def grdFrameImport(inFile, outFile, logFile, polar='VV,VH,HH,HV'):
'''
Import a single S1 GRD acquisition
:param inFile: original file (zip or manifest) or swath assembled product
:param outFile:
:return:
'''
print(' INFO: Importing {} by applying precise orbit file and'
' removing thermal noise'.format(os.path.basename(inFile)))
graph = ('/'.join(('graphs', 'S1_GRD2ARD', '1_AO_TNR.xml')))
graph = pkg_resources.resource_filename(package, graph)
frameImportCmd = '{} {} -x -q {} -Pinput={} -Ppolar={} \
-Poutput={}'.format(gpt_file, graph, os.cpu_count(),
inFile, polar, outFile)
rc = helpers.runCmd(frameImportCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Frame import exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(102)
def sliceAssembly(fileList, outFile, logFile, polar='VV,VH,HH,HV'):
"""
This function assembles consecutive frames acquired at the same date.
Can be either GRD or SLC products
:param fileList: a list of the frames to be assembled
:param outFile: the assembled file
:return:
"""
# get gpt file
gptFile = h.getGPT()
print(" INFO: Assembling consecutive frames:")
sliceAssemblyCmd = '{} SliceAssembly -x -q {} -PselectedPolarisations={} \
-t {} {}'.format(gptFile, os.cpu_count(), polar,
outFile, fileList)
# run command
rc = h.runCmd(sliceAssemblyCmd, logFile)
if rc == 0:
print(' INFO: Succesfully assembled products')
else:
print(' ERROR: Slice Assembly exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(111)
def slcCoherence(inFile, outFile, logFile):
"""
This is a wrapper of S1TBX for the creation of interferometric coherence
It includes Coherence (10x3 window) and deburst of the input product.
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD', 'S1_SLC_Coh_Deb.xml')
print(' INFO: Coherence estimation')
cohCmd = '{} {} -x -q {} -Pinput={} -Poutput={}' \
.format(gptFile, graph, 2 * os.cpu_count(), inFile, outFile)
rc = h.runCmd(cohCmd, logFile)
if rc == 0:
print(' INFO: Succesfully created Coherence product')
else:
print(' ERROR: Coherence exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(121)
def texture(inFile, outFile, logFile):
"""
This is a wrapper of S1TBX for the creation of the GLCM texture layers.
Input should be an GTC or RTC product,
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD', 'S1_SLC_Tex.xml')
print(" INFO: Calculating texture measures")
texCmd = '{} {} -x -q {} -Pinput={} -Poutput={}' \
.format(gptFile, graph, 2 * os.cpu_count(), inFile, outFile)
rc = h.runCmd(texCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Geocoding exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(123)
def slcLSMap(inFile, outFile, logFile, resol=20):
"""
This function is a wrapper function of the SNAP toolbox for the creation of
a layover/shadow mask.
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD', 'S1_SLC_LS_TC.xml')
print(" INFO: Compute Layover/Shadow mask")
lsCmd = '{} {} -x -q {} -Pinput={} -Presol={} -Poutput={}' \
.format(gptFile, graph, 2 * os.cpu_count(), inFile, resol, outFile)
rc = h.runCmd(lsCmd, logFile)
if rc == 0:
print(' INFO: Succesfully created Layover/Shadow mask')
else:
print(' ERROR: Layover/Shadow mask creation exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(121)
def slcCoregESD(fileList, outFile, logFile):
"""
This function co-registers a set of Sentinel-1 images (or subswaths)
based on the backgeocoding and the Enhanced-Spectral-Diversity (ESD).
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD', 'S1_SLC_BGD_ESD.xml')
print(" INFO: Co-registering with Enhanced Spectral Diversity")
coregCmd = '{} {} -x -q {} -Pfilelist={} -Poutput={}' \
.format(gptFile, graph, 2 * os.cpu_count(), fileList, outFile)
rc = h.runCmd(coregCmd, logFile)
if rc == 0:
print(' INFO: Succesfully coregistered product')
else:
print(' ERROR: Co-registration exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(112)
def slcFrameImport(inFile, outPrefix, logFile, polar='VV,VH,HH,HV'):
"""
This function imports a raw SLC file,
applies the precise orbit file (if available)
and splits the subswaths into separate files for further processing.
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD', 'S1_SLC_AO_Split.xml')
print(' INFO: Importing {} by applying the precise orbit file and'
' split into the subswaths'.format(os.path.basename(inFile)))
frameImportCmd = '{} {} -x -q {} -Pinput={} -Ppolar={} -Piw1={}_iw1 \
-Piw2={}_iw2 -Piw3={}_iw3' \
.format(gptFile, graph, os.cpu_count(), inFile, polar,
outPrefix, outPrefix, outPrefix)
rc = h.runCmd(frameImportCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Frame import exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(112)
def grdLSMap(inFile, lsFile, logFile, resol):
'''
'''
# get gpt file
gpt_file = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
print(" INFO: Creating the Layover/Shadow mask")
# get path to workflow xml
graph = opj(rootPath, 'graphs', 'S1_GRD2ARD', '3_LSmap.xml')
# construct command string
lsCmd = '{} {} -x -q {} -Pinput=\'{}\' -Presol={} \
-Poutput=\'{}\''.format(gpt_file, graph, 2 * os.cpu_count(),
inFile, resol, lsFile)
# run command
rc = h.runCmd(lsCmd, logFile)
# handle errors and logs
if rc == 0:
print(' INFO: Succesfully create a layover shadow mask')
else:
print(' ERROR: Lazover&Shadow Mask creation exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(112)
def grdFrameImport(inFile, outFile, logFile, polar='VV,VH,HH,HV'):
'''
Import a single S1 GRD acquisition
:param inFile: original file (zip or manifest) or swath assembled product
:param outFile:
:return:
'''
print(' INFO: Importing {} by applying precise orbit file and'
' removing thermal noise'.format(os.path.basename(inFile)))
# get gpt file
gpt_file = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
graph = opj(rootPath, 'graphs', 'S1_GRD2ARD', '1_AO_TNR.xml')
# construct command
frameImportCmd = '{} {} -x -q {} -Pinput=\'{}\' -Ppolar={} \
-Poutput=\'{}\''.format(gpt_file, graph, os.cpu_count(),
inFile, polar, outFile)
# run command
rc = h.runCmd(frameImportCmd, logFile)
# handle errors and logs
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Frame import exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(102)
def grdTC(inFile, outFile, logFile, resol):
'''
'''
# get gpt file
gpt_file = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
print(" INFO: Geocoding the calibrated product")
# calculate the multi-look factor
mlFactor = int(int(resol) / 10)
graph = opj(rootPath, 'graphs', 'S1_GRD2ARD', '3_ML_TC.xml')
# construct command string
geocodeCmd = '{} {} -x -q {} -Pinput=\'{}\' -Presol={} -Pml={} \
-Poutput=\'{}\''.format(gpt_file, graph, 2 * os.cpu_count(),
inFile, resol, mlFactor, outFile)
# run command
rc = h.runCmd(geocodeCmd, logFile)
# handle errors and logs
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Frame import exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(112)
def slcTC(inFile, outFile, logFile, resolution=20):
"""
This is a wrapper of S1TBX for the creation of a multi-looked, terrain-corrected product.
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
#rootPath = imp.find_module('ost')[1]
#graph = opj(rootPath, 'graphs', 'S1_SLC2ARD', 'S1_SLC_ML_TC.xml')
print(" INFO: Geocoding input scene")
#tcCmd = '{} {} -x -q {} -Pinput={} -Presol={} -Poutput={}' \
# .format(gptFile, SLC_tc_xml, 2 * os.cpu_count(),
# inFile, resolution, outFile)
tcCmd = '{} Terrain-Correction -x -q {} \
-PdemResamplingMethod=\'BILINEAR_INTERPOLATION\' \
-PimgResamplingMethod=\'BILINEAR_INTERPOLATION\' \
-PnodataValueAtSea=\'false\' \
-PpixelSpacingInMeter=\'{}\' \
-t {} {}' \
.format(gptFile, 2 * os.cpu_count(), resolution, outFile, inFile)
rc = h.runCmd(tcCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Geocoding exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(122)
def slcHalpha(inFile, outFile, logFile):
"""
This is a wrapper of S1TBX for the creation of the H-alpha dual-pol decomposition.
Input should be a frame imported product. Processing includes the deburst
and Polarimetric Speckle Filtering (Improved Lee Sigma) and the H-alpha dual-pol decomposition.
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD', 'S1_SLC_Deb_Halpha.xml')
print(" INFO: Calculating the H-alpha dual polarisation")
alphaCmd = '{} {} -x -q {} -Pinput={} -Poutput={}' \
.format(gptFile, graph, 2 * os.cpu_count(), inFile, outFile)
rc = h.runCmd(alphaCmd, logFile)
if rc == 0:
print(' INFO: Succesfully created H/Alpha product')
else:
print(' ERROR: H/Alpha exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(121)
def grdSpkFlt(inFile, outFile, logFile):
print(" INFO: Applying the Lee-Sigma Speckle Filter")
spkCmd = '{} Speckle-Filter -x -q {} -PestimateENL=true \
-t {} {}'.format(gpt_file, 2 * os.cpu_count(), outFile, inFile)
rc = helpers.runCmd(spkCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Speckle Filtering exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(111)
def grdBackscatter(inFile, outFile, logFile, prType='GTCgamma'):
'''
This function is a wrapper for the calibration of Sentinel-1
GRD backscatter data. 3 different calibration modes are supported.
- Radiometrically terrain corrected Gamma nought (RTC)
- ellipsoid based Gamma nought (GTCgamma)
- Sigma nought (GTCsigma).
:param inFile: an imported Sentinel-1 file
:param outFile: the calibrated file
:param prType: the product type (RTC, GTCgamma or GTCsigma)
:return:
'''
# get gpt file
gpt_file = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
if prType == 'RTC':
print(' INFO: Calibrating the product to a RTC product.')
graph = opj(rootPath, 'graphs', 'S1_GRD2ARD', '2_CalBeta_TF.xml')
elif prType == 'GTCgamma':
print(' INFO: Calibrating the product to a GTC product (Gamma0).')
graph = opj(rootPath, 'graphs', 'S1_GRD2ARD', '2_CalGamma.xml')
elif prType == 'GTCsigma':
print(' INFO: Calibrating the product to a GTC product (Sigma0).')
graph = opj(rootPath, 'graphs', 'S1_GRD2ARD', '2_CalSigma.xml')
else:
print(' ERROR: Wrong product type selected.')
exit
# create system command
#graph = pkg_resources.resource_filename(package, graph)
# construct command sring
calibrationCmd = '{} {} -x -q {} -Pinput=\'{}\' \
-Poutput=\'{}\''.format(gpt_file, graph,
2 * os.cpu_count(), inFile,
outFile)
# run command
rc = h.runCmd(calibrationCmd, logFile)
# handle errors and logs
if rc == 0:
print(' INFO: Succesfully calibrated product')
else:
print(' ERROR: Backscatter calibration exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(103)
def grdSubsetRegion(inFile, outFile, logFile, region):
gpt_file = '/usr/bin/gpt'
region = ','.join([str(int(x)) for x in region])
# extract window from scene
subsetCmd = '{} Subset -x -q {} -Pregion={} -t {}\
{}'.format(gpt_file, os.cpu_count(), region, outFile, inFile)
rc = helpers.runCmd(subsetCmd, logFile)
rc = 0
if rc == 0:
print(' INFO: Succesfully subsetted product')
else:
print(' ERROR: Subsetting exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(107)
def grdSubsetGeoRegion(inFile, outFile, logFile, geoRegion):
# get Snap's gpt file
gpt_file = h.getGPT()
# extract window from scene
subsetCmd = '{} Subset -x -q {} -Ssource=\'{}\' -t \'{}\' -PcopyMetadata=true \
-PgeoRegion=\'{}\''.format(gpt_file, os.cpu_count(), inFile,
outFile, geoRegion)
rc = h.runCmd(subsetCmd, logFile)
if rc == 0:
print(' INFO: Succesfully subsetted product')
else:
print(' ERROR: Subsetting exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(107)
def grdSubsetRegion(inFile, outFile, logFile, region):
# get Snap's gpt file
gpt_file = h.getGPT()
region = ','.join([str(int(x)) for x in region])
# extract window from scene
subsetCmd = '{} Subset -x -q {} -Pregion={} -t \'{}\'\
\'{}\''.format(gpt_file, os.cpu_count(), region, outFile,
inFile)
rc = h.runCmd(subsetCmd, logFile)
if rc == 0:
print(' INFO: Succesfully subsetted product')
else:
print(' ERROR: Subsetting exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(107)
def grdLSMap(inFile, lsFile, logFile, resol):
'''
'''
print(" INFO: Creating the Layover/Shadow mask")
graph = ('/'.join(('graphs', 'S1_GRD2ARD', '3_LSmap.xml')))
graph = pkg_resources.resource_filename(package, graph)
lsCmd = '{} {} -x -q {} -Pinput={} -Presol={} \
-Poutput={}'.format(gpt_file, graph, 2 * os.cpu_count(), inFile,
resol, lsFile)
rc = helpers.runCmd(lsCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Lazover&Shadow Mask creation exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(112)
def slcTerrainFlattening(inFile, outFile, logFile, reGrid=True):
# get gpt file
gptFile = h.getGPT()
print(
' INFO: Correcting for the illumination along slopes (Terrain Flattening).'
)
tfCmd = '{} Terrain-Flattening -x -q {} -PreGridMethod={} \
-PadditionalOverlap=0.2 -PoversamplingMultiple=1.5 -t {} {}' \
.format(gptFile, 2 * os.cpu_count(), reGrid, outFile, inFile)
rc = h.runCmd(tfCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Terrain Flattening exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(121)
def grdSpkFlt(inFile, outFile, logFile):
# get gpt file
gpt_file = h.getGPT()
print(" INFO: Applying the Lee-Sigma Speckle Filter")
# contrcut command string
spkCmd = '{} Speckle-Filter -x -q {} -PestimateENL=true \
-t \'{}\' \'{}\''.format(gpt_file, 2 * os.cpu_count(), outFile,
inFile)
# run command
rc = h.runCmd(spkCmd, logFile)
# hadle errors and logs
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Speckle Filtering exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(111)
def grdBackscatter(inFile, outFile, logFile, prType='GTCgamma'):
'''
This function is a wrapper for the calibration of Sentinel-1
GRD backscatter data. 3 different calibration modes are supported.
- Radiometrically terrain corrected Gamma nought (RTC)
- ellipsoid based Gamma nought (GTCgamma)
- Sigma nought (GTCsigma).
:param inFile: an imported Sentinel-1 file
:param outFile: the calibrated file
:param prType: the product type (RTC, GTCgamma or GTCsigma)
:return:
'''
if prType == 'RTC':
print(' INFO: Calibrating the product to a RTC product.')
graph = ('/'.join(('graphs', 'S1_GRD2ARD', '2_CalBeta_TF.xml')))
elif prType == 'GTCgamma':
print(' INFO: Calibrating the product to a GTC product (Gamma0).')
graph = ('/'.join(('graphs', 'S1_GRD2ARD', '2_CalGamma.xml')))
elif prType == 'GTCsigma':
print(' INFO: Calibrating the product to a GTC product (Sigma0).')
graph = ('/'.join(('graphs', 'S1_GRD2ARD', '2_CalSigma.xml')))
else:
print(' ERROR: Wrong product type selected.')
exit
# create system command
graph = pkg_resources.resource_filename(package, graph)
calibrationCmd = '{} {} -x -q {} -Pinput={} \
-Poutput={}'.format(gpt_file, graph, 2 * os.cpu_count(),
inFile, outFile)
rc = helpers.runCmd(calibrationCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Backscatter calibration exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(103)
def slcBackscatter(inFile, outFile, logFile, prType='GTCgamma'):
"""
This function is a wrapper function of the SNAP toolbox for the creation of
radiometrically terrain corrected product.
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
if prType == 'RTC':
print(' INFO: Calibrating the product to a RTC product.')
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD',
'S1_SLC_TNR_Calbeta_Deb.xml')
elif prType == 'GTCgamma':
print(' INFO: Calibrating the product to a GTC product (Gamma0).')
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD',
'S1_SLC_TNR_CalGamma_Deb.xml')
elif prType == 'GTCsigma':
print(' INFO: Calibrating the product to a GTC product (Sigma0).')
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD',
'S1_SLC_TNR_CalSigma_Deb.xml')
else:
print(' ERROR: Wrong product type selected.')
exit
print(" INFO: Removing thermal noise, calibrating and debursting")
calCmd = '{} {} -x -q {} -Pinput={} -Poutput={}' \
.format(gptFile, graph, 2 * os.cpu_count(), inFile, outFile)
rc = h.runCmd(calCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Frame import exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(121)
def slcBurstImport(inFile,
outPrefix,
logFile,
swath,
burst,
polar='VV,VH,HH,HV'):
"""
This function imports a raw SLC file,
applies the precise orbit file (if available)
and splits the subswaths into separate files for further processing.
:param
:param
:return
"""
# get gpt file
gptFile = h.getGPT()
# get path to graph
rootPath = imp.find_module('ost')[1]
graph = opj(rootPath, 'graphs', 'S1_SLC2ARD', 'S1_SLC_BurstSplit_AO.xml')
print(' INFO: Importing Burst {} from Swath {}'
' from scene {}'.format(burst, swath, os.path.basename(inFile)))
burstImportCmd = '{} {} -x -q {} -Pinput={} -Ppolar={} -Pswath={}\
-Pburst={} -Poutput={}' \
.format(gptFile, graph, os.cpu_count(), inFile, polar, swath,
burst, outPrefix)
rc = h.runCmd(burstImportCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Frame import exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(119)
def grdTC(inFile, outFile, logFile, resol):
'''
'''
print(" INFO: Geocoding the calibrated product")
# calculate the multi-look factor
mlFactor = int(int(resol) / 10)
graph = ('/'.join(('graphs', 'S1_GRD2ARD', '3_ML_TC.xml')))
graph = pkg_resources.resource_filename(package, graph)
geocodeCmd = '{} {} -x -q {} -Pinput={} -Presol={} -Pml={} \
-Poutput={}'.format(gpt_file, graph, 2 * os.cpu_count(),
inFile, resol, mlFactor, outFile)
rc = helpers.runCmd(geocodeCmd, logFile)
if rc == 0:
print(' INFO: Succesfully imported product')
else:
print(' ERROR: Frame import exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(112)
def mtSpeckle(inStack, outStack, logFile):
"""
:param inStack:
:param outStack:
:return:
"""
graph = ('/'.join(('graphs', 'S1_TS', '2_MT_Speckle.xml')))
graph = pkg_resources.resource_filename(package, graph)
print(" INFO: Applying the multi-temporal speckle-filtering")
mtSpkFltCmd = '{} {} -x -q {} -Pinput={} \
-Poutput={}'.format(gpt_file, graph, os.cpu_count(),
inStack, outStack)
rc = helpers.runCmd(mtSpkFltCmd, logFile)
if rc == 0:
print(' INFO: Succesfully applied multi-temporal speckle filtering')
else:
print(' ERROR: Multi-temporal speckle filtering exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(202)
def createStackPol(fileList, polarisation, outStack, logFile, wkt=None):
'''
:param fileList: list of single Files (space separated)
:param outFile: the stack that is generated
:return:
'''
if wkt is None:
graph = ('/'.join(('graphs', 'S1_TS', '1_BS_Stacking.xml')))
graph = pkg_resources.resource_filename(package, graph)
print(" INFO: Creating multi-temporal stack of images")
stackCmd = '{} {} -x -q {} -Pfilelist={} -Ppol={} \
-Poutput={}'.format(gpt_file, graph, os.cpu_count(), fileList,
polarisation, outStack)
else:
# does not work with gpt at the moment
graph = ('/'.join(('graphs', 'S1_TS', '1_BS_Stacking_Subset.xml')))
graph = pkg_resources.resource_filename(package, graph)
print(" INFO: Creating multi-temporal stack of images")
stackCmd = '{} {} -x -q {} -Pfilelist={} -Ppol={} \
-Pwkt=\'{}\' -Poutput={}'.format(gpt_file, graph,
os.cpu_count(), fileList,
polarisation, wkt, outStack)
#print(stackCmd)
rc = helpers.runCmd(stackCmd, logFile)
if rc == 0:
print(' INFO: Succesfully created multi-temporal stack')
else:
print(' ERROR: Stack creation exited with an error.'
' See {} for Snap Error output'.format(logFile))
sys.exit(201)
def sliceAssembly(fileList, outFile, logFile, polar='VV,VH,HH,HV'):
'''
This function assembles consecutive frames acquired at the same date.
Can be either GRD or SLC products
:param fileList: a list of Sentinel-1 product slices to be assembled
:param outFile: the assembled file
:return:
'''
print(" INFO: Assembling consecutive frames:")
#print([file for file in os.path.basename(fileList)])
sliceAssemblyCmd = '{} SliceAssembly -x -q {} -PselectedPolarisations={} \
-t {} {}'.format(gpt_file, os.cpu_count(), polar,
outFile, fileList)
rc = helpers.runCmd(sliceAssemblyCmd, logFile)
if rc == 0:
print(' INFO: Succesfully assembled products')
else:
print(' ERROR: Slice Assembly exited with an error. \
See {} for Snap Error output'.format(logFile))
sys.exit(101)
