"""Contains functions to export crowd data to a ZIP file and save it."""
# Copyright 2025 Institute of Light and Matter, CNRS UMR 5306, University Claude Bernard Lyon 1
# Contributors: Oscar DUFOUR, Maxime STAPELLE, Alexandre NICOLAS
# This software is a computer program designed to generate a realistic crowd from anthropometric data and
# simulate the mechanical interactions that occur within it and with obstacles.
# This software is governed by the CeCILL-B license under French law and abiding by the rules of distribution
# of free software. You can use, modify and/ or redistribute the software under the terms of the CeCILL-B
# license as circulated by CEA, CNRS and INRIA at the following URL "http://www.cecill.info".
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# economic rights, and the successive licensors have only limited liability.
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import io
import zipfile
from pathlib import Path
import configuration.backup.crowd_to_dict as to_dict
import configuration.backup.dict_to_xml_and_reverse as dict_to_xml
from configuration.models.crowd import Crowd
[docs]
def write_crowd_data_to_zip(current_crowd: Crowd) -> io.BytesIO:
"""
Generate an in-memory ZIP file containing XML representations of the nested dictionaries that summarize the crowd parameters.
Parameters
----------
current_crowd : Crowd
The current crowd object containing the parameters to be saved.
Returns
-------
io.BytesIO
An in-memory ZIP file containing the XML representations of crowd parameters.
"""
# Extract static pedestrian parameters and convert to XML
static_data_dict = to_dict.get_static_params(current_crowd)
static_data_bytes = dict_to_xml.static_dict_to_xml(static_data_dict)
# Extract dynamic pedestrian parameters and convert to XML
dynamic_data_dict = to_dict.get_dynamic_params(current_crowd)
dynamic_data_bytes = dict_to_xml.dynamic_dict_to_xml(dynamic_data_dict)
# Extract geometry parameters and convert to XML
geometry_data_dict = to_dict.get_geometry_params(current_crowd)
geometry_data_bytes = dict_to_xml.geometry_dict_to_xml(geometry_data_dict)
# Extract material parameters and convert to XML
materials_data_dict = to_dict.get_materials_params()
materials_data_bytes = dict_to_xml.materials_dict_to_xml(materials_data_dict)
# Create an in-memory ZIP file
zip_buffer = io.BytesIO()
with zipfile.ZipFile(zip_buffer, "w", zipfile.ZIP_DEFLATED) as zip_file:
# Write each XML file into the ZIP archive
zip_file.writestr("Agents.xml", static_data_bytes)
zip_file.writestr("AgentDynamics.xml", dynamic_data_bytes)
zip_file.writestr("Geometry.xml", geometry_data_bytes)
zip_file.writestr("Materials.xml", materials_data_bytes)
# Move the buffer's pointer to the beginning
zip_buffer.seek(0)
return zip_buffer
[docs]
def save_crowd_data_to_zip(current_crowd: Crowd, output_zip_path: Path) -> None:
"""
Save crowd data as a ZIP file containing multiple XML files.
Parameters
----------
current_crowd : Crowd
The current crowd object containing the parameters to be saved.
output_zip_path : Path
The path where the ZIP file will be saved.
Raises
------
TypeError
If `output_zip_path` is not a Path object.
ValueError
If `output_zip_path` does not have a .zip extension.
"""
if not isinstance(output_zip_path, Path):
raise TypeError("`output_zip_path` should be a Path object.")
if not output_zip_path.suffix == ".zip":
raise ValueError("`output_zip_path` should have a .zip extension.")
# Ensure the output directory exists
output_zip_path.parent.mkdir(parents=True, exist_ok=True)
# Generate the ZIP file in memory
zip_buffer = write_crowd_data_to_zip(current_crowd)
# Write the in-memory ZIP file to the specified output path
with open(output_zip_path, "wb") as output_file:
output_file.write(zip_buffer.read())
# Close the in-memory buffer
zip_buffer.close()