from scripts.district_heating_network.directory_manager import DirectoryManager import subprocess from building_modelling.ep_run_enrich import energy_plus_workflow from hub.imports.geometry_factory import GeometryFactory from hub.helpers.dictionaries import Dictionaries from hub.imports.construction_factory import ConstructionFactory from hub.imports.usage_factory import UsageFactory from hub.imports.weather_factory import WeatherFactory from hub.imports.results_factory import ResultFactory from building_modelling.geojson_creator import process_geojson import hub.helpers.constants as cte from hub.exports.exports_factory import ExportsFactory 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.district_heating_factory import DistrictHeatingFactory import json # Manage File Path base_path = "./" dir_manager = DirectoryManager(base_path) # Input files directory input_files_path = dir_manager.create_directory('input_files') geojson_file_path = input_files_path / 'Dombridge.geojson' pipe_data_file = input_files_path / 'pipe_data.json' # Output files directory output_path = dir_manager.create_directory('out_files') # Subdirectories for output files energy_plus_output_path = dir_manager.create_directory('out_files/energy_plus_outputs') simulation_results_path = dir_manager.create_directory('out_files/simulation_results') sra_output_path = dir_manager.create_directory('out_files/sra_outputs') cost_analysis_output_path = dir_manager.create_directory('out_files/cost_analysis') # Create ciry and run energyplus workflow city = GeometryFactory(file_type='geojson', path=geojson_file_path, height_field='maximum_roof_height', year_of_construction_field='year_built', function_field='building_type', function_to_hub=Dictionaries().montreal_function_to_hub_function).city ConstructionFactory('nrcan', city).enrich() UsageFactory('nrcan', city).enrich() WeatherFactory('epw', city).enrich() # energy_plus_workflow(city, energy_plus_output_path) ResultFactory('energy_plus_multiple_buildings', city, energy_plus_output_path).enrich() # District Heating Network Creator central_plant_locations = [(-73.66314280001727, 45.43813943275185)] # Add at least one location roads_file = "input_files/roads.json" dhn_creator = DistrictHeatingNetworkCreator(geojson_file_path, roads_file, central_plant_locations) network_graph = dhn_creator.run() # Pipe and pump sizing with open(pipe_data_file, 'r') as f: pipe_data = json.load(f) factory = DistrictHeatingFactory( city=city, graph=network_graph, supply_temperature=80 + 273, # in Kelvin return_temperature=60 + 273, # in Kelvin simultaneity_factor=0.9 ) factory.enrich() factory.sizing() factory.calculate_diameters_and_costs(pipe_data) pipe_groups, total_cost = factory.analyze_costs() # Save the pipe groups with total costs to a CSV file factory.save_pipe_groups_to_csv('pipe_groups.csv') import json import matplotlib.pyplot as plt import networkx as nx from shapely.geometry import shape, Polygon, MultiPolygon from shapely.validation import explain_validity # Load the GeoJSON file with open("input_files/Dombridge.geojson", "r") as file: geojson_data = json.load(file) # Initialize a figure fig, ax = plt.subplots(figsize=(15, 10)) # Set aspect to equal ax.set_aspect('equal') # Set figure and axes backgrounds to transparent fig.patch.set_facecolor('none') ax.set_facecolor('none') # Iterate over each feature in the GeoJSON for feature in geojson_data['features']: geom = shape(feature['geometry']) # Check if the geometry is valid if not geom.is_valid: print(f"Invalid geometry: {explain_validity(geom)}") continue # Skip invalid geometries # Plot polygons if isinstance(geom, Polygon): x, y = geom.exterior.xy ax.plot(x, y, color='black', linewidth=1) # Plot only the edges elif isinstance(geom, MultiPolygon): for poly in geom.geoms: x, y = poly.exterior.xy ax.plot(x, y, color='black', linewidth=1) # Plot only the edges else: print(f"Unhandled geometry type: {type(geom)}") continue # Prepare and plot the network graph G = network_graph # Get positions from node attributes pos = nx.get_node_attributes(G, 'pos') # Draw nodes, using different colors based on node type node_types = nx.get_node_attributes(G, 'type') colors = {'building': 'blue', 'generation': 'green', 'junction': 'red'} node_colors = [colors.get(node_types.get(node, 'junction'), 'black') for node in G.nodes()] nx.draw_networkx_nodes(G, pos, ax=ax, node_size=50, node_color=node_colors) nx.draw_networkx_edges(G, pos, ax=ax, edge_color="red", width=1.2) # Remove axes, ticks, and background ax.axis("off") # Adjust plot limits to the data x_values = [coord[0] for coord in pos.values()] y_values = [coord[1] for coord in pos.values()] ax.set_xlim(min(x_values) - 0.001, max(x_values) + 0.001) ax.set_ylim(min(y_values) - 0.001, max(y_values) + 0.001) # Save the plot with transparency plt.savefig("network_plot.png", bbox_inches='tight', pad_inches=0, transparent=True) plt.show()