def prediction_array(self, time, space_array):
# combine time with space dimension
space_array = self.space_class(space_array, copy=False)
t = DataArray(time * np.ones(space_array.ndata))
if space_array.original_shape is not None:
t.original_shape = space_array.original_shape
return t.adddim(space_array, type=self.data_class)
def predict(self, time, space_array, force_update=False):
"""
Generate a prediction from the trained model.
Supply single time and spatial sample points in separate arrays
If force_update=False then the spatial component is assumed unchanged, so only the time is altered.
This is important: updating the spatial sample points loses all cached net paths.
"""
if self.kde.targets_set and not force_update:
self.kde.update_target_times(time)
return self.kde.pdf()
else:
space_array = self.space_class(space_array, copy=False)
time_array = DataArray(np.ones(space_array.ndata) * time)
targets_array = time_array.adddim(space_array,
type=self.data_class)
return self.kde.pdf(targets=targets_array)
targets,
max_distance=radius,
max_split=1e4)
k = NetworkKernelEqualSplitLinear(sources.getone(0), 200.)
k.set_walker(nw)
z = k.pdf()
zn = z / max(z)
# plt.figure()
# itn_net.plot_network()
# plt.scatter(nodes[:, 0], nodes[:, 1], marker='x', s=15, c='k')
# plt.scatter(*targets.to_cartesian().separate, s=(zn * 20) ** 2)
# plt.scatter(*sources.getone(0).cartesian_coords, c='r', s=50)
# add time to sources and targets
times = DataArray(np.random.rand(num_pts))
sources_st = times.adddim(sources, type=NetworkSpaceTimeData)
targets_st = DataArray(np.ones(targets.ndata)).adddim(
targets, type=NetworkSpaceTimeData)
kst = NetworkTemporalKernelEqualSplit(
[sources_st.time.getone(0),
sources_st.space.getone(0)], [0.5, 200.])
kst.set_walker(nw)
zst = kst.pdf(target_times=targets_st.time)
zstn = zst / z.max()
# plt.figure()
# itn_net.plot_network()
# plt.scatter(nodes[:, 0], nodes[:, 1], marker='x', s=15, c='k')
# plt.scatter(*targets.to_cartesian().separate, s=(zstn * 20) ** 2)
# plt.scatter(*sources.getone(0).cartesian_coords, c=sources_st.time.getone(0), s=50, vmax=1., vmin=0.)
