def save(self, group):
"""
Save the state of the node into a HDF5 file.
group can be the root
"""
## if name is None:
## name = self.name
## subgroup = group.create_group(name)
for i in range(len(self.u)):
utils.write_to_hdf5(group, self.u[i], "u%d" % i)
utils.write_to_hdf5(group, self.observed, "observed")
def save(self, group):
"""
Save the state of the node into a HDF5 file.
group can be the root
"""
## if name is None:
## name = self.name
## subgroup = group.create_group(name)
for i in range(len(self.u)):
utils.write_to_hdf5(group, self.u[i], 'u%d' % i)
utils.write_to_hdf5(group, self.observed, 'observed')
def save(self, group):
"""
Save the state of the node into a HDF5 file.
group can be the root
"""
## if name is None:
## name = self.name
## subgroup = group.create_group(name)
for i in range(len(self.phi)):
utils.write_to_hdf5(group, self.phi[i], 'phi%d' % i)
utils.write_to_hdf5(group, self.f, 'f')
utils.write_to_hdf5(group, self.g, 'g')
super().save(group)
def save(self, group):
"""
Save the state of the node into a HDF5 file.
group can be the root
"""
## if name is None:
## name = self.name
## subgroup = group.create_group(name)
for i in range(len(self.phi)):
utils.write_to_hdf5(group, self.phi[i], 'phi%d' % i)
utils.write_to_hdf5(group, self.f, 'f')
utils.write_to_hdf5(group, self.g, 'g')
super().save(group)
def simulate_data(filename=None,
resolution=30,
M=50,
N=1000,
diffusion=1e-6,
velocity=4e-3,
innovation_noise=1e-3,
innovation_lengthscale=0.6,
noise_ratio=1e-1,
decay=0.9997,
burnin=1000,
thin=20):
# Simulate the process
# Because simulate_process simulates a unit square over unit time step we
# have to multiply parameters by the time length in order to get the effect
# of a long time :)
#
# Thin-parameter affects the temporal resolution.
diffusion *= (N + burnin/thin)
velocity *= (N + burnin/thin)
decay = decay ** (1/thin)
innovation_noise *= np.sqrt(N)
U = simulate_process(resolution,
resolution,
burnin+N*thin,
diffusion=diffusion,
velocity=velocity,
noise=innovation_noise,
lengthscale=innovation_lengthscale,
decay=decay)
# Put some stations randomly
x1x2 = np.random.permutation(resolution*resolution)[:M]
x1 = np.arange(resolution)[np.mod(x1x2, resolution)]
x2 = np.arange(resolution)[(x1x2/resolution).astype(int)]
#x1 = np.random.randint(0, resolution, M)
#x2 = np.random.randint(0, resolution, M)
# Get noisy observations
U = U[burnin::thin]
F = U[:, x1, x2].T
std = np.std(F)
Y = F + noise_ratio*std*np.random.randn(*np.shape(F))
X = np.array([x1, x2]).T
# Save data
if filename is not None:
f = h5py.File(filename, 'w')
try:
utils.write_to_hdf5(f, U, 'U')
utils.write_to_hdf5(f, diffusion/T, 'diffusion')
utils.write_to_hdf5(f, velocity/T, 'velocity')
utils.write_to_hdf5(f, decay, 'decay')
utils.write_to_hdf5(f, innovation_noise/np.sqrt(T), 'innovation_noise')
utils.write_to_hdf5(f, noise_ratio, 'noise_ratio')
utils.write_to_hdf5(f, Y, 'Y')
utils.write_to_hdf5(f, F, 'F')
utils.write_to_hdf5(f, X, 'X')
finally:
f.close()
return (U, Y, F, X)