get_clusters.py

def get_cluster(cluster, point, traversed_points):
  cluster.add(point)
  traversed_points = traversed_points - {point}
  untraversed_neighbors = point["neighbors"] - traversed_points
  while untraversed_neighbors:
    next_point = untraversed_neighbors.pop()
    custer = get_cluster(cluster, next_point, traversed_points)
  return cluster

def get_clusters(x_y_vectors, epsilon, min_connections):
  points = []
  clusters = []
  
  for coords in x_y_vectors:
    points.append({
      "coords": coords,
      "neighbors": set()
    })
    
  for i, point in enumerate(points):
    for other_point in points[i+1:]:
      if calculate_distance(point["coords"], other_point["coords"]) < epsilon:
        point["neighbors"].add(other_point)
        other_point["neighbors"].add(point)
 
  clusters = set()
  untraversed_points = set()
  while untraversed_points:
    point = untraversed_points.pop()
    cluster = get_cluster(set(), point, traversed_points)
    untraversed_points = untraversed_points - traversed_points
    if (len(cluster) >= min_connections):
      cluster.add(cluster)
  
  return clusters