Building Distribution Graph

Assuming you have list of parcels (of type ParcelModel from shift). Here is a script to generate distribution graph.

from shift import ParcelModel, GeoLocation, get_kmeans_clusters, PRSG

def _get_parcel_points(parcels: list[ParcelModel]) -> list[GeoLocation]:
    return [el.geometry[0] if isinstance(el.geometry, list) else el.geometry for el in parcels]


num_clusters = int(len(parcels) / 10)
clusters = get_kmeans_clusters(max([num_clusters, 1]), _get_parcel_points(parcels))

builder = PRSG(
    groups=clusters,
    source_location=GeoLocation(-87.7044461105055, 41.049957636092465),
)
graph = builder.get_distribution_graph()

Here we are first creating clusters of approximately 10 customers each and using cluster center as distribution transformer location to build distribution graph. A distribution graph is simply a connectivity model between nodes and edges. PRSG class builds primary distribution network by reducing road network available in the area abd builds secondary network using 2d grid approach. The node closest to source_location will be treated as substation.

If you want to visualize this graph, you can again use PlotManager.

from shift import add_distribution_graph, PlotManager
plot_manager = PlotManager(center=GeoLocation(-87.62, 41.095))
add_distribution_graph(graph,plot_manager )
plot_manager.show()