def read_baseline_info(baseline_file, reference_file):
"""Read date, bperp and/or DOP info
Parameters: baseline_file : str, path of bl_list.txt file
reference_file : str, path of ifgramStack.h5 file
Returns: date_list : list of str in YYMMDD format
tbase_list : list of int in days
pbase_list : list of float in meter
dop_list : None, list of 1D array in size of (3,)
"""
dop_list = None
if baseline_file:
date_list, pbase_list, dop_list = pnet.read_baseline_file(
baseline_file)[0:3]
date_list = ptime.yymmdd(date_list)
tbase_list = ptime.date_list2tbase(date_list)[0]
elif reference_file:
obj = ifgramStack(reference_file)
date12_list_all = obj.get_date12_list(dropIfgram=False)
date12_list_all = ptime.yymmdd_date12(date12_list_all)
m_dates = [i.split('-')[0] for i in date12_list_all]
s_dates = [i.split('-')[1] for i in date12_list_all]
date_list = sorted(list(set(m_dates + s_dates)))
tbase_list = ptime.date_list2tbase(date_list)[0]
pbase_list = obj.get_perp_baseline_timeseries(
dropIfgram=False).tolist()
return date_list, tbase_list, pbase_list, dop_list
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 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
