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)
def refine_voronoi_nodes_around_locations(self, new_seed_locations, min_point_dist=0.01, min_angle=2,
max_angle=15, num_child_points=20, failure_limit=5, num_adjacent=1):
"""
Regenerates voronoi boundary nodes, attempting to add more seed_points around the given location. If
min_point_dist is smaller than the value originally given when creating World then the cells will be
smaller/higher resolution, therefore adding detail to the map at the given location.
Process involves using existing cell centres as seed_points for voronoi process, but adding adding
additional
:param new_seed_points: list of [lon,lat] locations to place new sites around i.e. [[lon1, lat1], [lon2, lat2]]
:param min_point_dist:
:return:
"""
cartesian_seed_points = geographic_utils.geographic_to_cartesian(new_seed_locations)
# Populate self.voronoi_sites with (more) points that will create cells
pdp.poisson_disk_placement_on_sphere_given_seed_points(self.voronoi_sites, cartesian_seed_points,
min_point_dist, min_angle, max_angle,
num_child_points, failure_limit, num_adjacent)
# Re-initiate voronoi process
self.generate_voronoi_nodes()
def test_geographic_to_cartesian(self):
north_pole = [0,90]
south_pole = [0,-90]
equatorial_loc_a = [0,0] # Near Sao Tome and Principe
equatorial_loc_b = [180, 0] # Near Phoenix Islands, Pacific Ocean
equatorial_loc_c = [90,0] # Near Malaysia
equatorial_loc_d = [-90,0] # Near Galapagos Islands
geo_locs = [north_pole, south_pole, equatorial_loc_a, equatorial_loc_b, equatorial_loc_c, equatorial_loc_d]
cart_points = geographic_utils.geographic_to_cartesian(geo_locs)
coord_pairs = list()
coord_pairs.append([cart_points[0], [0,0,1]])
coord_pairs.append([cart_points[0], [0,0,1]])
coord_pairs.append([cart_points[1], [0,0,-1]])
coord_pairs.append([cart_points[2], [1,0,0]])
coord_pairs.append([cart_points[3], [-1,0,0]])
coord_pairs.append([cart_points[4], [0,1,0]])
coord_pairs.append([cart_points[5], [0,-1,0]])
for pair in coord_pairs:
for i in range(3):
self.assertAlmostEqual(pair[0][i], pair[1][i])