def generate_voronoi_nodes(self):
# TODO: If this is not the first construction of the voronoi cells, can any existing node info be kept?
# Structures must be emptied if this is not the first time constructing the voronoi cells
self.all_boundary_nodes = list()
self.all_cells = list()
self.all_centre_nodes = dict()
self.all_edges = list()
# SphericalVoronoi object can be queried for various point and edge information
self.spherical_voronoi = jellymatter_voronoi.SphericalVoronoi(self.voronoi_sites)
# Create node objects used for holding world information
# Adjacent cells share boundary nodes, so dictionary is used to look up if SpatialNode has already been
# created for given location
self.boundary_nodes_by_location = dict()
self.edges_by_location = dict()
for cell_index, cell_boundary_points in enumerate(self.spherical_voronoi.faces):
cell_boundary_nodes = list()
locations = cartesian_utils.cartesian_to_geographic(cell_boundary_points)
# Every intersection point is represented by a SpatialNode
for i in range(len(locations)):
longitude, latitude = locations[i]
x, y, z = cell_boundary_points[i]
key = (longitude, latitude)
# Use dict to re-use SpatialNode if it has already been created for this location
node = None
if key in self.boundary_nodes_by_location:
# Node already exists, so re-use
node = self.boundary_nodes_by_location[key]
else:
# Node does not already exist, so create
node = nodetools.SpatialNode(longitude, latitude, x, y, z)
self.boundary_nodes_by_location[key] = node
self.all_boundary_nodes.append(node)
cell_boundary_nodes.append(node)
# Cell boundary nodes form a ring of neighbour relations
for i in range(len(cell_boundary_nodes)):
cell_boundary_nodes[i].add_neighbour(cell_boundary_nodes[i-1])
node_relationship_key = frozenset([(cell_boundary_nodes[i].longitude, cell_boundary_nodes[i].latitude), (cell_boundary_nodes[i-1].longitude, cell_boundary_nodes[i-1].latitude)])
if node_relationship_key not in self.edges_by_location:
node_relationship = [cell_boundary_nodes[i], cell_boundary_nodes[i-1]]
self.edges_by_location[node_relationship_key] = node_relationship
self.all_edges.append(node_relationship)
# Create non-neighbour node for voronoi site at centre of cell
location = tuple(cartesian_utils.cartesian_to_geographic([self.voronoi_sites[cell_index]])[0])
centre_node = nodetools.SpatialNode(location[0], location[1], self.voronoi_sites[cell_index][0], self.voronoi_sites[cell_index][1], self.voronoi_sites[cell_index][2])
self.all_centre_nodes[location] = centre_node
# Store Cell object keyed on (lon, lat) tuple
self.all_cells.append(nodetools.Cell(centre_node, cell_boundary_nodes))
# Use delaunay connections to determine which Cell objects are adjacent to each other
# across a voronoi boundary so they can be given a neighbour relationship
for cell_indices in self.spherical_voronoi.hull.simplices:
cells_in_tri = list()
for i, cell_index in enumerate(cell_indices):
# Enforce neighbour relationship between adjacent cells
self.all_cells[cell_indices[i]].add_neighbour(self.all_cells[cell_indices[i-1]])
def test_cartesian_to_geographic(self):
north_pole = [0, 0, 1]
south_pole = [0, 0, -1]
equatorial_point_a = [1, 0, 0] # Near Sao Tome and Principe
equatorial_point_b = [-1, 0, 0] # Near Phoenix Islands, Pacific Ocean
equatorial_point_c = [0, 1, 0] # Near Malaysia
equatorial_point_d = [0, -1, 0] # Near Galapagos Islands
cart_points = [north_pole, south_pole, equatorial_point_a, equatorial_point_b, equatorial_point_c, equatorial_point_d]
geog_points = cartesian_utils.cartesian_to_geographic(cart_points)
self.assertEqual(geog_points[0][1], 90)
self.assertEqual(geog_points[1][1], -90)
self.assertEqual(geog_points[2][0], 0)
self.assertEqual(abs(geog_points[3][0]), 180)
self.assertEqual(geog_points[4][0], 90)
self.assertEqual(geog_points[5][0], -90)
print(geog_points)
