From 2ca52c157a98a3bd9c4c179cce21519c5997d32f Mon Sep 17 00:00:00 2001 From: Majid Rezaei Date: Wed, 31 Jul 2024 17:38:17 -0400 Subject: [PATCH] fix: replace id with name in node attributes --- main.py | 3 +- .../district_heating_network_creator.py | 19 +- work_in_progress.ipynb | 448 +++++++++++++----- 3 files changed, 351 insertions(+), 119 deletions(-) diff --git a/main.py b/main.py index be373421..63c73fbe 100644 --- a/main.py +++ b/main.py @@ -23,7 +23,8 @@ import hub.helpers.constants as cte from hub.exports.exports_factory import ExportsFactory from scripts.pv_feasibility import pv_feasibility import matplotlib.pyplot as plt -import numpy as np +from scripts.district_heating_network.district_heating_network_creator import DistrictHeatingNetworkCreator +from scripts.district_heating_network.road_processor import road_processor base_path = Path(__file__).parent dir_manager = DirectoryManager(base_path) diff --git a/scripts/district_heating_network/district_heating_network_creator.py b/scripts/district_heating_network/district_heating_network_creator.py index 4ccbb7f8..c83b3aa9 100644 --- a/scripts/district_heating_network/district_heating_network_creator.py +++ b/scripts/district_heating_network/district_heating_network_creator.py @@ -1,16 +1,17 @@ import json -import matplotlib.pyplot as plt -from shapely.geometry import Polygon, Point, LineString -import networkx as nx -from typing import List, Tuple -from rtree import index import math import logging +import matplotlib.pyplot as plt +import networkx as nx +from shapely.geometry import Polygon, Point, LineString +from typing import List, Tuple +from rtree import index # Configure logging logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') logging.getLogger('numexpr').setLevel(logging.ERROR) + def haversine(lon1, lat1, lon2, lat2): """ Calculate the great-circle distance between two points @@ -126,6 +127,7 @@ class DistrictHeatingNetworkCreator: """ Find the nearest point on each closest road for each centroid. """ + def find_nearest_point_on_line(point: Point, line: LineString) -> Point: return line.interpolate(line.project(point)) @@ -151,6 +153,7 @@ class DistrictHeatingNetworkCreator: """ Break down roads into segments connecting nearest points. """ + def break_down_roads(closest_roads: List[LineString], nearest_points_list: List[Point]) -> List[LineString]: new_segments = [] for road in closest_roads: @@ -190,6 +193,7 @@ class DistrictHeatingNetworkCreator: """ Create a Minimum Spanning Tree (MST) from the graph. """ + def find_paths_between_nearest_points(g: nx.Graph, nearest_points: List[Point]) -> List[Tuple]: edges = [] for i, start_point in enumerate(nearest_points): @@ -282,7 +286,10 @@ class DistrictHeatingNetworkCreator: for i, centroid in enumerate(self.centroids): centroid_tuple = (centroid.x, centroid.y) building_name = self.building_names[i] - self.final_mst.add_node(centroid_tuple, type='building', id=building_name) + + # Add the centroid node with its attributes + self.final_mst.add_node(centroid_tuple, type='building', name=building_name) + nearest_point = None min_distance = float('inf') for node in self.final_mst.nodes(): diff --git a/work_in_progress.ipynb b/work_in_progress.ipynb index 09cb3058..0151fa6a 100644 --- a/work_in_progress.ipynb +++ b/work_in_progress.ipynb @@ -6,8 +6,8 @@ "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2024-07-31T19:22:04.345161Z", - "start_time": "2024-07-31T19:22:04.333148Z" + "end_time": "2024-07-31T21:38:47.230085Z", + "start_time": "2024-07-31T21:38:47.206748Z" } }, "source": [ @@ -39,13 +39,13 @@ "import numpy as np" ], "outputs": [], - "execution_count": 37 + "execution_count": 110 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:22:05.595202Z", - "start_time": "2024-07-31T19:22:05.583203Z" + "end_time": "2024-07-31T21:38:47.861524Z", + "start_time": "2024-07-31T21:38:47.843529Z" } }, "cell_type": "code", @@ -68,13 +68,13 @@ ], "id": "7d895f0e4ec2b851", "outputs": [], - "execution_count": 38 + "execution_count": 111 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:22:21.507678Z", - "start_time": "2024-07-31T19:22:08.823019Z" + "end_time": "2024-07-31T21:39:02.661096Z", + "start_time": "2024-07-31T21:38:48.727802Z" } }, "cell_type": "code", @@ -90,18 +90,18 @@ "WindowsPath('C:/Users/ab_reza/Majid/Concordia/Repositories/energy_system_modelling_workflow/input_files/output_buildings.geojson')" ] }, - "execution_count": 39, + "execution_count": 112, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 39 + "execution_count": 112 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T15:44:21.196453Z", - "start_time": "2024-07-31T15:44:20.864064Z" + "end_time": "2024-07-31T21:39:02.992446Z", + "start_time": "2024-07-31T21:39:02.663422Z" } }, "cell_type": "code", @@ -115,26 +115,26 @@ ], "id": "c03ae7cae09d4b21", "outputs": [], - "execution_count": 5 + "execution_count": 113 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:25:35.578319Z", - "start_time": "2024-07-31T19:25:35.334298Z" + "end_time": "2024-07-31T21:39:03.340164Z", + "start_time": "2024-07-31T21:39:02.993466Z" } }, "cell_type": "code", "source": "ConstructionFactory('nrcan', city).enrich()", "id": "c7d73638802e40d9", "outputs": [], - "execution_count": 40 + "execution_count": 114 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:25:37.532009Z", - "start_time": "2024-07-31T19:25:36.680254Z" + "end_time": "2024-07-31T21:39:04.079698Z", + "start_time": "2024-07-31T21:39:03.342163Z" } }, "cell_type": "code", @@ -150,26 +150,26 @@ ] } ], - "execution_count": 41 + "execution_count": 115 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:25:40.774878Z", - "start_time": "2024-07-31T19:25:40.225856Z" + "end_time": "2024-07-31T21:39:04.648022Z", + "start_time": "2024-07-31T21:39:04.081700Z" } }, "cell_type": "code", "source": "WeatherFactory('epw', city).enrich()", "id": "f66c01cb42c33b64", "outputs": [], - "execution_count": 42 + "execution_count": 116 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:27:14.303067Z", - "start_time": "2024-07-31T19:25:41.283758Z" + "end_time": "2024-07-31T21:40:39.688386Z", + "start_time": "2024-07-31T21:39:04.650024Z" } }, "cell_type": "code", @@ -183,18 +183,18 @@ "exporting:\n", " idf exported...\n", "\r\n", - "C:/EnergyPlusV23-2-0\\energyplus.exe --weather C:\\Users\\ab_reza\\Majid\\Concordia\\Repositories\\energy_system_modelling_workflow\\hub\\data\\weather\\epw\\CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw --output-directory C:\\Users\\ab_reza\\Majid\\Concordia\\Repositories\\energy_system_modelling_workflow\\out_files\\energy_plus_outputs --idd C:\\Users\\ab_reza\\Majid\\Concordia\\Repositories\\energy_system_modelling_workflow\\hub\\exports\\building_energy\\idf_files\\Energy+.idd --expandobjects --readvars --output-prefix Laval_ C:\\Users\\ab_reza\\Majid\\Concordia\\Repositories\\energy_system_modelling_workflow\\out_files\\energy_plus_outputs\\Laval_1b0f01.idf\r\n", + "C:/EnergyPlusV23-2-0\\energyplus.exe --weather C:\\Users\\ab_reza\\Majid\\Concordia\\Repositories\\energy_system_modelling_workflow\\hub\\data\\weather\\epw\\CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw --output-directory C:\\Users\\ab_reza\\Majid\\Concordia\\Repositories\\energy_system_modelling_workflow\\out_files\\energy_plus_outputs --idd C:\\Users\\ab_reza\\Majid\\Concordia\\Repositories\\energy_system_modelling_workflow\\hub\\exports\\building_energy\\idf_files\\Energy+.idd --expandobjects --readvars --output-prefix Laval_ C:\\Users\\ab_reza\\Majid\\Concordia\\Repositories\\energy_system_modelling_workflow\\out_files\\energy_plus_outputs\\Laval_602570.idf\r\n", "\n" ] } ], - "execution_count": 43 + "execution_count": 117 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:47:50.325333Z", - "start_time": "2024-07-31T19:47:46.092907Z" + "end_time": "2024-07-31T21:53:14.440222Z", + "start_time": "2024-07-31T21:53:10.290860Z" } }, "cell_type": "code", @@ -207,53 +207,198 @@ "roads_file = road_processor(location[1], location[0], 0.001)\n", "\n", "dhn_creator = DistrictHeatingNetworkCreator(geojson_file_path, roads_file)\n", - "network_graph = dhn_creator.run()\n", "\n", - "dhn_creator.plot_network_graph()" + "network_graph = dhn_creator.run()" ], "id": "8403846b0831b51d", "outputs": [ { - "data": { - "text/plain": [ - "
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" - }, - "metadata": {}, - "output_type": "display_data" + "ename": "AttributeError", + "evalue": "'Graph' object has no attribute 'building_names'", + "output_type": "error", + "traceback": [ + "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[1;31mAttributeError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[1;32mIn[121], line 11\u001B[0m\n\u001B[0;32m 8\u001B[0m dhn_creator \u001B[38;5;241m=\u001B[39m DistrictHeatingNetworkCreator(geojson_file_path, roads_file)\n\u001B[0;32m 10\u001B[0m network_graph \u001B[38;5;241m=\u001B[39m dhn_creator\u001B[38;5;241m.\u001B[39mrun()\n\u001B[1;32m---> 11\u001B[0m \u001B[43mnetwork_graph\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mbuilding_names\u001B[49m\n", + "\u001B[1;31mAttributeError\u001B[0m: 'Graph' object has no attribute 'building_names'" + ] } ], - "execution_count": 54 + "execution_count": 121 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:48:06.764851Z", - "start_time": "2024-07-31T19:48:06.756855Z" + "end_time": "2024-07-31T21:43:05.521839Z", + "start_time": "2024-07-31T21:43:05.503748Z" } }, "cell_type": "code", "source": [ - "for node in network_graph.nodes(data=True):\n", - " node_id, node_attrs = node\n", - " if node_attrs.get('type') == 'building':\n", - " building_name = node_attrs.get('id')\n", - " for building in city.buildings:\n", - " if building.name == building_name:\n", - " building_attrs = vars(building)\n", - " for attr, value in building_attrs.items():\n", - " network_graph.nodes[node_id][attr] = value" + "for node_id, attrs in network_graph.nodes(data=True):\n", + " print(f\"Node {node_id} has attributes: {list(attrs.keys())}\")" ], - "id": "25e14bd5433e3d95", - "outputs": [], - "execution_count": 55 + "id": "9c4c32ed4a5b5434", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Node (-73.70263014634182, 45.52966550204674) has attributes: []\n", + "Node 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has attributes: ['type', 'id']\n", + "Node (-73.70224797036111, 45.531522088920134) has attributes: ['type', 'id']\n", + "Node (-73.70319066728962, 45.53075184355254) has attributes: ['type', 'id']\n", + "Node (-73.70309318391786, 45.53066844829803) has attributes: ['type', 'id']\n", + "Node (-73.70326346262547, 45.53124343502157) has attributes: ['type', 'id']\n", + "Node (-73.70289161913149, 45.53100954740511) has attributes: ['type', 'id']\n", + "Node (-73.7031243168426, 45.52969124795911) has attributes: ['type', 'id']\n", + "Node (-73.70332165936908, 45.531298238343524) has attributes: ['type', 'id']\n", + "Node (-73.70291683392738, 45.531464843960194) has attributes: ['type', 'id']\n", + "Node (-73.70257423757026, 45.53123533603945) has attributes: ['type', 'id']\n", + "Node (-73.70246354979903, 45.53116600989907) has attributes: ['type', 'id']\n", + "Node (-73.70137270924536, 45.53098156462814) has attributes: ['type', 'id']\n", + "Node (-73.70228611728258, 45.52973374332967) has attributes: ['type', 'id']\n", + "Node (-73.70192277090158, 45.530832193189546) has attributes: ['type', 'id']\n", + "Node (-73.70247403248253, 45.530300013163604) has attributes: ['type', 'id']\n", + "Node (-73.70233258364674, 45.53021274328478) has attributes: ['type', 'id']\n", + "Node (-73.70150159992788, 45.530157998392504) has attributes: ['type', 'id']\n", + "Node (-73.70178207574742, 45.53033147043354) has attributes: ['type', 'id']\n", + "Node (-73.70279118480165, 45.53007116190442) has attributes: ['type', 'id']\n", + "Node (-73.70290386342012, 45.53015742711493) has attributes: ['type', 'id']\n", + "Node (-73.70199360008198, 45.529972641218336) has attributes: ['type', 'id']\n", + "Node (-73.7032815855412, 45.52978985115031) has attributes: ['type', 'id']\n", + "Node (-73.70166271484868, 45.53063422765041) has attributes: ['type', 'id']\n", + "Node (-73.7015006171488, 45.530550593136034) has attributes: ['type', 'id']\n", + "Node (-73.70265213028476, 45.529962782747816) has attributes: ['type', 'id']\n", + "Node (-73.7029326957311, 45.53056979610127) has attributes: ['type', 'id']\n", + "Node (-73.70166661687237, 45.5297928936099) has attributes: ['type', 'id']\n", + "Node (-73.70193452736822, 45.53043505670828) has attributes: ['type', 'id']\n", + "Node (-73.70320906423977, 45.53033165241546) has attributes: ['type', 'id']\n", + "Node (-73.70242433058544, 45.531020523149344) has attributes: ['type', 'id']\n", + "Node (-73.70229173916934, 45.53104634226288) has attributes: ['type', 'id']\n", + "Node (-73.70164581777142, 45.53024975981883) has attributes: ['type', 'id']\n", + "Node (-73.70181323564402, 45.52988517687263) has attributes: ['type', 'id']\n", + "Node (-73.70207977647193, 45.53050710203167) has attributes: ['type', 'id']\n", + "Node (-73.70180201572698, 45.53073366018695) has attributes: ['type', 'id']\n", + "Node (-73.70260551746348, 45.53038579346295) has attributes: ['type', 'id']\n", + "Node (-73.7015368490746, 45.531520903846236) has attributes: ['type', 'id']\n", + "Node (-73.70277909755795, 45.530494359508104) has attributes: ['type', 'id']\n", + "Node (-73.7016306503588, 45.531601992190964) has attributes: ['type', 'id']\n", + "Node (-73.703188128229, 45.531634438129004) has attributes: ['type', 'id']\n", + "Node (-73.70225201894137, 45.5306050266003) has attributes: ['type', 'id']\n", + "Node (-73.70250211711432, 45.53079519337939) has attributes: ['type', 'id']\n", + "Node (-73.70143287673753, 45.53147394391961) has attributes: ['type', 'id']\n", + "Node (-73.7015564456529, 45.52971249323039) has attributes: ['type', 'id']\n", + "Node (-73.70213321668199, 45.530060293550356) has attributes: ['type', 'id']\n", + "Node (-73.70205098392802, 45.53092949418992) has attributes: ['type', 'id']\n", + "Node (-73.70273955351598, 45.53092005042424) has attributes: ['type', 'id']\n" + ] + } + ], + "execution_count": 119 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-07-31T19:36:41.941832Z", - "start_time": "2024-07-31T19:36:41.924833Z" + "end_time": "2024-07-31T21:29:21.717811Z", + "start_time": "2024-07-31T21:29:21.697811Z" + } + }, + "cell_type": "code", + "source": [ + "from scripts.district_heating_network.district_heating_factory import DistrictHeatingFactory\n", + "\n", + "DistrictHeatingFactory(city=city, graph=network_graph)" + ], + "id": "25e14bd5433e3d95", + "outputs": [ + { + "ename": "TypeError", + "evalue": "__init__() got an unexpected keyword argument 'graph'", + "output_type": "error", + "traceback": [ + "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[1;31mTypeError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[1;32mIn[94], line 3\u001B[0m\n\u001B[0;32m 1\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mscripts\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mdistrict_heating_network\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mdistrict_heating_factory\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m DistrictHeatingFactory\n\u001B[1;32m----> 3\u001B[0m \u001B[43mDistrictHeatingFactory\u001B[49m\u001B[43m(\u001B[49m\u001B[43mcity\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mcity\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mgraph\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mnetwork_graph\u001B[49m\u001B[43m)\u001B[49m\n", + "\u001B[1;31mTypeError\u001B[0m: __init__() got an unexpected keyword argument 'graph'" + ] + } + ], + "execution_count": 94 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-31T21:18:46.818842Z", + "start_time": "2024-07-31T21:18:46.799573Z" } }, "cell_type": "code", @@ -327,66 +472,145 @@ "Node (-73.7015262783945, 45.53176766055835) has attributes: []\n", "Node (-73.70142255824699, 45.531702316306436) has attributes: []\n", "Node (-73.70132694890151, 45.53164208190352) has attributes: []\n", - "Node (-73.70249378379357, 45.529882494691094) has attributes: ['type', 'id', '_name', '_level_of_detail', '_surfaces', '_type', '_city_object_lower_corner', '_city_object_upper_corner', '_detailed_polyhedron', '_simplified_polyhedron', '_min_x', '_min_y', '_min_z', '_max_x', '_max_y', '_max_z', '_centroid', '_volume', '_external_temperature', '_ground_temperature', '_global_horizontal', '_diffuse', '_direct_normal', '_sensors', '_neighbours', '_beam', '_city', '_households', '_basement_heated', '_attic_heated', '_terrains', '_year_of_construction', '_function', '_average_storey_height', '_storeys_above_ground', '_floor_area', '_roof_type', '_internal_zones', '_thermal_zones_from_internal_zones', '_shell', '_aliases', '_cold_water_temperature', '_heating_demand', '_cooling_demand', '_lighting_electrical_demand', '_appliances_electrical_demand', '_domestic_hot_water_heat_demand', '_heating_consumption', '_cooling_consumption', '_domestic_hot_water_consumption', '_distribution_systems_electrical_consumption', '_onsite_electrical_production', '_eave_height', '_energy_systems', '_systems_archetype_name', '_grounds', '_roofs', '_walls', '_internal_walls', '_ground_walls', '_attic_floors', '_interior_slabs', '_domestic_hot_water_peak_load', '_fuel_consumption_breakdown', '_pv_generation']\n", - "Node (-73.70236957992, 45.530697070843594) has attributes: ['type', 'id', '_name', '_level_of_detail', '_surfaces', '_type', '_city_object_lower_corner', '_city_object_upper_corner', '_detailed_polyhedron', '_simplified_polyhedron', '_min_x', '_min_y', '_min_z', '_max_x', '_max_y', '_max_z', '_centroid', '_volume', '_external_temperature', '_ground_temperature', '_global_horizontal', '_diffuse', '_direct_normal', '_sensors', '_neighbours', '_beam', '_city', '_households', '_basement_heated', '_attic_heated', '_terrains', '_year_of_construction', '_function', '_average_storey_height', '_storeys_above_ground', '_floor_area', '_roof_type', '_internal_zones', '_thermal_zones_from_internal_zones', '_shell', '_aliases', '_cold_water_temperature', '_heating_demand', '_cooling_demand', '_lighting_electrical_demand', '_appliances_electrical_demand', '_domestic_hot_water_heat_demand', '_heating_consumption', '_cooling_consumption', '_domestic_hot_water_consumption', '_distribution_systems_electrical_consumption', '_onsite_electrical_production', '_eave_height', '_energy_systems', '_systems_archetype_name', '_grounds', '_roofs', '_walls', '_internal_walls', '_ground_walls', '_attic_floors', '_interior_slabs', '_domestic_hot_water_peak_load', '_fuel_consumption_breakdown', '_pv_generation']\n", - "Node (-73.7023772579133, 45.52982887967387) has attributes: ['type', 'id', '_name', '_level_of_detail', '_surfaces', '_type', '_city_object_lower_corner', '_city_object_upper_corner', '_detailed_polyhedron', '_simplified_polyhedron', '_min_x', '_min_y', '_min_z', '_max_x', '_max_y', '_max_z', '_centroid', '_volume', '_external_temperature', '_ground_temperature', '_global_horizontal', '_diffuse', '_direct_normal', '_sensors', '_neighbours', '_beam', '_city', '_households', '_basement_heated', '_attic_heated', '_terrains', '_year_of_construction', '_function', '_average_storey_height', '_storeys_above_ground', '_floor_area', '_roof_type', '_internal_zones', '_thermal_zones_from_internal_zones', '_shell', '_aliases', '_cold_water_temperature', '_heating_demand', '_cooling_demand', '_lighting_electrical_demand', '_appliances_electrical_demand', '_domestic_hot_water_heat_demand', '_heating_consumption', '_cooling_consumption', '_domestic_hot_water_consumption', '_distribution_systems_electrical_consumption', '_onsite_electrical_production', '_eave_height', '_energy_systems', '_systems_archetype_name', '_grounds', '_roofs', '_walls', '_internal_walls', '_ground_walls', '_attic_floors', '_interior_slabs', '_domestic_hot_water_peak_load', '_fuel_consumption_breakdown', '_pv_generation']\n", - "Node (-73.70310348189996, 45.530242710105696) has attributes: ['type', 'id', '_name', '_level_of_detail', '_surfaces', '_type', '_city_object_lower_corner', '_city_object_upper_corner', '_detailed_polyhedron', '_simplified_polyhedron', '_min_x', '_min_y', '_min_z', '_max_x', '_max_y', '_max_z', '_centroid', '_volume', '_external_temperature', '_ground_temperature', '_global_horizontal', '_diffuse', '_direct_normal', '_sensors', '_neighbours', '_beam', '_city', '_households', '_basement_heated', '_attic_heated', '_terrains', '_year_of_construction', '_function', '_average_storey_height', '_storeys_above_ground', '_floor_area', '_roof_type', '_internal_zones', '_thermal_zones_from_internal_zones', '_shell', '_aliases', '_cold_water_temperature', '_heating_demand', '_cooling_demand', '_lighting_electrical_demand', '_appliances_electrical_demand', '_domestic_hot_water_heat_demand', 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attributes: ['type', 'id']\n", + "Node (-73.7015006171488, 45.530550593136034) has attributes: ['type', 'id']\n", + "Node (-73.70265213028476, 45.529962782747816) has attributes: ['type', 'id']\n", + "Node (-73.7029326957311, 45.53056979610127) has attributes: ['type', 'id']\n", + "Node (-73.70166661687237, 45.5297928936099) has attributes: ['type', 'id']\n", + "Node (-73.70193452736822, 45.53043505670828) has attributes: ['type', 'id']\n", + "Node (-73.70320906423977, 45.53033165241546) has attributes: ['type', 'id']\n", + "Node (-73.70242433058544, 45.531020523149344) has attributes: ['type', 'id']\n", + "Node (-73.70229173916934, 45.53104634226288) has attributes: ['type', 'id']\n", + "Node (-73.70164581777142, 45.53024975981883) has attributes: ['type', 'id']\n", + "Node (-73.70181323564402, 45.52988517687263) has attributes: ['type', 'id']\n", + "Node (-73.70207977647193, 45.53050710203167) has attributes: ['type', 'id']\n", + "Node (-73.70180201572698, 45.53073366018695) has attributes: ['type', 'id']\n", + "Node (-73.70260551746348, 45.53038579346295) has attributes: ['type', 'id']\n", + "Node (-73.7015368490746, 45.531520903846236) has attributes: ['type', 'id']\n", + "Node (-73.70277909755795, 45.530494359508104) has attributes: ['type', 'id']\n", + "Node (-73.7016306503588, 45.531601992190964) has attributes: ['type', 'id']\n", + "Node (-73.703188128229, 45.531634438129004) has attributes: ['type', 'id']\n", + "Node (-73.70225201894137, 45.5306050266003) has attributes: ['type', 'id']\n", + "Node (-73.70250211711432, 45.53079519337939) has attributes: ['type', 'id']\n", + "Node (-73.70143287673753, 45.53147394391961) has attributes: ['type', 'id']\n", + "Node (-73.7015564456529, 45.52971249323039) has attributes: ['type', 'id']\n", + "Node (-73.70213321668199, 45.530060293550356) has attributes: ['type', 'id']\n", + "Node (-73.70205098392802, 45.53092949418992) has attributes: ['type', 'id']\n", + "Node (-73.70273955351598, 45.53092005042424) has attributes: ['type', 'id']\n" ] } ], - "execution_count": 53 + "execution_count": 80 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-31T20:23:57.446448Z", + "start_time": "2024-07-31T20:23:57.431469Z" + } + }, + "cell_type": "code", + "source": [ + "for building in city.buildings:\n", + " print(building.name)" + ], + "id": "5b96a042e349e0eb", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "65418\n", + "70816\n", + "73478\n", + "82649\n", + "84906\n", + "87241\n", + "87719\n", + "88675\n", + "88747\n", + "89061\n", + "89062\n", + "89251\n", + "91214\n", + "92337\n", + "92399\n", + "92520\n", + "92979\n", + "93149\n", + "95265\n", + "95266\n", + "95465\n", + "95704\n", + "96241\n", + "96579\n", + "96580\n", + "96930\n", + "96931\n", + "96996\n", + "96997\n", + "97648\n", + "98087\n", + "98666\n", + "98667\n", + "102035\n", + "103043\n", + "103740\n", + "103795\n", + "107302\n", + "108296\n", + "108297\n", + "109211\n", + "109305\n", + "109773\n", + "110561\n", + "110873\n", + "113368\n", + "116927\n", + "118062\n", + "118250\n", + "119143\n", + "120435\n", + "124177\n", + "125538\n", + "128322\n", + "129429\n", + "130498\n" + ] + } + ], + "execution_count": 75 }, { "metadata": {