Refactor function to use vectorised version

cea/technologies/network_layout/connectivity_potential.py

@@ -270,24 +270,14 @@ def nearest_neighbor_within(others, point, max_distance):
 
 
 def near_analysis(building_centroids, street_network, crs):
-    near_point = []
-    building_name = []
-    for point, name in zip(building_centroids.geometry, building_centroids.Name):
-        point._crs = crs
-        distance = 10e10
-        for line in street_network.geometry:
-            line._crs = crs
-            nearest_point_candidate = line.interpolate(line.project(point))
-            distance_candidate = point.distance(nearest_point_candidate)
-            if distance_candidate < distance:
-                distance = distance_candidate
-                nearest_point = nearest_point_candidate
-        building_name.append(name)
-        near_point.append(nearest_point)
-
-    geometry = near_point
-    df = gdf(geometry=geometry, crs=crs)
-    df["Name"] = building_name
+    # Get the nearest edge for each building centroid
+    nearest_indexes = street_network.sindex.nearest(building_centroids.geometry, return_all=False)[1]
+    nearest_lines = street_network.iloc[nearest_indexes].reset_index(drop=True)  # reset index so vectorization works
+
+    # Find length along line that is closest to the point (project) and get interpolated point on the line (interpolate)
+    nearest_points = nearest_lines.interpolate(nearest_lines.project(building_centroids))
+
+    df = gdf({"Name": building_centroids["Name"]}, geometry=nearest_points, crs=crs)
     return df