Matsim exporter. Generates population and config
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__pycache__/matsim.cpython-39.pyc
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__pycache__/matsim.cpython-39.pyc
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main.py
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main.py
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@ -6,7 +6,7 @@ from hub.imports.usage_factory import UsageFactory
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from hub.helpers.dictionaries import Dictionaries
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from matsim_engine import MatSimEngine
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from matsim_visualizer import MatSimVisualizer
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from matsim import Matsim
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try:
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file_path = (Path(__file__).parent / 'input_files' / 'summerschool_all_buildings.geojson')
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@ -24,7 +24,8 @@ try:
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ConstructionFactory(construction_format, city).enrich()
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UsageFactory(usage_format, city).enrich()
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MatSimEngine(city, 'output_files')
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# Matsim(city, 'output_files')._export()
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MatSimEngine('output_files/Montreal_config.xml').run()
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# visualizer = MatSimVisualizer('output_files/network.xml.gz', 'output_files/output_events.xml.gz')
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# visualizer.visualize()
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266
matsim.py
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266
matsim.py
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@ -0,0 +1,266 @@
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import math
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import subprocess
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import xmltodict
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import gzip
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import shutil
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import geopandas as gpd
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from shapely.geometry import Point
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import hub.helpers.constants as cte
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from lxml import etree
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# TODO: remove xmltodict completely and replace with lxml as it doesnt allow for repeated mixed ordered tags
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class Matsim:
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def __init__(self, city, output_file_path):
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self.city = city
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self.output_file_path = output_file_path
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self.facilities = {
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'@name': self.city.name + ' Facilities',
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'facility': []
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}
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self.population = etree.Element("population")
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def _export(self):
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self._export_facilities()
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self._export_network()
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self._export_population()
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self._export_config()
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def _export_facilities(self):
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buildings_shape_data = {
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'id': [],
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'geometry': []
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}
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for building in self.city.buildings:
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for surface in building.grounds:
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for coord in surface.solid_polygon.coordinates:
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buildings_shape_data['id'].append(f"{building.name}")
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buildings_shape_data['geometry'].append(Point(coord[0], coord[1]))
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facility = {
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'@id': building.name,
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'@x': str(building.centroid[0]),
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'@y': str(building.centroid[1]),
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'activity': []
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}
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if len(building.thermal_zones_from_internal_zones) > 1:
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raise NotImplementedError("multi-zone buildings aren't yet supported")
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building_schedules = []
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capacity = 0
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for thermal_zone in building.thermal_zones_from_internal_zones:
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capacity = thermal_zone.occupancy.occupancy_density * building.floor_area * building.storeys_above_ground
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for schedule in thermal_zone.occupancy.occupancy_schedules:
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building_schedules.append(schedule)
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activity_info = {
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'@type': building.function,
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'capacity': {
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'@value': math.ceil(capacity)
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},
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'opentime': _convert_schedules(building_schedules)
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}
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facility['activity'].append(activity_info)
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self.facilities['facility'].append(facility)
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gdf = gpd.GeoDataFrame(
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buildings_shape_data,
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crs=self.city.srs_name
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)
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gdf.to_file("input_files/buildings_shapefile.shp")
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# Convert the Python dictionary to an XML string
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xml_content = xmltodict.unparse({'facilities': self.facilities}, pretty=True, short_empty_elements=True)
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# Write the XML to the file
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output_file = f"{self.output_file_path}/{self.city.name}_facilities.xml"
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with open(output_file, 'w') as file:
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file.write(xml_content)
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with open(output_file, 'rb') as f_in:
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with gzip.open(output_file + '.gz', 'wb') as f_out:
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shutil.copyfileobj(f_in, f_out)
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def _export_network(self):
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java_path = "java"
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jar_path = "matsim-network-from-osm.jar"
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command = [
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java_path,
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"-jar", jar_path,
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"input_files/merged-network.osm.pbf",
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"input_files/buildings_shapefile.shp",
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f"{self.output_file_path}/{self.city.name}_network.xml.gz"
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]
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subprocess.run(command)
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def _export_population(self):
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id = 0
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# Generate work facilities
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work = []
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for facility in self.facilities['facility']:
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if facility['activity'][0]['@type'] != cte.RESIDENTIAL:
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work.append({
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'type': facility['activity'][0]['@type'],
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'capacity': int(facility['activity'][0]['capacity']['@value']),
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'facility': facility['@id'],
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'x': facility['@x'],
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'y': facility['@y'],
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'start_time': '08:00:00',
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'end_time': '18:00:00'
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})
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# Generate the population from residential places first
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current_work = 0
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for facility in self.facilities['facility']:
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if facility['activity'][0]['@type'] == cte.RESIDENTIAL:
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max_capacity = int(facility['activity'][0]['capacity']['@value'])
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for _ in range(max_capacity):
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person = etree.SubElement(self.population, 'person', {
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'id': str(id),
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'sex': 'm',
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'age': '32',
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'car_avail': 'always',
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'employed': 'yes',
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})
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plan = etree.SubElement(person, 'plan', {'selected': 'yes'})
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# Residential activity
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etree.SubElement(plan, 'act', {
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'type': facility['activity'][0]['@type'],
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'facility': facility['@id'],
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'x': facility['@x'],
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'y': facility['@y'],
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'end_time': '7:30:00'
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})
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# Leg to work
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etree.SubElement(plan, 'leg', {'mode': 'car'})
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# Work activity
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etree.SubElement(plan, 'act', {
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'type': work[current_work]['type'],
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'facility': work[current_work]['facility'],
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'x': work[current_work]['x'],
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'y': work[current_work]['y'],
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'start_time': work[current_work]['start_time'],
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'end_time': work[current_work]['end_time'],
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})
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# Leg to home
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etree.SubElement(plan, 'leg', {'mode': 'car'})
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# Residential activity (return)
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etree.SubElement(plan, 'act', {
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'type': facility['activity'][0]['@type'],
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'facility': facility['@id'],
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'x': facility['@x'],
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'y': facility['@y'],
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})
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work[current_work]['capacity'] -= 1
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if work[current_work]['capacity'] == 0:
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current_work += 1
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id += 1
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# Convert the Python dictionary to an XML string
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xml_content = etree.tostring(self.population, pretty_print=True, encoding='UTF-8', xml_declaration=True).decode('utf-8')
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# Write the XML to the file
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output_file = f"{self.output_file_path}/{self.city.name}_population.xml"
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with open(output_file, 'w') as file:
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file.write(xml_content)
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with open(output_file, 'rb') as f_in:
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with gzip.open(output_file + '.gz', 'wb') as f_out:
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shutil.copyfileobj(f_in, f_out)
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def _export_config(self):
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parameterset = []
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for facility in self.facilities['facility']:
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if facility['activity'][0]['@type'] == cte.RESIDENTIAL:
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parameterset.append({'@type':'activityParams', 'param': [
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{'@name':'activityType','@value':facility['activity'][0]['@type']},
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{'@name':'typicalDuration', '@value' : '12:00:00'},
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{'@name':'priority','@value': '1'}
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]})
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else:
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parameterset.append({'@type':'activityParams', 'param': [
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{'@name': 'activityType', '@value': facility['activity'][0]['@type']},
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{'@name':'openingTime','@value': '08:00:00'},
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{'@name':'closingTime','@value': '18:00:00'},
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{'@name':'typicalDuration','@value': '08:00:00'},
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{'@name':'priority','@value': '1'}
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]
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})
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config = {
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'module': [
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{'@name': 'network', 'param': {'@name':'inputNetworkFile', '@value': f"{self.city.name}_network.xml.gz"}},
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{'@name': 'plans', 'param': {'@name':'inputPlansFile', '@value': f"{self.city.name}_population.xml.gz"}},
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{'@name': 'facilities', 'param': {'@name':'inputFacilitiesFile', '@value': f"{self.city.name}_facilities.xml.gz"}},
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{'@name': 'controler', 'param': [
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{'@name': 'outputDirectory', '@value': '/output'},
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{'@name': 'firstIteration', '@value': '0'},
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{'@name': 'lastIteration', '@value': '10'},
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]},
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{'@name': 'qsim', 'param': [
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{'@name': 'startTime', '@value': '00:00:00'},
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{'@name': 'endTime', '@value': '00:00:00'},
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{'@name': 'snapshotperiod', '@value': '00:00:00'},
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]},
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{'@name':'planCalcStore','param':[
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{'@name':'learningRate', '@value':'1.0'},
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{'@name':'BrainExpBeta', '@value':'2.0'},
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{'@name':'lateArrival', '@value':'-18'},
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{'@name':'earlyDeparture', '@value':'-0'},
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{'@name':'performing', '@value':'+6'},
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{'@name':'waiting', '@value':'-0'},
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],'parameterset': parameterset},
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{'@name':'strategy','param':[
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{'@name': 'maxAgentPlanMemorySize', '@value': '5'},
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{'@name': 'ModuleProbability_1', '@value': '0.9'},
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{'@name': 'Module_1', '@value': 'BestScore'},
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{'@name': 'ModuleProbability_2', '@value': '0.1'},
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{'@name': 'Module_2', '@value': 'ReRoute'},
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]}
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]
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}
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xml_content = xmltodict.unparse({'config': config}, pretty=True, short_empty_elements=True)
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with open(f"{self.output_file_path}/{self.city.name}_config.xml", 'w') as file:
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file.write(xml_content)
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def _convert_schedules(building_schedules):
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converted_schedules = []
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for schedule in building_schedules:
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opening_hour = 0
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closing_hour = 0
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for i, value in enumerate(schedule.values):
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if value > 0:
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opening_hour = i
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break
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for i, value in reversed(list(enumerate(schedule.values))):
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if value > 0:
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closing_hour = i
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break
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for day in schedule.day_types:
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if day[0:3] != 'hol':
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converted_schedules.append({
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'@day': day[0:3],
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'@start_time': opening_hour,
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'@end_time': closing_hour
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})
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return converted_schedules
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119
matsim_engine.py
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matsim_engine.py
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@ -9,121 +9,8 @@ from matsim_activity_to_matsim_schedule import MatsimActivityToMatsimSchedule
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from hub_function_to_matsim_activity import HubFunctionToMatsimActivity
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class MatSimEngine:
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def __init__(self, city, output_file_path):
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self._city = city
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self._output_file_path = output_file_path
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facilities_dict = {
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'facilities': {
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'@name': 'Montreal Facilities',
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'facility': []
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}
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}
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hub_function_to_matsim = HubFunctionToMatsimActivity()
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matsim_schedule = MatsimActivityToMatsimSchedule()
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buildings_shape_data = {
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'id': [],
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'geometry': []
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}
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# 1- Facilities
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# TODO: this should come from the factories, please check idf generation
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for building in city.buildings:
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activity = hub_function_to_matsim.dictionary[building.function].split(',')
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for surface in building.grounds:
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for coord in surface.solid_polygon.coordinates:
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buildings_shape_data['id'].append(f"{building.name}")
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buildings_shape_data['geometry'].append(Point(coord[0], coord[1]))
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facility = {
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'@id': building.name,
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'@x': str(building.centroid[0]),
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'@y': str(building.centroid[1]),
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'activity': []
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}
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if len(building.thermal_zones_from_internal_zones) > 1:
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raise NotImplementedError("multi-zone buildings aren't yet supported")
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building_schedules = []
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capacity = 0
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for thermal_zone in building.thermal_zones_from_internal_zones:
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capacity = thermal_zone.occupancy.occupancy_density * building.floor_area * building.storeys_above_ground
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for schedule in thermal_zone.occupancy.occupancy_schedules:
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building_schedules.append(schedule)
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for new_activity in activity:
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activity_info = {
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'@type': new_activity,
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'capacity': {
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'@value': math.ceil(capacity)
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},
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'opentime': []
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}
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for schedule in building_schedules:
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opening_hour = 0
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closing_hour = 0
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# Find opening hour (first hour > 0)
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for i, value in enumerate(schedule.values):
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if value > 0:
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opening_hour = i
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break
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for i, value in reversed(list(enumerate(schedule.values))):
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if value > 0:
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closing_hour = i
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break
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for day in schedule.day_types:
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if day[0:3] != 'hol':
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activity_info['opentime'].append({
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'@day': day[0:3],
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'@start_time': opening_hour,
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'@end_time': closing_hour
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})
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facility['activity'].append(activity_info)
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facilities_dict['facilities']['facility'].append(facility)
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gdf = gpd.GeoDataFrame(
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buildings_shape_data,
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crs=city.srs_name
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)
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gdf.to_file("input_files/buildings_shapefile.shp")
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# Convert the Python dictionary to an XML string
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xml_content = xmltodict.unparse(facilities_dict, pretty=True, short_empty_elements=True)
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# Write the XML to the file
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with open(f"{output_file_path}/{city.name}_facilities.xml", 'w') as file:
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file.write(xml_content)
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# 2- Network
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# First get only the part of the network necessary for the simulation
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java_path = "java"
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jar_path = "matsim-network-from-osm.jar"
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command = [
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java_path,
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"-jar", jar_path,
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"input_files/merged-network.osm.pbf",
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"input_files/buildings_shapefile.shp",
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f"{output_file_path}/network.xml.gz"
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]
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subprocess.run(command)
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# 3- Population
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# 3.1 - Public Transport
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# 4- Config Generation
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def __init__(self, config_file_path):
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self._config_file_path = config_file_path
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def run(self):
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java_path = "java"
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command = [java_path, "-jar", jar_path]
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# Must generate this config file first.
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# command.append(config_file_path)
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command.append(self._config_file_path)
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subprocess.run(command)
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