def main(argv):
inps = cmdLineParse()
#print '\n****************** mask *********************'
inps.file = ut.get_file_list(inps.file)
print('number of file to mask: ' + str(len(inps.file)))
print(inps.file)
# check outfile and parallel option
if inps.parallel:
num_cores, inps.parallel, Parallel, delayed = ut.check_parallel(
len(inps.file))
# masking
if len(inps.file) == 1:
mask_file(inps.file[0], inps.mask_file, inps.outfile, vars(inps))
elif inps.parallel:
#num_cores = min(multiprocessing.cpu_count(), len(inps.file))
#print 'parallel processing using %d cores ...'%(num_cores)
Parallel(n_jobs=num_cores)(
delayed(mask_file)(File, inps.mask_file, inps_dict=vars(inps))
for File in inps.file)
else:
for File in inps.file:
print('-------------------------------------------')
mask_file(File, inps.mask_file, inps_dict=vars(inps))
print('Done.')
return
def main(argv):
inps = cmdLineParse()
inps.file = ut.get_file_list(inps.file)
# check outfile and parallel option
if inps.parallel:
num_cores, inps.parallel, Parallel, delayed = ut.check_parallel(
len(inps.file))
# multilooking
if len(inps.file) == 1:
multilook_file(inps.file[0], inps.lks_y, inps.lks_x, inps.outfile)
elif inps.parallel:
#num_cores = min(multiprocessing.cpu_count(), len(inps.file))
#print 'parallel processing using %d cores ...'%(num_cores)
Parallel(n_jobs=num_cores)(
delayed(multilook_file)(file, inps.lks_y, inps.lks_x)
for file in inps.file)
else:
for File in inps.file:
print('-------------------------------------------')
multilook_file(File, inps.lks_y, inps.lks_x)
print('Done.')
return
def main(argv):
inps = cmdLineParse()
inps.file = ut.get_file_list(inps.file, abspath=True)
# Check input file type
ext = os.path.splitext(inps.file[0])[1]
if ext not in ['.unw', '.cor', '.int']:
print('No need to extract attributes for ROI_PAC ' + ext + ' file')
return
print('number of files: ' + str(len(inps.file)))
# check outfile and parallel option
if inps.parallel:
num_cores, inps.parallel, Parallel, delayed = ut.check_parallel(
len(inps.file))
if len(inps.file) == 1:
extract_attribute(inps.file[0])
elif inps.parallel:
Parallel(n_jobs=num_cores)(delayed(extract_attribute)(file)
for file in inps.file)
else:
for File in inps.file:
extract_attribute(File)
return
def main(argv):
inps = cmdLineParse()
inps.file = ut.get_file_list(inps.file)
print('number of files to geocode: ' + str(len(inps.file)))
print(inps.file)
print('interpolation method: ' + inps.method)
print('fill_value: ' + str(inps.fill_value))
# check outfile and parallel option
if inps.parallel:
num_cores, inps.parallel, Parallel, delayed = ut.check_parallel(
len(inps.file))
#####
if len(inps.file) == 1:
geocode_file_with_geo_lut(inps.file[0], inps.lookup_file, inps.method,
inps.fill_value, inps.outfile)
elif inps.parallel:
Parallel(n_jobs=num_cores)(delayed(geocode_file_with_geo_lut)\
(fname, inps.lookup_file, inps.method, inps.fill_value) for fname in inps.file)
else:
for fname in inps.file:
geocode_file_with_geo_lut(fname, inps.lookup_file, inps.method,
inps.fill_value)
print('Done.')
return
def subset_file_list(fileList, inps):
'''Subset file list'''
# check outfile and parallel option
if inps.parallel:
num_cores, inps.parallel, Parallel, delayed = ut.check_parallel(
len(fileList))
##### Subset files
if len(fileList) == 1:
subset_file(fileList[0], vars(inps), inps.outfile)
elif inps.parallel:
#num_cores = min(multiprocessing.cpu_count(), len(fileList))
#print 'parallel processing using %d cores ...'%(num_cores)
Parallel(n_jobs=num_cores)(delayed(subset_file)(file, vars(inps))
for file in fileList)
else:
for File in fileList:
print('----------------------------------------------------')
subset_file(File, vars(inps))
return
def main(argv):
inps = cmdLineParse()
inps.file = ut.get_file_list(inps.file, abspath=True)
print('number of files: ' + str(len(inps.file)))
# check outfile and parallel option
if inps.parallel:
num_cores, inps.parallel, Parallel, delayed = ut.check_parallel(
len(inps.file))
##### multiple datasets files
ext = os.path.splitext(inps.file[0])[1]
if ext in ['.unw', '.cor', '.int']:
if len(inps.file) == 1:
extract_attribute_interferogram(inps.file[0])
elif inps.parallel:
Parallel(n_jobs=num_cores)(
delayed(extract_attribute_interferogram)(file)
for file in inps.file)
else:
for File in inps.file:
extract_attribute_interferogram(File)
##### Single dataset files
elif ext in ['.dem']:
for File in inps.file:
atr_file = extract_attribute_dem_geo(File)
elif ext in ['.hgt_sim']:
for File in inps.file:
atr_file = extract_attribute_dem_radar(File)
elif ext in ['.UTM_TO_RDC']:
for File in inps.file:
atr_file = extract_attribute_lookup_table(File)
else:
print('No need to extract attributes for Gamma ' + ext + ' file')
print('Done.')
return
def main(argv):
inps = cmdLineParse()
inps.file = ut.get_file_list(inps.file)
atr = readfile.read_attribute(inps.file[0])
length = int(atr['FILE_LENGTH'])
width = int(atr['WIDTH'])
if inps.reset:
print(
'----------------------------------------------------------------------------'
)
for file in inps.file:
remove_reference_pixel(file)
return
##### Check Input Coordinates
# Read ref_y/x/lat/lon from reference/template
# priority: Direct Input > Reference File > Template File
if inps.template_file:
print('reading reference info from template: ' + inps.template_file)
inps = read_seed_template2inps(inps.template_file, inps)
if inps.reference_file:
print('reading reference info from reference: ' + inps.reference_file)
inps = read_seed_reference2inps(inps.reference_file, inps)
## Do not use ref_lat/lon input for file in radar-coord
#if not 'X_FIRST' in atr.keys() and (inps.ref_lat or inps.ref_lon):
# print 'Lat/lon reference input is disabled for file in radar coord.'
# inps.ref_lat = None
# inps.ref_lon = None
# Convert ref_lat/lon to ref_y/x
if inps.ref_lat and inps.ref_lon:
if 'X_FIRST' in list(atr.keys()):
inps.ref_y = subset.coord_geo2radar(inps.ref_lat, atr, 'lat')
inps.ref_x = subset.coord_geo2radar(inps.ref_lon, atr, 'lon')
else:
# Convert lat/lon to az/rg for radar coord file using geomap*.trans file
inps.ref_y, inps.ref_x = ut.glob2radar(np.array(inps.ref_lat), np.array(inps.ref_lon),\
inps.trans_file, atr)[0:2]
print('Input reference point in lat/lon: ' +
str([inps.ref_lat, inps.ref_lon]))
print('Input reference point in y/x : ' + str([inps.ref_y, inps.ref_x]))
# Do not use ref_y/x outside of data coverage
if (inps.ref_y and inps.ref_x
and not (0 <= inps.ref_y <= length and 0 <= inps.ref_x <= width)):
inps.ref_y = None
inps.ref_x = None
print('WARNING: input reference point is OUT of data coverage!')
print('Continue with other method to select reference point.')
# Do not use ref_y/x in masked out area
if inps.ref_y and inps.ref_x and inps.mask_file:
print('mask: ' + inps.mask_file)
mask = readfile.read(inps.mask_file)[0]
if mask[inps.ref_y, inps.ref_x] == 0:
inps.ref_y = None
inps.ref_x = None
print('WARNING: input reference point is in masked OUT area!')
print('Continue with other method to select reference point.')
##### Select method
if inps.ref_y and inps.ref_x:
inps.method = 'input-coord'
elif inps.coherence_file:
if os.path.isfile(inps.coherence_file):
inps.method = 'max-coherence'
else:
inps.coherence_file = None
if inps.method == 'manual':
inps.parallel = False
print('Parallel processing is disabled for manual seeding method.')
##### Seeding file by file
# check outfile and parallel option
if inps.parallel:
num_cores, inps.parallel, Parallel, delayed = ut.check_parallel(
len(inps.file))
if len(inps.file) == 1:
seed_file_inps(inps.file[0], inps, inps.outfile)
elif inps.parallel:
#num_cores = min(multiprocessing.cpu_count(), len(inps.file))
#print 'parallel processing using %d cores ...'%(num_cores)
Parallel(n_jobs=num_cores)(delayed(seed_file_inps)(file, inps)
for file in inps.file)
else:
for File in inps.file:
seed_file_inps(File, inps)
print('Done.')
return
def main(argv):
inps = cmdLineParse()
inps.file = ut.get_file_list(inps.file)
print('input file(s): '+str(len(inps.file)))
print(inps.file)
#print '\n*************** Phase Ramp Removal ***********************'
atr = readfile.read_attribute(inps.file[0])
length = int(atr['FILE_LENGTH'])
width = int(atr['WIDTH'])
# Read mask file if inputed
if inps.mask_file == 'no': inps.mask_file = None
if inps.mask_file:
try:
mask_atr = readfile.read_attribute(inps.mask_file)
except:
print('Can not open mask file: '+inps.mask_file)
inps.mask_file = None
# Update mask for multiple surfaces
if inps.ysub:
# Read mask
if not inps.mask_file:
Mask_temp = readfile.read(inps.mask_file)[0]
Mask = np.zeros((length, width), dtype=np.float32)
Mask[Mask_temp!=0] = 1
else:
Mask = np.ones((length, width))
# Update mask for multiple surface from inps.ysub
mask_multiSurface = np.zeros((length,width), dtype=np.float32)
surfNum = len(inps.ysub)/2
if surfNum == 1:
mask_multiSurface = Mask
else:
i = 0
mask_multiSurface[inps.ysub[2*i]:inps.ysub[2*i+1],:] = Mask[inps.ysub[2*i]:inps.ysub[2*i+1],:]
for i in range(1,surfNum):
if inps.ysub[2*i] < inps.ysub[2*i-1]:
mask_multiSurface[inps.ysub[2*i]:inps.ysub[2*i-1],:] += Mask[inps.ysub[2*i]:inps.ysub[2*i-1],:]*(i+1)
mask_multiSurface[inps.ysub[2*i]:inps.ysub[2*i-1],:] /= 2
mask_multiSurface[inps.ysub[2*i-1]:inps.ysub[2*i+1],:] = Mask[inps.ysub[2*i-1]:inps.ysub[2*i+1],:]*(i+1)
else:
mask_multiSurface[inps.ysub[2*i]:inps.ysub[2*i+1],:] = Mask[inps.ysub[2*i]:inps.ysub[2*i+1],:]*(i+1)
# Write updated mask for multiple surfaces into file
outFile = 'mask_'+str(surfNum)+inps.surface_type+'.h5'
atr['FILE_TYPE'] = 'mask'
writefile.write(mask_multiSurface, atr, outFile)
print('saved mask to '+outFile)
############################## Removing Phase Ramp #######################################
# check outfile and parallel option
if inps.parallel:
num_cores, inps.parallel, Parallel, delayed = ut.check_parallel(len(inps.file))
if len(inps.file) == 1:
rm.remove_surface(inps.file[0], inps.surface_type, inps.mask_file, inps.outfile, inps.ysub)
elif inps.parallel:
#num_cores = min(multiprocessing.cpu_count(), len(inps.file))
#print 'parallel processing using %d cores ...'%(num_cores)
Parallel(n_jobs=num_cores)(delayed(rm.remove_surface)(file, inps.surface_type, inps.mask_file, ysub=inps.ysub)\
for file in inps.file)
else:
for File in inps.file:
print('------------------------------------------')
rm.remove_surface(File, inps.surface_type, inps.mask_file, ysub=inps.ysub)
print('Done.')
return