mapping_utils.py

def find_best_loop(G: nx.Graph, root, target_dist, tol=1.0, min_elev: Optional[Union[int, float]] = None,
                   dataset: Optional[rasterio.DatasetReader] = None):
    if min_elev and not dataset:
        raise ValueError("If asking for elevation data, you must include a rasterio dataset")
    error = 1e8
    best_path = []
    for n in G.nodes():
        if nx.has_path(G, root, n):
            shortest_path = nx.shortest_path(G, root, n)
            paths = nx.all_simple_paths(G, root, n, cutoff=10)
            for path in paths:
                if path == shortest_path:
                    continue

                path_loop = path + nx.shortest_path(G, n, root, weight="length")[1:]

                path_diversity = len(set(path_loop)) / len(path_loop)

                dist = path_length(G, path_loop)
                e_new = np.abs(dist - target_dist) / path_diversity
                if e_new < error:
                    error = e_new
                    best_path = path_loop
                if error < tol:
                    if min_elev:
                        coords_list = path_to_coords_list(G, path_loop)
                        _, elev = get_elevation_profile_of_segment(dataset, coords_list)
                        elev_gain = elevation_gain(elev)
                        if elev_gain < min_elev:
                            continue
                    return best_path
    return best_path