utils.py 文件源码

def find_biggest_cluster(radius, points, order=None):
    graph = nx.Graph()
    for point in points:
            if order is '9QM=':
                #is a lure module - 9QM=
                now = int(time.time())
                remaining = now - point['last_modified_timestamp_ms']
                f = point['latitude'], point['longitude'], remaining
            else:
                f = point['latitude'], point['longitude'], 0
            graph.add_node(f)
            for node in graph.nodes():
                if node != f and distance(f[0], f[1], node[0], node[1]) <= radius*2:
                    graph.add_edge(f, node)
    cliques = list(find_cliques(graph))
    if len(cliques) > 0:
        max_clique = max(list(find_cliques(graph)), key=lambda l: (len(l), sum(x[2] for x in l)))
        merc_clique = [coord2merc(x[0], x[1]) for x in max_clique]
        clique_x, clique_y = zip(*merc_clique)
        best_point = np.mean(clique_x), np.mean(clique_y)
        best_coord = merc2coord(best_point)
        return {'latitude': best_coord[0], 'longitude': best_coord[1], 'num_points': len(max_clique)}
    else:
        return None