def read_network_info(inps):
ext = os.path.splitext(inps.file)[1]
# 1. Read dateList and pbaseList
if ext in ['.h5', '.he5']:
k = readfile.read_attribute(inps.file)['FILE_TYPE']
print('reading temporal/spatial baselines from {} file: {}'.format(k, inps.file))
if k == 'ifgramStack':
inps.dateList = ifgramStack(inps.file).get_date_list(dropIfgram=False)
inps.pbaseList = ifgramStack(inps.file).get_perp_baseline_timeseries(dropIfgram=False)
elif k == 'timeseries':
obj = timeseries(inps.file)
obj.open(print_msg=False)
inps.dateList = obj.dateList
inps.pbaseList = obj.pbase
else:
raise ValueError('input file is not ifgramStack/timeseries, can not read temporal/spatial baseline info.')
else:
print('reading temporal/spatial baselines from list file: '+inps.bl_list_file)
inps.dateList, inps.pbaseList = pnet.read_baseline_file(inps.bl_list_file)[0:2]
print('number of acquisitions: {}'.format(len(inps.dateList)))
# 2. Read All Date12/Ifgrams/Pairs
inps.date12List = pnet.get_date12_list(inps.file)
print('reading interferograms info from file: {}'.format(inps.file))
print('number of interferograms: {}'.format(len(inps.date12List)))
if inps.save_list:
txtFile = os.path.splitext(os.path.basename(inps.file))[0]+'_date12List.txt'
np.savetxt(txtFile, inps.date12List, fmt='%s')
print('save pairs/date12 info to file: '+txtFile)
# Optional: Read dropped date12 / date
inps.dateList_drop = []
inps.date12List_drop = []
if ext in ['.h5', '.he5'] and k == 'ifgramStack':
inps.date12List_keep = ifgramStack(inps.file).get_date12_list(dropIfgram=True)
inps.date12List_drop = sorted(list(set(inps.date12List) - set(inps.date12List_keep)))
print('-'*50)
print('number of interferograms marked as drop: {}'.format(len(inps.date12List_drop)))
print('number of interferograms marked as keep: {}'.format(len(inps.date12List_keep)))
mDates = [i.split('_')[0] for i in inps.date12List_keep]
sDates = [i.split('_')[1] for i in inps.date12List_keep]
inps.dateList_keep = sorted(list(set(mDates + sDates)))
inps.dateList_drop = sorted(list(set(inps.dateList) - set(inps.dateList_keep)))
print('number of acquisitions marked as drop: {}'.format(len(inps.dateList_drop)))
if len(inps.dateList_drop) > 0:
print(inps.dateList_drop)
# Optional: Read Coherence List
inps.cohList = None
if ext in ['.h5', '.he5'] and k == 'ifgramStack':
inps.cohList, cohDate12List = ut.spatial_average(inps.file,
datasetName='coherence',
maskFile=inps.maskFile,
saveList=True,
checkAoi=False)
if all(np.isnan(inps.cohList)):
inps.cohList = None
print('WARNING: all coherence value are nan! Do not use this and continue.')
if set(cohDate12List) > set(inps.date12List):
print('extract coherence value for all pair/date12 in input file')
inps.cohList = [inps.cohList[cohDate12List.index(i)] for i in inps.date12List]
elif set(cohDate12List) < set(inps.date12List):
inps.cohList = None
print('WARNING: not every pair/date12 from input file is in coherence file')
print('turn off the color plotting of interferograms based on coherence')
return inps
def main(argv):
inps = cmdLineParse()
if inps.timeseries_file:
inps.timeseries_file=ut.get_file_list([inps.timeseries_file])[0]
atr=readfile.read_attribute(inps.timeseries_file)
k = atr['FILE_TYPE']
if 'ref_y' not in list(atr.keys()) and inps.ref_yx:
print('No reference info found in input file, use input ref_yx: '+str(inps.ref_yx))
atr['ref_y'] = inps.ref_yx[0]
atr['ref_x'] = inps.ref_yx[1]
#****reading incidence angle file***/
if os.path.isfile(inps.inc_angle):
inps.inc_angle=readfile.read(inps.inc_angle, datasetName='incidenceAngle')[0]
inps.inc_angle=np.nan_to_num(inps.inc_angle)
else:
inps.inps.inc_angle = float(inps.inc_angle)
print('incidence angle: '+str(inps.inc_angle))
cinc=np.cos(inps.inc_angle*np.pi/180.0);
#****look up file****/
if inps.lookup_file:
inps.lookup_file = ut.get_file_list([inps.lookup_file])[0] #'geomap_32rlks_tight.trans'
#****GACOS****/
delay_source = 'GACOS'
# Get weather directory
if not inps.GACOS_dir:
if inps.timeseries_file:
inps.GACOS_dir = os.path.dirname(os.path.abspath(inps.timeseries_file))+'/../WEATHER/GACOS'
elif inps.lookup_file:
inps.GACOS_dir = os.path.dirname(os.path.abspath(inps.lookup_file))+'/../WEATHER/GACOS'
else:
inps.GACOS_dir = os.path.abspath(os.getcwd())
print('Store weather data into directory: '+inps.GACOS_dir)
#source_dir=os.path.dirname(os.path.abspath('timeseries_file'))+'/Agung/GACOS/data';print source_dir
#os.makedirs(GACOS_dir) -----------------------------------------------add part to copy/download weather data------#
#----get date list-----#
if not inps.date_list_file:
print('read date list info from: '+inps.timeseries_file)
h5=h5py.File(inps.timeseries_file,'r')
if 'timeseries' in list(h5.keys()):
date_list=sorted(h5[k].keys())
elif k in ['interferograms','coherence','wrapped']:
ifgram_list = sorted(h5[k].keys())
date12_list = pnet.get_date12_list(inps.timeseries_file)
m_dates = [i.split('-')[0] for i in date12_list]
s_dates = [i.split('-')[1] for i in date12_list]
date_list = ptime.yyyymmdd(sorted(list(set(m_dates + s_dates))))
else:
raise ValueError('Un-support input file type:'+k)
h5.close()
else:
date_list = ptime.yyyymmdd(np.loadtxt(inps.date_list_file, dtype=str, usecols=(0,)).tolist())
print('read date list info from: '+inps.date_list_file)
#****cheacking availability of delays****/
print('checking availability of delays')
delay_file_list=[]
for d in date_list:
if delay_source == 'GACOS': delay_file = inps.GACOS_dir+'/'+d+'.ztd';
delay_file_list.append(delay_file)
delay_file_existed = ut.get_file_list(delay_file_list)
if len(delay_file_existed)==len(date_list):
print('no missing files')
else:
print('no. of date files found:', len(delay_file_existed));
print('no. of dates:', len(date_list))
#*****Calculating delays***/
print('calculating delays')
length=int(atr['FILE_LENGTH'])
width=int(atr['WIDTH'])
#initialise delay files
date_num=len(date_list)
trop_ts=np.zeros((date_num, length, width), np.float32)
#reading wrf files for each epoch and getting delay
for i in range(date_num):
delay_file=delay_file_existed[i]
date=date_list[i]
print('calculating delay for date',date)
trop_ts[i] =get_delay(delay_file,atr,inps.lookup_file,cinc)
print('Delays Calculated')
# Convert relative phase delay on reference date
try: ref_date = atr['ref_date']
except: ref_date = date_list[0]
print('convert to relative phase delay with reference date: '+ref_date)
ref_idx = date_list.index(ref_date)
trop_ts -= np.tile(trop_ts[ref_idx,:,:], (date_num, 1, 1))
## Write tropospheric delay to HDF5
tropFile = 'GACOSdelays'+'.h5'
print('writing >>> %s' % (tropFile))
h5trop = h5py.File(tropFile, 'w')
group_trop = h5trop.create_group('timeseries')
print('number of acquisitions: '+str(date_num))
prog_bar = ptime.progress_bar(maxValue=date_num)
for i in range(date_num):
date = date_list[i]
group_trop.create_dataset(date, data=trop_ts[i], compression='gzip')
prog_bar.update(i+1, suffix=date)
prog_bar.close()
# Write Attributes
for key,value in atr.items():
group_trop.attrs[key] = value
h5trop.close()
## Write corrected Time series to HDF5
if k == 'timeseries':
if not inps.out_file:
inps.out_file = os.path.splitext(inps.timeseries_file)[0]+'_'+'GACOS'+'.h5'
print('writing trop corrected timeseries file %s' % (inps.out_file))
h5ts = h5py.File(inps.timeseries_file, 'r')
h5tsCor = h5py.File(inps.out_file, 'w')
group_tsCor = h5tsCor.create_group('timeseries')
print('number of acquisitions: '+str(date_num))
prog_bar = ptime.progress_bar(maxValue=date_num)
for i in range(date_num):
date = date_list[i];print(date)
ts = h5ts['timeseries'].get(date)[:]
group_tsCor.create_dataset(date, data=ts-trop_ts[i], compression='gzip')
prog_bar.update(i+1, suffix=date)
prog_bar.close()
h5ts.close()
# Write Attributes
for key,value in atr.items():
group_tsCor.attrs[key] = value
h5tsCor.close()
print('delays written to %s' % (inps.out_file))
print('finished')
return inps.out_file
def get_date12_to_drop(inps):
"""Get date12 list to dropped
Return [] if no ifgram to drop, thus KEEP ALL ifgrams;
None if nothing to change, exit without doing anything.
"""
obj = ifgramStack(inps.file)
obj.open()
date12ListAll = obj.date12List
dateList = obj.dateList
print('number of interferograms: {}'.format(len(date12ListAll)))
# Get date12_to_drop
date12_to_drop = []
# reference file
if inps.referenceFile:
date12_to_keep = pnet.get_date12_list(inps.referenceFile, dropIfgram=True)
print('--------------------------------------------------')
print('use reference pairs info from file: {}'.format(inps.referenceFile))
print('number of interferograms in reference: {}'.format(len(date12_to_keep)))
tempList = sorted(list(set(date12ListAll) - set(date12_to_keep)))
date12_to_drop += tempList
print('date12 not in reference file: ({})\n{}'.format(len(tempList), tempList))
# temp baseline threshold
if inps.tempBaseMax:
tempIndex = np.abs(obj.tbaseIfgram) > inps.tempBaseMax
tempList = list(np.array(date12ListAll)[tempIndex])
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with temporal baseline > {} days: ({})\n{}'.format(
inps.tempBaseMax, len(tempList), tempList))
# perp baseline threshold
if inps.perpBaseMax:
tempIndex = np.abs(obj.pbaseIfgram) > inps.perpBaseMax
tempList = list(np.array(date12ListAll)[tempIndex])
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with perp baseline > {} meters: ({})\n{}'.format(
inps.perpBaseMax, len(tempList), tempList))
# connection number threshold
if inps.connNumMax:
seq_date12_list = pnet.select_pairs_sequential(dateList, inps.connNumMax)
seq_date12_list = ptime.yyyymmdd_date12(seq_date12_list)
tempList = [i for i in date12ListAll if i not in seq_date12_list]
date12_to_drop += tempList
print('--------------------------------------------------')
msg = 'Drop ifgrams with temporal baseline beyond {} neighbors: ({})'.format(
inps.connNumMax, len(tempList))
if len(tempList) <= 200:
msg += '\n{}'.format(tempList)
print(msg)
# excludeIfgIndex
if inps.excludeIfgIndex:
tempList = [date12ListAll[i] for i in inps.excludeIfgIndex]
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with the following index number: {}'.format(len(tempList)))
for i, date12 in enumerate(tempList):
print('{} : {}'.format(i, date12))
# excludeDate
if inps.excludeDate:
tempList = [i for i in date12ListAll if any(j in inps.excludeDate for j in i.split('_'))]
date12_to_drop += tempList
print('-'*50+'\nDrop ifgrams including the following dates: ({})\n{}'.format(
len(tempList), inps.excludeDate))
print('-'*30+'\n{}'.format(tempList))
# startDate
if inps.startDate:
minDate = int(inps.startDate)
tempList = [i for i in date12ListAll if any(int(j) < minDate for j in i.split('_'))]
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with date earlier than: {} ({})\n{}'.format(
inps.startDate, len(tempList), tempList))
# endDate
if inps.endDate:
maxDate = int(inps.endDate)
tempList = [i for i in date12ListAll if any(int(j) > maxDate for j in i.split('_'))]
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with date later than: {} ({})\n{}'.format(
inps.endDate, len(tempList), tempList))
# coherence file
if inps.coherenceBased:
print('--------------------------------------------------')
print('use coherence-based network modification')
# get area of interest for coherence calculation
pix_box = get_aoi_pix_box(obj.metadata, inps.lookupFile, inps.aoi_pix_box, inps.aoi_geo_box)
# calculate spatial average coherence
cohList = ut.spatial_average(inps.file,
datasetName='coherence',
maskFile=inps.maskFile,
box=pix_box,
saveList=True)[0]
# get coherence-based network
coh_date12_list = list(np.array(date12ListAll)[np.array(cohList) >= inps.minCoherence])
# get MST network
mst_date12_list, msg = get_mst_date12(inps.keepMinSpanTree, cohList, date12ListAll, date12_to_drop,
min_par=inps.minCoherence,
par_name='average coherence')
# drop all dates (below cohh thresh AND not in MST)
tempList = sorted(list(set(date12ListAll) - set(coh_date12_list + mst_date12_list)))
date12_to_drop += tempList
msg += '({})'.format(len(tempList))
if len(tempList) <= 200:
msg += '\n{}'.format(tempList)
print(msg)
# area ratio file
if inps.areaRatioBased:
print('--------------------------------------------------')
print('use area-ratio-based network modification')
# get area of interest for coherence calculation
pix_box = get_aoi_pix_box(obj.metadata, inps.lookupFile, inps.aoi_pix_box, inps.aoi_geo_box)
# calculate average coherence in masked out areas as threshold
meanMaskCoh = np.nanmean(ut.spatial_average(inps.file,
datasetName='coherence',
maskFile=inps.maskFile,
saveList=True,
reverseMask=True)[0])
print(f'Average coherence of {inps.maskFile} reverse is {meanMaskCoh:.2f}')
# calculate area-ratio with pixels greater than meanMaskCoh
areaRatioList = ut.spatial_average(inps.file,
datasetName='coherence',
maskFile=inps.maskFile,
box=pix_box,
saveList=True,
checkAoi=True,
threshold=meanMaskCoh)[0]
# get area-ratio-based network
area_ratio_date12_list = list(np.array(date12ListAll)[np.array(areaRatioList) >= inps.minAreaRatio])
# get MST network
mst_date12_list, msg = get_mst_date12(inps.keepMinSpanTree, areaRatioList, date12ListAll, date12_to_drop,
min_par=inps.minAreaRatio,
par_name='coherent area ratio')
# drop all dates (below area-ratio thresh AND not in MST)
tempList = sorted(list(set(date12ListAll) - set(area_ratio_date12_list + mst_date12_list)))
date12_to_drop += tempList
msg += '({})'.format(len(tempList))
if len(tempList) <= 200:
msg += '\n{}'.format(tempList)
print(msg)
# Manually drop pairs
if inps.manual:
tempList = manual_select_pairs_to_remove(inps.file)
if tempList is None:
return None
tempList = [i for i in tempList if i in date12ListAll]
print('date12 selected to remove: ({})\n{}'.format(len(tempList), tempList))
date12_to_drop += tempList
## summary
# drop duplicate date12 and sort in order
date12_to_drop = sorted(list(set(date12_to_drop)))
date12_to_keep = sorted(list(set(date12ListAll) - set(date12_to_drop)))
print('--------------------------------------------------')
print('number of interferograms to remove: {}'.format(len(date12_to_drop)))
print('number of interferograms to keep : {}'.format(len(date12_to_keep)))
# print list of date to drop
date_to_keep = [d for date12 in date12_to_keep for d in date12.split('_')]
date_to_keep = sorted(list(set(date_to_keep)))
date_to_drop = sorted(list(set(dateList) - set(date_to_keep)))
if len(date_to_drop) > 0:
print('number of acquisitions to remove: {}\n{}'.format(len(date_to_drop), date_to_drop))
# checking:
# 1) no new date12 to drop against existing file
# 2) no date12 left after dropping
date12ListKept = obj.get_date12_list(dropIfgram=True)
date12ListDropped = sorted(list(set(date12ListAll) - set(date12ListKept)))
if date12_to_drop == date12ListDropped:
print('Calculated date12 to drop is the same as exsiting marked input file, skip updating file.')
date12_to_drop = None
elif date12_to_drop == date12ListAll:
raise Exception('Zero interferogram left! Please adjust your setting and try again.')
return date12_to_drop
def get_date12_to_drop(inps):
"""Get date12 list to dropped
Return [] if no ifgram to drop, thus KEEP ALL ifgrams;
None if nothing to change, exit without doing anything.
"""
obj = ifgramStack(inps.file)
obj.open()
date12ListAll = obj.date12List
dateList = obj.dateList
print('number of interferograms: {}'.format(len(date12ListAll)))
# Get date12_to_drop
date12_to_drop = []
# reference file
if inps.referenceFile:
date12_to_keep = pnet.get_date12_list(inps.referenceFile,
dropIfgram=True)
print('--------------------------------------------------')
print('use reference pairs info from file: {}'.format(
inps.referenceFile))
print('number of interferograms in reference: {}'.format(
len(date12_to_keep)))
tempList = sorted(list(set(date12ListAll) - set(date12_to_keep)))
date12_to_drop += tempList
print('date12 not in reference file: ({})\n{}'.format(
len(tempList), tempList))
# coherence file
if inps.coherenceBased:
print('--------------------------------------------------')
print('use coherence-based network modification')
coord = ut.coordinate(obj.metadata, lookup_file=inps.lookupFile)
if inps.aoi_geo_box and inps.lookupFile:
print('input AOI in (lon0, lat1, lon1, lat0): {}'.format(
inps.aoi_geo_box))
inps.aoi_pix_box = coord.bbox_geo2radar(inps.aoi_geo_box)
if inps.aoi_pix_box:
inps.aoi_pix_box = coord.check_box_within_data_coverage(
inps.aoi_pix_box)
print('input AOI in (x0,y0,x1,y1): {}'.format(inps.aoi_pix_box))
# Calculate spatial average coherence
cohList = ut.spatial_average(inps.file,
datasetName='coherence',
maskFile=inps.maskFile,
box=inps.aoi_pix_box,
saveList=True)[0]
coh_date12_list = list(
np.array(date12ListAll)[np.array(cohList) >= inps.minCoherence])
# MST network
if inps.keepMinSpanTree:
print(
'Get minimum spanning tree (MST) of interferograms with inverse of coherence.'
)
msg = ('Drop ifgrams with '
'1) average coherence < {} AND '
'2) not in MST network: '.format(inps.minCoherence))
mst_date12_list = pnet.threshold_coherence_based_mst(
date12ListAll, cohList)
mst_date12_list = ptime.yyyymmdd_date12(mst_date12_list)
else:
msg = 'Drop ifgrams with average coherence < {}: '.format(
inps.minCoherence)
mst_date12_list = []
tempList = sorted(
list(set(date12ListAll) - set(coh_date12_list + mst_date12_list)))
date12_to_drop += tempList
msg += '({})'.format(len(tempList))
if len(tempList) <= 200:
msg += '\n{}'.format(tempList)
print(msg)
# temp baseline threshold
if inps.tempBaseMax:
tempIndex = np.abs(obj.tbaseIfgram) > inps.tempBaseMax
tempList = list(np.array(date12ListAll)[tempIndex])
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with temporal baseline > {} days: ({})\n{}'.format(
inps.tempBaseMax, len(tempList), tempList))
# perp baseline threshold
if inps.perpBaseMax:
tempIndex = np.abs(obj.pbaseIfgram) > inps.perpBaseMax
tempList = list(np.array(date12ListAll)[tempIndex])
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with perp baseline > {} meters: ({})\n{}'.format(
inps.perpBaseMax, len(tempList), tempList))
# connection number threshold
if inps.connNumMax:
seq_date12_list = pnet.select_pairs_sequential(dateList,
inps.connNumMax)
seq_date12_list = ptime.yyyymmdd_date12(seq_date12_list)
tempList = [i for i in date12ListAll if i not in seq_date12_list]
date12_to_drop += tempList
print('--------------------------------------------------')
msg = 'Drop ifgrams with temporal baseline beyond {} neighbors: ({})'.format(
inps.connNumMax, len(tempList))
if len(tempList) <= 200:
msg += '\n{}'.format(tempList)
print(msg)
# excludeIfgIndex
if inps.excludeIfgIndex:
tempList = [date12ListAll[i] for i in inps.excludeIfgIndex]
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with the following index number: {}'.format(
len(tempList)))
for i in range(len(tempList)):
print('{} : {}'.format(i, tempList[i]))
#len(tempList), zip(inps.excludeIfgIndex, tempList)))
# excludeDate
if inps.excludeDate:
tempList = [
i for i in date12ListAll
if any(j in inps.excludeDate for j in i.split('_'))
]
date12_to_drop += tempList
print('-' * 50 +
'\nDrop ifgrams including the following dates: ({})\n{}'.format(
len(tempList), inps.excludeDate))
print('-' * 30 + '\n{}'.format(tempList))
# startDate
if inps.startDate:
minDate = int(inps.startDate)
tempList = [
i for i in date12ListAll if any(
int(j) < minDate for j in i.split('_'))
]
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with date earlier than: {} ({})\n{}'.format(
inps.startDate, len(tempList), tempList))
# endDate
if inps.endDate:
maxDate = int(inps.endDate)
tempList = [
i for i in date12ListAll if any(
int(j) > maxDate for j in i.split('_'))
]
date12_to_drop += tempList
print('--------------------------------------------------')
print('Drop ifgrams with date later than: {} ({})\n{}'.format(
inps.endDate, len(tempList), tempList))
# Manually drop pairs
if inps.manual:
tempList = manual_select_pairs_to_remove(inps.file)
if tempList is None:
return None
tempList = [i for i in tempList if i in date12ListAll]
print('date12 selected to remove: ({})\n{}'.format(
len(tempList), tempList))
date12_to_drop += tempList
# drop duplicate date12 and sort in order
date12_to_drop = sorted(list(set(date12_to_drop)))
date12_to_keep = sorted(list(set(date12ListAll) - set(date12_to_drop)))
print('--------------------------------------------------')
print('number of interferograms to remove: {}'.format(len(date12_to_drop)))
print('number of interferograms to keep : {}'.format(len(date12_to_keep)))
date_to_keep = [d for date12 in date12_to_keep for d in date12.split('_')]
date_to_keep = sorted(list(set(date_to_keep)))
date_to_drop = sorted(list(set(dateList) - set(date_to_keep)))
if len(date_to_drop) > 0:
print('number of acquisitions to remove: {}\n{}'.format(
len(date_to_drop), date_to_drop))
date12ListKept = obj.get_date12_list(dropIfgram=True)
date12ListDropped = sorted(list(set(date12ListAll) - set(date12ListKept)))
if date12_to_drop == date12ListDropped:
print(
'Calculated date12 to drop is the same as exsiting marked input file, skip updating file.'
)
date12_to_drop = None
elif date12_to_drop == date12ListAll:
raise Exception(
'Zero interferogram left! Please adjust your setting and try again.'
)
return date12_to_drop
def read_network_info(inps):
ext = os.path.splitext(inps.file)[1]
# 1. Read dateList and pbaseList
if ext in ['.h5', '.he5']:
k = readfile.read_attribute(inps.file)['FILE_TYPE']
print('reading temporal/spatial baselines from {} file: {}'.format(k, inps.file))
if k == 'ifgramStack':
inps.dateList = ifgramStack(inps.file).get_date_list(dropIfgram=False)
inps.pbaseList = ifgramStack(inps.file).get_perp_baseline_timeseries(dropIfgram=False)
elif k == 'timeseries':
obj = timeseries(inps.file)
obj.open(print_msg=False)
inps.dateList = obj.dateList
inps.pbaseList = obj.pbase
else:
raise ValueError('input file is not ifgramStack/timeseries, can not read temporal/spatial baseline info.')
else:
print('reading temporal/spatial baselines from list file: '+inps.bl_list_file)
inps.dateList, inps.pbaseList = pnet.read_baseline_file(inps.bl_list_file)[0:2]
print('number of acquisitions: {}'.format(len(inps.dateList)))
# 2. Read All Date12/Ifgrams/Pairs
inps.date12List = pnet.get_date12_list(inps.file)
print('reading interferograms info from file: {}'.format(inps.file))
print('number of interferograms: {}'.format(len(inps.date12List)))
if inps.save_list:
txtFile = os.path.splitext(os.path.basename(inps.file))[0]+'_date12List.txt'
np.savetxt(txtFile, inps.date12List, fmt='%s')
print('save pairs/date12 info to file: '+txtFile)
# Optional: Read dropped date12 / date
inps.dateList_drop = []
inps.date12List_drop = []
if ext in ['.h5', '.he5'] and k == 'ifgramStack':
inps.date12List_keep = ifgramStack(inps.file).get_date12_list(dropIfgram=True)
inps.date12List_drop = sorted(list(set(inps.date12List) - set(inps.date12List_keep)))
print('-'*50)
print('number of interferograms marked as drop: {}'.format(len(inps.date12List_drop)))
print('number of interferograms marked as keep: {}'.format(len(inps.date12List_keep)))
mDates = [i.split('_')[0] for i in inps.date12List_keep]
sDates = [i.split('_')[1] for i in inps.date12List_keep]
inps.dateList_keep = sorted(list(set(mDates + sDates)))
inps.dateList_drop = sorted(list(set(inps.dateList) - set(inps.dateList_keep)))
print('number of acquisitions marked as drop: {}'.format(len(inps.dateList_drop)))
if len(inps.dateList_drop) > 0:
print(inps.dateList_drop)
# Optional: Read Coherence List
inps.cohList = None
if ext in ['.h5', '.he5'] and k == 'ifgramStack':
inps.cohList, cohDate12List = ut.spatial_average(inps.file, datasetName='coherence', maskFile=inps.maskFile,
saveList=True, checkAoi=False)
if all(np.isnan(inps.cohList)):
inps.cohList = None
print('WARNING: all coherence value are nan! Do not use this and continue.')
if set(cohDate12List) > set(inps.date12List):
print('extract coherence value for all pair/date12 in input file')
inps.cohList = [inps.cohList[cohDate12List.index(i)] for i in inps.date12List]
elif set(cohDate12List) < set(inps.date12List):
inps.cohList = None
print('WARNING: not every pair/date12 from input file is in coherence file')
print('turn off the color plotting of interferograms based on coherence')
return inps