def plot_vertex_values(self, values, layout=None, num_subplots=1):
if layout is None:
layout = (num_subplots, 1)
self.fig = plt.figure(figsize=(3 * layout[1], 3 * layout[0]))
values = np.array(values)
if len(values.shape) == 1:
values = values[np.newaxis, :]
values -= np.min(values)
values = values / np.max(values)
sv = SphericalVoronoi(self.vertices, self.radius, self.center)
sv.sort_vertices_of_regions()
for i in range(num_subplots):
ax = self.fig.add_subplot(layout[0],
layout[1],
i + 1,
projection='3d')
vertex_colors = [self.cm(val) for val in values[i]]
for j, region in enumerate(sv.regions):
color = vertex_colors[j]
polygon = Poly3DCollection([sv.vertices[region]], alpha=1.0)
polygon.set_color(color)
ax.add_collection3d(polygon)
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.set_zlim(-1, 1)
ax.elev = 20
def calculate_weight(self):
radius = 1.0
center = np.array([0, 0, 0])
self.points = self._transfer_coordinate(radius, center)
#for _i in range(self.nstations):
# print("%10s: [%10.5f, %10.5f] -- [%10.5f, %10.5f, %10.5f]"
# % (self.station_tag[_i], self.station_loc[_i][0],
# self.station_loc[_i][1], self.points[_i][0],
# self.points[_i][1], self.points[_i][2]))
self.sv = SphericalVoronoi(self.points, 1, center)
self.sv.sort_vertices_of_regions()
surface_area = self.sv.compute_surface_area()
self.weight = surface_area ** self.order
self.weight = self._normalize(self.weight)
class VoronoiWeight(WeightBase):
def __init__(self, stations, event, order=1.0):
WeightBase.__init__(self, stations, event)
self.points = None
self.sv = None
self.order = order
def _transfer_coordinate(self, radius, center):
"""
Transfer (longitude, latitude) to (x, y, z) on sphere(radius, center)
"""
sphere_loc = np.zeros([self.nstations, 3])
for _i in range(self.station_loc.shape[0]):
lat = np.deg2rad(self.station_loc[_i, 0])
lon = np.deg2rad(self.station_loc[_i, 1])
sphere_loc[_i, 0] = radius * cos(lat) * cos(lon) + center[0]
sphere_loc[_i, 1] = radius * cos(lat) * sin(lon) + center[1]
sphere_loc[_i, 2] = radius * sin(lat) + center[2]
return sphere_loc
def calculate_weight(self):
radius = 1.0
center = np.array([0, 0, 0])
self.points = self._transfer_coordinate(radius, center)
#for _i in range(self.nstations):
# print("%10s: [%10.5f, %10.5f] -- [%10.5f, %10.5f, %10.5f]"
# % (self.station_tag[_i], self.station_loc[_i][0],
# self.station_loc[_i][1], self.points[_i][0],
# self.points[_i][1], self.points[_i][2]))
self.sv = SphericalVoronoi(self.points, 1, center)
self.sv.sort_vertices_of_regions()
surface_area = self.sv.compute_surface_area()
self.weight = surface_area ** self.order
self.weight = self._normalize(self.weight)
def plot_sphere(self):
points = self.points
sv = self.sv
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection='3d')
# plot the unit sphere for reference (optional)
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = np.outer(np.cos(u), np.sin(v))
y = np.outer(np.sin(u), np.sin(v))
z = np.outer(np.ones(np.size(u)), np.cos(v))
ax.plot_surface(x, y, z, color='y', alpha=0.05)
# plot Voronoi vertices
#ax.scatter(sv.vertices[:, 0], sv.vertices[:, 1], sv.vertices[:, 2],
# c='g')
# indicate Voronoi regions (as Euclidean polygons)
for region in sv.regions:
random_color = colors.rgb2hex(np.random.rand(3))
polygon = Poly3DCollection([sv.vertices[region]], alpha=1.0)
polygon.set_color(random_color)
ax.add_collection3d(polygon)
# plot generator points
ax.scatter(points[:, 0], points[:, 1], points[:, 2], c='b')
ax.set_xlim(-1,1)
ax.set_ylim(-1,1)
ax.set_zlim(-1,1);
ax.set_xticks([-1,1])
ax.set_yticks([-1,1])
ax.set_zticks([-1,1]);
plt.tick_params(axis='both', which='major', labelsize=6)
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
def plot_weight_histogram(self, outputdir=None, figformat="png"):
if outputdir is None:
figname = None
else:
figname = os.path.join(outputdir, "voronoi_weight_hist.%s"
% figformat)
self._plot_histogram(self.weight, title="Voronoi Weight",
figname=figname)
