From 6d39d181528ffd1e2252deef7d0f13b77b6deccb Mon Sep 17 00:00:00 2001
From: Majid Rezaei <majidrezaee734@gmail.com>
Date: Tue, 30 Jan 2024 09:01:27 -0500
Subject: [PATCH] buildings as buildings and the rest as junction nodes

---
 DistrictHeatingNetworkCreator.py | 60 +++++++++++++++++++++-----------
 1 file changed, 40 insertions(+), 20 deletions(-)

diff --git a/DistrictHeatingNetworkCreator.py b/DistrictHeatingNetworkCreator.py
index 4123709..2871e8a 100644
--- a/DistrictHeatingNetworkCreator.py
+++ b/DistrictHeatingNetworkCreator.py
@@ -126,37 +126,57 @@ class DistrictHeatingNetworkCreator:
         G = nx.Graph()
 
         # Add building nodes
-        building_idx = 1
-        for centroid in self.centroids_gdf.geometry:
-            label = f"Building_{building_idx}"
-            G.add_node(label, pos=(centroid.x, centroid.y), type='building')
-            building_idx += 1
+        for idx, centroid in enumerate(self.centroids_gdf.geometry):
+            node_label = f"Building_{idx + 1}"
+            G.add_node(node_label, pos=(centroid.x, centroid.y), type='building')
 
-        # Add junction nodes for the points along the line strings
-        junction_idx = 1
-        junction_positions = {}  # To keep track of junction positions
+        # Add junction nodes and keep track of them
+        junction_counter = 1
+        junction_points = set()  # To avoid duplicating junctions
+
+        # Process each line in gdf_cleanest
         for line in self.gdf_cleanest.geometry:
             for point in line.coords:
+                # Convert tuple to Point object for comparison
                 point_obj = Point(point)
-                if point_obj not in junction_positions:
-                    label = f"Junction_{junction_idx}"
-                    G.add_node(label, pos=(point_obj.x, point_obj.y), type='junction')
-                    junction_positions[point_obj] = label
-                    junction_idx += 1
 
-        # Add edges
+                # Check if this point is already a centroid (building)
+                if point_obj not in [centroid for centroid in self.centroids_gdf.geometry]:
+                    # Check if not already added as a junction
+                    if point_obj not in junction_points:
+                        node_label = f"Junction_{junction_counter}"
+                        G.add_node(node_label, pos=(point_obj.x, point_obj.y), type='junction')
+                        junction_points.add(point_obj)
+                        junction_counter += 1
+
+        # Add edges between nodes
         for line in self.gdf_cleanest.geometry:
             points = list(line.coords)
             for start, end in zip(points[:-1], points[1:]):
-                start_point_obj = Point(start)
-                end_point_obj = Point(end)
-                start_label = junction_positions.get(start_point_obj)
-                end_label = junction_positions.get(end_point_obj)
-                if start_label and end_label:
-                    G.add_edge(start_label, end_label, weight=LineString([start, end]).length)
+                start_node = self._find_closest_node(G, Point(start))
+                end_node = self._find_closest_node(G, Point(end))
+                if start_node and end_node:
+                    G.add_edge(start_node, end_node, weight=LineString([start, end]).length)
 
         return G
 
+    def _find_closest_node(self, graph, point):
+        """
+        Find the closest node to a given point.
+        :param graph: The NetworkX graph.
+        :param point: The point for which to find the closest node.
+        :return: The label of the closest node.
+        """
+        closest_node = None
+        min_dist = float('inf')
+        for node, data in graph.nodes(data=True):
+            node_point = Point(data['pos'])
+            dist = point.distance(node_point)
+            if dist < min_dist:
+                closest_node = node
+                min_dist = dist
+        return closest_node
+
     def plot_network_graph(self, network_graph):
         """
         Plot the network graph using matplotlib and networkx.