def run_tropospheric_delay_correction(self, step_name):
"""Correct tropospheric delays."""
geom_file = ut.check_loaded_dataset(self.workDir, print_msg=False)[2]
mask_file = 'maskTempCoh.h5'
fnames = self.get_timeseries_filename(self.template)[step_name]
in_file = fnames['input']
out_file = fnames['output']
if in_file != out_file:
poly_order = self.template['mintpy.troposphericDelay.polyOrder']
tropo_model = self.template['mintpy.troposphericDelay.weatherModel']
weather_dir = self.template['mintpy.troposphericDelay.weatherDir']
method = self.template['mintpy.troposphericDelay.method']
def get_dataset_size(fname):
atr = readfile.read_attribute(fname)
return (atr['LENGTH'], atr['WIDTH'])
# Phase/Elevation Ratio (Doin et al., 2009)
if method == 'height_correlation':
tropo_look = self.template['mintpy.troposphericDelay.looks']
tropo_min_cor = self.template['mintpy.troposphericDelay.minCorrelation']
scp_args = '{f} -g {g} -p {p} -m {m} -o {o} -l {l} -t {t}'.format(f=in_file,
g=geom_file,
p=poly_order,
m=mask_file,
o=out_file,
l=tropo_look,
t=tropo_min_cor)
print('tropospheric delay correction with height-correlation approach')
print('tropo_phase_elevation.py', scp_args)
if ut.run_or_skip(out_file=out_file, in_file=in_file) == 'run':
mintpy.tropo_phase_elevation.main(scp_args.split())
# Weather Re-analysis Data (Jolivet et al., 2011;2014)
elif method == 'pyaps':
scp_args = '-f {f} --model {m} -g {g} -w {w}'.format(f=in_file,
m=tropo_model,
g=geom_file,
w=weather_dir)
print('Atmospheric correction using Weather Re-analysis dataset (PyAPS, Jolivet et al., 2011)')
print('Weather Re-analysis dataset:', tropo_model)
tropo_file = './inputs/{}.h5'.format(tropo_model)
if ut.run_or_skip(out_file=out_file, in_file=[in_file, tropo_file]) == 'run':
if os.path.isfile(tropo_file) and get_dataset_size(tropo_file) == get_dataset_size(in_file):
scp_args = '{f} {t} -o {o} --force'.format(f=in_file, t=tropo_file, o=out_file)
print('--------------------------------------------')
print('Use existed tropospheric delay file: {}'.format(tropo_file))
print('diff.py', scp_args)
mintpy.diff.main(scp_args.split())
else:
if tropo_model in ['ERA5']:
from mintpy import tropo_pyaps3
print('tropo_pyaps3.py', scp_args)
tropo_pyaps3.main(scp_args.split())
else:
# opt 1 - using tropo_pyaps as python module and call its main function
# prefered, disabled for now to make it compatible with python2-pyaps
#print('tropo_pyaps.py', scp_args)
#from mintpy import tropo_pyaps
#tropo_pyaps.main(scp_args.split())
# opt 2 - using tropo_pyaps as executable script
# will be deprecated after python3-pyaps is fully funcational
cmd = 'tropo_pyaps.py '+scp_args
print(cmd)
status = subprocess.Popen(cmd, shell=True).wait()
else:
print('No tropospheric delay correction.')
return
def run_tropospheric_delay_correction(self, step_name):
"""Correct tropospheric delays."""
geom_file = ut.check_loaded_dataset(self.workDir, print_msg=False)[2]
mask_file = 'maskTempCoh.h5'
fnames = self.get_timeseries_filename(self.template)[step_name]
in_file = fnames['input']
out_file = fnames['output']
if in_file != out_file:
poly_order = self.template['mintpy.troposphericDelay.polyOrder']
tropo_model = self.template['mintpy.troposphericDelay.weatherModel']
weather_dir = self.template['mintpy.troposphericDelay.weatherDir']
method = self.template['mintpy.troposphericDelay.method']
def get_dataset_size(fname):
atr = readfile.read_attribute(fname)
return (atr['LENGTH'], atr['WIDTH'])
# Phase/Elevation Ratio (Doin et al., 2009)
if method == 'height_correlation':
tropo_look = self.template['mintpy.troposphericDelay.looks']
tropo_min_cor = self.template['mintpy.troposphericDelay.minCorrelation']
scp_args = '{f} -g {g} -p {p} -m {m} -o {o} -l {l} -t {t}'.format(f=in_file,
g=geom_file,
p=poly_order,
m=mask_file,
o=out_file,
l=tropo_look,
t=tropo_min_cor)
print('tropospheric delay correction with height-correlation approach')
print('tropo_phase_elevation.py', scp_args)
if ut.run_or_skip(out_file=out_file, in_file=in_file) == 'run':
mintpy.tropo_phase_elevation.main(scp_args.split())
# Weather Re-analysis Data (Jolivet et al., 2011;2014)
elif method == 'pyaps':
scp_args = '-f {f} --model {m} -g {g} -w {w}'.format(f=in_file,
m=tropo_model,
g=geom_file,
w=weather_dir)
print('Atmospheric correction using Weather Re-analysis dataset (PyAPS, Jolivet et al., 2011)')
print('Weather Re-analysis dataset:', tropo_model)
tropo_file = './inputs/{}.h5'.format(tropo_model)
if ut.run_or_skip(out_file=out_file, in_file=[in_file, tropo_file]) == 'run':
if os.path.isfile(tropo_file) and get_dataset_size(tropo_file) == get_dataset_size(in_file):
scp_args = '{f} {t} -o {o} --force'.format(f=in_file, t=tropo_file, o=out_file)
print('--------------------------------------------')
print('Use existed tropospheric delay file: {}'.format(tropo_file))
print('diff.py', scp_args)
mintpy.diff.main(scp_args.split())
else:
if tropo_model in ['ERA5']:
from mintpy import tropo_pyaps3
print('tropo_pyaps3.py', scp_args)
tropo_pyaps3.main(scp_args.split())
else:
# opt 1 - using tropo_pyaps as python module and call its main function
# prefered, disabled for now to make it compatible with python2-pyaps
#print('tropo_pyaps.py', scp_args)
#from mintpy import tropo_pyaps
#tropo_pyaps.main(scp_args.split())
# opt 2 - using tropo_pyaps as executable script
# will be deprecated after python3-pyaps is fully funcational
cmd = 'tropo_pyaps.py '+scp_args
print(cmd)
status = subprocess.Popen(cmd, shell=True).wait()
else:
print('No tropospheric delay correction.')
return
def run_tropospheric_delay_correction(self, step_name):
"""Correct tropospheric delays."""
geom_file = ut.check_loaded_dataset(self.workDir, print_msg=False)[2]
mask_file = 'maskTempCoh.h5'
fnames = self.get_timeseries_filename(self.template)[step_name]
in_file = fnames['input']
out_file = fnames['output']
if in_file != out_file:
poly_order = self.template['mintpy.troposphericDelay.polyOrder']
tropo_model = self.template['mintpy.troposphericDelay.weatherModel']
weather_dir = self.template['mintpy.troposphericDelay.weatherDir']
method = self.template['mintpy.troposphericDelay.method']
def get_dataset_size(fname):
atr = readfile.read_attribute(fname)
return (atr['LENGTH'], atr['WIDTH'])
# Phase/Elevation Ratio (Doin et al., 2009)
if method == 'height_correlation':
tropo_look = self.template['mintpy.troposphericDelay.looks']
tropo_min_cor = self.template['mintpy.troposphericDelay.minCorrelation']
iargs = [in_file,
'-g', geom_file,
'-p', poly_order,
'-m', mask_file,
'-o', out_file,
'-l', tropo_look,
'-t', tropo_min_cor]
print('tropospheric delay correction with height-correlation approach')
print('\ntropo_phase_elevation.py', ' '.join(iargs))
if ut.run_or_skip(out_file=out_file, in_file=in_file) == 'run':
mintpy.tropo_phase_elevation.main(iargs)
# Weather re-analysis data with iterative tropospheric decomposition (GACOS)
# Yu et al., 2017; 2018a; 2018b
elif method == 'gacos':
GACOS_dir = self.template['mintpy.troposphericDelay.gacosDir']
iargs = ['-f', in_file, '-g', geom_file, '-o', out_file, '--dir', GACOS_dir]
print('tropospheric delay correction with gacos approach')
print('\ntropo_gacos.py', ' '.join(iargs))
if ut.run_or_skip(out_file=out_file, in_file=in_file) == 'run':
mintpy.tropo_gacos.main(iargs)
# Weather Re-analysis Data (Jolivet et al., 2011;2014)
elif method == 'pyaps':
iargs = ['-f', in_file, '--model', tropo_model, '-g', geom_file, '-w', weather_dir]
print('Atmospheric correction using Weather Re-analysis dataset (PyAPS, Jolivet et al., 2011)')
print('Weather Re-analysis dataset:', tropo_model)
tropo_file = './inputs/{}.h5'.format(tropo_model)
if ut.run_or_skip(out_file=out_file, in_file=[in_file, tropo_file]) == 'run':
if os.path.isfile(tropo_file) and get_dataset_size(tropo_file) == get_dataset_size(in_file):
iargs = [in_file, tropo_file, '-o', out_file, '--force']
print('--------------------------------------------')
print('Use existed tropospheric delay file: {}'.format(tropo_file))
print('\ndiff.py', ' '.join(iargs))
mintpy.diff.main(iargs)
else:
if tropo_model in ['ERA5']:
from mintpy import tropo_pyaps3
print('\ntropo_pyaps3.py', ' '.join(iargs))
tropo_pyaps3.main(iargs)
else:
# opt 1 - using tropo_pyaps as python module and call its main function
# prefered, disabled for now to make it compatible with python2-pyaps
#print('tropo_pyaps.py', ' '.join(iargs))
#from mintpy import tropo_pyaps
#tropo_pyaps.main(iargs)
# opt 2 - using tropo_pyaps as executable script
# will be deprecated after python3-pyaps is fully funcational
cmd = 'tropo_pyaps.py '+' '.join(iargs)
print(cmd)
status = subprocess.Popen(cmd, shell=True).wait()
else:
print('No tropospheric delay correction.')
return
