def update_weights(self, point, n_jobs=1, plot=False):
"""
Updates weighting matrixes (in place) with respect to the point in the
solution space.
Parameters
----------
point : dict
with numpy array-like items and variable name keys
"""
gc = self.config
self.point2sources(point)
crust_inds = range(*gc.gf_config.n_variations)
thresh = 5
if len(crust_inds) > thresh:
logger.info('Updating geodetic velocity model-covariances ...')
for i, data in enumerate(self.datasets):
crust_targets = heart.init_geodetic_targets(
datasets=[data],
earth_model_name=gc.gf_config.earth_model_name,
interpolation=gc.interpolation,
crust_inds=crust_inds,
sample_rate=gc.gf_config.sample_rate)
logger.debug('Track %s' % data.name)
cov_pv = cov.geodetic_cov_velocity_models(
engine=self.engine,
sources=self.sources,
targets=crust_targets,
dataset=data,
plot=plot,
event=self.event,
n_jobs=1)
cov_pv = utility.ensure_cov_psd(cov_pv)
data.covariance.pred_v = cov_pv
choli = data.covariance.chol_inverse
self.weights[i].set_value(choli)
data.covariance.update_slog_pdet()
else:
logger.info(
'Not updating geodetic velocity model-covariances because '
'number of model variations is too low! < %i' % thresh)
def __init__(self, gc, project_dir, event, hypers=False):
super(GeodeticComposite, self).__init__()
self.event = event
logger.debug('Setting up geodetic structure ...\n')
self.name = 'geodetic'
self._like_name = 'geo_like'
geodetic_data_path = os.path.join(project_dir,
bconfig.geodetic_data_name)
self.datasets = utility.load_objects(geodetic_data_path)
logger.info('Number of geodetic datasets: %i ' % self.n_t)
# init geodetic targets
self.targets = heart.init_geodetic_targets(
datasets=self.datasets,
earth_model_name=gc.gf_config.earth_model_name,
interpolation=gc.interpolation,
crust_inds=[gc.gf_config.reference_model_idx],
sample_rate=gc.gf_config.sample_rate)
# merge geodetic data to calculate residuals on single array
datasets, los_vectors, odws, self.Bij = heart.concatenate_datasets(
self.datasets)
logger.info('Number of geodetic data points: %i ' %
self.Bij.ordering.size)
self.sdata = shared(datasets, name='geodetic_data', borrow=True)
self.slos_vectors = shared(los_vectors, name='los_vecs', borrow=True)
self.sodws = shared(odws, name='odws', borrow=True)
if gc.calc_data_cov:
logger.warning('Covariance estimation not implemented (yet)!'
' Using imported covariances!')
else:
logger.info('No data-covariance estimation! Using imported'
' covariances \n')
self.weights = []
for i, data in enumerate(self.datasets):
if int(data.covariance.data.sum()) == data.ncoords:
logger.warn('Data covariance is identity matrix!'
' Please double check!!!')
choli = data.covariance.chol_inverse
self.weights.append(
shared(choli, name='geo_weight_%i' % i, borrow=True))
data.covariance.update_slog_pdet()
if gc.fit_plane:
logger.info('Fit residual ramp selected!')
self._slocx = []
self._slocy = []
for j, data in enumerate(self.datasets):
if isinstance(data, heart.DiffIFG):
locy, locx = data.update_local_coords(self.event)
self._slocx.append(
shared(locx.astype(tconfig.floatX) / km,
name='localx_%s' % j,
borrow=True))
self._slocy.append(
shared(locy.astype(tconfig.floatX) / km,
name='localy_%s' % j,
borrow=True))
else:
logger.debug('Appending placeholder for non-SAR data!')
self._slocx.append(None)
self._slocy.append(None)
self.config = gc
if hypers:
self._llks = []
for t in range(self.n_t):
self._llks.append(
shared(num.array([1.]), name='geo_llk_%i' % t,
borrow=True))
def __init__(self, gc, project_dir, events, hypers=False):
super(GeodeticComposite, self).__init__(events)
logger.debug('Setting up geodetic structure ...\n')
self.name = 'geodetic'
self._like_name = 'geo_like'
geodetic_data_path = os.path.join(project_dir,
bconfig.geodetic_data_name)
self.datasets = utility.load_objects(geodetic_data_path)
logger.info('Number of geodetic datasets: %i ' % self.n_t)
# init geodetic targets
self.targets = heart.init_geodetic_targets(
datasets=self.datasets,
earth_model_name=gc.gf_config.earth_model_name,
interpolation=gc.interpolation,
crust_inds=[gc.gf_config.reference_model_idx],
sample_rate=gc.gf_config.sample_rate)
# merge geodetic data to calculate residuals on single array
datasets, los_vectors, odws, self.Bij = heart.concatenate_datasets(
self.datasets)
logger.info('Number of geodetic data points: %i ' %
self.Bij.ordering.size)
self.sdata = shared(datasets, name='geodetic_data', borrow=True)
self.slos_vectors = shared(los_vectors, name='los_vecs', borrow=True)
self.sodws = shared(odws, name='odws', borrow=True)
if gc.calc_data_cov:
logger.warning('Covariance estimation not implemented (yet)!'
' Using imported covariances!')
else:
logger.info('No data-covariance estimation! Using imported'
' covariances \n')
self.weights = []
for i, data in enumerate(self.datasets):
if int(data.covariance.data.sum()) == data.ncoords:
logger.warning('Data covariance is identity matrix!'
' Please double check!!!')
choli = data.covariance.chol_inverse
self.weights.append(
shared(choli, name='geo_weight_%i' % i, borrow=True))
data.covariance.update_slog_pdet()
if gc.corrections_config.has_enabled_corrections:
correction_configs = gc.corrections_config.iter_corrections()
logger.info('Initialising corrections ...')
for data in self.datasets:
data.setup_corrections(event=self.event,
correction_configs=correction_configs)
self.config = gc
if hypers:
self._llks = []
for t in range(self.n_t):
self._llks.append(
shared(num.array([1.]), name='geo_llk_%i' % t,
borrow=True))
lons=lons.ravel(),
los_vector=los,
displacement=num.zeros_like(data_yloc).ravel())
]
fault = discretize_sources(config,
sources=sources,
datatypes=['geodetic'],
varnames=varnames,
tolerance=0.5)
engine = LocalEngine(store_superdirs=[store_superdirs])
targets = init_geodetic_targets(datasets,
earth_model_name='ak135-f-continental.m',
interpolation='multilinear',
crust_inds=[0],
sample_rate=0.0)
print(event)
opt_fault, R = optimize_discretization(config,
fault,
datasets=datasets,
varnames=varnames,
crust_ind=0,
engine=engine,
targets=targets,
event=event,
force=True,
nworkers=nworkers,
plot=True,