fixing isolated graph issues

DistrictHeatingNetworkCreator.py

@@ -5,16 +5,50 @@ from shapely.geometry import Polygon, Point, LineString, MultiPoint
 import networkx as nx
 
 
-class DistrictHeatingNetworkCreator:
+def plot_network_graph(network_graph):
-    def __init__(self, buildings_file, roads_file):
     """
-        Initialize the class with paths to the buildings and roads data files.
+    Plot the network graph using matplotlib and networkx.
+
+    :param network_graph: The NetworkX graph to be plotted.
+    """
+    plt.figure(figsize=(12, 12))
+    pos = {node: (node[0], node[1]) for node in network_graph.nodes()}
+
+    # Draw nodes
+    nx.draw_networkx_nodes(network_graph, pos, node_color='blue', node_size=50)
+
+    # Draw edges
+    nx.draw_networkx_edges(network_graph, pos, edge_color='gray')
+
+    # Create a dictionary for node labels for centroids only
+    node_labels = {node: data['name'] for node, data in network_graph.nodes(data=True) if
+                   data.get('type') == 'centroid'}
+
+    # Adjust node label positions to reduce overlap
+    label_pos = {node: (coords[0], coords[1] + 0.03) for node, coords in pos.items()}  # Shift labels up
+
+    # Draw node labels for centroids
+    nx.draw_networkx_labels(network_graph, label_pos, labels=node_labels, font_size=8, verticalalignment='bottom')
+
+    plt.title('District Heating Network Graph')
+    plt.axis('off')
+    plt.show()
+
+
+class DistrictHeatingNetworkCreator:
+    def __init__(self, buildings_file, roads_file, central_plant_longitude, central_plant_latitude):
+        """
+        Initialize the class with paths to the buildings and roads data files, and central plant coordinates.
 
         :param buildings_file: Path to the GeoJSON file containing building data.
         :param roads_file: Path to the Shapefile containing road data.
+        :param central_plant_longitude: Longitude of the central plant.
+        :param central_plant_latitude: Latitude of the central plant.
         """
         self.buildings_file = buildings_file
         self.roads_file = roads_file
+        self.central_plant_longitude = central_plant_longitude
+        self.central_plant_latitude = central_plant_latitude
 
     def run(self):
         """
@@ -29,8 +63,11 @@ class DistrictHeatingNetworkCreator:
 
     def _load_and_process_data(self):
         """
-        Load and process the building and road data.
+        Load and process the building and road data, and add central plant node.
         """
+        # Load road data
+        self.gdf_road = gpd.read_file(self.roads_file)
+
         # Load building data
         with open(self.buildings_file, 'r') as file:
             city = json.load(file)
@@ -38,30 +75,30 @@ class DistrictHeatingNetworkCreator:
         # Extract centroids and building IDs from building data
         centroids = []
         building_ids = []  # List to store building IDs
-        buildings = city['features']
+        for building in city['features']:
-        for building in buildings:
             coordinates = building['geometry']['coordinates'][0]
             building_polygon = Polygon(coordinates)
             centroid = building_polygon.centroid
             centroids.append(centroid)
-            building_ids.append(building['id'])  # Extract building ID
+            building_ids.append(building['id'])
+
+        centroids.append(Point(self.central_plant_longitude, self.central_plant_latitude))
+        building_ids.append(1)
 
         # Convert centroids to a GeoDataFrame and include building IDs
         self.centroids_gdf = gpd.GeoDataFrame({
             'geometry': [Point(centroid.x, centroid.y) for centroid in centroids],
-            'building_id': building_ids  # Add building IDs as a column
+            'building_id': building_ids,
+            'type': ['centroid' for _ in centroids]  # Add type for centroids
         }, crs='EPSG:4326')
 
-        # Load road data
-        self.gdf_road = gpd.read_file(self.roads_file)
-
-        # Ensure centroids are in the same CRS as roads
-        self.centroids_gdf = self.centroids_gdf.to_crs(self.gdf_road.crs)
-
     def _find_nearest_roads(self):
         """
         Find the nearest road for each building centroid.
         """
+        # Ensure centroids are in the same CRS as roads
+        self.centroids_gdf = self.centroids_gdf.to_crs(self.gdf_road.crs)
+
         # Process road geometries
         self.gdf_clean = gpd.GeoDataFrame(
             {'geometry': [LineString([coord for coord in line.coords]) for line in self.gdf_road.geometry]})
@@ -88,9 +125,17 @@ class DistrictHeatingNetworkCreator:
         self.gdf_pts3 = gpd.GeoDataFrame({'geometry': self.nearest_points + list(self.gdf_pts.geometry)})
 
         # Identify intersections and create LineStrings based on intersections
-        self.gdf_clean["intersect"] = [
+        intersects = []
-            [y for y in range(len(self.gdf_pts2)) if self.gdf_pts2.geometry[y].distance(geom) <= 1.0] for geom in
+        for geom in self.gdf_clean.geometry:
-            self.gdf_clean.geometry]
+            intersecting_points = []
+            if geom is not None:
+                for y in range(len(self.gdf_pts2)):
+                    point_geom = self.gdf_pts2.geometry[y]
+                    if point_geom is not None and point_geom.distance(geom) <= 1.0:
+                        intersecting_points.append(y)
+            intersects.append(intersecting_points)
+
+        self.gdf_clean["intersect"] = intersects
         self.gdf_cleaner = self.gdf_clean[self.gdf_clean["intersect"].apply(len).gt(0)].reset_index(drop=True)
 
         self.test_list = []
@@ -127,83 +172,35 @@ class DistrictHeatingNetworkCreator:
         Create a NetworkX graph from the processed geospatial data.
         :return: A NetworkX graph representing the district heating network.
         """
-        G = nx.Graph()
+        g = nx.Graph()
 
         # Convert centroids to EPSG:4326 for Google Maps compatibility
         for idx, row in self.centroids_gdf.iterrows():
-            building_name = f"Building_{idx + 1}"
+            building_name = f"Building_{idx}"
-            G.add_node((row.geometry.x, row.geometry.y),
+            g.add_node((row.geometry.x, row.geometry.y),
                        type='centroid',
                        name=building_name,
-                       building_id=row['building_id'])  # Add building ID as an attribute
+                       building_id=str(row.get('building_id')))
 
         for point in self.nearest_points:
-            G.add_node((point.x, point.y), type='nearest_point')
+            g.add_node((point.x, point.y), type='nearest_point')
 
         # Add edges with lengths as weights for the road network
         for line in self.gdf_cleanest.geometry:
             length = line.length
             if isinstance(line.boundary, MultiPoint):
-                # Handle MultiPoint boundary
                 points = list(line.boundary.geoms)
                 for i in range(len(points) - 1):
                     start_point = points[i]
                     end_point = points[i + 1]
-                    G.add_edge((start_point.x, start_point.y), (end_point.x, end_point.y), weight=length)
+                    g.add_edge((start_point.x, start_point.y), (end_point.x, end_point.y), weight=length)
             else:
-                # Handle typical case with two endpoints
                 start_point, end_point = line.boundary
-                G.add_edge((start_point.x, start_point.y), (end_point.x, end_point.y), weight=length)
+                g.add_edge((start_point.x, start_point.y), (end_point.x, end_point.y), weight=length)
 
         # Add edges connecting nearest points to their centroids
         for point, centroid in zip(self.nearest_points, self.centroids_gdf.geometry):
             distance = point.distance(centroid)
-            G.add_edge((point.x, point.y), (centroid.x, centroid.y), weight=distance)
+            g.add_edge((point.x, point.y), (centroid.x, centroid.y), weight=distance)
-
-        return G
-
-    def plot_network_graph(self, network_graph):
-        """
-        Plot the network graph using matplotlib and networkx.
-
-        :param network_graph: The NetworkX graph to be plotted.
-        """
-        plt.figure(figsize=(12, 12))
-        pos = {node: (node[0], node[1]) for node in network_graph.nodes()}
-
-        # Draw nodes and edges
-        nx.draw_networkx_nodes(network_graph, pos, node_color='blue', node_size=50)
-        nx.draw_networkx_edges(network_graph, pos, edge_color='gray')
-
-        # Create a dictionary for node labels for centroids only
-        node_labels = {node: data['name'] for node, data in network_graph.nodes(data=True) if
-                       data.get('type') == 'centroid'}
-
-        # Adjust node label positions to reduce overlap
-        label_pos = {node: (coords[0], coords[1] + 0.03) for node, coords in pos.items()}  # Shift labels up
-
-        # Draw node labels for centroids
-        nx.draw_networkx_labels(network_graph, label_pos, labels=node_labels, font_size=8, verticalalignment='bottom')
-
-        plt.title('District Heating Network Graph')
-        plt.axis('off')
-        plt.show()
-
-    def graph_enrich(self, network_graph, city):
-        """
-        Enrich the nodes in the network graph with attributes from corresponding buildings in the city.
-
-        :param network_graph: NetworkX graph object representing the network.
-        :param city: Hub's City object.
-        """
-        for building in city.buildings:
-            for node, attrs in network_graph.nodes(data=True):
-                if attrs.get('type') == 'centroid' and attrs.get('building_id') == building.name:
-                    network_graph.nodes[node]['building_cooling_peak_load'] = building.cooling_peak_load
-                    network_graph.nodes[node]['building_cooling_demand'] = building.cooling_demand
-                    network_graph.nodes[node]['building_domestic_hot_water_demand'] = (
-                        building.domestic_hot_water_heat_demand)
-                    network_graph.nodes[node]['building_heating_demand'] = building.heating_demand
-                    network_graph.nodes[node]['building_heating_peak_load'] = building.heating_peak_load
-                    network_graph.nodes[node]['building_external_temperature'] = building.external_temperature
 
+        return g

main.py

@@ -54,12 +54,9 @@ network_creator = DistrictHeatingNetworkCreator(
 
 # Create the network graph
 network_graph = network_creator.run()
-
-network_creator.graph_enrich(network_graph, city)
-
-print("Network Graph Created")
-
-# Print attributes of the centroid nodes
 for node, attrs in network_graph.nodes(data=True):
     if attrs.get('type') == 'centroid':
-        print(f"Node: {node}, Attributes: {attrs}")
+        print(type(attrs.get('building_id')))
+
+for building in city.buildings:
+    network_creator.graph_enrich(network_graph=network_graph, building=building)

majid.py

@@ -0,0 +1,206 @@
+import json
+import geopandas as gpd
+import matplotlib.pyplot as plt
+from shapely.geometry import Polygon, Point, LineString, MultiPoint
+import networkx as nx
+
+
+def plot_network_graph(network_graph):
+    """
+    Plot the network graph using matplotlib and networkx.
+
+    :param network_graph: The NetworkX graph to be plotted.
+    """
+    plt.figure(figsize=(12, 12))
+    pos = {node: (node[0], node[1]) for node in network_graph.nodes()}
+
+    # Draw nodes
+    nx.draw_networkx_nodes(network_graph, pos, node_color='blue', node_size=50)
+
+    # Draw edges
+    nx.draw_networkx_edges(network_graph, pos, edge_color='gray')
+
+    # Create a dictionary for node labels for centroids only
+    node_labels = {node: data['name'] for node, data in network_graph.nodes(data=True) if
+                   data.get('type') == 'centroid'}
+
+    # Adjust node label positions to reduce overlap
+    label_pos = {node: (coords[0], coords[1] + 0.03) for node, coords in pos.items()}  # Shift labels up
+
+    # Draw node labels for centroids
+    nx.draw_networkx_labels(network_graph, label_pos, labels=node_labels, font_size=8, verticalalignment='bottom')
+
+    plt.title('District Heating Network Graph')
+    plt.axis('off')
+    plt.show()
+
+
+class DistrictHeatingNetworkCreator:
+    def __init__(self, buildings_file, roads_file, central_plant_longitude, central_plant_latitude):
+        """
+        Initialize the class with paths to the buildings and roads data files, and central plant coordinates.
+
+        :param buildings_file: Path to the GeoJSON file containing building data.
+        :param roads_file: Path to the Shapefile containing road data.
+        :param central_plant_longitude: Longitude of the central plant.
+        :param central_plant_latitude: Latitude of the central plant.
+        """
+        self.buildings_file = buildings_file
+        self.roads_file = roads_file
+        self.central_plant_longitude = central_plant_longitude
+        self.central_plant_latitude = central_plant_latitude
+
+    def run(self):
+        """
+        Main method to execute the district heating network creation process.
+        :return: NetworkX graph with nodes and edges representing the network.
+        """
+        self._load_and_process_data()
+        self._find_nearest_roads()
+        self._process_intersections()
+        network_graph = self._create_network_graph()
+        return network_graph
+
+    def _load_and_process_data(self):
+        """
+        Load and process the building and road data, and add central plant node.
+        """
+        # Load road data
+        self.gdf_road = gpd.read_file(self.roads_file)
+
+        # Load building data
+        with open(self.buildings_file, 'r') as file:
+            city = json.load(file)
+
+        # Extract centroids and building IDs from building data
+        centroids = []
+        building_ids = []  # List to store building IDs
+        for building in city['features']:
+            coordinates = building['geometry']['coordinates'][0]
+            building_polygon = Polygon(coordinates)
+            centroid = building_polygon.centroid
+            centroids.append(centroid)
+            building_ids.append(building['id'])
+
+        centroids.append(Point(self.central_plant_longitude, self.central_plant_latitude))
+        building_ids.append(1)
+
+        # Convert centroids to a GeoDataFrame and include building IDs
+        self.centroids_gdf = gpd.GeoDataFrame({
+            'geometry': [Point(centroid.x, centroid.y) for centroid in centroids],
+            'building_id': building_ids,
+            'type': ['centroid' for _ in centroids]  # Add type for centroids
+        }, crs='EPSG:4326')
+
+    def _find_nearest_roads(self):
+        """
+        Find the nearest road for each building centroid.
+        """
+        # Ensure centroids are in the same CRS as roads
+        self.centroids_gdf = self.centroids_gdf.to_crs(self.gdf_road.crs)
+
+        # Process road geometries
+        self.gdf_clean = gpd.GeoDataFrame(
+            {'geometry': [LineString([coord for coord in line.coords]) for line in self.gdf_road.geometry]})
+
+        # Find the nearest road line and point for each centroid
+        self.closest_linestrings = []
+        self.nearest_points = []
+        for centroid in self.centroids_gdf.geometry:
+            closest_road = min(self.gdf_clean.geometry, key=lambda x: x.distance(centroid))
+            self.closest_linestrings.append(closest_road)
+            nearest_point = closest_road.interpolate(closest_road.project(centroid))
+            self.nearest_points.append(nearest_point)
+
+    def _process_intersections(self):
+        """
+        Process intersections and create final geometries.
+        """
+        # Create additional GeoDataFrames for points and nearest points
+        self.gdf_pts = gpd.GeoDataFrame(
+            {'geometry': [Point(coord) for line in self.gdf_clean.geometry for coord in line.coords]})
+        self.gdf_pts2 = gpd.GeoDataFrame({'geometry': self.nearest_points})
+
+        # Combine nearest points and road points into one GeoDataFrame
+        self.gdf_pts3 = gpd.GeoDataFrame({'geometry': self.nearest_points + list(self.gdf_pts.geometry)})
+
+        # Identify intersections and create LineStrings based on intersections
+        intersects = []
+        for geom in self.gdf_clean.geometry:
+            intersecting_points = []
+            if geom is not None:
+                for y in range(len(self.gdf_pts2)):
+                    point_geom = self.gdf_pts2.geometry[y]
+                    if point_geom is not None and point_geom.distance(geom) <= 1.0:
+                        intersecting_points.append(y)
+            intersects.append(intersecting_points)
+
+        self.gdf_clean["intersect"] = intersects
+        self.gdf_cleaner = self.gdf_clean[self.gdf_clean["intersect"].apply(len).gt(0)].reset_index(drop=True)
+
+        self.test_list = []
+        for idx, row in self.gdf_cleaner.iterrows():
+            for i in range(len(row["intersect"]) + 1):
+                if i == 0:
+                    self.test_list.append(
+                        LineString([row['geometry'].coords[0], self.gdf_pts3.geometry[row['intersect'][i]]]))
+                elif i < len(row['intersect']):
+                    self.test_list.append(LineString(
+                        [self.gdf_pts3.geometry[row['intersect'][i - 1]], self.gdf_pts3.geometry[row['intersect'][i]]]))
+                else:
+                    self.test_list.append(
+                        LineString([self.gdf_pts3.geometry[row['intersect'][i - 1]], row['geometry'].coords[-1]]))
+
+        self.gdf_cleanest = gpd.GeoDataFrame({'geometry': self.test_list})
+
+        points = [coord for geom in self.gdf_cleanest.geometry for coord in geom.coords]
+        gdf_pts_cnt = self.gdf_pts.copy()
+        gdf_pts_cnt["count"] = gdf_pts_cnt.geometry.apply(lambda x: points.count(x.coords[0]))
+        gdf_pts_reset = gdf_pts_cnt[gdf_pts_cnt["count"] > 1].reset_index(drop=True)
+        gdf_pts_drop = gdf_pts_cnt[gdf_pts_cnt["count"] <= 1].reset_index(drop=True)
+
+        # Remove unnecessary geometries from gdf_cleanest
+        for idx, geom in self.gdf_cleanest.iterrows():
+            for coord in geom.geometry.coords:
+                if coord in [pt.coords[0] for pt in gdf_pts_drop.geometry]:
+                    self.gdf_cleanest = self.gdf_cleanest.drop(idx)
+
+        self.gdf_cleanest.reset_index(drop=True, inplace=True)
+
+    def _create_network_graph(self):
+        """
+        Create a NetworkX graph from the processed geospatial data.
+        :return: A NetworkX graph representing the district heating network.
+        """
+        g = nx.Graph()
+
+        # Convert centroids to EPSG:4326 for Google Maps compatibility
+        for idx, row in self.centroids_gdf.iterrows():
+            building_name = f"Building_{idx}"
+            g.add_node((row.geometry.x, row.geometry.y),
+                       type='centroid',
+                       name=building_name,
+                       building_id=str(row.get('building_id')))
+
+        for point in self.nearest_points:
+            g.add_node((point.x, point.y), type='nearest_point')
+
+        # Add edges with lengths as weights for the road network
+        for line in self.gdf_cleanest.geometry:
+            length = line.length
+            if isinstance(line.boundary, MultiPoint):
+                points = list(line.boundary.geoms)
+                for i in range(len(points) - 1):
+                    start_point = points[i]
+                    end_point = points[i + 1]
+                    g.add_edge((start_point.x, start_point.y), (end_point.x, end_point.y), weight=length)
+            else:
+                start_point, end_point = line.boundary
+                g.add_edge((start_point.x, start_point.y), (end_point.x, end_point.y), weight=length)
+
+        # Add edges connecting nearest points to their centroids
+        for point, centroid in zip(self.nearest_points, self.centroids_gdf.geometry):
+            distance = point.distance(centroid)
+            g.add_edge((point.x, point.y), (centroid.x, centroid.y), weight=distance)
+
+        return g

out_files/Westmount_out.bnd

@@ -1,4 +1,4 @@
-Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.02 18:55
+Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.04 23:26
 ! This file shows details about the branches, nodes, and other
 ! elements of the flow connections.
 ! This file is intended for use in "debugging" potential problems

out_files/Westmount_out.eio

@@ -1,4 +1,4 @@
-Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.02 18:55
+Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.04 23:26
 ! <Version>, Version ID
  Version, 9.5
 ! <Timesteps per Hour>, #TimeSteps, Minutes per TimeStep {minutes}

out_files/Westmount_out.end

@@ -1 +1 @@
-EnergyPlus Completed Successfully-- 36 Warning; 1 Severe Errors; Elapsed Time=00hr 00min 16.32sec
+EnergyPlus Completed Successfully-- 36 Warning; 1 Severe Errors; Elapsed Time=00hr 00min 15.60sec

out_files/Westmount_out.err

@@ -1,6 +1,6 @@
-Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.02 18:55,
+Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.04 23:26,
    ** Warning ** GetHTSurfaceData: Surfaces with interface to Ground found but no "Ground Temperatures" were input.
-   **   ~~~   ** Found first in surface=4A8C5510-4917-4962-B668-AC2B363E1666
+   **   ~~~   ** Found first in surface=9A71C69C-9586-4DA7-9E88-896BCC784F3F
    **   ~~~   ** Defaults, constant throughout the year of (18.0) will be used.
    ** Warning ** GetInternalHeatGains: People="173256_OCCUPANCY", Activity Level Schedule Name values
    **   ~~~   ** fall outside typical range [70,1000] W/person for Thermal Comfort Reporting.
@@ -73,4 +73,4 @@ Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.02 18:55,
    ************* Use Output:Diagnostics,DisplayUnusedObjects; to see them.
    ************* EnergyPlus Warmup Error Summary. During Warmup: 0 Warning; 0 Severe Errors.
    ************* EnergyPlus Sizing Error Summary. During Sizing: 0 Warning; 0 Severe Errors.
-   ************* EnergyPlus Completed Successfully-- 36 Warning; 1 Severe Errors; Elapsed Time=00hr 00min 16.32sec
+   ************* EnergyPlus Completed Successfully-- 36 Warning; 1 Severe Errors; Elapsed Time=00hr 00min 15.60sec

out_files/Westmount_out.eso

@@ -1,4 +1,4 @@
-Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.02 18:55
+Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.04 23:26
 1,5,Environment Title[],Latitude[deg],Longitude[deg],Time Zone[],Elevation[m]
 2,8,Day of Simulation[],Month[],Day of Month[],DST Indicator[1=yes 0=no],Hour[],StartMinute[],EndMinute[],DayType
 3,5,Cumulative Day of Simulation[],Month[],Day of Month[],DST Indicator[1=yes 0=no],DayType  ! When Daily Report Variables Requested

out_files/Westmount_out.mtr

@@ -1,4 +1,4 @@
-Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.02 18:55
+Program Version,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.04 23:26
 1,5,Environment Title[],Latitude[deg],Longitude[deg],Time Zone[],Elevation[m]
 2,8,Day of Simulation[],Month[],Day of Month[],DST Indicator[1=yes 0=no],Hour[],StartMinute[],EndMinute[],DayType
 3,5,Cumulative Day of Simulation[],Month[],Day of Month[],DST Indicator[1=yes 0=no],DayType  ! When Daily Meters Requested

out_files/Westmount_out.rvaudit

@@ -1,16 +1,16 @@
  ReadVarsESO
- processing:D:\concordia_university\Projects\system_assignation\out_files\Westmount_a8b376.rvi
+ processing:D:\concordia_university\Projects\system_assignation\out_files\Westmount_fb347d.rvi
  input file:D:\concordia_university\Projects\system_assignation\out_files\Westmount_out.eso
  output file:D:\concordia_university\Projects\system_assignation\out_files\Westmount_out.csv
  getting all vars from:D:\concordia_university\Projects\system_assignation\out_files\Westmount_out.eso
   number variables requested for output=          44
- ReadVars Run Time=00hr 00min  1.42sec
+ ReadVars Run Time=00hr 00min  1.12sec
  ReadVarsESO program completed successfully.
  ReadVarsESO
- processing:D:\concordia_university\Projects\system_assignation\out_files\Westmount_a8b376.mvi
+ processing:D:\concordia_university\Projects\system_assignation\out_files\Westmount_fb347d.mvi
  input file:D:\concordia_university\Projects\system_assignation\out_files\Westmount_out.mtr
  output file:D:\concordia_university\Projects\system_assignation\out_files\Westmount_mtr.csv
  getting all vars from:D:\concordia_university\Projects\system_assignation\out_files\Westmount_out.mtr
   number variables requested for output=           4
- ReadVars Run Time=00hr 00min  0.22sec
+ ReadVars Run Time=00hr 00min  0.20sec
  ReadVarsESO program completed successfully.

out_files/Westmount_tbl.csv

@@ -1,4 +1,4 @@
-Program Version:,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.02 18:55
+Program Version:,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.04 23:26
 Tabular Output Report in Format: ,Comma
 
 Building:,Buildings in b'Westmount'
@@ -196,7 +196,7 @@ FOR:,Entire Facility
 General
 
 ,,Value
-,Program Version and Build,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.02 18:55
+,Program Version and Build,EnergyPlus, Version 9.5.0-de239b2e5f, YMD=2024.02.04 23:26
 ,RunPeriod,RUN PERIOD 1
 ,Weather File,Montreal Int'l PQ CAN WYEC2-B-94792 WMO#=716270
 ,Latitude [deg],45.47
@@ -352,97 +352,97 @@ FOR:,Entire Facility
 Opaque Exterior
 
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 Opaque Interior
@@ -454,81 +454,81 @@ Opaque Interior
 Exterior Fenestration
 
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-,F174D83D-4D6B-4628-BA02-7CEB1BA5AEFC WINDOW,WINDOW_CONSTRUCTION_1,11.64,0.00,0.00,11.64,11.64,2.954,0.391,0.305,,,No,F174D83D-4D6B-4628-BA02-7CEB1BA5AEFC,176.03,90.00,S
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-,060DED99-1508-4619-9CEA-0110F324D0F2 WINDOW,WINDOW_CONSTRUCTION_1,7.42,0.00,0.00,7.42,7.42,2.954,0.391,0.305,,,No,060DED99-1508-4619-9CEA-0110F324D0F2,266.55,90.00,W
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-,A4833F7A-0137-432B-9CAF-D5B61B75C7E8 WINDOW,WINDOW_CONSTRUCTION_1,21.85,0.00,0.00,21.85,21.85,2.954,0.391,0.305,,,No,A4833F7A-0137-432B-9CAF-D5B61B75C7E8,176.10,90.00,S
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-,EC035472-9DAA-4E36-8FF4-92501F8FBB4F WINDOW,WINDOW_CONSTRUCTION_1,5.65,0.00,0.00,5.65,5.65,2.954,0.391,0.305,,,No,EC035472-9DAA-4E36-8FF4-92501F8FBB4F,176.54,90.00,S
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-,A3A28AB7-5EDA-48C8-9870-BCB88B3AE469 WINDOW,WINDOW_CONSTRUCTION_1,12.92,0.00,0.00,12.92,12.92,2.954,0.391,0.305,,,No,A3A28AB7-5EDA-48C8-9870-BCB88B3AE469,176.50,90.00,S
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-,88FE6E02-3BC5-415E-B0D1-E18FB9DAE858 WINDOW,WINDOW_CONSTRUCTION_1,1.06,0.00,0.00,1.06,1.06,2.954,0.391,0.305,,,No,88FE6E02-3BC5-415E-B0D1-E18FB9DAE858,180.60,90.00,S
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 ,Non-North Total or Average,,,,,,1300.13,2.954,0.391,0.305,,,,,,,

requirements.txt

@@ -1,26 +1,28 @@
-xmltodict
+xmltodict~=0.13.0
-numpy
+numpy~=1.24.3
-trimesh[all]
+trimesh[all]~=3.12.0
-pyproj
+pyproj~=3.6.0
-pandas
+pandas~=2.0.2
-requests
+requests~=2.31.0
 esoreader
-geomeppy
+geomeppy~=0.11.8
 PyWavefront
 xlrd
 openpyxl
-networkx
+networkx~=3.1
 parseidf==1.0.0
 ply
 scipy
-PyYAML
+PyYAML~=6.0
 pyecore==0.12.2
-python-dotenv
+python-dotenv~=1.0.0
-SQLAlchemy
+SQLAlchemy~=2.0.16
 bcrypt==4.0.1
-shapely
+shapely~=2.0.1
-geopandas
+geopandas~=0.13.2
 triangle
 psycopg2-binary
-Pillow
+Pillow~=9.5.0
-pathlib
+pathlib~=1.0.1
+setuptools~=67.8.0
+matplotlib~=3.7.1

test.py

@@ -0,0 +1,28 @@
+from DistrictHeatingNetworkCreator import DistrictHeatingNetworkCreator, plot_network_graph
+from geojson_creator import process_geojson
+
+geojson_file = process_geojson(x=-73.59318810862032, y=45.49021341690168, diff=0.0005)
+
+print("Input geojson file created!")
+
+buildings_file = './input_files/output_buildings.geojson'
+roads_file = './input_files/roads/geobase_mtl.shp'
+
+central_plant = [45.48895734472743, -73.59311297816515]
+# Replace these with the actual longitude and latitude of your central plant
+central_plant_longitude = central_plant[1]
+central_plant_latitude = central_plant[0]
+
+# Create an instance of DistrictHeatingNetworkCreator
+network_creator = DistrictHeatingNetworkCreator(
+    buildings_file,
+    roads_file,
+    central_plant_longitude,
+    central_plant_latitude
+)
+
+# Create the network graph
+network_graph = network_creator.run()
+
+# Plot the network graph with the minimum spanning tree
+plot_network_graph(network_graph)