def perform(self, node, inputs, output):
"""
Perform method of the Operator to calculate synthetic displacements.
Parameters
----------
inputs : list
of :class:`numpy.ndarray`
output : list
1) of synthetic waveforms of :class:`numpy.ndarray`
(n x nsamples)
2) of start times of the first waveform samples
:class:`numpy.ndarray` (n x 1)
"""
synths = output[0]
point = {vname: i for vname, i in zip(self.varnames, inputs)}
mpoint = utility.adjust_point_units(point)
source_points = utility.split_point(mpoint)
for i, source in enumerate(self.sources):
utility.update_source(source, **source_points[i])
# reset source time may result in store error otherwise
source.time = 0.
synths[0] = heart.geo_synthetics(
engine=self.engine,
targets=self.targets,
sources=self.sources,
outmode='stacked_array')
def perform(self, node, inputs, output):
"""
Perform method of the Operator to calculate synthetic displacements.
Parameters
----------
inputs : list
of :class:`numpy.ndarray`
output : list
1) of synthetic waveforms of :class:`numpy.ndarray`
(n x nsamples)
2) of start times of the first waveform samples
:class:`numpy.ndarray` (n x 1)
"""
synths = output[0]
tmins = output[1]
point = {vname: i for vname, i in zip(self.varnames, inputs)}
mpoint = utility.adjust_point_units(point)
source_points = utility.split_point(mpoint)
for i, source in enumerate(self.sources):
utility.update_source(source, **source_points[i])
source.time += self.event.time
synths[0], tmins[0] = heart.seis_synthetics(
engine=self.engine,
sources=self.sources,
targets=self.targets,
arrival_taper=self.arrival_taper,
wavename=self.wavename,
filterer=self.filterer,
pre_stack_cut=self.pre_stack_cut)
def point2sources(self, point):
"""
Updates the composite source(s) (in place) with the point values.
"""
tpoint = copy.deepcopy(point)
tpoint = utility.adjust_point_units(tpoint)
# remove hyperparameters from point
hps = self.config.get_hypernames()
for hyper in hps:
if hyper in tpoint:
tpoint.pop(hyper)
source = self.sources[0]
source_params = source.keys() + source.stf.keys()
for param in tpoint.keys():
if param not in source_params:
tpoint.pop(param)
tpoint['time'] += self.event.time
source_points = utility.split_point(tpoint)
for i, source in enumerate(self.sources):
utility.update_source(source, **source_points[i])
def point2sources(self, point):
"""
Updates the composite source(s) (in place) with the point values.
"""
tpoint = copy.deepcopy(point)
tpoint = utility.adjust_point_units(tpoint)
# remove hyperparameters from point
hps = self.config.get_hypernames()
for hyper in hps:
if hyper in tpoint:
tpoint.pop(hyper)
source_params = self.sources[0].keys()
for param in tpoint.keys():
if param not in source_params:
tpoint.pop(param)
source_points = utility.split_point(tpoint)
for i, source in enumerate(self.sources):
utility.update_source(source, **source_points[i])
# reset source time may result in store error otherwise
source.time = 0.
def init_reference_sources(source_points, n_sources, source_type, stf_type):
reference_sources = []
for i in range(n_sources):
#rf = source_catalog[source_type](stf=stf_catalog[stf_type]()) maybe future if several meshtypes
rf = RectangularSource(stf=stf_catalog[stf_type]())
utility.update_source(rf, **source_points[i])
reference_sources.append(rf)
return reference_sources
def perform(self, node, inputs, output):
synths = output[0]
tmins = output[1]
point = {
var: inp
for var, inp in zip(config.joint_vars_geometry, inputs)
}
mpoint = utility.adjust_point_units(point)
source_points = utility.split_point(mpoint)
for i, source in enumerate(self.sources):
utility.update_source(source, **source_points[i])
source.time += self.event.time
heart.adjust_fault_reference(source, input_depth='top')
synths[0], tmins[0] = heart.seis_synthetics(self.engine, self.sources,
self.targets,
self.arrival_taper,
self.filterer)
def point2sources(self, point):
"""
Updates the composite source(s) (in place) with the point values.
Parameters
----------
point : dict
with random variables from solution space
"""
tpoint = copy.deepcopy(point)
tpoint = utility.adjust_point_units(tpoint)
# remove hyperparameters from point
hps = self.config.get_hypernames()
for hyper in hps:
if hyper in tpoint:
tpoint.pop(hyper)
source = self.sources[0]
source_params = list(source.keys()) + list(source.stf.keys())
for param in list(tpoint.keys()):
if param not in source_params:
tpoint.pop(param)
# update source times
if self.nevents == 1:
tpoint['time'] += self.event.time # single event
else:
for i, event in enumerate(self.events): # multi event
tpoint['time'][i] += event.time
source_points = utility.split_point(tpoint)
for i, source in enumerate(self.sources):
utility.update_source(source, **source_points[i])
def point2sources(self, point, input_depth='top'):
"""
Updates the composite source(s) (in place) with the point values.
Parameters
----------
point : dict
with random variables from solution space
input_depth : string
may be either 'top'- input coordinates are transformed to center
'center' - input coordinates are not transformed
"""
tpoint = copy.deepcopy(point)
tpoint = utility.adjust_point_units(tpoint)
# remove hyperparameters from point
hps = self.config.get_hypernames()
for hyper in hps:
if hyper in tpoint:
tpoint.pop(hyper)
source = self.sources[0]
source_params = list(source.keys()) + list(source.stf.keys())
for param in list(tpoint.keys()):
if param not in source_params:
tpoint.pop(param)
tpoint['time'] += self.event.time
source_points = utility.split_point(tpoint)
for i, source in enumerate(self.sources):
utility.update_source(source,
input_depth=input_depth,
**source_points[i])
def get_synthetics(self, point, **kwargs):
"""
Get synthetics for given point in solution space.
Parameters
----------
point : :func:`pymc3.Point`
Dictionary with model parameters
kwargs especially to change output of seismic forward model
outmode = 'traces'/ 'array' / 'data'
Returns
-------
Dictionary with keys according to datasets containing the synthetics
as lists.
"""
tpoint = copy.deepcopy(point)
tpoint = utility.adjust_point_units(tpoint)
# remove hyperparameters from point
hps = self.config.problem_config.hyperparameters
if len(hps) > 0:
for hyper in hps.keys():
if hyper in tpoint:
tpoint.pop(hyper)
else:
pass
d = dict()
if self._seismic_flag:
tpoint['time'] += self.event.time
source_points = utility.split_point(tpoint)
for i, source in enumerate(self.sources):
utility.update_source(source, **source_points[i])
dsources = utility.transform_sources(
self.sources, self.config.problem_config.datasets)
# seismic
if self._seismic_flag:
sc = self.config.seismic_config
seis_synths, _ = heart.seis_synthetics(
engine=self.engine,
sources=dsources['seismic'],
targets=self.stargets,
arrival_taper=sc.arrival_taper,
filterer=sc.filterer, **kwargs)
d['seismic'] = seis_synths
# geodetic
if self._geodetic_flag:
gc = self.config.geodetic_config
crust_inds = [0]
geo_synths = []
for crust_ind in crust_inds:
for gtarget in self.gtargets:
disp = heart.geo_layer_synthetics(
gc.gf_config.store_superdir,
crust_ind,
lons=gtarget.lons,
lats=gtarget.lats,
sources=dsources['geodetic'])
geo_synths.append((
disp[:, 0] * gtarget.los_vector[:, 0] + \
disp[:, 1] * gtarget.los_vector[:, 1] + \
disp[:, 2] * gtarget.los_vector[:, 2]))
d['geodetic'] = geo_synths
return d
def update_weights(self, point, n_jobs=1, plot=False):
"""
Calculate and update model prediction uncertainty covariances
due to uncertainty in the velocity model with respect to one point
in the solution space. Shared variables are updated.
Parameters
----------
point : :func:`pymc3.Point`
Dictionary with model parameters, for which the covariance matrixes
with respect to velocity model uncertainties are calculated
n_jobs : int
Number of processors to use for calculation of seismic covariances
plot : boolean
Flag for opening the seismic waveforms in the snuffler
"""
tpoint = copy.deepcopy(point)
# update sources
tpoint = utility.adjust_point_units(tpoint)
# remove hyperparameters from point
hps = self.config.problem_config.hyperparameters
if len(hps) > 0:
for hyper in hps.keys():
tpoint.pop(hyper)
if self._seismic_flag:
tpoint['time'] += self.event.time
source_points = utility.split_point(tpoint)
for i, source in enumerate(self.sources):
utility.update_source(source, **source_points[i])
dsources = utility.transform_sources(
self.sources, self.config.problem_config.datasets)
# seismic
if self._seismic_flag:
sc = self.config.seismic_config
for j, channel in enumerate(sc.channels):
for i, station in enumerate(self.stations):
logger.debug('Channel %s of Station %s ' % (
channel, station.station))
crust_targets = heart.init_targets(
stations=[station],
channels=channel,
sample_rate=sc.gf_config.sample_rate,
crust_inds=range(sc.gf_config.n_variations))
cov_pv = cov.get_seis_cov_velocity_models(
engine=self.engine,
sources=dsources['seismic'],
targets=crust_targets,
arrival_taper=sc.arrival_taper,
filterer=sc.filterer,
plot=plot, n_jobs=n_jobs)
cov_pv = utility.ensure_cov_psd(cov_pv)
self.engine.close_cashed_stores()
index = j * len(self.stations) + i
self.stargets[index].covariance.pred_v = cov_pv
icov = self.stargets[index].covariance.inverse
self.sweights[index].set_value(icov)
# geodetic
if self._geodetic_flag:
gc = self.config.geodetic_config
for i, gtarget in enumerate(self.gtargets):
logger.debug('Track %s' % gtarget.track)
cov_pv = cov.get_geo_cov_velocity_models(
store_superdir=gc.gf_config.store_superdir,
crust_inds=range(gc.gf_config.n_variations),
dataset=gtarget,
sources=dsources['geodetic'])
cov_pv = utility.ensure_cov_psd(cov_pv)
gtarget.covariance.pred_v = cov_pv
icov = gtarget.covariance.inverse
self.gweights[i].set_value(icov)
