def print_date_list(fname, disp_num=False, drop_ifgram=False, print_msg=False):
"""Print time/date info of file"""
atr = readfile.read_attribute(fname)
k = atr['FILE_TYPE']
dateList = None
if k in ['timeseries']:
dateList = timeseries(fname).get_date_list()
elif k == 'HDFEOS':
obj = HDFEOS(fname)
obj.open(print_msg=False)
dateList = obj.dateList
elif k == 'giantTimeseries':
obj = giantTimeseries(fname)
obj.open(print_msg=False)
dateList = obj.dateList
elif k in ['ifgramStack']:
dateList = ifgramStack(fname).get_date12_list(dropIfgram=drop_ifgram)
elif k in ['giantIfgramStack']:
obj = giantIfgramStack(fname)
obj.open(print_msg=False)
dateList = obj.date12List
else:
print('--date option can not be applied to {} file, ignore it.'.format(k))
if print_msg and dateList is not None:
for i in range(len(dateList)):
if disp_num:
print('{}\t{}'.format(dateList[i], i))
else:
print(dateList[i])
return dateList
def open(self):
atr = readfile.read_attribute(self.insar_file)
k = atr['FILE_TYPE']
if k == 'timeseries':
ts_obj = timeseries(self.insar_file)
elif k == 'giantTimeseries':
ts_obj = giantTimeseries(self.insar_file)
ts_obj.open(print_msg=False)
self.metadata = dict(ts_obj.metadata)
self.num_date = ts_obj.numDate
self.insar_datetime = ts_obj.times
self.read_gps()
self.read_insar()
self.calculate_rmse()
return
def print_date_list(fname, disp_ifgram='all', disp_num=False, print_msg=False):
"""Print time/date info of file"""
k = readfile.read_attribute(fname)['FILE_TYPE']
dateList = None
if k in ['timeseries']:
dateList = timeseries(fname).get_date_list()
elif k == 'HDFEOS':
dateList = HDFEOS(fname).get_date_list()
elif k == 'giantTimeseries':
dateList = giantTimeseries(fname).get_date_list()
elif k in ['giantIfgramStack']:
dateList = giantIfgramStack(fname).get_date12_list()
elif k in ['ifgramStack']:
obj = ifgramStack(fname)
obj.open(print_msg=False)
dateListAll = obj.get_date12_list(dropIfgram=False)
dateListKept = obj.get_date12_list(dropIfgram=True)
# show dropped ifgram or not
if disp_ifgram == 'all':
dateList = list(dateListAll)
elif disp_ifgram == 'kept':
dateList = list(dateListKept)
else:
dateList = sorted(list(set(dateListAll) - set(dateListKept)))
else:
print('--date option can not be applied to {} file, ignore it.'.format(
k))
# print list info
if print_msg and dateList is not None:
for d in dateList:
if disp_num:
if k in ['ifgramStack']:
num = dateListAll.index(d)
else:
num = dateList.index(d)
msg = '{}\t{}'.format(d, num)
else:
msg = d
print(msg)
return dateList
def read_date_info(inps):
"""Get inps.excludeDate full list
Inputs:
inps - Namespace,
Output:
inps.excludeDate - list of string for exclude date in YYYYMMDD format
"""
if inps.key == 'timeseries':
tsobj = timeseries(inps.timeseries_file)
elif inps.key == 'giantTimeseries':
tsobj = giantTimeseries(inps.timeseries_file)
elif inps.key == 'HDFEOS':
tsobj = HDFEOS(inps.timeseries_file)
tsobj.open()
inps.excludeDate = read_exclude_date(inps, tsobj.dateList)
# Date used for estimation inps.dateList
inps.dateList = [i for i in tsobj.dateList if i not in inps.excludeDate]
inps.numDate = len(inps.dateList)
print('-' * 50)
print('dates from input file: {}\n{}'.format(tsobj.numDate,
tsobj.dateList))
print('-' * 50)
if len(inps.dateList) == len(tsobj.dateList):
print('using all dates to calculate the velocity')
else:
print('dates used to estimate the velocity: {}\n{}'.format(
inps.numDate, inps.dateList))
print('-' * 50)
# flag array for ts data reading
inps.dropDate = np.array(
[i not in inps.excludeDate for i in tsobj.dateList], dtype=np.bool_)
# output file name
if not inps.outfile:
outname = 'velocity'
if inps.key == 'giantTimeseries':
prefix = os.path.basename(inps.timeseries_file).split('PARAMS')[0]
outname = prefix + outname
outname += '.h5'
inps.outfile = outname
return inps
def read_attribute(fname, datasetName=None, standardize=True, meta_ext=None):
"""Read attributes of input file into a dictionary
Parameters: fname : str, path/name of data file
datasetName : str, name of dataset of interest, for file with multiple datasets
e.g. unwrapPhase in ifgramStack.h5
coherence in ifgramStack.h5
height in geometryRadar.h5
latitude in geometryRadar.h5
...
standardize : bool, grab standardized metadata key name
Returns: atr : dict, attributes dictionary
"""
fbase, fext = os.path.splitext(os.path.basename(fname))
fext = fext.lower()
if not os.path.isfile(fname):
msg = 'input file not existed: {}\n'.format(fname)
msg += 'current directory: ' + os.getcwd()
raise Exception(msg)
# HDF5 files
if fext in ['.h5', '.he5']:
f = h5py.File(fname, 'r')
g1_list = [i for i in f.keys() if isinstance(f[i], h5py.Group)]
d1_list = [
i for i in f.keys()
if isinstance(f[i], h5py.Dataset) and f[i].ndim >= 2
]
# FILE_TYPE - k
if any(i in d1_list for i in ['unwrapPhase']):
k = 'ifgramStack'
elif any(i in d1_list for i in ['height', 'latitude', 'azimuthCoord']):
k = 'geometry'
elif any(i in g1_list + d1_list
for i in ['timeseries', 'displacement']):
k = 'timeseries'
elif 'HDFEOS' in g1_list:
k = 'HDFEOS'
elif 'recons' in d1_list:
k = 'giantTimeseries'
elif any(i in d1_list for i in ['igram', 'figram']):
k = 'giantIfgramStack'
elif any(i in g1_list
for i in multi_group_hdf5_file): # old pysar format
k = list(set(g1_list) & set(multi_group_hdf5_file))[0]
elif len(d1_list) > 0:
k = d1_list[0]
elif len(g1_list) > 0:
k = g1_list[0]
else:
raise ValueError('unrecognized file type: ' + fname)
# metadata dict
if k == 'giantTimeseries':
atr = giantTimeseries(fname).get_metadata()
elif k == 'giantIfgramStack':
atr = giantIfgramStack(fname).get_metadata()
else:
if len(f.attrs) > 0 and 'WIDTH' in f.attrs.keys():
atr = dict(f.attrs)
else:
# grab the list of attrs in HDF5 file
global atr_list
def get_hdf5_attrs(name, obj):
global atr_list
if len(obj.attrs) > 0 and 'WIDTH' in obj.attrs.keys():
atr_list.append(dict(obj.attrs))
atr_list = []
f.visititems(get_hdf5_attrs)
# use the attrs with most items
if atr_list:
num_list = [len(i) for i in atr_list]
atr = atr_list[np.argmax(num_list)]
else:
raise ValueError('No attribute WIDTH found in file:',
fname)
# decode string format
for key, value in atr.items():
try:
atr[key] = value.decode('utf8')
except:
atr[key] = value
# attribute identified by PySAR
# 1. FILE_TYPE
atr['FILE_TYPE'] = str(k)
# 2. DATA_TYPE
ds = None
if datasetName and datasetName in f.keys():
ds = f[datasetName]
else:
# get the 1st dataset
global ds_list
def get_hdf5_dataset(name, obj):
global ds_list
if isinstance(obj, h5py.Dataset) and obj.ndim >= 2:
ds_list.append(obj)
ds_list = []
f.visititems(get_hdf5_dataset)
if ds_list:
ds = ds_list[0]
if ds is not None:
atr['DATA_TYPE'] = str(ds.dtype)
f.close()
# 3. PROCESSOR
if 'INSAR_PROCESSOR' in atr.keys():
atr['PROCESSOR'] = atr['INSAR_PROCESSOR']
if 'PROCESSOR' not in atr.keys():
atr['PROCESSOR'] = 'pysar'
else:
# get existing metadata files
metafile_exts = ['.rsc', '.xml', '.aux.xml', '.par', '.hdr']
if meta_ext:
metafile_exts = [i for i in metafile_exts if i.endswith(meta_ext)]
metafile_exts = [i for i in metafile_exts if os.path.isfile(fname + i)]
if len(metafile_exts) == 0:
raise FileNotFoundError(
'No metadata file found for data file: {}'.format(fname))
# Read metadata file and FILE_TYPE
while fext in ['.geo', '.rdr']:
fbase, fext = os.path.splitext(fbase)
if not fext:
fext = fbase
metafile0 = fname + metafile_exts[0]
if metafile0.endswith('.rsc'):
atr = read_roipac_rsc(metafile0)
if 'FILE_TYPE' not in atr.keys():
atr['FILE_TYPE'] = fext
elif metafile0.endswith('.xml'):
atr = read_isce_xml(metafile0)
if 'FILE_TYPE' not in atr.keys():
atr['FILE_TYPE'] = atr.get('image_type', fext)
elif metafile0.endswith('.par'):
atr = read_gamma_par(metafile0)
atr['FILE_TYPE'] = fext
elif metafile0.endswith('.hdr'):
atr = read_template(metafile0)
atr['DATA_TYPE'] = ENVI2NUMPY_DATATYPE[xmlDict.get(
'data type', '4')]
atr['FILE_TYPE'] = atr['file type']
# PROCESSOR
if any(i.endswith(('.xml', '.hdr')) for i in metafile_exts):
atr['PROCESSOR'] = 'isce'
#atr.update(read_isce_xml(fname+'.xml'))
elif any(i.endswith('.par') for i in metafile_exts):
atr['PROCESSOR'] = 'gamma'
elif any(i.endswith('.rsc') for i in metafile_exts):
if 'PROCESSOR' not in atr.keys():
atr['PROCESSOR'] = 'roipac'
if 'PROCESSOR' not in atr.keys():
atr['PROCESSOR'] = 'pysar'
# UNIT
k = atr['FILE_TYPE'].replace('.', '')
if k == 'ifgramStack':
if datasetName and datasetName in datasetUnitDict.keys():
atr['UNIT'] = datasetUnitDict[datasetName]
else:
atr['UNIT'] = 'radian'
elif 'UNIT' not in atr.keys():
if datasetName and datasetName in datasetUnitDict.keys():
atr['UNIT'] = datasetUnitDict[datasetName]
elif k in datasetUnitDict.keys():
atr['UNIT'] = datasetUnitDict[k]
else:
atr['UNIT'] = '1'
# FILE_PATH
atr['FILE_PATH'] = os.path.abspath(fname)
if standardize:
atr = standardize_metadata(atr)
return atr
def get_slice_list(fname):
"""Get list of 2D slice existed in file (for display)"""
fbase, fext = os.path.splitext(os.path.basename(fname))
fext = fext.lower()
atr = read_attribute(fname)
k = atr['FILE_TYPE']
global slice_list
# HDF5 Files
if fext in ['.h5', '.he5']:
with h5py.File(fname, 'r') as f:
d1_list = [i for i in f.keys() if isinstance(f[i], h5py.Dataset)]
if k == 'timeseries' and k in d1_list:
obj = timeseries(fname)
obj.open(print_msg=False)
slice_list = obj.sliceList
elif k in ['geometry'] and k not in d1_list:
obj = geometry(fname)
obj.open(print_msg=False)
slice_list = obj.sliceList
elif k in ['ifgramStack']:
obj = ifgramStack(fname)
obj.open(print_msg=False)
slice_list = obj.sliceList
elif k in ['HDFEOS']:
obj = HDFEOS(fname)
obj.open(print_msg=False)
slice_list = obj.sliceList
elif k in ['giantTimeseries']:
obj = giantTimeseries(fname)
obj.open(print_msg=False)
slice_list = obj.sliceList
elif k in ['giantIfgramStack']:
obj = giantIfgramStack(fname)
obj.open(print_msg=False)
slice_list = obj.sliceList
else:
## Find slice by walking through the file structure
length, width = int(atr['LENGTH']), int(atr['WIDTH'])
def get_hdf5_2d_dataset(name, obj):
global slice_list
if isinstance(obj, h5py.Dataset) and obj.shape[-2:] == (length,
width):
if obj.ndim == 2:
slice_list.append(name)
else:
warnings.warn(
'file has un-defined {}D dataset: {}'.format(
obj.ndim, name))
slice_list = []
with h5py.File(fname, 'r') as f:
f.visititems(get_hdf5_2d_dataset)
# Binary Files
else:
if fext.lower() in ['.trans', '.utm_to_rdc']:
slice_list = ['rangeCoord', 'azimuthCoord']
elif fbase.startswith('los'):
slice_list = ['incidenceAngle', 'azimuthAngle']
elif atr.get('number_bands', '1') == '2' and 'unw' not in k:
slice_list = ['band1', 'band2']
else:
slice_list = ['']
return slice_list
def read_init_info(inps):
# Time Series Info
ts_file0 = inps.timeseries_file[0]
atr = readfile.read_attribute(ts_file0)
inps.key = atr['FILE_TYPE']
if inps.key == 'timeseries':
obj = timeseries(ts_file0)
elif inps.key == 'giantTimeseries':
obj = giantTimeseries(ts_file0)
elif inps.key == 'HDFEOS':
obj = HDFEOS(ts_file0)
else:
raise ValueError('input file is {}, not timeseries.'.format(inps.key))
obj.open()
if not inps.file_label:
inps.file_label = [
str(i) for i in list(range(len(inps.timeseries_file)))
]
# default mask file
if not inps.mask_file and 'masked' not in ts_file0:
dir_name = os.path.dirname(ts_file0)
if 'Y_FIRST' in atr.keys():
inps.mask_file = os.path.join(dir_name, 'geo_maskTempCoh.h5')
else:
inps.mask_file = os.path.join(dir_name, 'maskTempCoh.h5')
if not os.path.isfile(inps.mask_file):
inps.mask_file = None
# date info
inps.date_list = obj.dateList
if inps.start_date:
inps.date_list = [
i for i in inps.date_list if int(i) >= int(inps.start_date)
]
if inps.end_date:
inps.date_list = [
i for i in inps.date_list if int(i) <= int(inps.end_date)
]
inps.num_date = len(inps.date_list)
inps.dates, inps.yearList = ptime.date_list2vector(inps.date_list)
(inps.ex_date_list, inps.ex_dates,
inps.ex_flag) = read_exclude_date(inps.ex_date_list, inps.date_list)
# initial display index
if obj.metadata['REF_DATE'] in inps.date_list:
inps.ref_idx = inps.date_list.index(obj.metadata['REF_DATE'])
else:
inps.ref_idx = 0
if inps.ref_date:
inps.ref_idx = inps.date_list.index(inps.ref_date)
if not inps.init_idx:
if inps.ref_idx < inps.num_date / 2.:
inps.init_idx = -3
else:
inps.init_idx = 3
# Display Unit
(inps.disp_unit,
inps.unit_fac) = pp.scale_data2disp_unit(metadata=atr,
disp_unit=inps.disp_unit)[1:3]
# Read Error List
inps.error_ts = None
inps.ex_error_ts = None
if inps.error_file:
error_fileContent = np.loadtxt(inps.error_file,
dtype=bytes).astype(str)
inps.error_ts = error_fileContent[:, 1].astype(
np.float) * inps.unit_fac
if inps.ex_date_list:
e_ts = inps.error_ts[:]
inps.ex_error_ts = e_ts[inps.ex_flag == 0]
inps.error_ts = e_ts[inps.ex_flag == 1]
# Zero displacement for 1st acquisition
if inps.zero_first:
inps.zero_idx = min(0, np.min(np.where(inps.ex_flag)[0]))
# default lookup table file
if not inps.lookup_file:
inps.lookup_file = ut.get_lookup_file('./INPUTS/geometryRadar.h5')
inps.coord = ut.coordinate(atr, inps.lookup_file)
# size and lalo info
inps.pix_box, inps.geo_box = subset.subset_input_dict2box(vars(inps), atr)
inps.pix_box = inps.coord.check_box_within_data_coverage(inps.pix_box)
inps.geo_box = inps.coord.box_pixel2geo(inps.pix_box)
# Out message
data_box = (0, 0, obj.width, obj.length)
print('data coverage in y/x: ' + str(data_box))
print('subset coverage in y/x: ' + str(inps.pix_box))
print('data coverage in lat/lon: ' +
str(inps.coord.box_pixel2geo(data_box)))
print('subset coverage in lat/lon: ' + str(inps.geo_box))
print(
'------------------------------------------------------------------------'
)
# reference pixel
if not inps.ref_lalo and 'REF_LAT' in atr.keys():
inps.ref_lalo = (float(atr['REF_LAT']), float(atr['REF_LON']))
if inps.ref_lalo:
if inps.ref_lalo[1] > 180.:
inps.ref_lalo[1] -= 360.
inps.ref_yx = inps.coord.geo2radar(inps.ref_lalo[0],
inps.ref_lalo[1],
print_msg=False)[0:2]
if not inps.ref_yx:
inps.ref_yx = [int(atr['REF_Y']), int(atr['REF_X'])]
# Initial Pixel Coord
if inps.lalo:
inps.yx = inps.coord.geo2radar(inps.lalo[0],
inps.lalo[1],
print_msg=False)[0:2]
try:
inps.lalo = inps.coord.radar2geo(inps.yx[0],
inps.yx[1],
print_msg=False)[0:2]
except:
inps.lalo = None
# Flip up-down / left-right
if inps.auto_flip:
inps.flip_lr, inps.flip_ud = pp.auto_flip_direction(atr)
# display unit ans wrap
# if wrap_step == 2*np.pi (default value), set disp_unit_v = radian;
# otherwise set disp_unit_v = disp_unit
inps.disp_unit_v = inps.disp_unit
if inps.wrap:
inps.range2phase = -4. * np.pi / float(atr['WAVELENGTH'])
if 'cm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 100.
elif 'mm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 1000.
elif 'm' == inps.disp_unit.split('/')[0]: inps.range2phase /= 1.
else:
raise ValueError('un-recognized display unit: {}'.format(
inps.disp_unit))
if (inps.wrap_range[1] - inps.wrap_range[0]) == 2 * np.pi:
inps.disp_unit_v = 'radian'
inps.vlim = inps.wrap_range
inps.cbar_label = 'Displacement [{}]'.format(inps.disp_unit_v)
return inps, atr
def diff_file(file1, file2, outFile=None, force=False):
"""Subtraction/difference of two input files"""
if not outFile:
fbase, fext = os.path.splitext(file1)
if len(file2) > 1:
raise ValueError('Output file name is needed for more than 2 files input.')
outFile = '{}_diff_{}{}'.format(fbase, os.path.splitext(os.path.basename(file2[0]))[0], fext)
print('{} - {} --> {}'.format(file1, file2, outFile))
# Read basic info
atr1 = readfile.read_attribute(file1)
k1 = atr1['FILE_TYPE']
atr2 = readfile.read_attribute(file2[0])
k2 = atr2['FILE_TYPE']
print('input files are: {} and {}'.format(k1, k2))
if k1 == 'timeseries':
if k2 not in ['timeseries', 'giantTimeseries']:
raise Exception('Input multiple dataset files are not the same file type!')
if len(file2) > 1:
raise Exception(('Only 2 files substraction is supported for time-series file,'
' {} input.'.format(len(file2)+1)))
obj1 = timeseries(file1)
obj1.open()
if k2 == 'timeseries':
obj2 = timeseries(file2[0])
unit_fac = 1.
elif k2 == 'giantTimeseries':
obj2 = giantTimeseries(file2[0])
unit_fac = 0.001
obj2.open()
ref_date, ref_y, ref_x = _check_reference(obj1.metadata, obj2.metadata)
# check dates shared by two timeseries files
dateListShared = [i for i in obj1.dateList if i in obj2.dateList]
dateShared = np.ones((obj1.numDate), dtype=np.bool_)
if dateListShared != obj1.dateList:
print('WARNING: {} does not contain all dates in {}'.format(file2, file1))
if force:
dateExcluded = list(set(obj1.dateList) - set(dateListShared))
print('Continue and enforce the differencing for their shared dates only.')
print('\twith following dates are ignored for differencing:\n{}'.format(dateExcluded))
dateShared[np.array([obj1.dateList.index(i) for i in dateExcluded])] = 0
else:
raise Exception('To enforce the differencing anyway, use --force option.')
# consider different reference_date/pixel
data2 = readfile.read(file2[0], datasetName=dateListShared)[0] * unit_fac
if ref_date:
data2 -= np.tile(data2[obj2.dateList.index(ref_date), :, :],
(data2.shape[0], 1, 1))
if ref_y and ref_x:
data2 -= np.tile(data2[:, ref_y, ref_x].reshape(-1, 1, 1),
(1, data2.shape[1], data2.shape[2]))
data = obj1.read()
mask = data == 0.
data[dateShared] -= data2
data[mask] = 0. # Do not change zero phase value
del data2
writefile.write(data, out_file=outFile, ref_file=file1)
elif all(i == 'ifgramStack' for i in [k1, k2]):
obj1 = ifgramStack(file1)
obj1.open()
obj2 = ifgramStack(file2[0])
obj2.open()
dsNames = list(set(obj1.datasetNames) & set(obj2.datasetNames))
if len(dsNames) == 0:
raise ValueError('no common dataset between two files!')
dsName = [i for i in ifgramDatasetNames if i in dsNames][0]
# read data
print('reading {} from file {} ...'.format(dsName, file1))
data1 = readfile.read(file1, datasetName=dsName)[0]
print('reading {} from file {} ...'.format(dsName, file2[0]))
data2 = readfile.read(file2[0], datasetName=dsName)[0]
# consider reference pixel
if 'unwrapphase' in dsName.lower():
print('referencing to pixel ({},{}) ...'.format(obj1.refY, obj1.refX))
ref1 = data1[:, obj1.refY, obj1.refX]
ref2 = data2[:, obj2.refY, obj2.refX]
for i in range(data1.shape[0]):
data1[i,:][data1[i, :] != 0.] -= ref1[i]
data2[i,:][data2[i, :] != 0.] -= ref2[i]
# operation and ignore zero values
data1[data1 == 0] = np.nan
data2[data2 == 0] = np.nan
data = data1 - data2
del data1, data2
data[np.isnan(data)] = 0.
# write to file
dsDict = {}
dsDict[dsName] = data
writefile.write(dsDict, out_file=outFile, ref_file=file1)
# Sing dataset file
else:
data1 = readfile.read(file1)[0]
data = np.array(data1, data1.dtype)
for fname in file2:
data2 = readfile.read(fname)[0]
data = np.array(data, dtype=np.float32) - np.array(data2, dtype=np.float32)
data = np.array(data, data1.dtype)
print('writing >>> '+outFile)
writefile.write(data, out_file=outFile, metadata=atr1)
return outFile
def diff_file(file1, file2, outFile=None, force=False):
"""Subtraction/difference of two input files"""
if not outFile:
fbase, fext = os.path.splitext(file1)
if len(file2) > 1:
raise ValueError(
'Output file name is needed for more than 2 files input.')
outFile = '{}_diff_{}{}'.format(
fbase,
os.path.splitext(os.path.basename(file2[0]))[0], fext)
print('{} - {} --> {}'.format(file1, file2, outFile))
# Read basic info
atr1 = readfile.read_attribute(file1)
k1 = atr1['FILE_TYPE']
atr2 = readfile.read_attribute(file2[0])
k2 = atr2['FILE_TYPE']
print('input files are: {} and {}'.format(k1, k2))
if k1 == 'timeseries':
if k2 not in ['timeseries', 'giantTimeseries']:
raise Exception(
'Input multiple dataset files are not the same file type!')
if len(file2) > 1:
raise Exception(
('Only 2 files substraction is supported for time series file,'
' {} input.'.format(len(file2) + 1)))
obj1 = timeseries(file1)
obj1.open()
if k2 == 'timeseries':
obj2 = timeseries(file2[0])
unit_fac = 1.
elif k2 == 'giantTimeseries':
obj2 = giantTimeseries(file2[0])
unit_fac = 0.001
obj2.open()
ref_date, ref_y, ref_x = _check_reference(obj1.metadata, obj2.metadata)
# check dates shared by two timeseries files
dateListShared = [i for i in obj1.dateList if i in obj2.dateList]
dateShared = np.ones((obj1.numDate), dtype=np.bool_)
if dateListShared != obj1.dateList:
print('WARNING: {} does not contain all dates in {}'.format(
file2, file1))
if force:
dateExcluded = list(set(obj1.dateList) - set(dateListShared))
print(
'Continue and enforce the differencing for their shared dates only.'
)
print(
'\twith following dates are ignored for differencing:\n{}'.
format(dateExcluded))
dateShared[np.array(
[obj1.dateList.index(i) for i in dateExcluded])] = 0
else:
raise Exception(
'To enforce the differencing anyway, use --force option.')
# consider different reference_date/pixel
data2 = readfile.read(file2[0],
datasetName=dateListShared)[0] * unit_fac
if ref_date:
data2 -= np.tile(data2[obj2.dateList.index(ref_date), :, :],
(data2.shape[0], 1, 1))
if ref_y and ref_x:
data2 -= np.tile(data2[:, ref_y, ref_x].reshape(-1, 1, 1),
(1, data2.shape[1], data2.shape[2]))
data = obj1.read()
mask = data == 0.
data[dateShared] -= data2
data[mask] = 0. # Do not change zero phase value
writefile.write(data, out_file=outFile, ref_file=file1)
# Sing dataset file
else:
data1 = readfile.read(file1)[0]
data = np.array(data1, data1.dtype)
for fname in file2:
data2 = readfile.read(fname)[0]
data = np.array(data, dtype=np.float32) - np.array(
data2, dtype=np.float32)
data = np.array(data, data1.dtype)
print('writing >>> ' + outFile)
writefile.write(data, out_file=outFile, metadata=atr1)
return outFile