"""
Module containing most of the utility functions for the binarycpython package
Functions here are mostly functions used in other classes/functions, or
useful functions for the user
"""
import json
import os
import tempfile
import copy
import inspect
from collections import defaultdict
import h5py
import numpy as np
import binary_c_python_api
########################################################
# utility functions
########################################################
def verbose_print(message, verbosity, minimal_verbosity):
"""
Function that decides whether to print a message based on the current verbosity
and its minimum verbosity
if verbosity is equal or higher than the minimum, then we print
"""
if verbosity >= minimal_verbosity:
print(message)
def remove_file(file, verbosity=0):
"""
Function to remove files but with verbosity
"""
if os.path.exists(file):
try:
verbose_print("Removed {}".format(file), verbosity, 1)
os.remove(file)
except FileNotFoundError as inst:
print("Error while deleting file {}: {}".format(file, inst))
def temp_dir():
"""
Function to return the path the custom logging library shared object
and script will be written to.
Makes use of os.makedirs exist_ok which requires python 3.2+
"""
tmp_dir = tempfile.gettempdir()
path = os.path.join(tmp_dir, "binary_c_python")
#
os.makedirs(path, exist_ok=True)
return path
def create_hdf5(data_dir, name):
"""
Function to create an hdf5 file from the contents of a directory:
- settings file is selected by checking on files ending on settings
- data files are selected by checking on files ending with .dat
TODO: fix missing settingsfiles
"""
# Make HDF5:
# Create the file
hdf5_filename = os.path.join(data_dir, "{}".format(name))
print("Creating {}".format(hdf5_filename))
hdf5_file = h5py.File(hdf5_filename, "w")
# Get content of data_dir
content_data_dir = os.listdir(data_dir)
# Settings
if any([file.endswith("_settings.json") for file in content_data_dir]):
print("Adding settings to HDF5 file")
settings_file = os.path.join(
data_dir,
[file for file in content_data_dir if file.endswith("_settings.json")][0],
)
with open(settings_file, "r") as settings_file:
settings_json = json.load(settings_file)
# Create settings group
settings_grp = hdf5_file.create_group("settings")
# Write version_string to settings_group
settings_grp.create_dataset("used_settings", data=json.dumps(settings_json))
# Get data files
data_files = [el for el in content_data_dir if el.endswith(".dat")]
if data_files:
print("Adding data to HDF5 file")
# Create the data group
data_grp = hdf5_file.create_group("data")
# Write the data to the file:
# Make sure:
for data_file in data_files:
# filename stuff
filename = data_file
full_path = os.path.join(data_dir, filename)
base_name = os.path.splitext(os.path.basename(filename))[0]
# Get header info
header_name = "{base_name}_header".format(base_name=base_name)
data_headers = np.genfromtxt(full_path, dtype="str", max_rows=1)
data_headers = np.char.encode(data_headers)
data_grp.create_dataset(header_name, data=data_headers)
# Add data
data = np.loadtxt(full_path, skiprows=1)
data_grp.create_dataset(base_name, data=data)
hdf5_file.close()
########################################################
# version_info functions
########################################################
def return_binary_c_version_info(parsed=False):
"""
Function that returns the version information of binary_c
"""
version_info = binary_c_python_api.return_version_info().strip()
if parsed:
version_info = parse_binary_c_version_info(version_info)
return version_info
def parse_binary_c_version_info(version_info_string):
"""
Function that parses the binary_c version info. Length function with a lot of branches
"""
version_info_dict = {}
for line in version_info_string.splitlines():
line = line.strip()
if line == "":
continue
if " is " in line:
split = line.split(" is ")
version_info_dict[split[0].strip()] = split[1].strip()
else:
if line.startswith("Binary_c/nucsyn"):
version_info_dict["intro"] = line
elif line.startswith("Email"):
emails = line.split("Email ")[1].split(",")
cleaned_emails = [email.strip() for email in emails]
version_info_dict["emails"] = cleaned_emails
elif line.startswith("DTlimit"):
split = line.split(" : ")
version_info_dict[split[0]] = ": ".join(split[1:])
elif line.startswith("Version"):
split = line.split("Version ")
version_number = split[1]
version_info_dict["version_number"] = version_number
elif line.startswith("git URL"):
split = line.split("git URL ")
git_url = split[1]
version_info_dict["git_url"] = git_url
elif line.startswith("Build: "):
split = line.split("Build: ")
build = split[1]
version_info_dict["build"] = build
elif line.startswith("Compiled for "):
split = line.split("Compiled for ")
compiled_for = split[1]
version_info_dict["compiled_for"] = compiled_for
elif line.startswith("Stack limit "):
split = line.split("Stack limit ")
stack_limit = split[1]
version_info_dict["stack_limit"] = stack_limit
elif line.startswith("SVN URL "):
split = line.split("SVN URL ")
svn_url = split[1]
version_info_dict["svn_url"] = svn_url
elif line.startswith("git branch "):
split = line.split("git branch ")
git_branch = split[1]
version_info_dict["git_branch"] = git_branch
elif line.startswith("_SC_CLK_TCK"):
split = line.split(" = ")
_SC_CLK_TCK = split[1]
version_info_dict["_SC_CLK_TCK"] = _SC_CLK_TCK
elif line.startswith("Random number mean "):
split = line.split("Random number mean ")
random_number_mean = split[1]
version_info_dict["Random number mean"] = random_number_mean
elif line.startswith("SVN revision "):
split = line.split("SVN revision ")
svn_revision = split[1]
version_info_dict["svn_revision"] = svn_revision
elif line.startswith("Size of :"):
split = line.split("Size of :")
data_type_sizes = split[1]
version_info_dict["data_type_sizes"] = data_type_sizes
elif line.startswith("git revision "):
split = line.split("git revision ")
git_revision = split[1]
version_info_dict["git_revision"] = git_revision
elif line.startswith("BINARY_C_PRE_VERSION "):
split = line.split("BINARY_C_PRE_VERSION ")
binary_c_pre_version = split[1]
version_info_dict["binary_c_pre_version"] = binary_c_pre_version
elif line.startswith("Comenv accretion:"):
split = line.split("Comenv accretion:")
comenv_accretion = split[1]
version_info_dict["comenv_accretion"] = comenv_accretion
elif line.startswith("Compiled in parameters:"):
split = line.split("Compiled in parameters:")
compiled_in_parameters = split[1]
version_info_dict["compiled_in_parameters"] = compiled_in_parameters
elif line.startswith("__short__ is"):
split = line.split("__short__ is")
short_type = split[1]
version_info_dict["short_type"] = short_type
else:
print("Still found unmatched items!:\n{}".format(repr(line)))
return version_info_dict
########################################################
# binary_c output functions
########################################################
def output_lines(output):
"""
Function that outputs the lines that were recieved from the binary_c run.
"""
return output.splitlines()
def parse_output(output, selected_header):
"""
Function that parses output of binary_c:
This function works in two cases:
if the caught line contains output like 'example_header time=12.32 mass=0.94 ..'
or if the line contains output like 'example_header 12.32 0.94'
You can give a 'selected_header' to catch any line that starts with that.
Then the values will be put into a dictionary.
TODO: Think about exporting to numpy array or pandas instead of a defaultdict
TODO: rethink whether this function is necessary at all
"""
value_dicts = []
# split output on newlines
for line in output.split("\n"):
# Skip any blank lines
if not line == "":
split_line = line.split()
# Select parts
header = split_line[0]
values_list = split_line[1:]
# print(values_list)
# Catch line starting with selected header
if header == selected_header:
# Check if the line contains '=' symbols:
value_dict = {}
if all("=" in value for value in values_list):
for value in values_list:
key, val = value.split("=")
value_dict[key.strip()] = val.strip()
value_dicts.append(value_dict)
else:
if any("=" in value for value in values_list):
raise ValueError(
"Caught line contains some = symbols but not \
all of them do. aborting run"
)
for j, val in enumerate(values_list):
value_dict[j] = val
value_dicts.append(value_dict)
if len(value_dicts) == 0:
print(
"Sorry, didnt find any line matching your header {}".format(selected_header)
)
return None
keys = value_dicts[0].keys()
# Construct final dict.
final_values_dict = defaultdict(list)
for value_dict in value_dicts:
for key in keys:
final_values_dict[key].append(value_dict[key])
return final_values_dict
########################################################
# Argument and default value functions
########################################################
def get_defaults(filter_values=False):
"""
Function that calls the binaryc get args function and cast it into a dictionary.
All the values are strings
filter_values: whether to filter out NULL and Function defaults.
"""
default_output = binary_c_python_api.return_arglines()
default_dict = {}
for default in default_output.split("\n"):
if not default in ["__ARG_BEGIN", "__ARG_END", ""]:
key, value = default.split(" = ")
default_dict[key] = value
if filter_values:
default_dict = filter_arg_dict(default_dict)
return default_dict
def get_arg_keys():
"""
Function that return the list of possible keys to give in the arg string
"""
return get_defaults().keys()
def filter_arg_dict(arg_dict):
"""
Function to filter out keys that contain values included in ['NULL', 'Function', '']
"""
old_dict = arg_dict.copy()
new_dict = {}
for key in old_dict.keys():
if not old_dict[key] in ["NULL", "Function"]:
if not old_dict[key] == "":
new_dict[key] = old_dict[key]
return new_dict
def create_arg_string(arg_dict, sort=False, filter_values=False):
"""
Function that creates the arg string for binary_c.
Options:
sort: sort the order of the keys.
filter_values: filters the input dict on keys that have NULL or `function` as value.
"""
arg_string = ""
if filter_values:
arg_dict = filter_values(arg_dict)
keys = sorted(arg_dict.keys()) if sort else arg_dict.keys()
for key in keys:
arg_string += "{key} {value} ".format(key=key, value=arg_dict[key])
arg_string = arg_string.strip()
return arg_string
########################################################
# Help functions
########################################################
def get_help(param_name="", print_help=True, fail_silently=False):
"""
Function that returns the help info for a given parameter.
Binary_c will output things in the following order;
- Did you mean?
- binary_c help for variable
- default
- available macros
This function reads out that structure and catches the different components of this output
Will print a dict
return_dict: wether to return the help info dictionary
"""
available_arg_keys = get_arg_keys()
if not param_name:
print(
"Please set the param_name to any of the following:\n {}".format(
sorted(available_arg_keys)
)
)
return None
if param_name in available_arg_keys:
help_info = binary_c_python_api.return_help(param_name)
cleaned = [el for el in help_info.split("\n") if not el == ""]
# Get line numbers
did_you_mean_nr = [
i for i, el in enumerate(cleaned) if el.startswith("Did you mean")
]
parameter_line_nr = [
i for i, el in enumerate(cleaned) if el.startswith("binary_c help")
]
default_line_nr = [
i for i, el in enumerate(cleaned) if el.startswith("Default")
]
macros_line_nr = [
i for i, el in enumerate(cleaned) if el.startswith("Available")
]
help_info_dict = {}
# Get alternatives
if did_you_mean_nr:
alternatives = cleaned[did_you_mean_nr[0] + 1 : parameter_line_nr[0]]
alternatives = [el.strip() for el in alternatives]
help_info_dict["alternatives"] = alternatives
# Information about the parameter
parameter_line = cleaned[parameter_line_nr[0]]
parameter_name = parameter_line.split(":")[1].strip().split(" ")[0]
parameter_value_input_type = (
" ".join(parameter_line.split(":")[1].strip().split(" ")[1:])
.replace("<", "")
.replace(">", "")
)
help_info_dict["parameter_name"] = parameter_name
help_info_dict["parameter_value_input_type"] = parameter_value_input_type
description_line = " ".join(
cleaned[parameter_line_nr[0] + 1 : default_line_nr[0]]
)
help_info_dict["description"] = description_line
# Default:
default_line = cleaned[default_line_nr[0]]
default_value = default_line.split(":")[-1].strip()
help_info_dict["default"] = default_value
# Get Macros:
if macros_line_nr:
macros = cleaned[macros_line_nr[0] + 1 :]
help_info_dict["macros"] = macros
if print_help:
for key in help_info_dict:
print("{}:\n\t{}".format(key, help_info_dict[key]))
return help_info_dict
else:
if not fail_silently:
print(
"{} is not a valid parameter name. Please choose from the \
following parameters:\n\t{}".format(
param_name, list(available_arg_keys)
)
)
return None
def get_help_all(print_help=True):
"""
Function that reads out the output of the help_all api call to binary_c
print_help: bool, prints all the parameters and their descriptions.
return_dict: returns a dictionary
"""
# Call function
help_all = binary_c_python_api.return_help_all()
# String manipulation
split = help_all.split(
"############################################################\n"
)
cleaned = [el for el in split if not el == "\n"]
section_nums = [i for i in range(len(cleaned)) if cleaned[i].startswith("#####")]
# Create dicts
help_all_dict = {}
# Select the section name and the contents of that section. Note, not all sections have content!
for i in range(len(section_nums)):
if not i == len(section_nums) - 1:
params = cleaned[section_nums[i] + 1 : section_nums[i + 1]]
else:
params = cleaned[section_nums[i] + 1 : len(cleaned)]
section_name = (
cleaned[section_nums[i]]
.lstrip("#####")
.strip()
.replace("Section ", "")
.lower()
)
#
params_dict = {}
if params:
# Clean it, replace in-text newlines with a space and then split on newlines.
split_params = params[0].strip().replace("\n ", " ").split("\n")
# Process params and descriptions per section
for split_param in split_params:
split_param_info = split_param.split(" : ")
if not len(split_param_info) == 3:
# there are ocassions where the semicolon
# is used in the description text itself.
if len(split_param_info) == 4:
split_param_info = [
split_param_info[0],
": ".join([split_param_info[1], split_param_info[2]]),
split_param_info[3],
]
# other occassions?
# Put the information in a dict
param_name = split_param_info[0]
param_description = split_param_info[1]
rest = split_param_info[2]
params_dict[param_name] = {
"param_name": param_name,
"description": param_description,
"rest": rest,
}
# make section_dict
section_dict = {
"section_name": section_name,
"parameters": params_dict.copy(),
}
# Put in the total dict
help_all_dict[section_name] = section_dict.copy()
# Print things
if print_help:
for section in sorted(help_all_dict.keys()):
print(
"##################\n###### Section {}\n##################".format(
section
)
)
section_dict = help_all_dict[section]
for param_name in sorted(section_dict["parameters"].keys()):
param = section_dict["parameters"][param_name]
print(
"\n{}:\n\t{}: {}".format(
param["param_name"], param["description"], param["rest"]
)
)
# # Loop over all the parameters an call the help() function on it.
# # Takes a long time but this is for testing
# for section in help_all_dict.keys():
# section_dict = help_all_dict[section]
# for param in section_dict['parameters'].keys():
# get_help(param)
return help_all_dict
def get_help_super(print_help=False, fail_silently=True):
"""
Function that first runs get_help_all, and then per argument also run
the help function to get as much information as possible.
"""
# Get help_all information
help_all_dict = get_help_all(print_help=False)
for section_name in help_all_dict:
section = help_all_dict[section_name]
print(section_name)
for parameter_name in section["parameters"].keys():
print("\t", parameter_name)
help_all_super_dict = help_all_dict.copy()
# Loop over all sections and stuff
for section_name in help_all_dict:
# Skipping the section i/o because that one shouldn't be available to python anyway
if not section_name == "i/o":
section = help_all_dict[section_name]
for parameter_name in section["parameters"].keys():
parameter = section["parameters"][parameter_name]
# Get detailed help info
detailed_help = get_help(
parameter_name, print_help=False, fail_silently=fail_silently,
)
if detailed_help:
# check whether the descriptions of help_all and detailed help are the same
if not fail_silently:
if not parameter["description"] == detailed_help["description"]:
print(json.dumps(parameter, indent=4))
## put values into help all super dict
# input type
parameter["parameter_value_input_type"] = detailed_help[
"parameter_value_input_type"
]
# default
parameter["default"] = detailed_help["default"]
# macros
if "macros" in detailed_help.keys():
parameter["macros"] = detailed_help["macros"]
section["parameters"][parameter_name] = parameter
if print_help:
print(json.dumps(help_all_super_dict, indent=4))
return help_all_super_dict
########################################################
# logfile functions
########################################################
def load_logfile(logfile):
"""
Experimental function that parses the generated logfile of binary_c.
"""
with open(logfile, "r") as file:
logfile_data = file.readlines()
time_list = []
m1_list = []
m2_list = []
k1_list = []
k2_list = []
sep_list = []
ecc_list = []
rel_r1_list = []
rel_r2_list = []
event_list = []
# random_seed = logfile_data[0].split()[-2]
# random_count = logfile_data[0].split()[-1]
# probability = logfile_data[-1].split()
for line in logfile_data[1:-1]:
split_line = line.split()
time_list.append(split_line[0])
m1_list.append(split_line[1])
m2_list.append(split_line[2])
k1_list.append(split_line[3])
k2_list.append(split_line[4])
sep_list.append(split_line[5])
ecc_list.append(split_line[6])
rel_r1_list.append(split_line[7])
rel_r2_list.append(split_line[8])
event_list.append(" ".join(split_line[9:]))
print(event_list)
########################################################
# Ensemble dict functions
########################################################
def inspect_dict(dict_1, indent=0, print_structure=True):
"""
Function to inspect a dict.
Works recursively if there is a nested dict.
Prints out keys and their value types
"""
structure_dict = {}
for key, value in dict_1.items():
structure_dict[key] = type(value)
if print_structure:
print("\t" * indent, key, type(value))
if isinstance(value, dict):
structure_dict[key] = inspect_dict(value, indent=indent + 1, print_structure=print_structure)
return structure_dict
def merge_dicts(dict_1, dict_2):
"""
Function to merge two dictionaries.
Behaviour:
When dict keys are present in both, we decide based on the value types how to combine them:
- dictionaries will be merged by calling recursively calling this function again
- numbers will be added
- (opt) lists will be appended
- In the case that the instances do now match: for now I will raise an error
When dict keys are only present in one of either, we just add the content to the new dict
"""
# Set up new dict
new_dict = {}
#
keys_1 = dict_1.keys()
keys_2 = dict_2.keys()
# Find overlapping keys of both dicts
overlapping_keys = set(keys_1).intersection(set(keys_2))
# Find the keys that are unique
unique_to_dict_1 = set(keys_1).difference(set(keys_2))
unique_to_dict_2 = set(keys_2).difference(set(keys_1))
# Add the unique keys to the new dict
for key in unique_to_dict_1:
if isinstance(dict_1[key], (float, int)):
new_dict[key] = dict_1[key]
else:
copy_dict = copy.deepcopy(dict_1[key])
new_dict[key] = copy_dict
for key in unique_to_dict_2:
if isinstance(dict_2[key], (float, int)):
new_dict[key] = dict_2[key]
else:
copy_dict = copy.deepcopy(dict_2[key])
new_dict[key] = copy_dict
# Go over the common keys:
for key in overlapping_keys:
# See whether the types are actually the same
if not type(dict_1[key]) is type(dict_2[key]):
print(
"Error {} and {} are not of the same type and cannot be merged".format(
dict_1[key], dict_2[key]
)
)
raise ValueError
# Here we check for the cases that we want to explicitly catch. Ints will be added,
# floats will be added, lists will be appended (though that might change) and dicts will be
# dealt with by calling this function again.
else:
# ints
if isinstance(dict_1[key], int) and isinstance(dict_2[key], int):
new_dict[key] = dict_1[key] + dict_2[key]
# floats
elif isinstance(dict_1[key], float) and isinstance(dict_2[key], float):
new_dict[key] = dict_1[key] + dict_2[key]
# lists
elif isinstance(dict_1[key], list) and isinstance(dict_2[key], list):
new_dict[key] = dict_1[key] + dict_2[key]
# dicts
elif isinstance(dict_1[key], dict) and isinstance(dict_2[key], dict):
new_dict[key] = merge_dicts(dict_1[key], dict_2[key])
else:
print(
"Object types {},{} not supported".format(
type(dict_1[key]), type(dict_2[key])
)
)
#
return new_dict
class binarycDecoder(json.JSONDecoder):
"""
Custom decoder to transform the numbers that are strings to actual floats
"""
def decode(self, s):
result = super().decode(
s
) # result = super(Decoder, self).decode(s) for Python 2.x
return self._decode(result)
def _decode(self, o):
"""
Depending on the type of object is will determine whether to loop over the elements,
or try to change the type of the object from string to float
The try except might be a somewhat rough solution but it catches all cases.
"""
# Check if we can turn it into a float
# if isinstance(o, str) or isinstance(o, unicode):
if isinstance(o, str):
try:
return float(o)
except ValueError:
return o
elif isinstance(o, dict):
return {k: self._decode(v) for k, v in o.items()}
elif isinstance(o, list):
return [self._decode(v) for v in o]
else:
return o
def binaryc_json_serializer(obj):
"""
Custom serializer for binary_c to use when functions are present in the dictionary
that we want to export.
Function objects will be turned into str representations of themselves
"""
if inspect.isfunction(obj):
return str(obj)
return obj