def analyse_noise(self, tpoint=None, chop_bounds=['b', 'c']):
"""
Analyse seismic noise in datatraces and set
data-covariance matrixes accordingly.
"""
if self.config.noise_estimator.structure == 'non-toeplitz':
results = self.assemble_results(tpoint,
order='wmap',
chop_bounds=chop_bounds)
else:
results = [None] * len(self.wavemaps)
for wmap, wmap_results in zip(self.wavemaps, results):
logger.info(
'Retrieving seismic data-covariances with structure "%s" '
'for %s ...' %
(self.config.noise_estimator.structure, wmap._mapid))
cov_ds_seismic = self.noise_analyser.get_data_covariances(
wmap=wmap,
results=wmap_results,
sample_rate=self.config.gf_config.sample_rate,
chop_bounds=chop_bounds)
for j, trc in enumerate(wmap.datasets):
if trc.covariance is None:
trc.covariance = heart.Covariance(data=cov_ds_seismic[j])
else:
trc.covariance.data = cov_ds_seismic[j]
if int(trc.covariance.data.sum()) == trc.data_len():
logger.warning('Data covariance is identity matrix!'
' Please double check!!!')
def load_SAR_data(datadir, tracks):
'''
Load SAR data in given directory and tracks.
Returns Diff_IFG objects.
'''
DIFFGs = []
for k in tracks:
# open matlab.mat files
data = scipy.io.loadmat(datadir + 'quad_' + k + '.mat',
squeeze_me=True,
struct_as_record=False)
covs = scipy.io.loadmat(datadir + 'CovMatrix_' + k + '.mat',
squeeze_me=True,
struct_as_record=False)
utmx = data['cfoc'][:, 0]
utmy = data['cfoc'][:, 1]
lons, lats = utility.utm_to_lonlat(utmx, utmy, 36)
Lv = data['lvQT']
covariance = heart.Covariance(data=covs['Cov'])
DIFFGs.append(
heart.DiffIFG(track=k,
displacement=data['sqval'],
utme=utmx,
utmn=utmy,
lons=lons,
lats=lats,
covariance=covariance,
incidence=Lv.inci,
heading=Lv.head,
odw=data['ODW_sub']))
return DIFFGs
def load_SAR_data(datadir, names):
"""
Load SAR data in given directory and filenames.
Returns Diff_IFG objects.
"""
diffgs = []
tobeloaded_names = set(copy.deepcopy(names))
for k in names:
# open matlab.mat files
data = load_matfile(datadir + 'quad_' + k + '.mat',
squeeze_me=True,
struct_as_record=False)
covs = load_matfile(datadir + 'CovMatrix_' + k + '.mat',
squeeze_me=True,
struct_as_record=False)
if data is not None and covs is not None:
utmx = data['cfoc'][:, 0]
utmy = data['cfoc'][:, 1]
lons, lats = utility.utm_to_lonlat(utmx, utmy, 36)
Lv = data['lvQT']
covariance = heart.Covariance(data=covs['Cov'])
diffgs.append(
heart.DiffIFG(name=k,
displacement=data['sqval'],
utme=utmx,
utmn=utmy,
lons=lons,
lats=lats,
covariance=covariance,
incidence=Lv.inci,
heading=Lv.head,
odw=data['ODW_sub']))
tobeloaded_names.discard(k)
else:
logger.info('File %s was no SAR data?!' % datadir)
names = list(tobeloaded_names)
return diffgs
def __init__(self, sc, event, project_dir, hypers=False):
super(SeismicComposite, self).__init__()
logger.debug('Setting up seismic structure ...\n')
self.name = 'seismic'
self._like_name = 'seis_like'
self.correction_name = 'time_shift'
self.event = event
self.engine = LocalEngine(
store_superdirs=[sc.gf_config.store_superdir])
seismic_data_path = os.path.join(project_dir,
bconfig.seismic_data_name)
self.datahandler = heart.init_datahandler(
seismic_config=sc, seismic_data_path=seismic_data_path)
self.wavemaps = []
for wc in sc.waveforms:
if wc.include:
wmap = heart.init_wavemap(waveformfit_config=wc,
datahandler=self.datahandler,
event=event)
if sc.calc_data_cov:
logger.info('Estimating seismic data-covariances '
'for %s ...\n' % wmap.name)
cov_ds_seismic = cov.seismic_data_covariance(
data_traces=wmap.datasets,
filterer=wc.filterer,
sample_rate=sc.gf_config.sample_rate,
arrival_taper=wc.arrival_taper,
engine=self.engine,
event=self.event,
targets=wmap.targets)
else:
logger.info('No data-covariance estimation, using imported'
' covariances...\n')
cov_ds_seismic = []
at = wc.arrival_taper
n_samples = int(
num.ceil(at.duration * sc.gf_config.sample_rate))
for trc in wmap.datasets:
if trc.covariance is None:
logger.warn('No data covariance given/estimated! '
'Setting default: eye')
cov_ds_seismic.append(num.eye(n_samples))
else:
data_cov = trc.covariance.data
if data_cov.shape[0] != n_samples:
raise ValueError(
'Imported covariance %i does not agree '
' with taper duration %i!' %
(data_cov.shape[0], n_samples))
cov_ds_seismic.append(data_cov)
weights = []
for t, trc in enumerate(wmap.datasets):
trc.covariance = heart.Covariance(data=cov_ds_seismic[t])
if int(trc.covariance.data.sum()) == trc.data_len():
logger.warn('Data covariance is identity matrix!'
' Please double check!!!')
icov = trc.covariance.chol_inverse
weights.append(
shared(icov,
name='seis_%s_weight_%i' % (wc.name, t),
borrow=True))
wmap.add_weights(weights)
self.wavemaps.append(wmap)
else:
logger.info('The waveform defined in "%s" config is not '
'included in the optimization!' % wc.name)
if hypers:
self._llks = []
for t in range(self.n_t):
self._llks.append(
shared(num.array([1.]),
name='seis_llk_%i' % t,
borrow=True))
