def get_delay(grib_file, inps):
"""Get delay matrix using PyAPS for one acquisition
Inputs:
grib_file - strng, grib file path
atr - dict, including the following attributes:
dem_file - string, DEM file path
trop_model - string, Weather re-analysis data source
delay_type - string, comb/dry/wet
ref_y/x - string, reference pixel row/col number
inc_angle - np.array, 0/1/2 D
Output:
phs - 2D np.array, absolute tropospheric phase delay relative to ref_y/x
"""
if inps.geocoded:
aps = pa.PyAPS_geo(grib_file,
inps.dem_file,
grib=inps.trop_model,
verb=True,
Del=inps.delay_type)
else:
aps = pa.PyAPS_rdr(grib_file,
inps.dem_file,
grib=inps.trop_model,
verb=True,
Del=inps.delay_type)
phs = np.zeros((aps.ny, aps.nx), dtype=np.float32)
aps.getdelay(phs, inc=0.0)
# Get relative phase delay in space
phs -= phs[inps.ref_yx[0], inps.ref_yx[1]]
phs /= np.cos(inps.inc_angle) # Project into LOS direction
phs *= -1 # reverse the sign for consistency between different phase correction steps/methods
return phs
def get_delay(grib_file, atr, inps_dict):
'''Get delay matrix using PyAPS for one acquisition
Inputs:
grib_file - strng, grib file path
atr - dict, including the following attributes:
dem_file - string, DEM file path
grib_source - string, Weather re-analysis data source
delay_type - string, comb/dry/wet
ref_y/x - string, reference pixel row/col number
inc_angle - np.array, 0/1/2 D
Output:
phs - 2D np.array, absolute tropospheric phase delay relative to ref_y/x
'''
if 'X_FIRST' in atr.keys():
aps = pa.PyAPS_geo(grib_file, inps_dict['dem_file'], grib=inps_dict['grib_source'],\
verb=True, Del=inps_dict['delay_type'])
else:
aps = pa.PyAPS_rdr(grib_file, inps_dict['dem_file'], grib=inps_dict['grib_source'],\
verb=True, Del=inps_dict['delay_type'])
phs = np.zeros((aps.ny, aps.nx), dtype=np.float32)
aps.getdelay(phs, inc=0.0)
# Get relative phase delay in space
yref = int(atr['ref_y'])
xref = int(atr['ref_x'])
phs -= phs[yref, xref]
# project into LOS direction
phs /= np.cos(inps_dict['inc_angle'])
# reverse the sign for consistency between different phase correction steps/methods
phs *= -1
return phs
def get_delay(grib_file, inps):
"""Get delay matrix using PyAPS for one acquisition
Inputs:
grib_file - strng, grib file path
atr - dict, including the following attributes:
dem_file - string, DEM file path
trop_model - string, Weather re-analysis data source
delay_type - string, comb/dry/wet
ref_y/x - string, reference pixel row/col number
inc_angle - np.array, 0/1/2 D
Output:
phs - 2D np.array, absolute tropospheric phase delay relative to ref_y/x
"""
# initiate pyaps object
if inps.geocoded:
aps = pa.PyAPS_geo(grib_file,
inps.dem_file,
grib=inps.trop_model,
demtype=np.float32,
demfmt='RMG',
verb=False,
Del=inps.delay_type)
else:
aps = pa.PyAPS_rdr(grib_file,
inps.dem_file,
grib=inps.trop_model,
demtype=np.float32,
demfmt='RMG',
verb=False,
Del=inps.delay_type)
# estimate delay
phs = np.zeros((aps.ny, aps.nx), dtype=np.float32)
if not inps.geocoded and inps.lat_file is not None:
aps.getgeodelay(phs,
lat=inps.lat_file,
lon=inps.lon_file,
inc=inps.inc_angle_file)
else:
aps.getdelay(phs, inc=0.)
phs /= np.cos(inps.inc_angle * np.pi / 180.)
# Get relative phase delay in space
phs -= phs[inps.ref_yx[0], inps.ref_yx[1]]
phs *= -1 # reverse the sign for consistency between different phase correction steps/methods
return phs
def get_delay(grib_file, atr, inps_dict):
# Get delay matrix using PyAPS
if 'X_FIRST' in atr.keys():
aps = pa.PyAPS_geo(grib_file, inps_dict['dem_file'], grib=inps_dict['grib_source'],\
verb=True, Del=inps_dict['delay_type'])
else:
aps = pa.PyAPS_rdr(grib_file, inps_dict['dem_file'], grib=inps_dict['grib_source'],\
verb=True, Del=inps_dict['delay_type'])
phs = np.zeros((aps.ny, aps.nx))
aps.getdelay(phs)
# Get relative phase delay in space
yref = int(atr['ref_y'])
xref = int(atr['ref_x'])
phs -= phs[yref, xref]
# project into LOS direction
phs /= np.cos(inps_dict['incidence_angle'])
return phs
def get_delay(grib_file, atr, inps_dict):
# Get delay matrix using PyAPS
if 'X_FIRST' in atr.keys():
aps = pa.PyAPS_geo(grib_file, inps_dict['dem_file'], grib=inps_dict['grib_source'],\
verb=True, Del=inps_dict['delay_type'])
else:
aps = pa.PyAPS_rdr(grib_file, inps_dict['dem_file'], grib=inps_dict['grib_source'],\
verb=True, Del=inps_dict['delay_type'])
phs = np.zeros((aps.ny, aps.nx), dtype=np.float32)
aps.getdelay(phs, inc=0.0)
# Get relative phase delay in space
yref = int(atr['ref_y'])
xref = int(atr['ref_x'])
phs -= phs[yref, xref]
# project into LOS direction
phs /= np.cos(inps_dict['incidence_angle'])
# reverse the sign for consistency between different phase correction steps/methods
phs *= -1
return phs
plt.title('With latlon file')
plt.colorbar()
print 'Without Lat Lon files'
aps1.getdelay(phs1,inc=23.0,wvl=0.056)
aps2.getdelay(phs2,inc=23.0,wvl=0.056)
phs = phs2-phs1
plt.subplot(122)
plt.imshow(phs[10:600,10:350])
plt.title('Without latlon file')
plt.colorbar()
plt.show()
print 'Testing ECMWF in Geographic coordinates, with a FLT dem'
aps1 = pa.PyAPS_geo('ECMWF/ERA-Int_20030426_12.grb','Dem_crop.dem',grib='ECMWF')
aps2 = pa.PyAPS_geo('ECMWF/ERA-Int_20040526_12.grb','Dem_crop.dem',grib='ECMWF')
print 'With Lat Lon files'
phs1 = np.zeros((aps1.ny,aps1.nx))
phs2 = np.zeros((aps2.ny,aps2.nx))
aps1.getdelay(phs1,inc=23.0,wvl=0.056)
aps2.getdelay(phs2,inc=23.0,wvl=0.056)
del phs1
del phs2
print 'ECMWF OK'
print '------------------------------------------------'
print '------------------------------------------------'
def main(argv):
DelayType = 'comb'
try:
opts, args = getopt.getopt(argv, "f:d:s:h:D:i:")
except getopt.GetoptError:
Usage()
sys.exit(1)
for opt, arg in opts:
if opt == '-f': timeSeriesFile = arg
elif opt == '-d': demFile = arg
elif opt == '-s': atmSource = arg
elif opt == '-h': hr = arg
elif opt == '-D': DelayType = arg
elif opt == '-i': inc_angle = arg
try:
timeSeriesFile
demFile
except:
Usage()
sys.exit(1)
demFile = ut.check_variable_name(demFile)
demCoord = ut.radar_or_geo(demFile)
h5timeseries = h5py.File(timeSeriesFile)
yref = h5timeseries['timeseries'].attrs['ref_y']
xref = h5timeseries['timeseries'].attrs['ref_x']
###############################################################
#incidence angle to map the zenith delay to the slant delay
try:
inc_angle
except:
print '+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++'
print 'WARNING:'
print 'incedence angle is not specified >>>> Average look angle is used ... '
print 'For more precise results use input option -i to introduce the incidence angle file or average incodence angle'
print '++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++'
input_inc_angle = 'None'
wavelength = float(h5timeseries['timeseries'].attrs['WAVELENGTH'])
inc_angle1 = float(h5timeseries['timeseries'].attrs['LOOK_REF1'])
inc_angle2 = float(h5timeseries['timeseries'].attrs['LOOK_REF2'])
inc_angle = (inc_angle1 + inc_angle2) / 2.0
print '*******************************************************************************'
print 'Near Look Angle: ' + str(inc_angle1)
print 'Far Look Angle:' + str(inc_angle2)
print 'Average Look Angle (used in pyaps to calculate delay): ' + str(
inc_angle)
print 'Acquisition time is : ' + hr
print '*******************************************************************************'
inc_angle = str(inc_angle)
if os.path.isfile(inc_angle):
incidenceFile = inc_angle
h5incidence = h5py.File(incidenceFile, 'r')
iset = h5incidence['mask'].get('mask')
inc_angle = iset[0:iset.shape[0], 0:iset.shape[1]]
h5incidence.close()
else:
inc_angle = float(inc_angle)
print 'incidence angle = ' + str(inc_angle)
inc_angle = inc_angle * pi / 180.0
################################################################
dateList = h5timeseries['timeseries'].keys()
if atmSource in ['ecmwf', 'ECMWF']:
gribSource = 'ECMWF'
if not os.path.isdir('ECMWF'):
print 'making directory: ECMWF'
os.mkdir('ECMWF')
ecmwf_file = []
for d in dateList:
ecm = './ECMWF/ERA-Int_' + d + '_' + hr + '.grb'
ecmwf_file.append(ecm)
print[d]
if not os.path.isfile(ecm):
pa.ECMWFdload([d], hr, './ECMWF/')
else:
print ecm + ' already exists.'
elif atmSource in ['narr', 'NARR']:
gribSource = 'NARR'
if not os.path.isdir('NARR'):
print 'making directory: NARR'
os.mkdir('NARR')
ecmwf_file = []
for d in dateList:
ecm = './NARR/narr-a_221_' + d + '_' + hr + '00_000.grb'
ecmwf_file.append(ecm)
print[d]
if not os.path.isfile(ecm):
pa.NARRdload([d], hr, './NARR/')
else:
print ecm + ' already exists.'
elif atmSource in ['era', 'ERA']:
gribSource = 'ERA'
if not os.path.isdir('ERA'):
print 'making directory: ERA'
os.mkdir('ERA')
ecmwf_file = []
for d in dateList:
ecm = './ERA/ERA_' + d + '_' + hr + '.grb'
ecmwf_file.append(ecm)
print[d]
if not os.path.isfile(ecm):
pa.ERAdload([d], hr, './ERA/')
else:
print ecm + ' already exists.'
elif atmSource in ['merra', 'MERRA']:
gribSource = 'MERRA'
if not os.path.isdir('MERRA'):
print 'making directory: MERRA'
os.mkdir('MERRA')
ecmwf_file = []
for d in dateList:
ecm = './MERRA/merra-' + d + '-' + hr + '.hdf'
ecmwf_file.append(ecm)
print[d]
if not os.path.isfile(ecm):
pa.MERRAdload([d], hr, './MERRA/')
else:
print ecm + ' already exists.'
else:
Usage()
sys.exit(1)
print '*******************************************************************************'
print 'Calcualting delay for each epoch.'
h5phsName = atmSource + '.h5'
h5phs = h5py.File(h5phsName, 'w')
outName = timeSeriesFile.replace(
'.h5', '_') + atmSource + '.h5' #Yunjun, Feb 15, 2015
#outName=timeSeriesFile.replace('.h5','')+'_tropCorPyAPS.h5'
h5apsCor = h5py.File(outName, 'w')
group = h5apsCor.create_group('timeseries')
group_phs = h5phs.create_group('timeseries')
#if 'X_FIRST' in h5timeseries['timeseries'].attrs.keys():
# demCoord='geo'
# print 'The coordinate system is : Geo'
#else:
# demCoord='radar'
# print 'The coordinate system is : radar'
print ecmwf_file[0]
if demCoord == 'radar':
aps1 = pa.PyAPS_rdr(str(ecmwf_file[0]),
demFile,
grib=gribSource,
verb=True,
Del=DelayType)
else:
aps1 = pa.PyAPS_geo(str(ecmwf_file[0]),
demFile,
grib=gribSource,
verb=True,
Del=DelayType)
phs1 = zeros((aps1.ny, aps1.nx))
aps1.getdelay(phs1)
phs1 = (phs1 - phs1[yref, xref]) / cos(inc_angle)
dset = group.create_dataset(dateList[0],
data=phs1 - phs1,
compression='gzip')
for i in range(1, len(ecmwf_file)):
ecm = ecmwf_file[i]
print ecm
if demCoord == 'radar':
aps = pa.PyAPS_rdr(str(ecm),
demFile,
grib=gribSource,
verb=True,
Del=DelayType)
else:
aps = pa.PyAPS_geo(str(ecm),
demFile,
grib=gribSource,
verb=True,
Del=DelayType)
phs = zeros((aps.ny, aps.nx))
aps.getdelay(phs)
phs = (phs - phs[yref, xref]) / cos(inc_angle)
phs = phs - phs1
dset = group_phs.create_dataset(dateList[i],
data=phs,
compression='gzip')
dset1 = h5timeseries['timeseries'].get(dateList[i])
data1 = dset1[0:dset1.shape[0], 0:dset1.shape[1]]
dset = group.create_dataset(dateList[i],
data=data1 + phs,
compression='gzip')
for key, value in h5timeseries['timeseries'].attrs.iteritems():
group.attrs[key] = value
group_phs.attrs[key] = value
dset1 = h5timeseries['mask'].get('mask')
Mask = dset1[0:dset1.shape[0], 0:dset1.shape[1]]
group = h5apsCor.create_group('mask')
dset = group.create_dataset('mask', data=Mask, compression='gzip')
def download_atmosphereModel(inps): #EMRE
S, N, W, E = [val for val in inps.bbox.split()] #EMRE
start_year, start_month, start_day = [
int(val) for val in inps.start_date.split('-')
] #EMRE
end_year, end_month, end_day = [
int(val) for val in inps.end_date.split('-')
] #EMRE
start_date = date(start_year, start_month, start_day) #EMRE
end_date = date(end_year, end_month, end_day) #EMRE
d1 = start_date
d2 = end_date
dateList = []
# d1 = datetime.date(2002,1,1)
# d2 = datetime.date(2002,2,1)
diff = d2 - d1
day_step = 1 #EMRE
hr = '18'
for i in range(0, diff.days + 1, day_step):
dd = (d1 + datetime.timedelta(i)).isoformat()
dateList.append(dd.replace('-', ''))
# if atmSource in ['ecmwf','ECMWF']:
if inps.data_source in ['ecmwf', 'ECMWF']: #EMRE
gribSource = 'ECMWF'
if not os.path.isdir('ECMWF'):
print 'making directory: ECMWF'
os.mkdir('ECMWF')
ecmwf_file = []
for d in dateList:
ecm = './ECMWF/ERA-Int_' + d + '_' + hr + '.grb'
ecmwf_file.append(ecm)
print[d]
if not os.path.isfile(ecm):
pa.ECMWFdload([d], hr, './ECMWF/')
else:
print ecm + ' already exists.'
# elif atmSource in ['narr','NARR']:
elif inps in ['narr', 'NARR']: #EMRE
gribSource = 'NARR'
if not os.path.isdir('NARR'):
print 'making directory: NARR'
os.mkdir('NARR')
ecmwf_file = []
for d in dateList:
ecm = './NARR/narr-a_221_' + d + '_' + hr + '00_000.grb'
ecmwf_file.append(ecm)
print[d]
if not os.path.isfile(ecm):
pa.NARRdload([d], hr, './NARR/')
else:
print ecm + ' already exists.'
# elif atmSource in ['era','ERA']:
elif inps in ['era', 'ERA']:
gribSource = 'ERA'
if not os.path.isdir('ERA'):
print 'making directory: ERA'
os.mkdir('ERA')
ecmwf_file = []
for d in dateList:
ecm = './ERA/ERA_' + d + '_' + hr + '.grb'
ecmwf_file.append(ecm)
print[d]
if not os.path.isfile(ecm):
pa.ERAdload([d], hr, './ERA/')
else:
print ecm + ' already exists.'
# elif atmSource in ['merra','MERRA']:
elif inps in ['merra', 'MERRA']:
gribSource = 'MERRA'
if not os.path.isdir('MERRA'):
print 'making directory: MERRA'
os.mkdir('MERRA')
ecmwf_file = []
for d in dateList:
ecm = './MERRA/merra-' + d + '-' + hr + '.hdf'
ecmwf_file.append(ecm)
print[d]
if not os.path.isfile(ecm):
pa.MERRAdload([d], hr, './MERRA/')
else:
print ecm + ' already exists.'
else:
# Usage();
print 'FAILED' #EMRE
sys.exit(1)
print '*******************************************************************************'
print 'Calculating delay for each epoch.'
h5phs = h5py.File('aps.h5', 'w')
outName = 'ECMWF.h5'
#h5apsCor=h5py.File(outName,'w')
# group=h5apsCor.create_group('timeseries')
group_phs = h5phs.create_group('timeseries')
demCoord = 'geo'
print ecmwf_file[0]
#demCoord='radar'
if demCoord == 'radar':
aps1 = pa.PyAPS_rdr(str(ecmwf_file[0]),
demFile,
grib=gribSource,
verb=True,
Del=DelayType)
else:
aps1 = pa.PyAPS_geo(str(ecmwf_file[0]),
demFile,
grib=gribSource,
verb=True,
Del=DelayType)
phs1 = np.zeros((aps1.ny, aps1.nx))
print aps1.ny
print aps1.nx
# aps1.getdelay(phs1,inc=inc_angle,wvl=wavelength)
aps1.getdelay(phs1)
dset = group_phs.create_dataset(dateList[0], data=phs1, compression='gzip')
# phs1=(phs1 - phs1[yref,xref])*wavelength/(4*np.pi)
# dset = group.create_dataset(dateList[0], data= phs1- phs1, compression='gzip')
for i in range(1, len(ecmwf_file)):
ecm = ecmwf_file[i]
print ecm
if demCoord == 'radar':
aps = pa.PyAPS_rdr(str(ecm),
demFile,
grib=gribSource,
verb=True,
Del=DelayType)
else:
aps = pa.PyAPS_geo(str(ecm),
demFile,
grib=gribSource,
verb=True,
Del=DelayType)
phs = np.zeros((aps.ny, aps.nx))
# aps.getdelay(phs,inc=inc_angle,wvl=wavelength)
aps.getdelay(phs)
# phs=(phs - phs[yref,xref])*wavelength/(4*np.pi)
# phs=phs-phs1
dset = group_phs.create_dataset(dateList[i],
data=phs,
compression='gzip')
# dset1 = h5timeseries['timeseries'].get(dateList[i])
# data1 = dset1[0:dset1.shape[0],0:dset1.shape[1]]
# dset = group.create_dataset(dateList[i], data= data1+phs, compression='gzip')
for key, value in h5timeseries['timeseries'].attrs.iteritems():
# group.attrs[key] = value
group_phs.attrs[key] = value
aps2.getgeodelay(phs2, inc=23.0, wvl=0.056, lat='lat.flt', lon='lon.flt')
phs = phs2 - phs1
plt.subplot(122)
plt.imshow(phs[10:600, 10:350])
plt.title('MERRA')
plt.colorbar()
plt.show()
print 'Radar Coordinates OK'
print '------------------------------------------------'
print '------------------------------------------------'
print 'Testing ECMWF in GEO geometry, with a FLT dem'
aps1 = pa.PyAPS_geo('ECMWF/ERA-Int_20030426_12.grb',
'Dem_crop.dem',
grib='ECMWF',
verb=True)
aps2 = pa.PyAPS_geo('ECMWF/ERA-Int_20040526_12.grb',
'Dem_crop.dem',
grib='ECMWF',
verb=True)
print 'With Lat Lon files'
phs1 = np.zeros((aps1.ny, aps1.nx))
phs2 = np.zeros((aps2.ny, aps2.nx))
aps1.getdelay(phs1, inc=23.0, wvl=0.056)
aps2.getdelay(phs2, inc=23.0, wvl=0.056)
LLphs = phs2 - phs1
plt.subplot(121)
def estimateDelay(self):
'''Estimate the delay using PyAPS.'''
self.outfile = 'corrections_pyAPS_%s'%(self.model)
print('Processing master delay')
delay = np.zeros((self.length, self.width), dtype=np.float32)
######Processing in radar coordinates
if not self.geo:
try:
atmobj = pyaps.PyAPS_rdr(self.flist[0],self.hgt,grib=self.model,demfmt='HGT')
atmobj.getgeodelay(delay, lat=self.lat, lon=self.lon, inc=self.inc,wvl=self.wvl)
except Exception as e:
toContext(process,ErrorCodes['Master Delay Estimation Failed'],str(e))
print(e)
sys.exit(ErrorCodes['Master Delay Estimation Failed'])
else:
#######Processing in geo coordinates
try:
atmobj = pyaps.PyAPS_geo(self.flist[0], self.hgt, grib=self.model,demfmt='HGT')
atmobj.getdelay(delay, inc=self.inc,wvl=sel.wvl)
except Exception as e:
toContext(process,ErrorCodes['Master Delay Estimation Failed'],str(e))
print(e)
sys.exit(ErrorCodes['Master Delay Estimation Failed'])
del atmobj
if(np.isnan(np.sum(delay))):
print("pyAPSCorrect.py estimateDelay: found NaN. Aborting")
toContext(process,ErrorCodes['NaN Present'],"pyAPSCorrect.py estimateDelay: found NaN. Aborting")
sys.exit(ErrorCodes['NaN Present'])
print('Processing slave delay')
delay_slav = np.zeros((self.length, self.width), dtype=np.float32)
if not self.geo:
try:
atmobj = pyaps.PyAPS_rdr(self.flist[1],self.hgt,grib=self.model,demfmt='HGT')
atmobj.getgeodelay(delay_slav, lat=self.lat, lon=self.lon, inc=self.inc,wvl=self.wvl)
except Exception as e:
print(e)
toContext(process,ErrorCodes['Slave Delay Estimation Failed'],str(e))
sys.exit(ErrorCodes['Slave Delay Estimation Failed'])
else:
try:
atmobj = pyaps.PyAPS_geo(self.flist[1], self.hgt,grib=self.model,demfmt='HGT')
atmobj.getdelay(delay_slav, inc=self.inc,wvl=self.wvl)
except Exception as e:
toContext(process,ErrorCodes['Slave Delay Estimation Failed'],str(e))
print(e)
sys.exit(ErrorCodes['Slave Delay Estimation Failed'])
del atmobj
if(np.isnan(np.sum(delay_slav))):
print("pyAPSCorrect.py estimateDelay: found NaN. Aborting")
toContext(process,ErrorCodes['NaN Present'],"pyAPSCorrect.py estimateDelay: found NaN. Aborting")
sys.exit(ErrorCodes['NaN'])
delay -= delay_slav
del delay_slav
try:
#import pdb
#pdb.set_trace()
self.insar._insar.correctionsFilename = self.outfile+'.rdr'
delay.astype(np.float32).tofile(self.insar._insar.correctionsFilename)
ifImage = IF.createImage()
accessMode = 'read'
dataType = 'FLOAT'
ifImage.initImage(self.insar._insar.correctionsFilename,accessMode,self.width,dataType)
descr = 'Troposheric corrections'
ifImage.setImageType('sbi')
ifImage.addDescription(descr)
ifImage.renderHdr()
except Exception as e:
toContext(process,ErrorCodes['Write Error'],str(e))
print(e)
sys.exit(ErrorCodes['Write Error'])
cJ = np.complex64(1.0j)
delay = np.exp(cJ*(delay))
try:
delay.tofile(self.outfile+'.mph')
except Exception as e:
toContext(process,ErrorCodes['Write Error'],str(e))
print(e)
sys.exit(ErrorCodes['Write Error'])
#since some time this is the only stage executed dump the pickle
#if there are other stages they'll be overwritten
fp = open(self.pickle,'w')
cp.dump(self.insar,fp)
fp.close()
toContext(process,0,'pyAPSCorrections delay created')
