Exemplo n.º 1
0
 def test_cartesian_distance(self):
     v1 = [1,0]
     v2 = [0,1]
     dist_1 = vector_utils.cartesian_distance_2d(v1, v2)
     dist_2 = math.sqrt((v1[0]-v2[0])**2+(v1[1]-v2[1])**2)
     self.assertEqual(dist_1, dist_2)
     v1 = [1,0]
     v2 = [0,0]
     dist_1 = vector_utils.cartesian_distance_2d(v1, v2)
     self.assertEqual(dist_1, 1)
     v1 = [1,0]
     v2 = [-1,0]
     dist_1 = vector_utils.cartesian_distance_2d(v1, v2)
     self.assertEqual(dist_1, 2)
Exemplo n.º 2
0
 def test_neighbour_distance(self):
     """
     TODO: This test contains no asserts and has just been used as a way of eye-balling distances when debug is
     uncommented.
     Create a world with a fixed number of cells, where the expected approximate distance between neighbouring
     nodes is know, so aberrant configurations can be detected
     """
     # Calculate min_dist
     # Create world
     total_cells=50
     w = world.World(total_cells_desired=total_cells)
     starting_node = random.choice(w.all_boundary_nodes)
     for node in w.all_boundary_nodes:
         # Confirm node has neighbours
         self.assertGreater(len(starting_node.neighbours), 0)
         for neighbour in node.neighbours:
             #print("{0} to {1}".format(node.loc, neighbour.loc))
             angular_dist = math.degrees(geographic_utils.radians_between_locations(node.loc, neighbour.loc))
             node_cartesian_pos = geographic_utils.geographic_to_cartesian([np.array(node.loc)])[0]
             neighbour_cartesian_pos = geographic_utils.geographic_to_cartesian([np.array(neighbour.loc)])[0]
             direct_dist = vector_utils.cartesian_distance_2d(node_cartesian_pos, neighbour_cartesian_pos)
Exemplo n.º 3
0
def geographic_direct_distance(a, b):
    """
    Calculates direct distance between two coordinate locations, with a path that passes through the sphere
    """
    cartesian_points = geographic_to_cartesian([a, b])
    return cartesian_distance_2d(cartesian_points[0], cartesian_points[1])