def seed_file(File,outName,refList,ref_x='',ref_y=''):
## Seed Input File with reference value in refList
print 'Reference value: '
print refList
##### IO Info
atr = readfile.read_attributes(File)
k = atr['FILE_TYPE']
print 'file type: '+k
##### Multiple Dataset File
if k in ['timeseries','interferograms','wrapped','coherence']:
##### Input File Info
h5file = h5py.File(File,'r')
epochList = h5file[k].keys()
epochList = sorted(epochList)
epochNum = len(epochList)
print 'number of epochs: '+str(epochNum)
##### Check Epoch Number
if not epochNum == len(refList):
print '\nERROR: Reference value has different epoch number'+\
'from input file.'
print 'Reference List epoch number: '+str(refList)
print 'Input file epoch number: '+str(epochNum)
sys.exit(1)
##### Output File Info
h5out = h5py.File(outName,'w')
group = h5out.create_group(k)
print 'writing >>> '+outName
## Loop
if k == 'timeseries':
for i in range(epochNum):
epoch = epochList[i]
print epoch
data = h5file[k].get(epoch)[:]
data -= refList[i]
dset = group.create_dataset(epoch, data=data, compression='gzip')
atr = seed_attributes(atr,ref_x,ref_y)
for key,value in atr.iteritems(): group.attrs[key] = value
elif k in ['interferograms','wrapped','coherence']:
for i in range(epochNum):
epoch = epochList[i]
#print epoch
data = h5file[k][epoch].get(epoch)[:]
atr = h5file[k][epoch].attrs
data -= refList[i]
atr = seed_attributes(atr,ref_x,ref_y)
gg = group.create_group(epoch)
dset = gg.create_dataset(epoch, data=data, compression='gzip')
for key, value in atr.iteritems(): gg.attrs[key] = value
ut.printProgress(i+1,epochNum,'seeding:',epoch)
##### Single Dataset File
else:
data,atr = readfile.read(File)
data -= refList
atr = seed_attributes(atr,ref_x,ref_y)
writefile.write(data,atr,outName)
##### End & Cleaning
try:
h5file.close()
h5out.close()
except: pass
return 1
def main(argv):
## Default value
phase_velocity = "no" # 'no' means use 'phase history'
update_timeseries = "yes"
if len(sys.argv) > 2:
try:
opts, args = getopt.getopt(argv, "h:f:F:o:v:", ["phase-velocity", "no-timeseries-update"])
except getopt.GetoptError:
print "Error in reading input options!"
Usage()
sys.exit(1)
for opt, arg in opts:
if opt in ["-h", "--help"]:
Usage()
sys.exit()
elif opt == "-f":
timeSeriesFile = arg
elif opt == "-F":
igramsFile = arg
elif opt == "-o":
outname = arg
elif opt == "--phase-velocity":
phase_velocity = "yes"
elif opt == "--no-timeseries-update":
update_timeseries = "no"
elif len(sys.argv) == 2:
if argv[0] in ["-h", "--help"]:
Usage()
sys.exit(1)
else:
timeSeriesFile = argv[0]
else:
Usage()
sys.exit(1)
try:
outname
except:
outname = timeSeriesFile.replace(".h5", "") + "_demCor.h5"
##### Read Time Series
print "\n*************** Topographic Error Correction ****************"
print "Loading time series: " + timeSeriesFile
atr = readfile.read_attributes(timeSeriesFile)
h5timeseries = h5py.File(timeSeriesFile)
dateList = h5timeseries["timeseries"].keys()
dateList = sorted(dateList)
lt = len(dateList)
print "number of epochs: " + str(lt)
dateIndex = {}
for ni in range(len(dateList)):
dateIndex[dateList[ni]] = ni
nrows = int(atr["FILE_LENGTH"])
ncols = int(atr["WIDTH"])
timeseries = np.zeros((len(dateList), nrows * ncols), np.float32)
for date in dateList:
print date
d = h5timeseries["timeseries"].get(date)[:]
timeseries[dateIndex[date]][:] = d.flatten("F")
del d
h5timeseries.close()
print "**************************************"
##### Temporal Baseline
print "read temporal baseline"
tbase, date_dict = ptime.date_list2tbase(dateList)
tbase = np.array(tbase).reshape(lt, 1)
##### Perpendicular Baseline
try:
Bp = [float(i) for i in atr["P_BASELINE_TIMESERIES"].split()]
Bp = np.array(Bp).reshape(lt, 1)
except:
print "Cannot find P_BASELINE_TIMESERIES from timeseries file."
print "Trying to calculate it from interferograms file"
try:
Bp = ut.Baseline_timeseries(igramsFile)
Bp = np.array(Bp).reshape(lt, 1)
except:
print "Error in calculating baseline time series!"
sys.exit(1)
Bp_v = (Bp[1:lt] - Bp[0 : lt - 1]) / (tbase[1:lt] - tbase[0 : lt - 1])
##### Cubic Temporal Deformation Model
## Formula (10) in (Fattahi and Amelung, 2013, TGRS)
if phase_velocity == "yes":
print "using phase velocity history"
M1 = np.ones((lt - 1, 1))
M2 = (tbase[1:lt] + tbase[0 : lt - 1]) / 2
M3 = (tbase[1:lt] ** 2 + tbase[1:lt] * tbase[0 : lt - 1] + tbase[0 : lt - 1] ** 2) / 6
M = np.hstack((M1, M2, M3))
else:
print "using phase history"
M = np.hstack((0.5 * tbase ** 2, tbase, np.ones((lt, 1))))
## Testing
# teta = (tetaN+tetaF)/2
# r = (rN+rF)/2
# teta=19.658799999999999*np.pi/180
# r=846848.2
# Bperp=1000*np.random.random((lt,1))
##### Range and Look Angle
near_range = float(atr["STARTING_RANGE1"])
dR = float(atr["RANGE_PIXEL_SIZE"])
r = float(atr["EARTH_RADIUS"])
H = float(atr["HEIGHT"])
far_range = near_range + dR * (ncols - 1)
incidence_n = np.pi - np.arccos((r ** 2 + near_range ** 2 - (r + H) ** 2) / (2 * r * near_range))
incidence_f = np.pi - np.arccos((r ** 2 + far_range ** 2 - (r + H) ** 2) / (2 * r * far_range))
various_range = "yes"
if various_range == "yes":
range_x = np.linspace(near_range, far_range, num=ncols, endpoint="FALSE")
look_angle_x = np.linspace(incidence_n, incidence_f, num=ncols, endpoint="FALSE")
else:
print "using center range and look angle to represent the whole area"
center_range = (near_range + far_range) / 2
center_look_angle = np.pi - np.arccos((r ** 2 + center_range ** 2 - (r + H) ** 2) / (2 * r * center_range))
range_x = np.tile(center_range, ncols)
look_angle_x = np.tile(center_look_angle, ncols)
# C1_v = Bp_v / (center_range * np.sin(center_look_angle))
# C1 = Bp / (center_range * np.sin(center_look_angle))
# timeseries_v = (timeseries[1:lt,:] - timeseries[0:lt-1,:]) / (tbase[1:lt] - tbase[0:lt-1])
##### Inversion column by column
print "inversing using L2-norm minimization (unweighted least squares)..."
dz = np.zeros([1, nrows * ncols])
for i in range(ncols):
## Design Matrix Inversion
C1_v = Bp_v / (range_x[i] * np.sin(look_angle_x[i]))
C1 = Bp / (range_x[i] * np.sin(look_angle_x[i]))
if phase_velocity == "yes":
C = np.hstack((M, C1_v))
else:
C = np.hstack((M, C1))
# print ' rank of the design matrix : '+str(np.linalg.matrix_rank(C))
# if np.linalg.matrix_rank(C) == 4: print ' design matrix has full rank'
Cinv = np.linalg.pinv(C)
## (Phase) Velocity History
ts_x = timeseries[:, i * nrows : (i + 1) * nrows]
ts_xv = (ts_x[1:lt, :] - ts_x[0 : lt - 1, :]) / (tbase[1:lt] - tbase[0 : lt - 1])
## DEM error
if phase_velocity == "yes":
par = np.dot(Cinv, ts_xv)
else:
par = np.dot(Cinv, ts_x)
dz_x = par[3].reshape((1, nrows))
## Update DEM error matrix and timeseries matrix
dz[0][i * nrows : (i + 1) * nrows] = dz_x
timeseries[:, i * nrows : (i + 1) * nrows] -= np.dot(C1, dz_x)
ut.printProgress(i + 1, ncols)
# dz[0][:] = par[3][:]
dz = np.reshape(dz, [nrows, ncols], order="F")
########## Output - DEM error #######################
# print '**************************************'
# print 'writing DEM_error.hgt'
# writefile.write_float32(dz,'DEM_error.hgt')
# f = open('DEM_error.hgt.rsc','w')
# f.write('FILE_LENGTH '+str(int(nrows))+'\n')
# f.write('WIDTH '+str(int(ncols))+'\n')
# print '**************************************'
h5fileDEM = "DEM_error.h5"
print "writing >>> " + h5fileDEM
h5rmse = h5py.File(h5fileDEM, "w")
group = h5rmse.create_group("dem")
dset = group.create_dataset(os.path.basename("dem"), data=dz, compression="gzip")
for key, value in atr.iteritems():
group.attrs[key] = value
group.attrs["UNIT"] = "m"
print "**************************************"
########### Output - Corrected Time Series ##########
if update_timeseries == "yes":
print "writing >>> " + outname
print "number of dates: " + str(len(dateList))
h5timeseriesDEMcor = h5py.File(outname, "w")
group = h5timeseriesDEMcor.create_group("timeseries")
for i in range(len(dateList)):
print dateList[i]
d = np.reshape(timeseries[i][:], [nrows, ncols], order="F")
dset = group.create_dataset(dateList[i], data=d, compression="gzip")
# for date in dateList:
# print date
# if not date in h5timeseriesDEMcor['timeseries']:
# d = np.reshape(timeseries[dateIndex[date]][:],[nrows,ncols],order='F')
# dset = group.create_dataset(date, data=d, compression='gzip')
for key, value in atr.iteritems():
group.attrs[key] = value
h5timeseriesDEMcor.close()
def main(argv):
try:
igramsFile = argv[0]
timeSeriesFile = argv[1]
except:
Usage()
sys.exit(1)
try:
tempCohFile = argv[2]
except:
tempCohFile = "temporal_coherence.h5"
########################################################
print "\n********** Temporal Coherence ****************"
print "load time series: " + timeSeriesFile
atr_ts = readfile.read_attributes(timeSeriesFile)
h5timeseries = h5py.File(timeSeriesFile)
dateList = h5timeseries["timeseries"].keys()
numDates = len(dateList)
print "number of epoch: " + str(numDates)
dateIndex = {}
for ni in range(numDates):
dateIndex[dateList[ni]] = ni
dset = h5timeseries["timeseries"].get(h5timeseries["timeseries"].keys()[0])
nrows, ncols = np.shape(dset)
timeseries = np.zeros((len(h5timeseries["timeseries"].keys()), np.shape(dset)[0] * np.shape(dset)[1]), np.float32)
for i in range(numDates):
date = dateList[i]
dset = h5timeseries["timeseries"].get(date)
d = dset[0 : dset.shape[0], 0 : dset.shape[1]]
timeseries[dateIndex[date]][:] = d.flatten(0)
ut.printProgress(i + 1, numDates, "loading:", date)
del d
h5timeseries.close()
lt, numpixels = np.shape(timeseries)
range2phase = -4 * np.pi / float(atr_ts["WAVELENGTH"])
timeseries = range2phase * timeseries
######################################################
print "load interferograms: " + igramsFile
h5igrams = h5py.File(igramsFile)
ifgramList = h5igrams["interferograms"].keys()
numIfgrams = len(ifgramList)
print "number of epochs: " + str(numIfgrams)
A, B = design_matrix(h5igrams)
p = -1 * np.ones([A.shape[0], 1])
Ap = np.hstack((p, A))
print "calculating temporal coherence ..."
# data = np.zeros((numIfgrams,numpixels),np.float32)
qq = np.zeros(numpixels) + 0j
for ni in range(numIfgrams):
## read interferogram
igram = ifgramList[ni]
dset = h5igrams["interferograms"][igram].get(igram)
data = dset[0 : dset.shape[0], 0 : dset.shape[1]]
data = data.flatten(0)
## calculate difference between observed and estimated data
## interferogram by interferogram, less memory, Yunjun - 2016.06.10
dataEst = np.dot(Ap[ni, :], timeseries)
dataDiff = data - dataEst
qq += np.exp(1j * dataDiff)
## progress bar
ut.printProgress(ni + 1, numIfgrams, "calculating:", igram)
del timeseries, data, dataEst, dataDiff
h5igrams.close()
# qq=np.absolute(np.sum(np.exp(1j*dataDiff),0))/numIfgrams
qq = np.absolute(qq) / numIfgrams
Temp_Coh = np.reshape(qq, [nrows, ncols])
##### write temporal coherence file ####################
print "writing >>> " + tempCohFile
h5TempCoh = h5py.File(tempCohFile, "w")
group = h5TempCoh.create_group("temporal_coherence")
dset = group.create_dataset(os.path.basename("temporal_coherence"), data=Temp_Coh, compression="gzip")
for key, value in atr_ts.iteritems():
group.attrs[key] = value
group.attrs["UNIT"] = "1"
h5TempCoh.close()