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