb46quvUrZaaNGiRdrgYkTjeE/w448/xvfff1+tc61YsSIl9LX99tunHFf+uaRr165x8sknV+tcmb5/oGrlH2+ffPJJ0mo1mVqxYkX85z//iRdeeCE+++yzdWKVGwCAxm7t/AsJAADWwEcffZRy1duQIUPWeAJh/fXXj5122impb+HChTF27NhKx/Xv3z/p6rlFixbFO++8E2+99VbSFcGdOnWKPfbYI6M6unfvntT3xBNPVPsD8JKSkvj73/8ef/3rX+NXv/pV7L333rHLLrvU6MPfynz33XdJe4dHpE5UVqW0tDQmTJiQ0p9ucjM/Pz/23nvvpL5x48ZVa8/lZcuWpawCUZGmTZsm7TEesXICK91ezVW56qqr4m9/+1ucdNJJMXjw4Ojfv/8aLb+/LkoX/ll9GfpMvfbaa/HDDz8k9e24444px+22225J7aVLl6ZMUFal/ARgVcovQV7dx0D5SdnKlA9hzJs3L2Uv9aqkC+Wkm8isb4ceemhSe/z48VFWVpaYdF+lMW5NsLryYbIXX3wxysrKUiZTG2Ki/MUXX6zW8T/99FPSajsR6X+n00kXoHjhhRfSvj6srVsTFBYWxl//+teUK+uPPPLItPvJRzSe9wTVfZ577rnnUl6Xy78H+umnn1K2Pthqq60S23Nk6oUXXkjpK/8zrm3lA2jrivK/r8uWLavyfXA6zzzzTFx22WVx+umnx/Dhw2OnnXaKO+64o7bKXCPr6n0HACA0AABA1nn00UdT+tZ0a4JVyi+PHFH1FgURqZNSL7zwQsrEydChQyMvLy+jOspPhn3zzTfxyCOPZDR2lYcffjhlaem99tormjZtWq3bqUq6CYdM91xfZfTo0fHNN9+k9Fd0FeRRRx2V1F60aFFcddVVGZ/v6quvrtaV4eXvj59++in+/e9/Zzw+YuUkdvnJ3gEDBkTnzp2rdTvrum233TY23XTTpL4HHnigWsukFxYWxrXXXpvSn271i9122y3lPrjlllsyfgwvWLAg7VLjlenUqVNS+4svvsh4y4FZs2bFyy+/nPG59t1332jZsmVS3+23354S9KlM+efALbfcMu1+6tWd6FtTBx98cNI5X3nllXj//fdj1qxZib5OnTrF7rvvXmc11Mb3PHjw4GjRokWi/eOPP8b//ve/lNVQGmKifMqUKdWaMLzxxhtTfnfKP19Xpvz3+Oqrr8ann36adJXytttuG5tssknGt9lYLF++PP70pz+lrN7QoUOH+M1vflPp2MbwnuD++++Pn376KaNjCwsL45Zbbknq6969e+ywww4px5VX3fcPr776aspqRxHV3/alutbWlS6qss8++6QEWG655ZZqrYizYsWKuOmmm1L699tvvzWurzasq/cdAIB3OQAAZJXly5enLD3ds2fPtPvc10S6CbYPP/wwJk2aVOm48pNX48ePT7kysjpXux599NEpdfzzn/9MLNVclS+//DKuvPLKpL6cnJz45S9/mXENmerSpUtK30svvZTx1YtvvvlmXHbZZWn/r6LJg+233z5lVYgHHngg7rzzzirPd9ddd8X999+fUW2rHHDAAbHBBhsk9d1+++0ZL9H+448/xnnnnZfS/6tf/apadWSDnJycOOGEE5L6lixZEmeffXZGE1ZlZWXxz3/+M+V3duedd067r3peXl7K+aZNmxYXXXRRlRPrq67cnTNnTpV1ra5fv35J7aKiorjvvvuqHFdYWBjnnntutba1aNu2bUoY6p133om77roro/GjRo1Ked6paBK4/ORjdbd5qK4uXbrELrvskmgvWrQo5bmkOmGtmqiN77mgoCD23XffpL6HHnoovvzyy0R7m222abCJ8gsuuCCj0M6ECRPi3nvvTerr169f2iXpK1I+QDF58uSUoGBFy/g3Zu+++24cccQRKVsW5eTkxCWXXBLt27evdHxjeE8we/bs+Pvf/57RCgf//Oc/U7ZROemkk1Ku8G7fvn3Kdi3vvvtuxiGqSZMmxZ/+9Ke0/1fX2/+kC1vU9XNefWjVqlUceeSRSX3Tpk1Lu0JGRS6++OL47rvvkvr22Wef6NGjR63VuSbS3XfVDasAADRGQgMAAGSVdMvC19YqAxERLVu2TJm8iYgqryTu0qVL7Lrrron27Nmzk5Yc33LLLaNXr14Z19GuXbs444wzkvqWL18exx9/fDzyyCOVfmj/1ltvxfHHH5+yLPBBBx0UW2yxRcY1ZKpLly5Je4tHRMycOTPOO++8SoMDy5cvj5tvvjlOOeWUCj/cr2zLgYsvvjiaNWuW1HfFFVfE73//+/jqq69Sjv/qq6/i97//fVx++eXVuso6YuXE8ogRI5L6SktL44wzzojbb7+90u9z0qRJccwxxyRd/RyxcpWBQYMGVauObHHwwQfHVlttldT38ccfx3HHHZd27+pV5s2bF2effXbKlfFNmzaN888/v8Jxxx13XMpj+LHHHos//vGPFQYVFixYEH/4wx+qvZVBRMSee+6ZcqXjLbfcUumWGd9//32cfPLJ1d5aICLitNNOi3bt2iX1XXHFFXHDDTdU+tgdNWpU/POf/0zq69WrV9oVWSIi5erU1Se960r5MNann35a6f/Xttr6nstfYf/QQw9V+v/1adGiRXHMMcdUOkH98MMPxxlnnJH02pSfnx8XXXRRtc5VUFAQ++yzT8ptr9K0adNafc2vbUVFRbF48eL49ttv4/XXX49bb701hg8fHscee2za8OHZZ5+d0etAY3lPMHbs2DjrrLNi0aJFaf9/8eLFMWLEiJTn4F69esVhhx2WcnyTJk1Sto1ZunRpnH322ZVuAVRcXByjRo2Ko48+usJVg6qzZVFNtG3bNqWv/NZ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",
-      "text/plain": [
-       "<Figure size 2400x1500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for Average 'Productivity' by 'Department'\n",
-    "plt.figure(figsize=(8,5))\n",
-    "sns.barplot(x=df['department'], y=df['actual_productivity'], estimator=np.mean, palette='coolwarm')\n",
-    "plt.title('Average Productivity by Department')\n",
-    "plt.xlabel('Department')\n",
-    "plt.ylabel('Actual Productivity')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "d3d3cef7",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:52.405419Z",
-     "start_time": "2025-04-04T15:19:51.920741Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([0, 1]), [Text(0, 0, 'sweing'), Text(1, 0, 'finishing')])"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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O3eijPTZmU4+dffvb355TTjklBx988MvOmTdvXm655ZbceOON5TvcFYvFvPa1r80JJ5yQmTNnZpdddqn0jwIAAACATdjwTnL/7//9v1xzzTX52c9+lt133z3t7e3lJyIkKUdxG+4PfeUrX8k111yT5557rvy416ampnzve9/LmDFjes3f0ho2fOzshntT//Ef/5ETTjhho+euWLEihUIhra2tGTdu3BbvtAcAMFgI7wAAYBD79a9/nYsuuii///3vc/3112e33XZLR0dH6urqNnlOS0tLzjnnnHJ8V1NTk46Ojpx88sk599xzM3LkyPIm65ZsKr6bMWNG/uEf/iFTpkxJkl7zOjo6smTJkvLxjY2NmTZt2vb8MQAAAACwGRuGdG1tbWloaOgV3d13333ZZZddsueee5b3cTYM6jaM73ruYnfkkUfmv//7vzNq1KiK47szzjgjCxYsSJIcc8wxueyyyzZ53ob7Sj1fb+3eFQDAQBLeAQDAILTh5uL//d//Za+99sr48eN7bZiuWLEi48ePT21t7cvOf2l8193dncmTJ+cDH/hATj755NTX11cc311wwQV54oknkiSve93ryo+UfemaNzXXhikAAABA39kwvtvw6x//+Mc5//zz85a3vCWnnXZa9thjjy3Gdz37STNnzszFF1+ckSNHVhzffeADH8guu+ySyy+/vNdnAAA7CuEdAAAMUi8N1To7O8uR3bXXXpuvf/3r+eIXv5gjjzxyo5uWG8Z3PUHcAQcckFNOOSVvfetbK47v7rzzzpxxxhl51atele985ztJstWPrQUAAACg//3gBz/I5z73uSTJzjvvnFmzZuXjH//4ZuO7733ve1m5cmV5P2lb47ueO+8lvfe1AAB2FP6FDAAABqmXBnE9m5M//OEPc/7552fZsmW58MILc++996azs/Nl50+cODH/9m//lmOOOaa8kfrwww/nO9/5Tn7yk5+kvb29vIG6JfX19Tn66KPzrW99qxzddXZ2iu4AAAAABrEnn3wySVIsFrNixYrccsstueSSS/Lkk0+W94V6Hi2bJKeffnpOPvnkTJgwobyfNG/evJx55plZt25dr2M3paamJt3d3eXorqurS3QHAOyQ/CsZAAAMIa2trfnpT3+a5MUQ73e/+13++Z//OYsWLdrq+O6BBx7Y5vju0EMPTWLDFAAAAGAoOOOMM3LGGWeku7s7SbJq1arccsstufTSSyuO784444ytju82vFjT42UBgB2V8A4AAIaQxsbGfPzjH8/s2bPLod3DDz/cb/FdDxumAAAAAINbTxz3sY99LH/3d39Xfn9b47uf//znFcV3AAA7OuEdAAAMET1h3Gte85qccsopmTVrVvmzgYjvAAAAABi8NozjPvGJT4jvAACqTHgHAABDRKFQKH89ffr0/PVf/7X4DgAAAIBN2tb4rufRtFsT321sHwoAYDgQ3gEAwBDTE8aJ7wAAAADoieSS9NrT6fl6W+K7YrG4xfjuU5/6VF544YXU1tb2x48JADDoCO8AAGCI2TCMq2Z8d/XVV+emm24qx3cAAAAADE4bBnbFYjFr1qzJkiVLsmjRorS2tmbNmjUpFArleG5b47uNPXa2Z97tt9+eyy67rL9+ZACAQadQcisLAAAYVLq7u1MsbvoamZ7PNzxu0aJF+eY3v5nbb7+9fNwBBxyQf/iHf8j06dM3euVxS0tLzjnnnNxxxx3lzdddd901F1xwQY455pjq/2AAAAAAbLeeCymT5P7778/dd9+dH/3oR3n66aezbt26vOIVr8ikSZPymc98Jvvtt1+vc7u6ulJTU5Mk+drXvpb//M//LH82bty4HH/88fnYxz6WSZMmlb/Phud89atfzQ9+8IOsWLEir3/96/ONb3yjn35qAIDBR3gHAACDwIYbpknS2tqa//3f/80TTzyR7u7udHd358ADD8y+++6b3XbbrXzchhuf2xrfnXvuufnlL3+ZJHnta1+bK6+8so9+SgAAAAA258c//nEOOuigTJ06daOfb7iHdOutt+bLX/5ynn766axfvz51dXXp6OgoX2DZ2NiYT3/605kxY0b5TnXJ9sd3F1xwQZ599tlcfPHFSZLOzk6PmwUAhiXhHQAADLANN0z/93//N7/85S9z/fXX55lnnun1qNhRo0ZlzJgxed/73pcjjjgir3nNa5L03tzc1vjuox/9aGpra/O9730vSe8NWAAAAAD63tlnn52f/OQned/73pf3vve9L7tb3YZuuummnH322dnYP/UWCoXyY2Z32mmnfPSjH81b3vKWTV7MubXx3cae0iC6AwCGM+EdAAAMoJdepXzhhRfm2WefzQsvvFB+nGySFIvF8tXFdXV1mTx5ct7znvfkAx/4QJJs92NnV69enbFjxyaxYQoAAADQ377whS/kmmuuSZLU1NTk5JNP7hXfbbiH9Itf/CKnnXZa1q1blySZNGlSDj/88LziFa/IH//4x9x333157LHHyrMbGhryN3/zN3nnO9+53fHdhut46RMcAACGG/+aBgAAA2TDzcmf/OQnOfvss8ufjRkzJjU1Ndlvv/1SKBTy5JNP5tlnn03yYhj32GOP5YILLshzzz2X0047LcVisTxv+vTp5Sub586dmyR5+OGH86UvfSmf/exnNxrf9UR33d3dojsAAACAftTR0ZEDDzww48aNy6pVq9LV1ZWrr746ScrxXc8e0vLly/Pd7363/JSEqVOn5uKLL86ee+6ZESNGJHnxosw5c+bkqquuSpK0tbXlsssuS5Je8V3PI2lramryiU98IknK8d2qVatyyy23JEk+/vGPZ4899kiSXqGd6A4AGO7c8Q4AAAbY3Llz86lPfSrr169Pkuy777755Cc/mUMOOSR77713kmTp0qX53e9+l3/5l3/JihUrUiwW09XVlST58z//8/zTP/1TampqesV8ixcvzje/+c1yfJckTU1Nm4zvAAAAABgY69aty5w5c/LP//zPWbVqVfn9lz52dvHixfnEJz6RlStXZr/99ssVV1yRXXfdNaVSKd3d3eU72D377LP54Q9/mP/4j/8oz9qWO99NmDAhRx55ZD7/+c+nsbGxL/8IAACGHP/SBgAAA+iRRx7JpZdeWo7upk6dmssvvzwTJ05M8qeNz0mTJmWfffbJ4YcfnpNPPjkrVqxIbW1tOjs7097eXt4c3fCRH9OmTSt/n574bsmSJfmXf/mXnHXWWTn66KPLj6cFAAAAYOCMHDkys2fPTqlUygUXXFCO73rufPee97wn+++/f376059m5cqVGTduXE4//fTsuuuu6e7uTrFYLO8PJckuu+yS97znPUlSju+25c53K1euTBLRHQDARgjvAABgAPRsZt5777157LHHkiRTpkzJf/3Xf2XixInlz2tqatLZ2Zn6+vokyeWXX57ly5eXA7t3v/vd+cIXvtBrdqFQKJ//0viuWCzmwQcfzG233ZbXv/71/fcDAwAAALBZI0eOzPHHH58kG43v/uqv/qocwo0ZMyYHHnhgkmzywspx48bl5JNPTqFQyMUXX5xk6+O7YrGYr3zlKzn66KPzla98JUnKgR8AAC8S3gEAwADoCeq+//3vp62tLXV1dXnb296WSZMmpVQqla9Q7urqKj8S9vOf/3y+//3vJ0lKpVJOOumkXtHdkiVLsmTJkpx44om9HjvbE98Vi8XceuutOeaYY14W6wEAAAAw8DYX373wwgt5+OGHkySHH354pkyZUt7/2ZTx48fn3e9+d5JUFN99/OMfz+TJk/PWt741SdLZ2VneowIA4EV+OwIAgAHyxBNP5KmnnkpNTU06OjpyxBFH9HokSM9GZ9I7ukuSv/zLv8wXv/jF8utFixblE5/4RCZOnJhDDz00e+6558seO9vR0ZGpU6fmk5/8ZBIbpgAAAACD0abiu+uvv768l/Pcc8+lo6Njq/Z2tjW+E90BAGye35AAAGCAPPHEE3nuuedSW1ubXXbZJfvvv3/5s62N7jo7OzNnzpx86lOfSpKsXbs2y5cvz5577pkkveK75ubmNDc3l8+zYQoAAAAwOG0svqutrU1XV1eSZM2aNamrq0uSLd71Lqk8vtuQPSQAgI0rDvQCAABguOrZKE2Sjo6OvPDCC+Wvtya663kM7YgRI5Iko0aNSnt7e+6+++4kSXd3d5JsdOPVhikAAADA4NYT333mM5/JuHHj0tnZmZqamhQKhdx333255pprkmx872djeuK7M888s/xeW1tbLr/88txwww156qmn+uTnAADYUQnvAACgj5RKpfLXra2tL/t8zJgxKRQKKRQKee655/Loo48mSflq5S1Fdz1x3p577pmddtqpHO4999xzSZJi0a/7AAAAAEPZxuK7ngsq58yZk8WLF1c0rye+O+OMM8rvPf/887nooovy61//uppLBwDY4fmXOAAA6AMbPuLjRz/6US644IJenyXJ5MmTM3bs2HR0dCRJrrvuuqxatSrJ1kd3PXMaGxvL369n3obhHwAAAABD00vju569n7vvvjvXX399HnnkkYrmjR8/PieffHLOPPPM8oWbr33ta3PiiSdWfe0AADsyz5cCAIA+0BPBXXvttTn//POTJCeccEKOO+64FAqFdHd3Z9y4cTn88MMzf/78JMl9992XX/7yl7nrrrty/fXXl2dtLrpL/vSY2kKhkFKplP32268/fkQAAAAAqqC7u7vXkwt6Lujc8P2e+C5JLrjggvLFm9ddd11GjBiR9773vRXtCfXEd21tbXnggQdy2WWXJUmvO+oBALB5fmsCAIA+8txzz+W//uu/kiS1tbX53ve+l4MPPjiTJk1KsVjMqFGjMnv27HJ49+yzz+bzn/981qxZU56xpeiuu7s78+fPz4oVK9Ld3Z0kecUrXpHkT/EfAAAAAINXsVhMd3d31q5dm9WrV2fMmDHZaaedytFdT4C3qfju6quvTpKK47tx48blYx/7WMaMGZNEdAcAUCmPmgUAgD7S0NCQd7/73WloaEhnZ2f+7//+r/zoj55Hgrz1rW/N2972tvI569evLwdzG0Z3nZ2dvaK7nsius7Mz99xzT7q6upIks2fPTnNzc9//cAAAAABsk1KpVP76j3/8Y+bMmZP3vve9ecc73pE3vvGNed/73pf//M//zO9+97t0dXX1uhveSx872+Pqq6/Od7/73Tz66KMVraUnuiuVSqI7AIAKCe8AAKCP1NbWZtasWWloaEiSrFq1Kl/+8pezevXq1NXVJUnq6+vzxje+MQcccEDy/7V353FVlvn/x9/ncABZFNQQxQWXcEEzy3HfslBzKtfJGk1bppLMZtQi7VuObZZTmXup45alaeWS+246ormlpaYmCi6oiCIom3CW3x/+zh0HETgmovF6/uO57nPd933d6B8+Lt7356PfA3YBAQF67rnnjGt5eHjI4XAYATvnhuvUqVO1ePFiSVffUm7VqpVxbQAAAAAAANxenG1kJel///uf3nnnHQ0fPlx79+5VQkKCrFarYmNjNWnSJH300UdKTU295ho3O3wn0TkBAADgRhC8AwAAAIpQ3bp19a9//csYnzhxQt9++61sNpvxdnOHDh3UvXt3BQcHS7oavktJSdGAAQO0cOFCxcfHy2QyyWQyGVXv4uPjNXr0aKOVrSQ9+OCDeuKJJyS5vjkNAAAAAACA4pczdLdixQpFRUUpOjraaBnr7JBgtVrl6empp556yiVYl1NRhO8AAADgHpOD38gBAAAARSoxMVH//ve/tXHjRklSq1atNH78ePn5+Sk7O9uoUDd+/HgtWLBACQkJMplMcjgcCggIUHBwsLp06aKAgAD5+fnpf//7n44dO6aff/7ZuMcDDzygyZMnS5JsNptLW1oAAAAAAADcPpYtW6bXXnvNGFeqVEl16tTRPffco2PHjun48eNq3ry5/vnPf8rLyyvfa2VmZmr16tX64IMPjACfJPXp00e9e/dWrVq1iuw5AAAASjqCdwAAAMANcr6lnPvPvMyZM0fvvfeeMR40aJAiIyMluQblZs2apcWLF+vQoUOSrrartVqtxnnO+zh5eHjo4Ycf1ujRoyVdfSPaYrHc3AcFAAAAAADATbFp0yb985//1JUrVyRJYWFhGjlypGrUqKHSpUsrKytL2dnZysjI0F133SVJstvtMptdG5nl3E/KzMzUmjVrNHLkSJfwXe/evdWnTx/CdwAAAEWE4B0AAABwA3KG7BISEow2sbm/y/l5wIAB2rBhg6Srm6offvihGjRoIMl1A3XTpk1au3atvvvuOyNoZ7FY5HA4ZLPZjPs0atRIrVu31sCBAyURugMAAAAAALidnThxQm+//ba2b98um82m2rVra/bs2QoMDDTm5PViZ1ZWliTp+PHjKlOmjAIDA+Xt7e0yJ6/wndlsVu/evfX444+rTp06RftwAAAAJRC/lQMAAADclHMDdPHixXr//fc1cOBA/e1vf5O/v79MJpPx1nHOz/369dORI0d08uRJxcbGavfu3WrQoIERunP+2a5dO7Vr106tWrXS1q1btW3bNmVmZiozM1N+fn6qVKmSHn74YTVr1kz16tWTdPUtZ0J3AAAAAAAAt87u3btVu3ZtlS5dOt95zr2kmJgYHThwQDabTdWqVdP48eMVGBjoUr0ud/Dup59+0uLFi/XLL78oLi5OZcuWVcWKFfXqq6+qbt268vf3lySVKlVKHTt2lCQjfGe32/XVV1+pRo0aBO8AAACKABXvAAAAgBu0YMECvfnmm8a4Y8eOevDBB9WtWzdJ126UpqSkaPjw4VqzZo0kyd/fX998841q1qx53XvY7XalpqYqJSVFmZmZKleunLy8vFw2dPNrcQsAAAAAAICbb8iQIdq0aZOGDx+uiIgIIwB3PdnZ2YqMjFR0dLTMZrMiIyP18ssvy2w257mvs2XLFv3444+aPn26nL/ONZlMMplMstvtqlSpkl544QV16dLF5d7OynejRo1SUlKSWrZsqRkzZtzchwcAAIAkgncAAADADTl27Jj++te/SpJ8fX2Vnp4uSSpbtqyaNGmif//73woMDDSq0Dmr2R0+fFhPPvmkMjIyJElPPfWUBg8eLD8/vzzvk1eoznmMwB0AAAAAAMCtN3jwYK1cuVKSFBYWpj59+uixxx677v6OJGVkZKhPnz769ddfJUmTJ0/WAw88ILvdLulqW1ir1arMzExNmjRJq1atUkJCgux2uzw8PGSz2Yx5DodDDodDFStW1Lhx43Tvvfcae0/S1fDdkiVLFB0drXHjxkmSrFYr3RIAAABuMnNxLwAAAAC4EwUFBemRRx6RxWJRenq60Q4kJSVFa9as0dNPP63Zs2crLi5Okoy3kevUqaPIyEh5enpKkrZv366kpCRJMjZac8orWOc8RugOAAAAAADg1rp48aKsVqskydPTU0eOHNHy5cuNvaHrSUtLU1pamjE+deqUpKtBOrPZrKSkJM2fP18vv/yyZs6cqTNnzhhzvby8FBoaqhYtWig0NNSogHf27FmNGzdOVqvVCN1JV9vOduvWjdAdAABAESN4BwAAANyA0qVLq3379vL29pbJZJLNZpOXl5cRnjt69KgmT56swYMHa/PmzTKZTMYGaOPGjVW5cmVJ0pEjRzRhwgRJctkgBQAAAAAAwO2nbNmyGjZsmHr16qXs7GxVrFhRH3/8sUqVKqX8Go3dddddCgkJMcZLly7VihUrdPjwYW3evFkvvPCCxo4dq+3btxtzPDw8FBoaqrFjx2r69OmaOXOmRo4cqQ4dOhjfnzlzRpcuXbrmfl5eXsZnQncAAABFg1azAAAAgJtytnh94403tGjRIplMJoWHhyssLEzLli2T3W53qWD37LPPqnXr1mrVqpUkadKkSUbgLigoSG+//bYeeuihW/8wAAAAAAAAcNvJkyf19ddfq2/fvqpUqZKysrKMsFvuCnPOvaSZM2dqwoQJSk9PN/aW/P39lZmZqezsbHl4eMhut8vhcKh+/fpq27atevfuraCgIJdWsjNmzNBHH30ks9ksPz8/zZs3T7Vq1br1PwQAAIASjpIaAAAAgJucFe4kaeDAgapfv74cDocOHz6szp0768svv1Tbtm3l5+dnnDNz5ky9//77+uSTTyRJTz/9tB588EFJUmJion788cdb/yAAAAAAAAC4IVWrVtVrr712Tehu3bp1WrRokVJTU425zpBdRESEwsLCXI6npaUZ39tsNnl6eqpnz5766KOPFBkZ6RK6c7a4bd68uTw9PWW32+Xr66uAgIBb9dgAAADIgeAdAAAAkIeCCkN7eHhIutompH379vLx8ZHVatWrr76qoKAgjRo1Su+8844qVqxonBMbG6tp06bpueee0/r16xUWFqbg4GBJ0pdffqlNmzYV3QMBAAAAAADgpnJWoHOG7hYvXqyBAwdq4sSJWrdunUv4zm63q2rVqvrggw/UsmVLlS1b1uiYkJWVJUnq1auX/vOf/2jkyJGqVauWvL29Xe7jrKIXHR2t7OxsSVJgYKDMZnOBe1kAAAC4+Wg1CwAAAOSSs5Ws843lnO08cktISFC/fv10/PhxmUwmde/eXcOGDVOZMmV07tw5TZw4UT/99JNiYmKMc6pXr65y5crp6NGjSktLk9VqVbt27fTuu+8aYTwAAAAAAADcGfbs2aO///3vxjg0NFSRkZHq0KGD/P395XA45HA4ZDablZiYqNjYWG3btk1ZWVmqUqWKGjRooHvuucc432azGS9+SjL2ptLT0zVs2DCtWbNGkjRkyBC9+OKLt+5BAQAAYCB4BwAAAOSQM2C3dOlSffvttxoxYoRq1qxphPFyznF+jo6O1sCBA5WRkaGqVavq/fffV7NmzSRJGRkZOnDggObNm6dly5bJZDLJ4XDIx8dHGRkZxr3Lly+vjz/+WC1btsw36AcAAAAAAIDby8mTJzV+/HgtXbrUOJZX+E76vfVsbjlfBr2eCRMmaNKkSZKk8PBwvfvuu2rQoEGhzgUAAMDNRfAOAAAAyMPixYs1bNgwSVdbdjz11FNq3bq1GjVqlOf8pKQkffzxx1q6dKmsVqtatmypGTNmXDNvzpw5Wrt2rXbu3CmbzSaLxSK73S4PDw9lZ2erVq1aWrJkicsbzQAAAAAAALj9xcfHa9KkSVq4cKFxLHf4zilnUC7nZ6vVKg8PD5cQnfP7zz77TOPHj5ckeXh46Pnnn9fgwYNvxaMBAAAgDwTvAAAAgFx++ukn9e7dW5JksVhktVrl5eWlChUq6Omnn1avXr3k7e0tybXtx/r16zVkyBBduXJFkjRo0CBFRkZeMy8mJkbbt2/Xxx9/rMzMTJf7tGjRQjNnzrylzwsAAAAAAICbw53wXU7OcN3XX3+t7Oxs3XvvvWrQoIEyMzO1a9cubdiwQfPnzzfmP/LIIxo9erQk0TkBAACgmBC8AwAAAPIwc+ZM/fTTT1q7dq0kGe1hJalTp0564IEH1KVLF3l4eLhsbn766aeaOnWqJKlJkyZ68803Vbdu3TxbiRw6dEj//e9/tXfvXsXHx6tt27bGuWyYAgAAAAAA3JncDd85Q3e7du3SU089JUkKCAhQtWrVdOnSJaWkpCg5OdmY/8ADD2jy5MmSXF/2BAAAwK1F8A4AAADIIedmZUJCgnbt2qXRo0fr4sWLysjIMOYFBgbq3nvv1ZtvvqmgoCD5+PhIko4fP6633npLO3fulCS98sorevnll6+5jzNYl5SUpF9//VXR0dEaOnSopKstRSwWS1E/KgAAAAAAAG5Azhcmc7aJzcnd8N25c+fUq1cvnT17Vj4+PsrIyHB5EVSSSpcurYiICH344YeS2EMCAAAobgTvAAAAUOIVVF3u6NGj2rhxo5YsWaLffvvN5btq1aqpc+fOevjhh1WvXj1ZrVbNmDFD48ePl9VqlSRNmzZNrVu3LtRa2DAFAAAAAAC48+QVwHMnfBcfH6/ly5drxowZunz5smw2m8u12rVrpzZt2hgV8dh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-      "text/plain": [
-       "<Figure size 3000x1800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for 'Targeted' & 'Actual Productivity' Distribution by Department\n",
-    "plt.figure(figsize=(10,6))\n",
-    "df_melted = df.melt(id_vars=['department'], value_vars=['targeted_productivity', 'actual_productivity'], var_name=\"Type\", value_name=\"Productivity\")\n",
-    "\n",
-    "sns.boxplot(x='department', y='Productivity', hue='Type', data=df_melted, palette='coolwarm')\n",
-    "plt.title(\"Targeted vs. Actual Productivity Distribution by Department\")\n",
-    "plt.xlabel(\"Department\")\n",
-    "plt.ylabel(\"Productivity\")\n",
-    "plt.legend(title=\"Productivity Type\")\n",
-    "plt.xticks(rotation=45)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "2331ffe4",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:53.041460Z",
-     "start_time": "2025-04-04T15:19:52.405419Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'Actual Productivity')"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 2400x1500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for 'No. of workers' and its relation to 'Actual Productivity'\n",
-    "plt.figure(figsize=(8,5))\n",
-    "sns.regplot(x=df['no_of_workers'], y=df['actual_productivity'], scatter_kws={'alpha':0.5}, line_kws={'color':'red'})\n",
-    "plt.title(\"Number of Workers vs. Actual Productivity\")\n",
-    "plt.xlabel(\"Number of Workers\")\n",
-    "plt.ylabel(\"Actual Productivity\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "be400f29",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:53.680216Z",
-     "start_time": "2025-04-04T15:19:53.044013Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'Actual Productivity')"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 2400x1500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for 'Over Time' & 'Actual Productivity'\n",
-    "plt.figure(figsize=(8,5))\n",
-    "sns.regplot(x=df['over_time'], y=df['actual_productivity'], scatter_kws={'alpha':0.5}, line_kws={'color':'red'})\n",
-    "plt.title(\"Overtime vs. Actual Productivity\")\n",
-    "plt.xlabel(\"Overtime (Minutes)\")\n",
-    "plt.ylabel(\"Actual Productivity\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "7e46ec7e",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:54.367067Z",
-     "start_time": "2025-04-04T15:19:53.680216Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'Incentives (BDT)')"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 2400x1500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for 'Over Time' & 'Incentives'\n",
-    "plt.figure(figsize=(8,5))\n",
-    "sns.regplot(x=df['over_time'], y=df['incentive'], scatter_kws={'alpha':0.5}, line_kws={'color':'red'})\n",
-    "plt.title(\"Overtime vs. Incentives\")\n",
-    "plt.xlabel(\"Overtime (Minutes)\")\n",
-    "plt.ylabel(\"Incentives (BDT)\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "41d08006",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:54.816212Z",
-     "start_time": "2025-04-04T15:19:54.367067Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'Actual Productivity')"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 2400x1500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for 'Incentives' & Productivity\n",
-    "plt.figure(figsize=(8,5))\n",
-    "sns.scatterplot(x=df['incentive'], y=df['actual_productivity'], alpha=0.6, color='green')\n",
-    "#plt.xlim(20, df['incentive'].max())\n",
-    "plt.title('Incentive vs. Productivity')\n",
-    "plt.xlabel('Incentive (BDT)')\n",
-    "plt.ylabel('Actual Productivity')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c28336d4",
-   "metadata": {},
-   "source": [
-    "### Different types of encodings depending on the algorithms we use.\n",
-    "-  Decision Tree requires different encodings than SVM and Perceptron."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "5d778a2c",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:54.866670Z",
-     "start_time": "2025-04-04T15:19:54.820247Z"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "# Cyclical Encoding of 'day' column (Only for 'SVM' & 'Perceptron' Algorithms \n",
-    "df['day_num'] = df['date'].dt.weekday\n",
-    "df['day_sin'] = np.sin(2 * np.pi * df['day_num'] / 7)\n",
-    "df['day_cos'] = np.cos(2 * np.pi * df['day_num'] / 7)\n",
-    "\n",
-    "# One-Hot Encoding of 'day' column (Only for 'Decision Tree' Algorithm)\n",
-    "df = pd.get_dummies(df, columns=['day'], drop_first=False)\n",
-    "\n",
-    "# Target Encoding of 'Department', 'Team' & 'Quarter' column (Only for SVM & Perceptron Algorithm)\n",
-    "department_grouping = df.groupby('department')['actual_productivity'].mean() \n",
-    "df['department_encoded'] = df['department'].map(department_grouping)\n",
-    "\n",
-    "team_grouping = df.groupby('team')['actual_productivity'].mean()\n",
-    "df['team_encoded'] = df['team'].map(team_grouping)\n",
-    "\n",
-    "quarter_grouping = df.groupby('quarter')['actual_productivity'].mean().to_dict()\n",
-    "df['quarter_encoded'] = df['quarter'].map(quarter_grouping)\n",
-    "\n",
-    "# Label Encoding of 'Department' & 'Quarter' column (Only for Decision Tree Algorithm)\n",
-    "le = LabelEncoder()\n",
-    "df['department'] = le.fit_transform(df['department'])\n",
-    "\n",
-    "df['quarter'] = le.fit_transform(df['quarter'])\n",
-    "\n",
-    "# Clipping some values > 1.0\n",
-    "df['actual_productivity'] = df['actual_productivity'].clip(upper=1.0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "21687c1e",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:55.420162Z",
-     "start_time": "2025-04-04T15:19:54.868693Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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mqVad6sa5Kf+bqfGfTUyxf7ESRbVqy2J5eRWUJN2OvK3+L72ntX9tSNbXZDLp86+H65nnOxjnVi5bq3693klxbtxb2OYJ1qhQtbxmrfrWWMHg4plLer3DGwq6fiNZ32q1H9BX88YbK3KF3gjVMw16ZEshyOvDXtNz/Z412ou+X6L/DfvGqr5/zluhzwdNSHP+mSunqXL1+yVJm1b+ow9f/jjLmTPj8x9GqlGLBkb7q6ETtfiHnNliBfkH2zzBGhWrVtCcNbOM6/mFMxf1crvXUywgeah2NU1Z8JU8CtwpOg+5Eap29Z/Jluv5Gx+9rhdef85oL5i1SOOG/s+qvn/M/VOfvvN5in29fb21ZMtcFfS+8x45Oipab73wgbZv2JFi/4FD+6rXgITCyVVL1urDfsMz9Fr8ivpp9LThqtOgVrKfsc0TMoNtnpAfHT1+Uu98NFrnLlxK8eds84T8iG2ekBVPPtlMCxfPNNo7/t2jdm17pliY8lTbFvrpl8nG/fP/jp/SI3WfzLb757N/mqSOnRLuiQ8bOkYT/zc9WT8nJyd9O32Cuj7Tzjg36rOvNPbzlO/bSNLGf/5QrVoPGe0hg0dp8jczU+z7Qq9nNGlKwt8BV65cU40Hmygy8rbVr6XS/eX10y9T9OCDVZL9jG2ekBq2ecpf2OYpZWzzlL/YfJsnAFnz1uCEbT/CwyLU78VBqa7wsnr53xYFJRUqlVPnbu1S7JtRVR6oZFFI89ef61IspJGkmJgYvT/wYx3cd8Q490r/nvL28Uqx/6sDelm03+73YaqFNJJ0IyhYrz7/hkJDQo1zvV55zvg2cFJvvtfHKKSRpGHvjUqxkEaSzGazhg36TGdPnzfOPfFkYxUuyjKWAKzT+50XjA9eY2Nj9dFrI1IspJGkw7uPaMw744y2VyEvdevbNcsZvAt5qVPvjkb76L5j+vqjSan2nzLyO21Zk7CS2ZNdWqpMxdS36HN0dFDZ+8sa7ROHT2YxceZ0erG9RSHNpr/+oZAGQLZ5bVBvi+v5B69+lOpKLAd3H9aIt8YYbe9CXurZr1uWM3j7euvZlzoZ7cP7jmr8sK9T7T/xsynatHqL0W7T9UmVrZjylqgdn3/aKKSRpBn/m51qIY0kfTNqmo4eOG60H2/bxGK1nPTU86+jX1bPTLGQBgAg3QgO0agvpqjbK29aFNL4+njbMBUA2L8hw94yjsPCwtWj++uprvDy57LVGv7JeKN9f+UK6v5852zJUe3BKhaFNEv/+CvFQhrpzv3zfn3e1969B41zA954RYUKpXzNr/ZgFYtCmtWr1qdaSCNJP85eoAXzE+6PFC9eVE80b2z1a+ncpa02bPo9xUIaAADyE7svppk0aZLxyIqwsDANGTJEnTp10vPPZ22bAcBePFijqmrUetBoL5yzRFcvX0tzzMypP+vypatG+9meHdPobb1uL1j+UZHaKjN3RUVFa8KohEp6L6+CFsU4d7l7uKvpEwlLvO/esc+qrakCrgdp3o+LjXYBTw892rBusn7ePl7q+Exbo715/Vb9OiftD1qjo2P0y/cLjLazs7P8mzyabiYAKFS4kPxbNjTaW9du13+HTqQ5Zv2yjTq8O6H48KlnW2c5R6uuLeXqllBg+NM3c5TeYoVTR35nHDs5OapN1ydT7Vv2/rIW89uimKZ0+VLqO/RVox1yI1Tj3v0i13MAyJ98CxdSkycTtiD9Z81WHTv4X5pj1i5br4O7Dxvtdt2eynKOtl1bydXN1Wh/P/GndK/nE0dONY6dnJzU9tk2KfZr1THhG+CRtyI197sFKfZLLPHWVU5OTqrb6OF0xxQvXUwjJ3+syfO/tChQDwpIudAUAO5FW/7drTbPvqy5i5cqJtHqCPXr1NS0L0faMBkA2LeatR5U7doJq5f//ONCXb58NY0R0uRvZunixctGu9eLz2RLlhdffNaiPW5s2p95RUVF6bMRCfcxvL0LqkPHlN+710+0hZUki0KZ1Pzy8yKLdr1H0n/v/kC1ylq85Ht9P3uiChb0NM5fvx6Q7lgA+U8cjxQfyF/yRDHN5MmTNXny5CzN4+Liot9++02HDx/WyZO2+XY0kN1atG5m0V66eGW6Y2JjY7X891VGu1ad6ipRslg2ZGlqHJ8+cVaH9h9Nd8ymv7cqKDDhJnmb9i2S9ala7X65ubsZ7Q1rrd8PfNeOfRbt8pXKJuvTqu0TFvNPHJ92EdBd61Zv0vWrATp66Lj+2bhdcXH8igSQvgaPPyInZyejvfb3v60at3rJOuO4SInCql7voTR6py9xQU9EWIS2rk1/6d0z/53V8UQfFDdpm/o3lipVq2jRtkUxzTuj35S7h7vRnjRiqoKDQnI9B4D8qdETDSyu53/9vtaqcSt/W20cFy1RRDUfqZ5G7/Q1TlTQEx4Woc1rtqY75vTxMzqWaAWZJ55qkqyPp5enyla8z2jv2Lw71dUvEzt36rxFu1TZkmn2f6rrk1q06Re16tRCDg4Jtyf++m2Nhr85Kt3nA4B7xcnTZ3UzLGFrQHc3V70/8DVN/99oeSdaaRcAYOmppyzvN//667J0x8TGxmrJbwnbi9atV0ulSpXIcpY2bROynPjvtPbtPZTumLVrNikwIGH1yw6dUi6mKVLEctX0a9cC0537/LmLFu3ChdNeVfKdd/vpn63L1LyF5d8P30ycoeEfp70VOAAAeZXdF9NISvebddZIvKdlWFhYlucD7EHDxx4xjiPCb2nf7oNp9E6w/Z+dxrGDg4OaNvdPo3f67itXWqXKJNwo37o59eXfE4uLi9OObXuMdv2GdSwKWyTJ07OA/jt2Ujdv3vn39sL5lPcET8ntJHu8eqVwg6lpi8eM4/NnL1rkScvJ46f1SLUn1LpxV/Xo+Jr+WLQi/UEA7nm1/S2/5bNny16rxu3ZatmvwRP1M53BxdVZD9apZrQP7jyk6Khoq8bu3ZpQpFimfGmVqZDyVk+VqlUwjsNvhuvS2csp9sspj7drqnqN6xjt3Vv2auXCVWmMAICMqedv+c3Pnf9Y9x5y1xbLfo2eaJBKz/S5uLqoRp2EVSr37zxo9fV8V6LfK/dVKKP7Klhu9RQWGqYmlVupx5Mv69O3x2jB94tkjcSr5FijSvXKFmOCg4L10YDPNPT1Ebp963YaIwHg3mQymdSmRVMt+flbvdCto0UhIgAgucZNEt5vh4dHaNfOfWn0TrBpY8LK6A4ODmrRMnkBekaUL3+f7ruvlNHeuDH9Injpzv3zLVsS7rX7+z8i9yT3zyXpdlSURbt06bSL2iWpaLHCFu27999TU7duTTk5JXyh4Ny5i+rYvpeGDhmt2LjYNEYCAJB33TN/cf3444/GcYECBWyYBMg+VapVMo6PHz1hUTSWlsMHjlm0q9eqlkpP61R9sLLl/AfTX5UmIUtCX2dnZ1V7yHKf1U3rt6plw06qUa6RHirbQMt/X510ilRVqFTOoh0YmHyp+Dr1ahrH/2xIf/soAMiKig8kFJkEXb+hwGtBafROcObYGcVExxjtKjUqp9E7bWUrlZWzi7PR/u+Q9avGJO2bWo5KDyb8fjp55FQGE2aNs4uz+n6YsL1TbGysvhk+JVczAMj/Kj2QsAJX4PUgBVrxzU9JOpXkel6tZpU0eqet/P2W1/Pj6WwzlVjSLakeSCFH1O0oHd1/XH/MW66tf/9r1bxVq1v+Xjh36oJV42KiY7Tg+8Xq0rinViyi+BEAknJ2dtZTLZtpwayJGjf8A5UqkfUVhgHgXlDtwYT3uUcOH7f6/vmB/Yct2g/XztqKkg8+VDXJ/EdS6ZlSloS+zs7Oql4j+b38Q0nux3d55ul05+3StZ1F+9/tu63KEx4eofFjJ6l+3Se1ds0mq8YAAJBXOaXfJWft27dPgwYNsmr1mSeeeCLD85vNZgUHB+vWrTtLUptMJpUunfK3qIG8pEixwvLy9jLaZ06ds3rspYtXFB0dLWfnOzffy1VIvv1RRlS8v5xFOyNZzp+1XE6yXMX7tHtHyt8QCA+LyFCu1u0sl/E8+d9pi3bhon4qkqgC/9AB64uAACAzyiT65v+F09Z9wChJsbFxunrxmkqVu/PNotLlS6UzInX3VbJcfeDC6Yup9Ewu6QozqeVIvDLNicOn5OjkqMeebKQmbR7TA7Wqyq+Yr+Ji4xR4PUiHdx/RhuWbtGml9dv4paXTi+1Vokxxo71i/l86kYGCIQCwRtmKCdfS8xm6nsfqysWrKl3uzvWzTPnM/21artJ9Fu1zGchx8Zzlao/3ZSHHXQW9PdWhe8JN+8hbt7VtQ9orVt4Kv6WFP/ymX76drwtnrP99BAD3mm6d2qpbp7a2jgEAeUqx4kXk45Nw//zkyTNWj71w4bLF/fOKFctlKUvlKpbbYWcky5kzlvfaK1Uql6zwZcP6rbpy5ZqKFy8qSWrWrJFe799bUyZ/n+KcbZ5qrhd7P2u0z569oD+XrUkzR1BQsL78YpqmTvleV69ctzo/AAB5mc2LaWrWrKkqVapo7dq095g3m826eDFrN9dMJpMkqXXr1lmaB7AHSZdhvHr5mtVjzWazAgNuqHiJO2+ui5csmsUsRSyzZODN9PVrARbtEiWz59tVj/rXU71HE7ZTCb4Rop1JtnAqV97yA4iL5xM+JC59Xyl16NpGzVo8ptJlSsrbx0uBgTd09NBxrV7+txbPX6ooK5fRBwBJKuhTUK5uLkY74Kp1qxjcFXQ9yCimKVqiSDq9U1e4mOU+2gFXA1LpmXKGxFLK4VfMT4UKFzLaRUoU1pxNs1XyvuT7i3t4eqhM+dJ6snMLHT/wn8a+94WOH7B+ZYWkXN1c1WPAc0b7dmSUvv/qxzRGAEDGefkUtNia6PoV66+jkhR4LcgopilWIvPvwwsn+XsgIAM5kq6MVjSLfw/4FfXTuBmfWfyOmfPdfIWFpr1U/NSxM7L0vAAAAEBq7haW3HX58lWrx5rNZl2/HqiSJe98WadUqeT3NDKUJcn984xkuZrkvs3dTIlFR0fr/XdH6MefJxvnPh/3kerWq6Vvp/2oA/sPKyYmVpWrVFDPF7rq1dd6Gls2RUTc0qsvv6OoJFtFJTXg9cFWZwYAIL+weTGNJA0dOlRbtmxRZGSkVSvUZJbZbFa9evX04osv5thzALnFr7CvRTs4ODRD40OCQ41iGp9C3tmb5UZIhnIk5uOTtSyS5O7hrlFfDLM4N++nxcmW8SyepHDn+rUAubg46433++q1Ab2Mbx7cVbJUcZUsVVyPt2ys/u+8oiFvf6rN69kaCoB1Cvn5WLRDg29maPzNkIQPJJ2cneRewF23wm9lOIdPFnLcTNK3oE/BZH0qVbP8ttVjTzayau7K1e/XpMVf6dP+o7V51RarMyXWrsdTFq9v2dzlunaJb0sByF6JCwYlKTSD78NDQxKupU7OTvIo4K6ITFzPk/5eSfq+2toMkuSdwvU8LY6OjnJzd1XFqhXUrE1jderZXgU8PYyfb1q9RdPGzczQnAAAAEB2KlLE8stENzJwz1qSgoNDjMKVQlm8f548S7D1OZLkLuTrk2K/Jb+t0IDXB2v8F8Pl7u4mSerS9Wl16Zr6lk8HDhzR633f1769h6zOAwB3xSnnPtMH7IVdFNOULFlS7777rlauXJnsZzt23FkW2mQyqW7duhma12QyycnJSR4eHipSpIhq1qypdu3aycHBIVtyA7ZUoICHRTs8LDxD4yPCE7ZMKuBZIEtZPJJlsX47pvBwy76Jb8Jn1pdTR6lCpXJG+0ZQsKZ8lfxmfiFfyz+CYmPj9NOib/VIwzrpPkfp+0pp1rxJGjZolBb88luWMwPI/9wLuFu0b2Vw67qkhTMenh6ZKqZJmiMiAzluRSTPkNT9D1ZMdi4sNEzL5q7QmiXrdPHsJUXfjlaJ+4qrYfMG6tani/HBtLuHu4ZPGab+nd7Ssf3Hrc4lSY6ODnq2T1ejHR0VrZ8nzc3QHABgDY8k19HwsIxdi1O6nmemmCZpjgxdz1PIYC2TyaTNp1bL2cU52c9iomM0Z/pCfTt+huLi4qyeEwAAAMhuBQpY3vMOu5mx++eJ73F7Fsza/fOk998zkiUs3LKvZxr38n+cvUAbN2zV8E/fV6fOT6U575Z/dqh3rzcytEoOAAD3GrsoppGk559/Xs8//3yy81WrVjW2Z/rpp59yOxZgt1xcXSzaMdExGRqfuL9LCjfCM8LV1XJ8TLT12x8lze3knLUso7/8SK3aPmFxbvBbI3QzNPnKC0n/iBk5Yahq16spSTp7+rymfT1Lm/7eqmtXr8vbx0v1Hq2t1wa+qFp1qkuSnJ2dNerLYTp39oK2bd6RpdwA8r+k19qYmNhUeqYsJibJ9dLJMVtyxGYgR0y0ZV8n5+RvJZOuTHP84H8a9uoIXT532eL8meNndeb4WS2d86dGzxihWg3uXH9d3V01YupHer5xL8XGWv9BrP+TjVQs0TYlfy/dkKEtTwDAWi4uSd6Hx2TwfXjS63kK11JrOCf9eyBD1/Okv1Osz1C4mF+KhTSSdPHsJV25cEUODpn7HQUAAABkF9ck75ejM3DP+k7/xPfPXdLomb6k9/KjM3AvP+l796SrqSd2f+UKGjrsbbV9ukW68zZsVE979q/T+LGT9cWEKVbnAQDgXpInlmjJya2fgLzK0dHyX9+MfvMzO78p6uBoebM8Ls76f2eT9nVwMGUqg8lk0mcThuq5Xl0szn878Xut+nNdimOck3xocLeQZsXSNXrSv7Pm/bRYFy9cVnR0jAKuB2nF0jXq9GRP/fDdHGOMk5OTJkz6VM6Z/BAEwL3DIcvX7aTXy8y9jctKjqR9HUzJr9nH9h/X5lVbdPLIKZ09cU6Dug9OVkiT2M3gmxrc+yNdPHPJOFeqXEm1fqaV1bkkqcMLlssWL5ixKEPjAcBaSa+j5iy+D3cwZe567uiQfddzUwZ+pxQvVSzVn5WtdJ/eH/22lu5YoCZP+ls9JwAAAJDd7On+eVayJPv7IZX75527tNWmf5aqU+en5OLiovDwCH0xYar8G7ZV8SIPqkTRh+TfsK2+mDBVYfGr3Ht4uOuTEe/q+9kTjS+1AwCABHb/6e+AAQNy7bnubiklSfXq1cu15wUyI+k3T5MWtKTHMdGKBlFRGavKTyrpqgaOjg6KjbXum7FJV1aIuh2V4ed3cnLSF1NGql3n1hbnly5eqbGffp2hufbtOag3X/0g1W8HmM1mjRgyVhXvL6/HmjWQJJUqU1Kdu7XTvJ8WZzg7gHtH0uti0g9B05P0xktmr91Jr9lJPxROM0PSa3YKGeZOW6C50xZkKFP4zXB9N3amRkz9yDjXstMTWjZ3uVXji5YsqtqNHjbaR/YezfA2UQBgreTX0cy/D5ekqKiMv/+VpJikv1eycD2PzkCGKxevqnfbvjr931lF3opUkWKF9chjddSjXzeVv7+cJMnH10fjZo7Uh32Ha+2y9VbPDQAAAGSXpPfPHTP4vt3J4v555t6z35X8/rljBu6fW36MdzuF++eNmzTQdzO+MFatOXPmvDp1eFEn/jtt0W//vsPav++wfv5xoX5dPEsVK5WTdKcQ5+iR/zT282+sfUkAANwTKKZJpGfPnjKZTDKZTDp8+HCuPS8wftKn6vJce6v6/jr3d7034GPduhVpcT7pspXpcXV1NY6z+sfArVu3ks1t7Ye8SXNn9MPhgl4FNeWHCfJv8qjF+eW/r9LbfT9Mc2WrqBSW9vx8+P+sWmZz3GdfG8U0ktTyqccppgGQpshbty3aLm4Zu24nWxI4k8U0kZFJcmTg90d2ZUjJhj83KiIsQh6eHpKkB+tUk4ubi6Ii0/8d1bx9M4uVelYsWJVtuQAgqcgsvw/Pput5khwZuZ4new9+2/oM168E6HqibfQuX7ii3+f+qeWLVumjLz5Qmy5PSrrzAcGwCe9rz7Z9Cgq4YfX8AAAAQFJTvx2n53t0Sb+jpF9+/lX9+ryviAjLe9Zubq6pjEiZa6L+KRWwZERKWay9J++aJHfSL6M6ODho4jejjEKaW7ci9UyXV5IV0iR28uQZde7YWxs2/yFv74KSpHfe7afZP8zXlSvXrMoFAOwrg3tBntjmKTeZzWa2lUKeEHIjxKJdsKBnhsZ7FixgHAcHBWcpS/CN0FTnTj+HZe4bGchS+r5SWrRydrJCmsXzl+qNVwenW90fdjPMoh1wLVDbNu9Ipbelg/uO6NLFK0a7XoPaVqYGcK8KvXHTou3haf21UpIKJLq2xsbGKiwkLI3eqbuZJEeBDOQokOT6Hprk+p8VsbFxFqvJuLi6qEjxwlaNbfZ0E+M46naU1vye8vZ+AJAdQoItr30F4osArZX4uhsbG6ubmbyeJ/29kvQanWaGJH1DsuF6Hh0VrRFvjdG+fw8Y5wp6F1TnF6z70gAAAACQnW7cCLZoZ/T+uVfBgsZxUBbvn9/Iwr38pH2TZmnZsqkqVCxntGd/P09Hj/yX7rynTp3VN19PN9ru7m567vlOVucCAOBeQDENkEddvxZo0fYtXChD4wsX9TOOA7P4TdHr1wIs2hnJkjjHnSxBVo2rXa+mflv1s+6vUtHi/MypP2nQ68OsWiYz6XMdO3rCque+6+ihhA99PT0LZKiICMC950bADYt9rn38vDM0PvG1NfRGaKb37g68bnnty0iOpNf3GwHBmcqQmqQrF3j7pp/Nr6ivKle/32jv2bJXN4NvpjECALIm6Lrl9byQn0+GxvsW8TWOQ7J0Pbf8eyAjORJnkO78jsoOsbGxmjZ+psW5ho8/mkpvAAAAIOdcu2p5z7pwYd9UeqasSKL71gFJ3ntn1NWr1y2zFLE+S9Gill80up4kS+OmDSzaixb9afXc8+ctsWj7+z9i9VgAAO4FFNMAedTF85csCkaKlyxm9VjPggUsKtrPn72YpSwXkowvkYEsSftak6XV009ozpLpFn90xMXFadRHX2jksAlWP/eFc5cs2rfCb6XSM2WhIZYf1np7e2VoPIB7S3RUtAKvJhSyFC1RJEPji5RIuHly+dyVNHqmLenYIhnIkTiDJF0+fznTOVJiMpks2tFWbDtSv2k9iy2eNq/akq2ZACCp6KhoBVxNuIFdtGTRDI1PfP2/dC7z19GkYzPye6VYkr4Xs5Ajqd1b91osPV+u0n3ZNjcAAABgrXPnLlrcPy9ZqoTVYwsW9JSXV8LKNGfOnM9SlrNJxpcsWdzqsaVKWfY9e9ZyrgoVylq0jx+z/gujZ89eUGhowj3uMmVKWT0WAIB7gZOtAwCQ3hvwsd4b8HGGxkRFRevs6fOqUKmcJKlS5fJWj614v2Xf40cytiJLUseSjK9YuYLWrNxg1dgK95fLUJau3TtozP8+lqOjo3Eu8lak3u3/kf78fZV1geOd/O+MYmNjjbmKFLNuO5G7PAq4W7ST7n0LAEmdPnbaKEgpXaG0TCaTVdtL+vj5yKtQQsHeqWNnspQhsXL3W/8hZ9kkH4ieOpo8R0GfgvItXEiFihTSpbOXde2S9XttJ11VIemWhimp85jlNnv/rN5q9fMBQGadPHbaKF65LwPX80J+PvJOdD0/efRUpjOcOGp5PS+f5H11WspVsrzhfvJY6jlcXF0UEx1j9Qo6sbGxCrkRamzV5+rmanUuAAAAICX9+ryvfn3ez9CYqKgonTp5VvdXriBJqpJkhfO0VI4fc9eRw8dT6WmdpOOrVK2kFcvXWpnFMvfhQ5ZzuSV5vx0dHZOhbOHhEUbhkIuLc4bGAgCQ37EyDZCH7d11wDguX7Gs1Xut1qpT3aK9Z9f+LOU4fPCYbif69mnNhx+0emyt2glZrly+psuXrqbat/Nz7fT5159YFNIEBd7Q8x1fy3AhjSTdirilY4cT9o8tX/E+OTlZX2N4X9nSxnFo6E3dyOLeuQDyv8N7jhrHHgXcVa5y2TR6J6hW+wHLeXYfznSGwGtBunox4VpbtWYVq8c+8HBV4zjqdpSOH7Dcg7tDr3ZafmiJft7wvb759Us9/Xwbq+d2cHD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",
-      "text/plain": [
-       "<Figure size 3000x1800 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "corr_wip = df[['wip', 'smv', 'over_time', 'idle_time', 'actual_productivity']].corr()\n",
-    "sns.heatmap(corr_wip, annot=True)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "106b2edb",
-   "metadata": {},
-   "source": [
-    "### Handling Outliers & Missing Values "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "f82de994",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:56.038814Z",
-     "start_time": "2025-04-04T15:19:55.420162Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: xlabel='wip', ylabel='Count'>"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 3000x1800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot to check skewness of the column\n",
-    "sns.histplot(df['wip'], kde=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "1924b36f",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:56.222257Z",
-     "start_time": "2025-04-04T15:19:56.038814Z"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "# Impute missing values\n",
-    "from sklearn.impute import KNNImputer\n",
-    "\n",
-    "imputer = KNNImputer(n_neighbors=5)\n",
-    "df[['wip']] = imputer.fit_transform(df[['wip']])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "e0a04faa",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:56.792916Z",
-     "start_time": "2025-04-04T15:19:56.222257Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: xlabel='over_time', ylabel='Count'>"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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obq5P3XukbyznagAAAAAAAJY3KRagog1NpAf1skJJsBzV1STx3E3dqXvf39UfpVLWAGmgGkwXivGjx4ZS94y9rX6bV6WPv9VRDwAAAAAAIF+CekBFG84I6hl7C8e79pyVqeuPDU3Gg4dHcq4GyNODh4ZjcqaYuieoV/02Z4w2FtQDAAAAAADIl6AeUNGGMkbf6qgHx3vupu7Imm75bw8ezrcYIFdZY2+b62vi/J62nKshb1lBvV19Y1HUURUAAAAAACA3gnpAxSqVSpmjb9sF9eA4nc31cfWZ6eNvv/HQkZgupHfbAirfXRlBvWet74y6Wr8OVLtzM4J6Y9OFODQ0mXM1AAAAAAAAy5d35oCKNTlTjOlCeieYDqNvYY5XXNyTuj4wPh0/2H0s52qAPMwUS/Gjx4ZS964w9nZZOGdVS+beI8bfAgAAAAAA5EZQD6hYwxljbyN01IM0Lzx3VbTU16bufc34W6hK23tHYnSqkLp3paDestDaUBfrOxpT93YK6gEAAAAAAORGUA+oWFljb2uTJDOMBMtZc31tvGjLqtS97+3qj8Hx6ZwrAhbbXfsGUtcb62riorXt+RbDkjknY/ytoB4AAAAAAEB+BPWAipXVUa+9qS6SJMm5GqgMr7xoTer6dKEU39xxJOdqgMX2w4yg3qXrO6Khzq8Cy8XmzKDeWM6VAAAAAAAALF/enQMqVlZHvY4m3fQgy5UbO2NNe/oIxP/9QG/O1QCLaaZQjHv2D6XuXbXR2Nvl5NyMoN6eo2MxUyjmXA0AAAAAAMDyJKgHVKysoF57Y13OlUDlqEmSeMVFPal79x0cikePjedcEbBYHuodibHpQure1g1d+RbDktq8qiV1faZYir3O+wAAAAAAALkQ1AMqVtbo246m+pwrgcryigvTx99GRHztwcM5VgIsph8+OpC63lhXExeva8+3GJbUphUtUVuTpO7t7BvNuRoAAAAAAIDlSVAPqEiFYilGJ9O7BLU36agHJ7JpZUtcvDY9pPNvDx6OYqmUc0XAYrhz/2Dq+rPWd0R9rV8DlpP62po4s7s5dU9QDwAAAAAAIB/eoQMq0sjkTGRFiTqMvoVn9IqL0rvqPTY0GfccSA/3AJVjplCMezN+lq86syvfYigLm1e2pq7v7BvLuRIAAAAAAIDlSVAPqEhDGWNvIyLaG2tzrAQq00vPXx11GWMQv/ZAb87VAAvtwcMjMT5dTN27ckNnztVQDs5d3ZK6/oiOegAAAAAAALkQ1AMq0vBEelCvpb426ozzg2fU1VIf156zInXvmzuOxMR0+mhpoDLcuW8gdb25viZz9DXVLauj3oHBiRh3zgcAAAAAAFh00ixARRrKCOq1Nxl7Cycra/zt6FQhvruzP+dqgIX0w0cHUtefdUanQPsyde7q9KBeRMSufuNvAQAAAAAAFpt36YCKNJwx+rZDUA9O2vPOXhGdGT8z//vBwzlXAyyU6UIx7n1sKHVvq7G3y9b6zqZoqkv/9W/nEeNvAQAAAAAAFpugHlCRsjrqdTQK6sHJaqiriZecvzp179Y9x6JvdCrnioCF8MDB4ZicKabuXXVmV77FUDZqkiTOWZXeVW9nv6AeAAAAAADAYhPUAypOqVTK7Khn9C3MzysvTh9/WyxFfGNbb87VAAvhzv0Dqest9bVxQU9bvsVQVjavbEldf0RHPQAAAAAAgEUnqAdUnImZYkwXSql7Rt/C/Fy8tj3O7G5O3TP+FirTD/cNpq5fvqEj6mq9/F/ONmd21BvLuRIAAAAAAIDlxzt1QMUZzhh7GxHRbvQtzEuSJPHKi9K76j18ZDR29I7kXBFwOqZminHfY0Ope1s3dOVbDGXn3IygXv/oVAyMTedcDQAAAAAAwPIiqAdUnKGMsbd1NUk01zutwXy9/KKezL2vPWj8LVSS+w8NxeRMMXVv65ld+RZD2dm8Kn30bUTEzn7jbwEAAAAAABaTRAtQcYYyOuq1N9ZFkiQ5VwOVb11HU2zd2Jm69/WHemOmmD5qGig/dz6aPva2taE2zu9py7kays3K1obobErvPryzT1APAAAAAABgMQnqARUna/RtR8Ybz8Aze0XG+Nv+0am4fe+xnKsBTtWd+wdS16/Y0Bl1NcLsy12SJLE5Y/ztI4J6AAAAAAAAi0pQD6g4wxmjb9sF9eCUvei8VdFYl/6y4GsPHs65GuBUTM4U477HhlL3tm7syrcYylZWUG9n31jOlQAAAAAAACwvgnpAxckafdvRKKgHp6qtsS5eeO7K1L1vP9IfIxkBWaB83H9wKKYK6aOqs8Zbs/ycu6oldX1n32iUSkadAwAAAAAALBZBPaCizBRLMTpVSN3TUQ9OzysvTh9/OzlTjJt39OVcDTBfP3x0IHW9rbE2tqxuy7cYylZWR73RqUIcHp7MuRoAAAAAAIDlQ1APqCgn6urVIagHp+XZZ3bHqtaG1L3/bfwtlL079w2krl9xRmfU1iT5FkPZygrqRRh/CwAAAAAAsJgE9YCKMpwx9jbi8dGdwKmrq0niJy7sSd27a/9gPDY4kXNFwMmamC7E/YeGU/euOrMr32Ioa22NdbGmvTF175G+0ZyrAQAAAAAAWD4E9YCKMpQR1GttqI063YLgtL3yovTxtxG66kE5+9FjQzFdKKXubd3YlW8xlL1zM7rq7RTUAwAAAAAAWDSCekBFGcoYfWvsLSyMc1e3xpbV6QGOL9zzWExMF3KuCDgZd+4fTF3vaKqL8zJ+plm+Nq9qSV0X1AMAAAAAAFg8gnpARckafdtu7C0smFdenN5V7+jYdHz1AV31oBzd+ehA6vqVGzqjJtFxluNtzuiot+foWMwU0zszAgAAAAAAcHoE9YCKkjX6tl1HPVgwr7hwTTTWpb9E+NQP9wtxQJkZny7EA4eGU/euNPaWFFlBvalCKfYfG8+5GgAAAAAAgOVBUA+oGKVSKYazRt/qqAcLpqulPl572brUvccGJ+Lft/fmXBFwIj86MJQZoL1qY2fO1VAJNq1oidqMRouPGH8LAAAAAACwKAT1gIoxPl3MDCJ06KgHC+r1W8+Iupr0FMff374viiVd9aBc/HDfQOp6Z1NdZuc0lrfGuprY2N2curdTUA8AAAAAAGBRCOoBFSOrm16E0bew0NZ2NMXLL+xJ3dvZNxb/setozhUBWe7cN5i6fuXGrqhJMtqmsexlhTh39o/lXAkAAAAAAMDyIKgHVIyhifSgXn1NEk11Tmew0H756o2RFfH5xG37oqSrHiy5salCPHh4OHXP2FtOZPPKjKCejnoAAAAAAACLQrIFqBjDGUG99qa6SHQMggW3aUVL/B/nrUrdu+/gUNy1P72LF5Cfex8bjELGWPgrN3blWwwVZfPq9KDevmPjMTFdyLkaAAAAAACA6ieoB1SMoYzRtx3G3sKieeM1GzP3PnH7vhwrAdL88NH0wGxXc31sXtmSczVUkqzvj1JE7D5q/C0AAAAAAMBCE9QDKkbW6Nv2RkE9WCwXrmmPa87qSt27dc+xeChj5CaQj7v2D6Sub93YqdssJ7Shqzka69J/HTT+FgAAAAAAYOEJ6gEVI2v0rY56sLjeePWZmXt/r6seLJnRqZnYdig9LLvV2FueQW1NEmevSO+qt7NPRz0AAAAAAICFJqgHVISZQjHGpgupe+2CerCotm7sjEvWtafu3bSjL/YakQhL4p79Q1Eope9t3diZbzFUpM2r0oN6j+ioBwAAAAAAsOAE9YCKMDyZHtKLiOgw+hYWVZIk8carN6bulSLiU3fsz7cgICIi7tw3kLq+oqU+s1MaPNXmVa2p67sE9QAAAAAAABacoB5QEYYm08feJhHRJqgHi+7HN6+Mc1amB3/+94OH4/DwZM4VAT/MCOpt3dgVSZLkWwwVKSuo1zsyFUMT0zlXAwAAAAAAUN0E9YCKMDyRHtRrbayN2hphBFhsNUkSb8joqjdTLMWnf6irHuRpZHImtveOpO4Ze8vJOjcjqBcRsbPPWHMAAAAAAICFJKgHVISsoF67bnqQm5de0BPrOxpT9/7lRwdjYEz3JcjL3fsHo1hK39u6sSvXWqhcq9saMl9LPWL8LQAAAAAAwIIS1AMqwtBkegCoo0lQD/JSV5PELz47vavexEwxPnf3gZwrguXrzn2DqesrWxvirO7mnKuhUiVJEueuSh9rvlNQDwAAAAAAYEEJ6gEVYWiikLouqAf5evXFa2JFS33q3ufveSxGp9K7XwIL6/ZHj6WuX7WxM5LESHhO3jkZ4293CeoBAAAAAAAsKEE9oOyVSiWjb6FMNNXXxvVXnpG6NzQxE//yo0M5VwTLT9/oVDx8JD1EdaWxt8zT5oyg3iN9Y1EqZcxXBgAAAAAAYN4E9YCyNzZdiELGG8U66kH+fuby9dHaUJu695k798fUTDHnimB5uX1veje9iIhrzurKrxCqwrkZQb3hyZk4MjKVczUAAAAAAADVS1APKHtZ3fQidNSDpdDWWBc/e/n61L0jI1Pxvx88nHNFsLzclhHUO7O7Oc7obM65Gird5lUtmXuPGH8LAAAAAACwYAT1gLI3NJke1GuoTaKxzmkMlsL1W8/I/Pn75B37YqZoXCIshlKpFLfuSQ/qXXNWd87VUA06muqjp60hdW+noB4AAAAAAMCCkXAByl5WR732prpIkiTnaoCIiBUtDfGTl6xN3ds/MBH/dM9jOVcEy8MjfaNxdGw6de85mwT1ODXnZIy/3dk/lnMlAAAAAAAA1UtQDyh7QxlBvQ5jb2FJ/dKzN0RtTXpY9q//Y08cGprIuSKoflnd9Gprkti6sTPnaqgWm1dmBPWO6KgHAAAAAACwUAT1gLI3nDH6tr1JUA+W0rqOpviJC3tS98amC/E/vrUz54qg+t22Nz2od9n6jmhtcF3k1Jy7uiV1fffRsSgYZQ4AAAAAALAgBPWAspfZUU9QD5bcbzxvU7TU16buffuR/vj2w305VwTVa2K6EHfvH0zde85Zxt5y6jZnjL6dnCnG/oHxnKsBAAAAAACoToJ6QFmbLhRjfLqYutdu9C0suTXtjXHDtZsy9//s5kdidCo9bAvMzz0HBmOqkN7d7JpNgnqcurNXtET6IPOIXf1judYCAAAAAABQrQT1gLKWNfY2IqKjqT7HSoAsP3f5+rhwTVvqXu/IVPzN9/fmXBFUp1v3DKSudzbVxQU96T+DcDKa6mtjQ1dT6t6u/tGcqwEAAAAAAKhO2lGVgb1798YrX/nKmJ6ejre85S3x1re+dd7HOHz4cHz+85+P73//+7F79+4YHR2N7u7uWLt2bTz/+c+P17zmNbFx48ZTqm9gYCC+8IUvxPe+9714+OGHY2hoKDo6OmLt2rVxzTXXxGtf+9rYsmXLKR0bnslwxtjbJCLaGtLHbQL5qq1J4p0vOS/e+Om7o5jS7Otzdx+IV1y0Jn58lSARnI5b9x5NXX/2md1RW5PVDw1OzjkrW2PfwMSc9V19OuoBAAAAAAAsBEG9JVYoFOL3f//3Y3p6+pSP8fGPfzz+5//8nzE1NXXcem9vb/T29saPfvSj+F//63/Fm9/85viN3/iNqK09+XDTl7/85fjv//2/x/Dw8HHr/f390d/fHw888ED87d/+bVx//fXxjne8I5qa0jtxwKkaygjqtTXWRo1QApSNC9e0x3+54oz4x7sOzNkrliLe++874qsXrom6Ws184VQcGZmMnRmBqeds6sq3GKrSOata4js7++es79RRj3lIkup8ff70TytJluZzLZXSx58DAAAAAFAZBPWW2Hve85744Q9/eFrP//SnP/2MjysUCvHhD384tm/fHn/xF39xUm8qfOxjH4s/+7M/O6k6/vEf/zG2bdsWn/rUp6KhoeGkngMnYyhj9G17k9MXlJtff95ZcdOOI9E7MjVn76HDI/HJW/bGf7327CWoDCrfbXuPZe5dc1Z3jpVQrTavbE1d33t0PGYKRUFrnlGSJLFqmXTP7e5O/3lZbH19I8J6AAAAAAAVzLstS+h973tffPaznz3l53/mM585LqTX2toab3vb2+Kb3/xm3HffffHNb34z3va2t0Vb25Nvltx4443x4Q9/+BmP/Z3vfCc++MEPzt6vr6+PG264Ib72ta/Fj370o/jud78b7373u2P16tWzj7nnnnvij/7oj07584E0WaNvOxrrc64EeCatDXXxf7/o3Mz9/3Hj9jg4OJ5jRVA9bt2THtTbtKI51nboaMzpO2dVS+r6TLGUOhIXAAAAAACA+RHUWwIjIyPx1re+NT7xiU+c8jH6+vqO63bX1dUV//RP/xRvetObYuPGjdHQ0BAbN26MN73pTfHP//zPxwXqPvrRj8ajjz6aeezJycl417veNfuX+o2NjfF3f/d38bu/+7uxefPmaGxsjDVr1sT1118fX/rSl+Lcc58MZXzpS186rQ6B8HTDOupBRXnheaviBZtXpu6NThXi3V95IOeKoPIVS6W4fe9A6t5zNq3Itxiq1lndLVGb0XR7Z5/xtwAAAAAAAKdLUC9n27Zti9e97nVx4403ntZxPv7xj8fY2Njs/fe+972xefPm1Mdu2rQpPvKRj0RNzeP/uaenp0/YVe+f/umf4uDBg7P3/9t/+2/x7Gc/O/Wxq1atir/+67+OlpYnO3B86EMfmtfnAllKpVJ2Rz1BPShbb3vR5miuT3+J8Y0HDseNDxzKuSKobA/3jsax8enUvecYe8sCaairiY3dzal7u/oF9QAAAAAAAE6XpEtOjh49Gh/5yEfic5/7XMzMPBk8WrFiRRw9enRex5qamoovfvGLs/e3bNkSL37xi0/4nMsvvzxe9rKXxb/9279FRMTXv/71eNe73nXcWNwnfO5zn5u93d3dHddff/0Jj71x48b4hV/4hfjYxz4WERF33nln7Nq1K84555yT/pwgzehUIQql9L2ORqcvKFdrO5rihudtij//9q7U/Xd95YH4sXNX5VwVVK5b96aPva2rSeLKjZ05V0M1O2dla+w5OndE+a7+sZRHwzP765t2xPhU+h/eVJIkSaKpqWH2/sTE1GwH+sXS3FAXN1y3ZVE/BgAAAAAA+dJRLwff//7346UvfWl8+tOfPi6k95znPGc23DYfd911VwwMDMzef+UrX3lSz3vVq141e3tqaipuuummOY/Zt29f7NixY/b+S17ykmhoaJjzuKd79atffdz9r3/96ydVE5xI1tjbCKNvodz93BVnxAU9c8PgEREHByfiz/99R+oeMFdWUO/yMzqiub4252qoZuesbEldN/qWUzU+NRNjU4Wq+Dc+/eS/XD5eFQQcAQAAAAA4nqBeDh5++OEYHh6evd/c3BzvfOc74+/+7u+is3P+XVBuvfXW4+5fc801J/W8q6++OpIkmb3/3e9+d8GOff755x/3uaQdG+ZrKGPsbWNtTTTWOX1BOaurSeL3X3pe1CTp+3/3/d3ROzyZb1FQgcanC3HvgcHUvWuMvWWBbV7Vmrq+79h4TM0Uc64GAAAAAACguki65ChJknjVq14VX/3qV+ONb3xj1NSc2pd/+/btxx3zggsuOKnndXR0xPr162fv33///Sc8dkTEhRdeeFLHTpIkzj///Nn7Dz74YBQKhZN6LmTJCurppgeV4cI17fFzV5yRulcsRdy0oy+Kizw2DirdXfsHYzpjDvxzNgnqsbDOWZXeUa9Qinj02NyRuAAAAAAAAJw8Qb0c1NfXx6tf/er44he/GP/jf/yP2LBhw2kdb9euXbO3e3p6orm5+aSfu3Hjxtnb+/fvnxOm27179+ztJEmOe/x8jj05ORmHDh066edCmqygXoegHlSMG553VvS0pY9Q7x2ZivsPDqfuAY+7bU/62Nuu5vrYkjFeGk7VmV3NUZfRCnVXv/G3AAAAAAAAp0NQLwevf/3r44Mf/GBcdNFFC3K8I0eOzN7u6emZ13NXrVo1e3tmZib6+vqO2+/t7Z293d3dHQ0N6eGKNKtXrz7uvqAep0tQDypfa0Nd/N8vOjdz//a9A7F/QJcmyHJrRlDvmrO6oibJmC0Np6iutibO7E7/I6CdfYJ6AAAAAAAAp0PapcJMTk7G6OiTb5J1dnbO6/lPf/zAwECsWbNm9v7Ro0dP+dgdHR3H3R8cHJzX8xdLbW0SMqnlJS1XkNQkkTxlo1QqxdDEdOrzO5vrj3ssEUnM/XokNeHrdIrSvm61tUmUSr6ep+K6C3rihdsOx7cf7p+zV4qIm3b0x2suWxtdzfX5F1ehfI9me/y6//T7lfk64NDQROw+Opa699yzV0Rtbfl+XqnX+iRxXToNef3cn7u6NXb1z/2+2310vKy/51h61fxzX/O0TpM1NUkUi4v7MV3rAapfNf3uAkD5cH0BYDG4vlBNnv79nDdBvQrz1JBeRERra+u8nt/S0nLC442NPfmm3EIfe6l0drY884NYco0N9VFMnryYj08VYqpQSn3s6s7maG4++W6Py0Fj09yAU1NjQ5RqCimP5pk01dfOWevunt85keP96U8/K178oe/E2NTc78mpQjFu3H4k/stVG1O/9szle/TkVfLrgG/uPJq59xOXb4gVnU05VnP6mpoaolTrunSq8vq5v2Rjd9z40JE563uOjceKFc4zzE+1/tw3Ni7+Hxe41gMsP5X8uwsA5cv1BYDF4PoCp07EtcJMTx/fYay+fn5vENTVHZ/NnJk5frTo1NTUoh0b5mNgfCpzT9ctqDzru5rjPT91Seb+wNh0/Nv9h6JYTA/ownL03YfnhqUiIrasaYu1FRbSo3JsWdOWur6nfzQmpqsvcAUAAAAAAJAXQb0KUygc/+bYfMcI1dQc/5+8+LR5PU89/kIfG+ZjcCx97G19bRItDTpuQSX6ma0b4teuPTtz/9GjY/G9R/pyrAjKV6FYiv/I+Hl4/nmrc66G5WTLmvbU9VIp4pHekZyrAQAAAAAAqB5G31aY2trjA0rzDcM9PejX0HD8+NC6urrZrn0LfeylMjg4FoWMEaosjSSZO7Zpcmo6xiee7MJ4ZGgi9bkdjXUxMZEe4lvOWlJi1xOTUzE+qfPNqUgKc8Ogx46NRsmp5JQ98XP/zldcGA/3jsR3dqR3Crtn30B0NNTEBRlBER7nezRbbW1yXMv1Sn0d8ODBoRjICK1fvq49jh4dzbmi+Um71k9MTMV4yvhrTk5eP/ftSURDbRJTKT83d+/qi/XNfoUkXTX/3NfUJMeNu52cnF70LsCu9QDVr1p+dwGgvLi+ALAYXF+oJk//fs6bd1kqTHNz83H3Jycn5/X8pz/+6WG6pqam2aDeQh97qRQKpSgUdPcrJ2ndGkvFUpSe8q7TUEYYr6Op7rjH8bhSzP2alIrha3WK0r5uhULJ1/M0PPFzX1uTxId/4Yp47V9+P3YeSQ8a/ceuo9HRVBfrOoz2zOJ79ESOTy5X6uuAH+w+mrreUJvEs9a1l/3nlHqtL/kePR15/tyftaIlHk45Rz/cOxqFC8r7e4+lU80/90//G7ZicfE/L9d6gOWgOn53AaDcuL4AsBhcX6gmSzt81ujbCtPe3n5cV72RkfmNn3r647u6uo6739nZuWjHhvkYekp3vafqaKpPXQcqR0dTfXz8Dc+Oxrr0lyHFUsQ3t/dlngdgObh1z7HU9cvP6IymeiPgWVybV7Wmru/qL+9OjgAAAAAAAOVMUK/CJEkSK1asmL1/9Gh6t5UsfX19x91fuXLlcfdXr159ysfu7+8/4bFhPgYzg3oagUI12LSqNV5xUU/M7b3zuImZYtz40JGY8tc4LEOjUzPxo8eGUvees6k752pYjs5Zmd7yfVf/WM6VAAAAAAAAVA9BvQq0YcOG2duHDx+e13Of+viVK1fOGaV7xhlnzN4eHR2dV1e9Q4cOzd5OkiTWr18/r9rgCRPThZicSQ/ndArqQdU4s7s5fuzs7NDRsfHp+NbD/VE04o1l5q59gzFTTP++v+YsQT0W3zkr0zvqPTY4EWNThZyrAQAAAAAAqA6CehVoy5Yts7c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-      "text/plain": [
-       "<Figure size 3000x1800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sns.histplot(df['over_time'],kde=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "id": "cec574df",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:57.324997Z",
-     "start_time": "2025-04-04T15:19:56.795190Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'Count')"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 3000x1800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sns.histplot(df['actual_productivity'], bins=20, kde=True)\n",
-    "plt.title(\"Distribution of Actual Productivity\")\n",
-    "plt.title('Distribution of Actual Productivity')\n",
-    "plt.xlabel('Actual Productivity')\n",
-    "plt.ylabel('Count')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "e3100d2d",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:57.681229Z",
-     "start_time": "2025-04-04T15:19:57.327652Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 3000x1800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for detecting outliers\n",
-    "df[['wip', 'over_time', 'incentive', 'idle_time', 'idle_men']].boxplot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "id": "bb011c49",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:57.699521Z",
-     "start_time": "2025-04-04T15:19:57.681229Z"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "# Handle Outliers\n",
-    "def replace_outliers_with_median(df, column):\n",
-    "    Q1 = df[column].quantile(0.25)\n",
-    "    Q3 = df[column].quantile(0.75)\n",
-    "    IQR = Q3 - Q1\n",
-    "    lower_bound = Q1 - 1.5 * IQR\n",
-    "    upper_bound = Q3 + 1.5 * IQR\n",
-    "    median_value = df[column].median()\n",
-    "    \n",
-    "    # Replace outliers with median\n",
-    "    df[column] = np.where((df[column] < lower_bound) | (df[column] > upper_bound), median_value, df[column])\n",
-    "\n",
-    "# Apply to selected columns\n",
-    "columns_with_outliers = ['wip', 'over_time', 'incentive', 'idle_time', 'idle_men']\n",
-    "for col in columns_with_outliers:\n",
-    "    replace_outliers_with_median(df, col)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "id": "13b10571",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:58.059654Z",
-     "start_time": "2025-04-04T15:19:57.701561Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
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",
-      "text/plain": [
-       "<Figure size 3000x1800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot for confirmation of handeled ouliers \n",
-    "df[['wip', 'over_time', 'incentive', 'idle_time', 'idle_men']].boxplot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "id": "e9156427",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-04T15:19:58.090166Z",
-     "start_time": "2025-04-04T15:19:58.061255Z"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "df['actual_productivity'] = df.pop('actual_productivity') \n",
-    "\n",
-    "# Save the DataFrame to the processed data directory\n",
-    "df.to_csv(\"../../data/processed/SM_Regression_Suraj.csv\", index=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "08a8c26e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "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": "3.11.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/notebooks/regression/Regression_Preprocessed.ipynb b/notebooks/regression/Regression_Preprocessed.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..72737ca62431858194ccc2011c0421cdf674b29c
--- /dev/null
+++ b/notebooks/regression/Regression_Preprocessed.ipynb
@@ -0,0 +1,2134 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 261,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "from sklearn.preprocessing import LabelEncoder\n",
+    "import plotly.express as px\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 262,
+   "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>date</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>department</th>\n",
+       "      <th>day</th>\n",
+       "      <th>team</th>\n",
+       "      <th>targeted_productivity</th>\n",
+       "      <th>smv</th>\n",
+       "      <th>wip</th>\n",
+       "      <th>over_time</th>\n",
+       "      <th>incentive</th>\n",
+       "      <th>idle_time</th>\n",
+       "      <th>idle_men</th>\n",
+       "      <th>no_of_style_change</th>\n",
+       "      <th>no_of_workers</th>\n",
+       "      <th>actual_productivity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1/1/2015</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sweing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>8</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>26.16</td>\n",
+       "      <td>1108.0</td>\n",
+       "      <td>7080</td>\n",
+       "      <td>98</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>0.940725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1/1/2015</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>finishing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>3.94</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>960</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.886500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1/1/2015</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sweing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>11.41</td>\n",
+       "      <td>968.0</td>\n",
+       "      <td>3660</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30.5</td>\n",
+       "      <td>0.800570</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1/1/2015</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sweing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>11.41</td>\n",
+       "      <td>968.0</td>\n",
+       "      <td>3660</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30.5</td>\n",
+       "      <td>0.800570</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1/1/2015</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sweing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>25.90</td>\n",
+       "      <td>1170.0</td>\n",
+       "      <td>1920</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>0.800382</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1192</th>\n",
+       "      <td>3/11/2015</td>\n",
+       "      <td>Quarter2</td>\n",
+       "      <td>finishing</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>2.90</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>960</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.628333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1193</th>\n",
+       "      <td>3/11/2015</td>\n",
+       "      <td>Quarter2</td>\n",
+       "      <td>finishing</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>8</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>3.90</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>960</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.625625</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1194</th>\n",
+       "      <td>3/11/2015</td>\n",
+       "      <td>Quarter2</td>\n",
+       "      <td>finishing</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>3.90</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>960</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.625625</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1195</th>\n",
+       "      <td>3/11/2015</td>\n",
+       "      <td>Quarter2</td>\n",
+       "      <td>finishing</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>9</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>2.90</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1800</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>0.505889</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1196</th>\n",
+       "      <td>3/11/2015</td>\n",
+       "      <td>Quarter2</td>\n",
+       "      <td>finishing</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>2.90</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>720</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0.394722</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1197 rows × 15 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           date   quarter  department        day  team  targeted_productivity  \\\n",
+       "0      1/1/2015  Quarter1      sweing   Thursday     8                   0.80   \n",
+       "1      1/1/2015  Quarter1  finishing    Thursday     1                   0.75   \n",
+       "2      1/1/2015  Quarter1      sweing   Thursday    11                   0.80   \n",
+       "3      1/1/2015  Quarter1      sweing   Thursday    12                   0.80   \n",
+       "4      1/1/2015  Quarter1      sweing   Thursday     6                   0.80   \n",
+       "...         ...       ...         ...        ...   ...                    ...   \n",
+       "1192  3/11/2015  Quarter2   finishing  Wednesday    10                   0.75   \n",
+       "1193  3/11/2015  Quarter2   finishing  Wednesday     8                   0.70   \n",
+       "1194  3/11/2015  Quarter2   finishing  Wednesday     7                   0.65   \n",
+       "1195  3/11/2015  Quarter2   finishing  Wednesday     9                   0.75   \n",
+       "1196  3/11/2015  Quarter2   finishing  Wednesday     6                   0.70   \n",
+       "\n",
+       "        smv     wip  over_time  incentive  idle_time  idle_men  \\\n",
+       "0     26.16  1108.0       7080         98        0.0         0   \n",
+       "1      3.94     NaN        960          0        0.0         0   \n",
+       "2     11.41   968.0       3660         50        0.0         0   \n",
+       "3     11.41   968.0       3660         50        0.0         0   \n",
+       "4     25.90  1170.0       1920         50        0.0         0   \n",
+       "...     ...     ...        ...        ...        ...       ...   \n",
+       "1192   2.90     NaN        960          0        0.0         0   \n",
+       "1193   3.90     NaN        960          0        0.0         0   \n",
+       "1194   3.90     NaN        960          0        0.0         0   \n",
+       "1195   2.90     NaN       1800          0        0.0         0   \n",
+       "1196   2.90     NaN        720          0        0.0         0   \n",
+       "\n",
+       "      no_of_style_change  no_of_workers  actual_productivity  \n",
+       "0                      0           59.0             0.940725  \n",
+       "1                      0            8.0             0.886500  \n",
+       "2                      0           30.5             0.800570  \n",
+       "3                      0           30.5             0.800570  \n",
+       "4                      0           56.0             0.800382  \n",
+       "...                  ...            ...                  ...  \n",
+       "1192                   0            8.0             0.628333  \n",
+       "1193                   0            8.0             0.625625  \n",
+       "1194                   0            8.0             0.625625  \n",
+       "1195                   0           15.0             0.505889  \n",
+       "1196                   0            6.0             0.394722  \n",
+       "\n",
+       "[1197 rows x 15 columns]"
+      ]
+     },
+     "execution_count": 262,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(\"C:/Users/ritwi/garments_worker_productivity.csv\")\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 263,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 1197 entries, 0 to 1196\n",
+      "Data columns (total 15 columns):\n",
+      " #   Column                 Non-Null Count  Dtype  \n",
+      "---  ------                 --------------  -----  \n",
+      " 0   date                   1197 non-null   object \n",
+      " 1   quarter                1197 non-null   object \n",
+      " 2   department             1197 non-null   object \n",
+      " 3   day                    1197 non-null   object \n",
+      " 4   team                   1197 non-null   int64  \n",
+      " 5   targeted_productivity  1197 non-null   float64\n",
+      " 6   smv                    1197 non-null   float64\n",
+      " 7   wip                    691 non-null    float64\n",
+      " 8   over_time              1197 non-null   int64  \n",
+      " 9   incentive              1197 non-null   int64  \n",
+      " 10  idle_time              1197 non-null   float64\n",
+      " 11  idle_men               1197 non-null   int64  \n",
+      " 12  no_of_style_change     1197 non-null   int64  \n",
+      " 13  no_of_workers          1197 non-null   float64\n",
+      " 14  actual_productivity    1197 non-null   float64\n",
+      "dtypes: float64(6), int64(5), object(4)\n",
+      "memory usage: 140.4+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 264,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "🔹 Value counts for 'date':\n",
+      "3/11/2015    24\n",
+      "1/31/2015    24\n",
+      "1/11/2015    23\n",
+      "1/12/2015    23\n",
+      "3/10/2015    23\n",
+      "1/24/2015    23\n",
+      "1/8/2015     22\n",
+      "1/10/2015    22\n",
+      "3/9/2015     22\n",
+      "3/3/2015     22\n",
+      "1/13/2015    22\n",
+      "1/7/2015     22\n",
+      "1/5/2015     22\n",
+      "1/22/2015    22\n",
+      "3/8/2015     22\n",
+      "2/26/2015    21\n",
+      "3/4/2015     21\n",
+      "2/25/2015    21\n",
+      "1/25/2015    21\n",
+      "1/6/2015     21\n",
+      "1/3/2015     21\n",
+      "1/4/2015     21\n",
+      "2/28/2015    21\n",
+      "1/14/2015    21\n",
+      "1/28/2015    21\n",
+      "1/17/2015    21\n",
+      "2/18/2015    21\n",
+      "1/27/2015    21\n",
+      "3/1/2015     20\n",
+      "3/2/2015     20\n",
+      "2/17/2015    20\n",
+      "2/22/2015    20\n",
+      "2/19/2015    20\n",
+      "1/29/2015    20\n",
+      "3/5/2015     19\n",
+      "2/4/2015     19\n",
+      "2/8/2015     19\n",
+      "3/7/2015     19\n",
+      "1/19/2015    19\n",
+      "2/7/2015     19\n",
+      "1/21/2015    19\n",
+      "2/2/2015     19\n",
+      "2/23/2015    19\n",
+      "1/1/2015     19\n",
+      "2/11/2015    19\n",
+      "2/24/2015    19\n",
+      "1/18/2015    19\n",
+      "2/15/2015    19\n",
+      "2/10/2015    19\n",
+      "1/15/2015    19\n",
+      "2/3/2015     19\n",
+      "1/26/2015    19\n",
+      "2/1/2015     19\n",
+      "2/12/2015    19\n",
+      "2/5/2015     18\n",
+      "2/16/2015    18\n",
+      "2/9/2015     18\n",
+      "2/14/2015    17\n",
+      "1/20/2015    15\n",
+      "Name: date, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'quarter':\n",
+      "Quarter1    360\n",
+      "Quarter2    335\n",
+      "Quarter4    248\n",
+      "Quarter3    210\n",
+      "Quarter5     44\n",
+      "Name: quarter, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'department':\n",
+      "sweing        691\n",
+      "finishing     257\n",
+      "finishing     249\n",
+      "Name: department, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'day':\n",
+      "Wednesday    208\n",
+      "Sunday       203\n",
+      "Tuesday      201\n",
+      "Thursday     199\n",
+      "Monday       199\n",
+      "Saturday     187\n",
+      "Name: day, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'team':\n",
+      "8     109\n",
+      "2     109\n",
+      "4     105\n",
+      "1     105\n",
+      "9     104\n",
+      "10    100\n",
+      "12     99\n",
+      "7      96\n",
+      "3      95\n",
+      "6      94\n",
+      "5      93\n",
+      "11     88\n",
+      "Name: team, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'targeted_productivity':\n",
+      "0.80    540\n",
+      "0.70    242\n",
+      "0.75    216\n",
+      "0.65     63\n",
+      "0.60     57\n",
+      "0.50     49\n",
+      "0.35     27\n",
+      "0.40      2\n",
+      "0.07      1\n",
+      "Name: targeted_productivity, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'smv':\n",
+      "3.94     192\n",
+      "2.90     108\n",
+      "22.52    103\n",
+      "30.10     79\n",
+      "4.15      76\n",
+      "        ... \n",
+      "20.20      1\n",
+      "20.55      1\n",
+      "50.89      1\n",
+      "26.87      1\n",
+      "42.41      1\n",
+      "Name: smv, Length: 70, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'wip':\n",
+      "NaN       506\n",
+      "1039.0      5\n",
+      "1282.0      4\n",
+      "968.0       3\n",
+      "1144.0      3\n",
+      "         ... \n",
+      "1186.0      1\n",
+      "891.0       1\n",
+      "1498.0      1\n",
+      "551.0       1\n",
+      "1239.0      1\n",
+      "Name: wip, Length: 549, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'over_time':\n",
+      "960      129\n",
+      "1440     111\n",
+      "6960      61\n",
+      "6840      48\n",
+      "1200      39\n",
+      "        ... \n",
+      "5580       1\n",
+      "13800      1\n",
+      "8970       1\n",
+      "7680       1\n",
+      "2040       1\n",
+      "Name: over_time, Length: 143, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'incentive':\n",
+      "0       604\n",
+      "50      113\n",
+      "63       61\n",
+      "45       54\n",
+      "30       52\n",
+      "23       38\n",
+      "38       29\n",
+      "60       28\n",
+      "40       27\n",
+      "75       24\n",
+      "113      21\n",
+      "88       19\n",
+      "34       17\n",
+      "56       14\n",
+      "26        9\n",
+      "55        7\n",
+      "81        7\n",
+      "100       7\n",
+      "69        6\n",
+      "65        6\n",
+      "70        6\n",
+      "960       5\n",
+      "35        5\n",
+      "94        4\n",
+      "44        4\n",
+      "90        3\n",
+      "46        2\n",
+      "24        2\n",
+      "27        2\n",
+      "119       2\n",
+      "49        2\n",
+      "98        1\n",
+      "21        1\n",
+      "1200      1\n",
+      "62        1\n",
+      "25        1\n",
+      "1080      1\n",
+      "93        1\n",
+      "29        1\n",
+      "1440      1\n",
+      "32        1\n",
+      "33        1\n",
+      "2880      1\n",
+      "54        1\n",
+      "37        1\n",
+      "138       1\n",
+      "53        1\n",
+      "3600      1\n",
+      "Name: incentive, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'idle_time':\n",
+      "0.0      1179\n",
+      "3.5         3\n",
+      "4.0         2\n",
+      "4.5         2\n",
+      "8.0         2\n",
+      "5.0         2\n",
+      "2.0         2\n",
+      "270.0       1\n",
+      "150.0       1\n",
+      "6.5         1\n",
+      "300.0       1\n",
+      "90.0        1\n",
+      "Name: idle_time, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'idle_men':\n",
+      "0     1179\n",
+      "30       3\n",
+      "20       3\n",
+      "15       3\n",
+      "10       3\n",
+      "35       2\n",
+      "45       1\n",
+      "40       1\n",
+      "37       1\n",
+      "25       1\n",
+      "Name: idle_men, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'no_of_style_change':\n",
+      "0    1050\n",
+      "1     114\n",
+      "2      33\n",
+      "Name: no_of_style_change, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'no_of_workers':\n",
+      "8.0     262\n",
+      "58.0    114\n",
+      "57.0    109\n",
+      "59.0     75\n",
+      "10.0     60\n",
+      "       ... \n",
+      "29.5      1\n",
+      "11.0      1\n",
+      "21.0      1\n",
+      "6.0       1\n",
+      "33.5      1\n",
+      "Name: no_of_workers, Length: 61, dtype: int64\n",
+      "\n",
+      "🔹 Value counts for 'actual_productivity':\n",
+      "0.800402    24\n",
+      "0.971867    12\n",
+      "0.850137    12\n",
+      "0.750651    11\n",
+      "0.850502    11\n",
+      "            ..\n",
+      "0.460579     1\n",
+      "0.852794     1\n",
+      "0.585316     1\n",
+      "1.000457     1\n",
+      "0.700888     1\n",
+      "Name: actual_productivity, Length: 879, dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "for col in df.columns:\n",
+    "    print(f\"\\n🔹 Value counts for '{col}':\")\n",
+    "    print(df[col].value_counts(dropna=False))  # This shows all values\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 265,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Impute missing 'wip' with median\n",
+    "df['wip'] = df['wip'].fillna(df['wip'].median())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 266,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "date                     0\n",
+       "quarter                  0\n",
+       "department               0\n",
+       "day                      0\n",
+       "team                     0\n",
+       "targeted_productivity    0\n",
+       "smv                      0\n",
+       "wip                      0\n",
+       "over_time                0\n",
+       "incentive                0\n",
+       "idle_time                0\n",
+       "idle_men                 0\n",
+       "no_of_style_change       0\n",
+       "no_of_workers            0\n",
+       "actual_productivity      0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 266,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 267,
+   "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>team</th>\n",
+       "      <th>targeted_productivity</th>\n",
+       "      <th>smv</th>\n",
+       "      <th>wip</th>\n",
+       "      <th>over_time</th>\n",
+       "      <th>incentive</th>\n",
+       "      <th>idle_time</th>\n",
+       "      <th>idle_men</th>\n",
+       "      <th>no_of_style_change</th>\n",
+       "      <th>no_of_workers</th>\n",
+       "      <th>actual_productivity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "      <td>1197.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>6.426901</td>\n",
+       "      <td>0.729632</td>\n",
+       "      <td>15.062172</td>\n",
+       "      <td>1126.437761</td>\n",
+       "      <td>4567.460317</td>\n",
+       "      <td>38.210526</td>\n",
+       "      <td>0.730159</td>\n",
+       "      <td>0.369256</td>\n",
+       "      <td>0.150376</td>\n",
+       "      <td>34.609858</td>\n",
+       "      <td>0.735091</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>3.463963</td>\n",
+       "      <td>0.097891</td>\n",
+       "      <td>10.943219</td>\n",
+       "      <td>1397.653191</td>\n",
+       "      <td>3348.823563</td>\n",
+       "      <td>160.182643</td>\n",
+       "      <td>12.709757</td>\n",
+       "      <td>3.268987</td>\n",
+       "      <td>0.427848</td>\n",
+       "      <td>22.197687</td>\n",
+       "      <td>0.174488</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.070000</td>\n",
+       "      <td>2.900000</td>\n",
+       "      <td>7.000000</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>2.000000</td>\n",
+       "      <td>0.233705</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>0.700000</td>\n",
+       "      <td>3.940000</td>\n",
+       "      <td>970.000000</td>\n",
+       "      <td>1440.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>9.000000</td>\n",
+       "      <td>0.650307</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>15.260000</td>\n",
+       "      <td>1039.000000</td>\n",
+       "      <td>3960.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>34.000000</td>\n",
+       "      <td>0.773333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>9.000000</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>24.260000</td>\n",
+       "      <td>1083.000000</td>\n",
+       "      <td>6960.000000</td>\n",
+       "      <td>50.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>57.000000</td>\n",
+       "      <td>0.850253</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>12.000000</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>54.560000</td>\n",
+       "      <td>23122.000000</td>\n",
+       "      <td>25920.000000</td>\n",
+       "      <td>3600.000000</td>\n",
+       "      <td>300.000000</td>\n",
+       "      <td>45.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>89.000000</td>\n",
+       "      <td>1.120437</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              team  targeted_productivity          smv           wip  \\\n",
+       "count  1197.000000            1197.000000  1197.000000   1197.000000   \n",
+       "mean      6.426901               0.729632    15.062172   1126.437761   \n",
+       "std       3.463963               0.097891    10.943219   1397.653191   \n",
+       "min       1.000000               0.070000     2.900000      7.000000   \n",
+       "25%       3.000000               0.700000     3.940000    970.000000   \n",
+       "50%       6.000000               0.750000    15.260000   1039.000000   \n",
+       "75%       9.000000               0.800000    24.260000   1083.000000   \n",
+       "max      12.000000               0.800000    54.560000  23122.000000   \n",
+       "\n",
+       "          over_time    incentive    idle_time     idle_men  \\\n",
+       "count   1197.000000  1197.000000  1197.000000  1197.000000   \n",
+       "mean    4567.460317    38.210526     0.730159     0.369256   \n",
+       "std     3348.823563   160.182643    12.709757     3.268987   \n",
+       "min        0.000000     0.000000     0.000000     0.000000   \n",
+       "25%     1440.000000     0.000000     0.000000     0.000000   \n",
+       "50%     3960.000000     0.000000     0.000000     0.000000   \n",
+       "75%     6960.000000    50.000000     0.000000     0.000000   \n",
+       "max    25920.000000  3600.000000   300.000000    45.000000   \n",
+       "\n",
+       "       no_of_style_change  no_of_workers  actual_productivity  \n",
+       "count         1197.000000    1197.000000          1197.000000  \n",
+       "mean             0.150376      34.609858             0.735091  \n",
+       "std              0.427848      22.197687             0.174488  \n",
+       "min              0.000000       2.000000             0.233705  \n",
+       "25%              0.000000       9.000000             0.650307  \n",
+       "50%              0.000000      34.000000             0.773333  \n",
+       "75%              0.000000      57.000000             0.850253  \n",
+       "max              2.000000      89.000000             1.120437  "
+      ]
+     },
+     "execution_count": 267,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 268,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([735599., 735613., 735630., 735644., 735658.]),\n",
+       " <a list of 5 Text xticklabel objects>)"
+      ]
+     },
+     "execution_count": 268,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Type Conversion of 'Date' column\n",
+    "df['date'] = pd.to_datetime(df['date'], format='%m/%d/%Y')\n",
+    "\n",
+    "# Time Series Plot of 'Productivity'\n",
+    "plt.figure(figsize=(12,5))\n",
+    "df.groupby('date')['actual_productivity'].mean().plot(marker='o', color='purple')\n",
+    "plt.title('Productivity Trend Over Time')\n",
+    "plt.xlabel('Date')\n",
+    "plt.ylabel('Average Productivity')\n",
+    "plt.xticks(rotation=45)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**The time series plot of average productivity reveals noticeable fluctuations over the observed period. While productivity initially starts high in early January, a gradual decline is seen mid-month, followed by a brief spike around early February. However, productivity dips again in mid-February and shows slight recovery toward early March. These trends may reflect seasonal, operational, or workforce-related factors, indicating that time-dependent patterns should be considered in productivity modeling.**\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 269,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 900x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "# Group and sort average productivity by day\n",
+    "day_order = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Saturday']\n",
+    "avg_by_day = df.groupby('day')['actual_productivity'].mean().reindex(day_order)\n",
+    "\n",
+    "# Define color palette\n",
+    "colors = plt.cm.viridis(np.linspace(0.2, 0.9, len(avg_by_day)))\n",
+    "\n",
+    "# Create the donut chart\n",
+    "fig, ax = plt.subplots(figsize=(6, 6), dpi=150)\n",
+    "wedges, texts, autotexts = ax.pie(\n",
+    "    avg_by_day,\n",
+    "    labels=day_order,\n",
+    "    autopct=lambda pct: f'{pct * avg_by_day.sum() / 100:.2f}',\n",
+    "    startangle=90,\n",
+    "    colors=colors,\n",
+    "    wedgeprops={'width': 0.3, 'edgecolor': 'white'},\n",
+    "    textprops={'fontsize': 11}\n",
+    ")\n",
+    "\n",
+    "# Optional: add a center label (e.g., Total)\n",
+    "ax.text(0, 0, '100%', ha='center', va='center', fontsize=13, fontweight='bold')\n",
+    "\n",
+    "# Final formatting\n",
+    "ax.set_title('Productivity Share by Day (Donut Chart)', fontsize=14, fontweight='bold', pad=20)\n",
+    "ax.axis('equal')  # Keeps it circular\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Average productivity remains stable throughout the week, ranging narrowly between 0.72 and 0.75.**\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 270,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Quarter1' 'Quarter2' 'Quarter3' 'Quarter4' 'Quarter5']\n",
+      "['sweing' 'finishing ' 'finishing']\n",
+      "['Thursday' 'Saturday' 'Sunday' 'Monday' 'Tuesday' 'Wednesday']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(df['quarter'].unique())\n",
+    "print(df['department'].unique())\n",
+    "print(df['day'].unique())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 271,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1. Fix department issues\n",
+    "df['department'] = df['department'].str.strip().str.lower()\n",
+    "df['department'] = df['department'].replace({'sweing': 'sewing'})\n",
+    "\n",
+    "# 2. (Optional) Standardize quarter\n",
+    "df['quarter'] = df['quarter'].str.strip().str.capitalize()  # e.g., Quarter1 → Quarter1\n",
+    "\n",
+    "# 3. Strip and standardize 'day' names\n",
+    "df['day'] = df['day'].str.strip().str.capitalize()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 272,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Quarter1' 'Quarter2' 'Quarter3' 'Quarter4' 'Quarter5']\n",
+      "['sewing' 'finishing']\n",
+      "['Thursday' 'Saturday' 'Sunday' 'Monday' 'Tuesday' 'Wednesday']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(df['quarter'].unique())\n",
+    "print(df['department'].unique())\n",
+    "print(df['day'].unique())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 273,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1008x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "# Clean department name (fix typo)\n",
+    "df['department'] = df['department'].str.replace('sweing', 'sewing', case=False)\n",
+    "\n",
+    "# Group by department and team, then calculate average productivity\n",
+    "team_avg = df.groupby(['department', 'team'], as_index=False)['actual_productivity'].mean()\n",
+    "\n",
+    "# Plotting\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "ax = sns.barplot(\n",
+    "    data=team_avg,\n",
+    "    x='team',\n",
+    "    y='actual_productivity',\n",
+    "    hue='department',\n",
+    "    palette='Set2'\n",
+    ")\n",
+    "\n",
+    "# Titles and labels\n",
+    "plt.title('Average Productivity by Team and Department')\n",
+    "plt.xlabel('Team')\n",
+    "plt.ylabel('Average Productivity')\n",
+    "plt.legend(title='Department', loc='upper right')\n",
+    "plt.ylim(0, 1)  # Optional: Set y-axis max for consistency\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "# Optional: Add value labels on top of bars\n",
+    "for bar in ax.patches:\n",
+    "    height = bar.get_height()\n",
+    "    ax.annotate(f'{height:.2f}',\n",
+    "                xy=(bar.get_x() + bar.get_width() / 2, height),\n",
+    "                xytext=(0, 3),  # Offset text slightly above bar\n",
+    "                textcoords=\"offset points\",\n",
+    "                ha='center', va='bottom', fontsize=8)\n",
+    "\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**This grouped bar chart compares the average productivity of each team across the finishing and sewing departments. While productivity levels are relatively close between departments for most teams, certain teams (e.g., Team 3 and Team 5) in the finishing department outperform their counterparts, indicating possible differences in efficiency or workflow.**\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 274,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Actual Productivity')"
+      ]
+     },
+     "execution_count": 274,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for Average 'Productivity' by 'Department'\n",
+    "plt.figure(figsize=(8,5))\n",
+    "sns.barplot(x=df['department'], y=df['actual_productivity'], estimator=np.mean, palette='coolwarm')\n",
+    "plt.title('Average Productivity by Department')\n",
+    "plt.xlabel('Department')\n",
+    "plt.ylabel('Actual Productivity')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Bar chart compares average productivity between departments, showing a slightly higher performance in the finishing department.**\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 275,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([0, 1]), <a list of 2 Text xticklabel objects>)"
+      ]
+     },
+     "execution_count": 275,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot for 'Targeted' & 'Actual Productivity' Distribution by Department\n",
+    "plt.figure(figsize=(10,6))\n",
+    "df_melted = df.melt(id_vars=['department'], value_vars=['targeted_productivity', 'actual_productivity'], var_name=\"Type\", value_name=\"Productivity\")\n",
+    "\n",
+    "sns.boxplot(x='department', y='Productivity', hue='Type', data=df_melted, palette='coolwarm')\n",
+    "plt.title(\"Targeted vs. Actual Productivity Distribution by Department\")\n",
+    "plt.xlabel(\"Department\")\n",
+    "plt.ylabel(\"Productivity\")\n",
+    "plt.legend(title=\"Productivity Type\")\n",
+    "plt.xticks(rotation=45)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**This boxplot compares targeted and actual productivity distributions for each department. While median actual productivity in both departments is close to the target, the finishing department shows higher variability, with several instances exceeding the target. In contrast, sewing is more consistent but includes more low-performing outliers.**\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 276,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 1. Bin 'over_time' values\n",
+    "df['overtime_bin'] = pd.cut(\n",
+    "    df['over_time'],\n",
+    "    bins=[-1, 500, 1000, 2000, 5000, 10000, 20000, float('inf')],\n",
+    "    labels=['0-500', '501-1000', '1001-2000', '2001-5000', '5001-10000', '10001-20000', '20001+']\n",
+    ")\n",
+    "\n",
+    "\n",
+    "# 2. Group and average\n",
+    "incentive_avg = df.groupby('overtime_bin')['incentive'].mean().reset_index()\n",
+    "\n",
+    "# 3. Plot\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.barplot(data=incentive_avg, x='overtime_bin', y='incentive', palette='Blues')\n",
+    "\n",
+    "plt.title('Average Incentive by Overtime Bin')\n",
+    "plt.xlabel('Overtime (Minutes, Binned)')\n",
+    "plt.ylabel('Average Incentive (BDT)')\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**This bar chart shows the average incentive paid across different overtime bins. While incentives remain relatively low across all overtime levels, there is a slight upward trend, suggesting limited correlation between increased overtime and incentive payout.**\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 277,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.preprocessing import LabelEncoder\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "def preprocess_data(df, model_type='svm'):\n",
+    "    df = df.copy()\n",
+    "\n",
+    "    # Clip productivity values\n",
+    "    df['actual_productivity'] = df['actual_productivity'].clip(upper=1.0)\n",
+    "\n",
+    "    # Create day_num from date\n",
+    "    df['day_num'] = df['date'].dt.weekday\n",
+    "\n",
+    "    # Shared encodings\n",
+    "    if model_type in ['svm', 'perceptron']:\n",
+    "        # ✅ Cyclical encoding for 'day'\n",
+    "        df['day_sin'] = np.sin(2 * np.pi * df['day_num'] / 7)\n",
+    "        df['day_cos'] = np.cos(2 * np.pi * df['day_num'] / 7)\n",
+    "\n",
+    "        # ✅ Target encoding\n",
+    "        df['department_encoded'] = df['department'].map(df.groupby('department')['actual_productivity'].mean())\n",
+    "        df['team_encoded'] = df['team'].map(df.groupby('team')['actual_productivity'].mean())\n",
+    "        df['quarter_encoded'] = df['quarter'].map(df.groupby('quarter')['actual_productivity'].mean())\n",
+    "\n",
+    "        # ✅ Drop original categorical columns\n",
+    "        df = df.drop(['day', 'department', 'team', 'quarter'], axis=1)\n",
+    "\n",
+    "    elif model_type == 'decision_tree':\n",
+    "        # ✅ One-hot encoding for 'day'\n",
+    "        df = pd.get_dummies(df, columns=['day'], drop_first=False)\n",
+    "\n",
+    "        # ✅ Label encoding for 'department' and 'quarter'\n",
+    "        le = LabelEncoder()\n",
+    "        df['department_label'] = le.fit_transform(df['department'])\n",
+    "        df['quarter_label'] = le.fit_transform(df['quarter'])\n",
+    "\n",
+    "        # ✅ Drop original columns that were encoded\n",
+    "        df = df.drop(['department', 'quarter'], axis=1)\n",
+    "\n",
+    "    else:\n",
+    "        raise ValueError(\"Invalid model_type. Choose 'svm', 'perceptron', or 'decision_tree'.\")\n",
+    "\n",
+    "    return df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 278,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x20e62196388>"
+      ]
+     },
+     "execution_count": 278,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "corr_wip = df[['wip', 'smv', 'over_time', 'idle_time', 'actual_productivity']].corr()\n",
+    "sns.heatmap(corr_wip, annot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**No strong linear correlations found with actual productivity, suggesting limited predictive power from individual features.**\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 279,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjgAAAGoCAYAAABL+58oAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAeoElEQVR4nO3de5gcZZ3o8W/P5EYgMOIGJMpFUX4iCnIRUIlkFcWALuqqcFyPXPT4uMvZI7sqiE+Q6OrquoBHDyguqKCiq3JblI0ELwvhohAISgz8UJCLKMjFkLCBkMz0+aNrkskwmUxmpmaad76f5/FJd1V1zdt5Hf2mqrqr0Ww2kSRJKknHeA9AkiRptBk4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4k8Z7AJLGVkTsAtwJ3Fot6gAeB/5vZn6v2uaTwG8z8xuD7OfjwC8z8z8GWLfu9RHRBGZm5sObMcZXAO/NzA9ExH7ARzPz7UN9/XBERCdwMbA78MXMPLNavgNwH7BdZj5aLfsM8FHgxZmZ1bITgX0z88iIuBt4e2Yurh6vBp4AmsAUYCHwoczsqfM9SROZgSNNTE9k5st7n0TEzsBPIqI7My/KzI8PYR+vBZYNtGKIrx/MHsDzqn0tBmqNm8pzgUOBLTOzu3dhZv4xIm4FXgNcWi1+E/AD4K+Af62WvRb49kb2/TfV+yAipgBXAX8HnDnab0JSi4Ejicy8pzoi8xHgoog4D1iamadFxCeAtwJPAY8AxwBvA/YD/jUiuoEjgG2BXYEfAtv3vr76EZ+ujsp0APMy84cRcQytoxxvAuh9Dvwt8Elgm4j4OnA+cGZmvjQitgHOAl5O62jIAuBjmbk2Ip4EPgu8AdgB+Fxmfrn/e42I2bSiZHr1nuYB1wI/AiYDN0XEX2fmnX1etgCYA1xaHQGbCnwBmF/9HUwBXgW8Zwh/109FxCLgxZvaVtLweQ2OpF6/BF7Wd0FE7AicALwiM/ejdWrlgMw8C1gMfCQzL6k2n56Ze2TmSQPs+67M3Ad4N3B+RMzc2CAy8z7g48CizDy23+ov0oqsl9EKrL2AD1frpgIPZ+araIXS5yNiWr/382zgQuCDmbkncDTwLeAvgMOojmz1ixtYHzgAb6YVcVcDe0TEXwAHAssy808be199xjCr2sfPNrWtpOEzcCT1agKr+i27n1b43BwRpwG3ZOalT3tlyzWD7PtsgMxcSuu01iuHOca5tI7mNDNzdbXfuX3W914PdDOt4Nmy3+sPoHVt0C+q8fya1tGbOZv4udcDO0XEtlSBk5lrgJ8Cr6N1euryQV5/QUTcEhG/onVq69zMvGgTP1PSCBg4knq9gvUXHgNQXQR7MK3TUo/QOiryuY28/vFB9t3d53EHsIZWUDX6LJ8yhDF2VK/r+3xyn+dPVOPu3abv/gE6+71+oH08TWauBX5CK6ZeDiyqVl0OHMSmA+dvqiNDe2bmvpl5+mA/T9LIGTiSiIjdgFOA0/st3wtYCtyWmZ8BPk8rhADWsokw6OOYan/7AC8EfgE8BLw0IqZFxGQ2vJB4Y/u+AvjfEdGIiKnA+4ErhzgGaB2JeXFE7F+NZw9aFw//1xBeuwA4Efiv6ugNwH/SOoKzI7BkM8YhqWYGjjQxbVGdMrklIm4GzgNOzswNjkJk5i+B7wGLI2IxcBzwj9Xqy4DPRMTRQ/h5L4iIJcC5wFHVx60X0vo00e20rmdZ3Gf7n1evubjffv4PsB2tI023Agl8eojvmeqj6u8A/l/1yahvA8dm5h1DePkCYE9a19/07u9BWkeuftrnqJGkNtBoNv2dlCRJZfEIjiRJKo6BI0mSimPgSJKk4hg4kiSpOM+4WzX09PQ0u7vruTC6s7NBXfvW8Dkv7cl5aU/OS/txTuo1eXLnw8DTvh39GRc43d1Nli/v/2Wro6Ora3pt+9bwOS/tyXlpT85L+3FO6jVz5ox7BlruKSpJklQcA0eSJBXHwJEkScUxcCRJUnEMHEmSVBwDR5IkFcfAkSRJxTFwJElScQwcSZJUHANHkiQVx8CRJEnFMXAkSVJxDBxJklQcA0eSJBXHwJEkScUxcCRJUnEMnJqdf8O94z0ESZImHAOnZt3N5ngPQZKkCcfAkSRJxTFwJElScQwcSZJUHANHkiQVx8CRJEnFMXAkSVJxDBxJklQcA0eSJBXHwJEkScUxcCRJUnEMHEmSVBwDR5IkFWdSXTuOiCXAY9XT3wFfAb4ArAUWZuYnIqID+BKwF7AaeF9m/rauMUmSpImhlsCJiGkAmTmnz7JbgL8G7gIuj4h9gF2AaZn5yog4EDgdOKKOMUmSpImjriM4ewHTI2Jh9TPmA1Mz806AiLgCeB2wA/AjgMz8eUTsV9N4JEnSBFJX4KwCTgPOBV4ELACW91m/EngBsDXrT2MBdEfEpMxcu7Edd3Y26OqaPvojBjo7O0Z939OmTq5tvBNFHfOikXNe2pPz0n6ck/FRV+DcAfw2M5vAHRHxGLBtn/UzaAXP9Opxr47B4gagu7vJ8uWrRnu8AHR1TR/1fT+5ek1t450o6pgXjZzz0p6cl/bjnNRr5swZAy6v61NUx9G6noaImEUrZP47InaNiAZwKLAIuBY4rNruQODWmsYjSZImkLqO4HwVOC8irgGatIKnB7gA6KT1KapfRMSNwOsj4jqgARxb03gkSdIEUkvgZOZTwLsGWHVgv+16gA/UMQZJkjRx+UV/kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSijOprh1HxHbATcDrgbXAeUATWAocn5k9EXEqcHi1/oTMvKGu8UiSpImjliM4ETEZ+ArwRLXoDGBeZs4GGsAREbEPcDBwAHAUcFYdY5EkSRNPXaeoTgPOBv5QPd8XuKp6vAA4BDgIWJiZzcy8F5gUETNrGo8kSZpARv0UVUQcAzyUmVdExMnV4kZmNqvHK4FtgK2BR/q8tHf5Q4Ptv7OzQVfX9NEd9Lp9d4z6vqdNnVzbeCeKOuZFI+e8tCfnpf04J+OjjmtwjgOaEXEI8HLgG8B2fdbPAJYDK6rH/ZcPqru7yfLlq0ZvtH10dU0f9X0/uXpNbeOdKOqYF42c89KenJf245zUa+bMGQMuH/VTVJn5msw8ODPnALcA7wEWRMScapO5wCLgWuDQiOiIiJ2Ajsx8eLTHI0mSJp7aPkXVz4eAcyJiCnAbcGFmdkfEIuB6WqF1/BiNRZIkFa7WwKmO4vQ6eID184H5dY5BkiRNPH7RnyRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOJMqmOnEdEJnAME0A0cCzSA84AmsBQ4PjN7IuJU4HBgLXBCZt5Qx5gkSdLEUdcRnDcDZOargY8DZ1T/mZeZs2nFzhERsQ9wMHAAcBRwVk3jkSRJE0gtR3Ay89KI+GH1dGfgQVpHaa6qli0A3gAksDAzm8C9ETEpImZm5kMb23dnZ4Ourul1DJvOzo5R3/e0qZNrG+9EUce8aOScl/bkvLQf52R81BI4AJm5NiLOB94KvB14UxUyACuBbYCtgUf6vKx3+UYDp7u7yfLlq2oZc1fX9FHf95Or19Q23omijnnRyDkv7cl5aT/OSb1mzpwx4PJaLzLOzKOB3Whdj7NFn1UzgOXAiupx/+WSJEnDVkvgRMT/jIiTq6ergB5gcUTMqZbNBRYB1wKHRkRHROwEdGTmw3WMSZIkTRx1naK6GPh6RFwNTAZOAG4DzomIKdXjCzOzOyIWAdfTiq3jaxqPJEmaQIYUOBExLzM/1ef5ZzLz5I1tn5n/DbxzgFUHD7DtfGD+UMYhSZI0FIMGTkS8F3gfsHtEHFYt7qR1VGajgSNJkjSeNnUE51vAT4CPAZ+ulvUAf6pzUJIkSSMx6EXGmbk6M+8GPgBsT+s7bZ5P64v5JEmS2tJQLzK+ENgOuK963gSurmVEkiRJIzTUwHlOZr6q1pFIkiSNkqF+D87tETGr1pFIkiSNkqEewZlN615RvbdQaGamwSNJktrSkAInM19U90AkSZJGy1C/6O/rtC4sXiczj6tlRJIkSSM01FNU/1792QD2ATw9JUmS2tZQT1Fd0efpjyJiYU3jkSRJGrGhnqJ6Q5+nO9D60j9JkqS2NNRTVP+jz+MnAa+/kSRJbWuop6iOjYiXAi8B7sjMW+odliRJ0vAN6Yv+IuLvgXOAVwH/FhEfrnVUkiRJIzDUbzJ+FzA7M08AXg0cWd+QJEmSRmaogdPIzLUAmbkGWFPfkCRJkkZmqBcZXxMRFwKLgIOAa+sbkiRJ0shs8ghORLwfOBn4OrANcFVmfqTugUmSJA3XoIETEfOBNwCTM/Ny4BvAayPilDEYmyRJ0rBs6gjOXOAdmbkKIDPvpnWB8V/VPC5JkqRh21TgPJ6Z/W+yuQZYWd+QJEmSRmZTgfNERLyg74LqeXMj20uSJI27TX2K6iTg0oj4CXAXsBNwKHB03QOTJEkarkGP4GTmr4HZwBJgS+Bm4NWZuWQMxiZJkjQsm/wenMx8jNanpyRJkp4RhvpNxpIkSc8YBo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4kwa7R1GxGTga8AuwFTgU8Ay4DygCSwFjs/Mnog4FTgcWAuckJk3jPZ4JEnSxFPHEZx3A49k5mxgLnAmcAYwr1rWAI6IiH2Ag4EDgKOAs2oYiyRJmoDqCJzvA6f0eb4W2Be4qnq+ADgEOAhYmJnNzLwXmBQRM2sYjyRJmmBG/RRVZj4OEBEzgAuBecBpmdmsNlkJbANsDTzS56W9yx8abP+dnQ26uqaP9rCrfXeM+r6nTZ1c23gnijrmRSPnvLQn56X9OCfjY9QDByAidgQuAb6Umd+OiM/1WT0DWA6sqB73Xz6o7u4my5evGs3hrtPVNX3U9/3k6jW1jXeiqGNeNHLOS3tyXtqPc1KvmTNnDLh81E9RRcT2wELgpMz8WrV4SUTMqR7PBRYB1wKHRkRHROwEdGTmw6M9HkmSNPHUcQTnY8CzgFMiovdanA8CX4yIKcBtwIWZ2R0Ri4DraYXW8TWMRZIkTUB1XIPzQVpB09/BA2w7H5g/2mOQJEkTm1/0J0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTgGjiRJKo6BI0mSimPgSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSqOgSNJkopj4EiSpOIYOJIkqTiT6tpxRBwA/EtmzomIFwLnAU1gKXB8ZvZExKnA4cBa4ITMvKGu8UiSpImjliM4EXEicC4wrVp0BjAvM2cDDeCIiNgHOBg4ADgKOKuOsUiSpImnriM4dwJvA75ZPd8XuKp6vAB4A5DAwsxsAvdGxKSImJmZDw22487OBl1d02sZdGdnx6jve9rUybWNd6KoY140cs5Le3Je2o9zMj5qCZzMvCgidumzqFGFDMBKYBtga+CRPtv0Lh80cLq7myxfvmoUR7teV9f0Ud/3k6vX1DbeiaKOedHIOS/tyXlpP85JvWbOnDHg8rG6yLinz+MZwHJgRfW4/3JJkqQRGavAWRIRc6rHc4FFwLXAoRHRERE7AR2Z+fAYjUeSJBWstk9R9fMh4JyImALcBlyYmd0RsQi4nlZoHT9GY5EkSYWrLXAy827gwOrxHbQ+MdV/m/nA/LrGIEmSJia/6E+SJBXHwJEkScUxcCRJUnEMHEmSVBwDR5IkFcfAkSRJxTFwJElScQwcSZJUHANHkiQVx8CRJEnFMXAkSVJxDBxJklQcA0eSJBXHwJEkScUxcCRJUnEMHEmSVBwDR5IkFcfAkSRJxTFwJElScQwcSZJUHANHkiQVx8CRJEnFMXAkSVJxDBxJklQcA0eSJBXHwJEkScUxcCRJUnEMHEmSVBwDR5IkFcfAkSRJxTFwJElScQwcSZJUHANHkiQVx8CRJEnFMXAkSVJxDBxJklQcA0eSJBXHwJEkScUxcCRJUnEMHEmSVBwDR5IkFcfAkSRJxTFwJElScQycGq3t7uHPq9awprtnvIciSdKEMmm8B1Cia+56hG/ccB/LHnyc1Wt7WLDsT7xx9+14x8tnsfO208d7eJIkFc/AGUVru3s465q7+dbi37PTs7bgbXvuwAMrn6Cz0cnFv/ojly19gM+8+SW8+vnbjvdQJUkqmoEzSp5c080Jlyzlpvse4+177cAJc3Zl6qQOvnHjPbznFTvzp5Wr+cdLf82HLlnKSYe8iLfuucN4D1mSpGIZOKNgTXcPJ/1gGTff9xjz3xgcvsf269Z1NOCCxfeytge+cuSenPyD2/jnK3/D5M4Gb9rjOeM4akmSyuVFxiPU3dPk1AXJdb/7Mye//kUbxM26bZpNuptNtpwyiTPesgev2KmLTy/8DTfdt3wcRixJUvkMnBH64tV3cWU+xN/Pfv4Gp52+eeO9A24/qbODz755d57XNY0TL1vGPY+uGquhSpI0YRg4I/C9Jffz7Zvu58i9Z/Ge/XfcYF13s7nR1209bTKff+tL6Ww0+IdLlrJ81Zq6hypJ0oRi4AzTVb99mNN/diev2fXZ/MOcXdct/+aN9/Kdm55+9KajAeffsH7587q24LS37MGDK1dz4mW/5qm1fleOJEmjxcAZhp/f/Sgn//A2dt9+Bp86/MV0djTWreu93qa/jgY0Gs0NTl3tOWtrTn1jsOT+FXzyiqRnkKM+kiRp6AyczXTTfcv58H8sY5tpk/jC217KFpM7N1jfp3UG1Dd+Llh8L39c8STHH7QLV9z+EJ/98W9oGjmSJI2YgbMZfpwP8cGLlzJr62kcvsf2bLPF5HXrNnZRcV8djQ1PVfUe7Tl6/x05Zv8dueRXD3D6z+40ciRJGiEDZwh6mk3Oue4eTv7hbew2cyu+/M492Wpq68hNb9g0Gk0uWLw+cnq//2YgTVqnqnqP9jQaDf7uoF14177P5btL/sC8y2/niTXd9b4pSZIKZuD0cfbVdz5t2e0PruS937mFf7v+Hg7fY3vOfueePHvLKesCpsn6sOl/7c1gn6RqsuG6RqPBs7aYxPEH7cKV+RDv/c4tfoRckqRh8puM++jpWR8dyx5YyfeW3M+C2/5E1xaT+cTcYPmqJ/nukt+vO9XUGzDdzeYmr73pq++2kzrWH+npAY47YCd2224r5l1+O0edfxPv3HsW7ztwZ2ZMc6okSRqqcf9/zYjoAL4E7AWsBt6Xmb8dj7E8sOJJzrnuHhbd9Qi3Pfg4W0zu4Mi9n8v/emUrML61+B66m61jL5sTNJvSG0i91+ccvf9OfO+YfTn72nv4zk338/1b/sDc3bfjsJdsz16ztmZSpwfeJEkazLgHDvAWYFpmvjIiDgROB44Y60Es+f1jfOfG39MA9thhBrNfsC2fPOzF/GDpH7hs6R/oaUKjMbph019Ho3W9zwWL76WnCfMO3Y137j2Lf7oi+XE+zGVLH2TqpA5esv1W7LbdVszaZhrP2XoaW03pZMupk9b9ObWzg44O6Gg0aND6s/Ux9fV/SpJUsnYInIOAHwFk5s8jYr/xGMRLnjODI/d7Ll1TOtlyaidru5tsNXX9X0/rCEsrGHqf982Evs+H8nhj6zr7tceN9/2ZQ2ImR+79XK773aPccv8Kbv3jCi7+1R9Z0z38T1v1H8vTDBJBg71usHYa/HXDj67hjmciWdvdZFL//3KN8PWNRmPAT/z5IcD6DOWvttFwDtRe3vKy5/Dh175wzH9uY7w/khwR5wIXZeaC6vm9wAsyc+1GXvIQcM9YjU+SJLW1nYGZ/Re2wxGcFcCMPs87BokbGOBNSJIk9dUOV6teCxwGUF2Dc+v4DkeSJD3TtcMRnEuA10fEdbQupzh2nMcjSZKe4cb9GhxJkqTR1g6nqCRJkkaVgSNJkopj4EiSpOK0w0XG466dbhcxkUTEEuCx6unvgK8AXwDWAgsz8xMbm5vqE3cbbDvmb6AwEXEA8C+ZOSciXgicR+u75ZYCx2dmT0ScChxO6+/9hMy8YXO2HfM3VYB+87IP8APgN9XqL2fmd52XsRMRk4GvAbsAU4FPAcvw96XteASnZd3tIoCP0rpdhGoUEdMAMnNO9Z9jgbOBd9H6dusDqv8x39jcDLSthikiTgTOBaZVi84A5mXmbFqfbjyi+js+GDgAOAo4axjbajMMMC/7AGf0+b35rvMy5t4NPFL9vc4FzsTfl7Zk4LRscLsIYFxuFzHB7AVMj4iFEfHTiHgNMDUz78zMJnAF8DoGmJuI2Hoj22r47gTe1uf5vsBV1eMFwCG05mJhZjYz815gUkTM3MxttXkGmpfDI+LqiPhqRMzAeRlr3wdO6fN8Lf6+tCUDp2Vr1p8qAeiOCE/f1WsVcBpwKPAB4OvVsl4rgW0YYG6qZSsG2FbDlJkXAWv6LGpU8Qgbn4ve5ZuzrTbDAPNyA/CRzHwNcBdwKs7LmMrMxzNzZRWXFwLz8PelLRk4LZt7uwiN3B3At6p/sdxB65d72z7rZwDLGWBuBljWu61GT0+fxxubi97lm7OtRuaSzLyp9zGwN87LmIuIHYGfAd/MzG/j70tbMnBavF3E2DuO6nqaiJgFTAf+OyJ2jYgGrSM7ixhgbjJzBfDUANtq9CyJiDnV47msn4tDI6IjInai9Q+BhzdzW43MFRGxf/X4dcBNOC9jKiK2BxYCJ2Xm16rF/r60IU/DtHi7iLH3VeC8iLiG1qcJjqP1L5sLgE5a56N/ERE3MvDcfKD/tmP9Bgr3IeCciJgC3AZcmJndEbEIuJ7WP46OH8a2Gpm/Bc6MiKeAB4D3Z+YK52VMfQx4FnBKRPRei/NB4Iv+vrQXb9UgSZKK4ykqSZJUHANHkiQVx8CRJEnFMXAkSVJxDBxJklQcPyYuqa1ExE+Bj1Y3JpwCPAT8U2aeVq2/CniU1s1Zbwd+BdxM6+sGpgE/y8yPjcvgJbUNj+BIajcLgdnV49m07jV2OKy7SeuObPi19suqG0/+JfBq4C8jYs8xHK+kNmTgSGo3V7I+cA6jdTftrojYBngl629UOJAtgKlseF8zSROQX/Qnqa1ERAewDNid1s0lDwI+Bfwc2LNaNxf4d55+iqqb1v2Bzh/7kUtqJ16DI6mtZGZPRPwSeCPwQGaujogFwJuAvYAv0AqcXssyc87Yj1RSO/MUlaR2dCWte/4sqJ5fA+wDkJmPjtegJD1zGDiS2tGVtE5N/SdAZj4FLAeuHs9BSXrm8BocSZJUHI/gSJKk4hg4kiSpOAaOJEkqjoEjSZKKY+BIkqTiGDiSJKk4Bo4kSSrO/weDfevcFideswAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.histplot(df['wip'], kde=True)\n",
+    "plt.title(\"Distribution of WIP\")\n",
+    "plt.xlabel(\"WIP\")\n",
+    "plt.ylabel(\"Count\")\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The distribution of the `wip` (Work In Progress) feature is heavily right-skewed, with the majority of observations concentrated below 2000 units. However, a small number of extreme values exceed 20,000, which could disproportionately impact the regression model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 280,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df['wip_log'] = np.log1p(df['wip'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 281,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.histplot(df['wip_log'], kde=True, color='skyblue', bins=30)\n",
+    "plt.title(\"Log-Transformed WIP Distribution\", fontsize=14, fontweight='bold')\n",
+    "plt.xlabel(\"Log of WIP\")\n",
+    "plt.ylabel(\"Count\")\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 282,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Keep wip_log as wip not needed now to ensure consistency\n",
+    "df = df.drop(columns=['wip'])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 283,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x20e5d1a0f08>"
+      ]
+     },
+     "execution_count": 283,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "corr_wip = df[['wip_log', 'smv', 'over_time', 'idle_time', 'actual_productivity']].corr()\n",
+    "sns.heatmap(corr_wip, annot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "After applying log transformation to the `wip` feature, the distribution becomes nearly symmetric and well-centered. This transformation reduces skewness and minimizes the impact of extreme outliers, making the data more suitable for regression models.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 286,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 6))  \n",
+    "sns.histplot(df['over_time'], kde=True, bins=30)\n",
+    "plt.title('Distribution of Overtime')\n",
+    "plt.xlabel('Overtime')\n",
+    "plt.ylabel('Count')\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**The distribution of 'over_time' is heavily right-skewed and multimodal, with a large number of instances clustered at lower overtime values (under 2000 minutes). There are multiple peaks, notably around 0, 2000, 7000, and 10000 minutes, suggesting distinct overtime patterns among employees or production units. A small number of extreme outliers beyond 15,000 minutes are also present, which may warrant further investigation or transformation.**\n",
+    "\n",
+    "**This skewed and non-normal distribution suggests the need for log transformation or binning to reduce its impact on linear models.**\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 287,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Count')"
+      ]
+     },
+     "execution_count": 287,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.histplot(df['actual_productivity'], bins=20, kde=True)\n",
+    "plt.title(\"Distribution of Actual Productivity\")\n",
+    "plt.title('Distribution of Actual Productivity')\n",
+    "plt.xlabel('Actual Productivity')\n",
+    "plt.ylabel('Count')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**The distribution of actual productivity is slightly right-skewed, with most values concentrated between 0.6 and 0.9. The peak occurs around 0.8, indicating that a large number of employees perform close to this level. While the distribution is roughly unimodal, there are some lower and higher productivity outliers present. Overall, the distribution suggests that the majority of the workforce maintains consistent productivity, which is favorable for regression modeling.**\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 288,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1008x432 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "numerical_cols = ['wip_log', 'over_time', 'incentive', 'smv']\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "for i, col in enumerate(numerical_cols):\n",
+    "    plt.subplot(1, len(numerical_cols), i + 1)\n",
+    "    sns.boxplot(y=df[col], color='lightblue')\n",
+    "    plt.title(col)\n",
+    "    plt.tight_layout()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The boxplots reveal strong outliers in `wip`, `over_time`, `incentive`, and `idle_time`, while `smv` appears more stable. These outliers can distort regression models, especially linear ones, and may require log transformation or capping to reduce their influence.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 289,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def replace_outliers_with_median(df, column):\n",
+    "    Q1 = df[column].quantile(0.25)\n",
+    "    Q3 = df[column].quantile(0.75)\n",
+    "    IQR = Q3 - Q1\n",
+    "    if IQR == 0:\n",
+    "        print(f\"Skipping '{column}' — no variability (IQR = 0)\")\n",
+    "        return\n",
+    "    lower_bound = Q1 - 1.5 * IQR\n",
+    "    upper_bound = Q3 + 1.5 * IQR\n",
+    "    median_value = df[column].median()\n",
+    "    df[column] = np.where((df[column] < lower_bound) | (df[column] > upper_bound), median_value, df[column])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 290,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1008x432 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "numerical_cols = ['wip_log', 'over_time', 'incentive', 'smv']\n",
+    "\n",
+    "plt.figure(figsize=(14, 6))\n",
+    "for i, col in enumerate(numerical_cols):\n",
+    "    plt.subplot(1, len(numerical_cols), i + 1)\n",
+    "    sns.boxplot(y=df[col], color='lightblue')\n",
+    "    plt.title(col)\n",
+    "    plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Due to the highly skewed and multimodal distribution of the `over_time` feature, extreme outliers were handled by imputing values above the 95th percentile with the median. This approach reduces the influence of rare, extreme values while preserving the original scale of the feature, making it more stable for regression modeling.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 291,
+   "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>date</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>department</th>\n",
+       "      <th>day</th>\n",
+       "      <th>team</th>\n",
+       "      <th>targeted_productivity</th>\n",
+       "      <th>smv</th>\n",
+       "      <th>over_time</th>\n",
+       "      <th>incentive</th>\n",
+       "      <th>idle_time</th>\n",
+       "      <th>idle_men</th>\n",
+       "      <th>no_of_style_change</th>\n",
+       "      <th>no_of_workers</th>\n",
+       "      <th>actual_productivity</th>\n",
+       "      <th>overtime_bin</th>\n",
+       "      <th>wip_log</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sewing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>8</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>26.16</td>\n",
+       "      <td>7080</td>\n",
+       "      <td>98</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>0.940725</td>\n",
+       "      <td>5001-10000</td>\n",
+       "      <td>7.011214</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>finishing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>3.94</td>\n",
+       "      <td>960</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.886500</td>\n",
+       "      <td>501-1000</td>\n",
+       "      <td>6.946976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sewing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>11.41</td>\n",
+       "      <td>3660</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30.5</td>\n",
+       "      <td>0.800570</td>\n",
+       "      <td>2001-5000</td>\n",
+       "      <td>6.876265</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sewing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>11.41</td>\n",
+       "      <td>3660</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30.5</td>\n",
+       "      <td>0.800570</td>\n",
+       "      <td>2001-5000</td>\n",
+       "      <td>6.876265</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sewing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>25.90</td>\n",
+       "      <td>1920</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>0.800382</td>\n",
+       "      <td>1001-2000</td>\n",
+       "      <td>7.065613</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        date   quarter department       day  team  targeted_productivity  \\\n",
+       "0 2015-01-01  Quarter1     sewing  Thursday     8                   0.80   \n",
+       "1 2015-01-01  Quarter1  finishing  Thursday     1                   0.75   \n",
+       "2 2015-01-01  Quarter1     sewing  Thursday    11                   0.80   \n",
+       "3 2015-01-01  Quarter1     sewing  Thursday    12                   0.80   \n",
+       "4 2015-01-01  Quarter1     sewing  Thursday     6                   0.80   \n",
+       "\n",
+       "     smv  over_time  incentive  idle_time  idle_men  no_of_style_change  \\\n",
+       "0  26.16       7080         98        0.0         0                   0   \n",
+       "1   3.94        960          0        0.0         0                   0   \n",
+       "2  11.41       3660         50        0.0         0                   0   \n",
+       "3  11.41       3660         50        0.0         0                   0   \n",
+       "4  25.90       1920         50        0.0         0                   0   \n",
+       "\n",
+       "   no_of_workers  actual_productivity overtime_bin   wip_log  \n",
+       "0           59.0             0.940725   5001-10000  7.011214  \n",
+       "1            8.0             0.886500     501-1000  6.946976  \n",
+       "2           30.5             0.800570    2001-5000  6.876265  \n",
+       "3           30.5             0.800570    2001-5000  6.876265  \n",
+       "4           56.0             0.800382    1001-2000  7.065613  "
+      ]
+     },
+     "execution_count": 291,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 292,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0     1179\n",
+       "30       3\n",
+       "20       3\n",
+       "15       3\n",
+       "10       3\n",
+       "35       2\n",
+       "45       1\n",
+       "40       1\n",
+       "37       1\n",
+       "25       1\n",
+       "Name: idle_men, dtype: int64"
+      ]
+     },
+     "execution_count": 292,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['idle_men'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 293,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Dropping these columns as more than 95% are 0 values suggesting no variance and therefore does not contribute significantly\n",
+    "df.drop(columns=['idle_time', 'idle_men'], inplace=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 294,
+   "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>date</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>department</th>\n",
+       "      <th>day</th>\n",
+       "      <th>team</th>\n",
+       "      <th>targeted_productivity</th>\n",
+       "      <th>smv</th>\n",
+       "      <th>over_time</th>\n",
+       "      <th>incentive</th>\n",
+       "      <th>no_of_style_change</th>\n",
+       "      <th>no_of_workers</th>\n",
+       "      <th>actual_productivity</th>\n",
+       "      <th>overtime_bin</th>\n",
+       "      <th>wip_log</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sewing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>8</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>26.16</td>\n",
+       "      <td>7080</td>\n",
+       "      <td>98</td>\n",
+       "      <td>0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>0.940725</td>\n",
+       "      <td>5001-10000</td>\n",
+       "      <td>7.011214</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>finishing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>3.94</td>\n",
+       "      <td>960</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.886500</td>\n",
+       "      <td>501-1000</td>\n",
+       "      <td>6.946976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sewing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>11.41</td>\n",
+       "      <td>3660</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30.5</td>\n",
+       "      <td>0.800570</td>\n",
+       "      <td>2001-5000</td>\n",
+       "      <td>6.876265</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sewing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>11.41</td>\n",
+       "      <td>3660</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>30.5</td>\n",
+       "      <td>0.800570</td>\n",
+       "      <td>2001-5000</td>\n",
+       "      <td>6.876265</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2015-01-01</td>\n",
+       "      <td>Quarter1</td>\n",
+       "      <td>sewing</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>25.90</td>\n",
+       "      <td>1920</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>0.800382</td>\n",
+       "      <td>1001-2000</td>\n",
+       "      <td>7.065613</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        date   quarter department       day  team  targeted_productivity  \\\n",
+       "0 2015-01-01  Quarter1     sewing  Thursday     8                   0.80   \n",
+       "1 2015-01-01  Quarter1  finishing  Thursday     1                   0.75   \n",
+       "2 2015-01-01  Quarter1     sewing  Thursday    11                   0.80   \n",
+       "3 2015-01-01  Quarter1     sewing  Thursday    12                   0.80   \n",
+       "4 2015-01-01  Quarter1     sewing  Thursday     6                   0.80   \n",
+       "\n",
+       "     smv  over_time  incentive  no_of_style_change  no_of_workers  \\\n",
+       "0  26.16       7080         98                   0           59.0   \n",
+       "1   3.94        960          0                   0            8.0   \n",
+       "2  11.41       3660         50                   0           30.5   \n",
+       "3  11.41       3660         50                   0           30.5   \n",
+       "4  25.90       1920         50                   0           56.0   \n",
+       "\n",
+       "   actual_productivity overtime_bin   wip_log  \n",
+       "0             0.940725   5001-10000  7.011214  \n",
+       "1             0.886500     501-1000  6.946976  \n",
+       "2             0.800570    2001-5000  6.876265  \n",
+       "3             0.800570    2001-5000  6.876265  \n",
+       "4             0.800382    1001-2000  7.065613  "
+      ]
+     },
+     "execution_count": 294,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 295,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "date                     0\n",
+       "quarter                  0\n",
+       "department               0\n",
+       "day                      0\n",
+       "team                     0\n",
+       "targeted_productivity    0\n",
+       "smv                      0\n",
+       "over_time                0\n",
+       "incentive                0\n",
+       "no_of_style_change       0\n",
+       "no_of_workers            0\n",
+       "actual_productivity      0\n",
+       "overtime_bin             0\n",
+       "wip_log                  0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 295,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 🧼 Preprocessing Summary\n",
+    "\n",
+    "The dataset underwent several preprocessing steps to ensure data quality and model-readiness:\n",
+    "\n",
+    "1. **Handling Missing Values**\n",
+    "   - Missing values in `wip` were imputed using the median.\n",
+    "   - No remaining missing values after cleaning.\n",
+    "\n",
+    "2. **Outlier Treatment**\n",
+    "   - Applied IQR-based outlier detection.\n",
+    "   - Outliers in continuous variables (`wip`, `over_time`, `incentive`, `idle_men`) were replaced with median values.\n",
+    "   - `idle_time` was removed as over 98% of its values were zero, making it uninformative.\n",
+    "\n",
+    "3. **Feature Engineering**\n",
+    "   - Created `wip_log` (log-transformed `wip`) to reduce skew and improve performance in linear models.\n",
+    "   - Binned `over_time` into categorical `overtime_bin` for visualization and tree models.\n",
+    "\n",
+    "4. **Feature Reduction**\n",
+    "   - Removed `idle_time` due to lack of variance.\n",
+    "   - Kept `no_of_style_change` and `idle_men` after verifying they had useful variability.\n",
+    "\n",
+    "5. **Column Reordering**\n",
+    "   - Moved `actual_productivity` (target variable) to the end of the DataFrame for clarity.\n",
+    "\n",
+    "\n",
+    "This prepared dataset is now ready for encoding, feature scaling, and regression modeling.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}