Source code for pyroSAR.snap.util

###############################################################################
# Convenience functions for SAR image batch processing with ESA SNAP

# Copyright (c) 2016-2021, the pyroSAR Developers.

# This file is part of the pyroSAR Project. It is subject to the
# license terms in the LICENSE.txt file found in the top-level
# directory of this distribution and at
# https://github.com/johntruckenbrodt/pyroSAR/blob/master/LICENSE.txt.
# No part of the pyroSAR project, including this file, may be
# copied, modified, propagated, or distributed except according
# to the terms contained in the LICENSE.txt file.
###############################################################################
import os
import pyroSAR
from ..ancillary import multilook_factors
from ..auxdata import get_egm_lookup
from .auxil import parse_recipe, parse_node, gpt, groupbyWorkers

from spatialist import crsConvert, Vector, Raster, bbox, intersect
from spatialist.ancillary import dissolve

import logging
log = logging.getLogger(__name__)


[docs]def geocode(infile, outdir, t_srs=4326, tr=20, polarizations='all', shapefile=None, scaling='dB', geocoding_type='Range-Doppler', removeS1BorderNoise=True, removeS1BorderNoiseMethod='pyroSAR', removeS1ThermalNoise=True, offset=None, allow_RES_OSV=False, demName='SRTM 1Sec HGT', externalDEMFile=None, externalDEMNoDataValue=None, externalDEMApplyEGM=True, terrainFlattening=True, basename_extensions=None, test=False, export_extra=None, groupsize=1, cleanup=True, tmpdir=None, gpt_exceptions=None, gpt_args=None, returnWF=False, nodataValueAtSea=True, demResamplingMethod='BILINEAR_INTERPOLATION', imgResamplingMethod='BILINEAR_INTERPOLATION', alignToStandardGrid=False, standardGridOriginX=0, standardGridOriginY=0, speckleFilter=False, refarea='gamma0'): """ general function for geocoding of SAR backscatter images with SNAP. This function performs the following steps: - (if necessary) identify the SAR scene(s) passed via argument `infile` (:func:`pyroSAR.drivers.identify`) - (if necessary) create the directories defined via `outdir` and `tmpdir` - (if necessary) download Sentinel-1 OSV files - parse a SNAP workflow (:class:`pyroSAR.snap.auxil.Workflow`) - write the workflow to an XML file in `outdir` - execute the workflow (:func:`pyroSAR.snap.auxil.gpt`) Note ---- The function may create workflows with multiple `Write` nodes. All nodes are parametrized to write data in ENVI format, in which case the node parameter `file` is going to be a directory. All nodes will use the same temporary directory, which will be created in `tmpdir`. Its name is created from the basename of the `infile` (:meth:`pyroSAR.drivers.ID.outname_base`) and a suffix identifying each processing node of the workflow (:meth:`pyroSAR.snap.auxil.Workflow.suffix`). For example: `S1A__IW___A_20180101T170648_NR_Orb_Cal_ML_TF_TC`. Parameters ---------- infile: str or ~pyroSAR.drivers.ID or list the SAR scene(s) to be processed; multiple scenes are treated as consecutive acquisitions, which will be mosaicked with SNAP's SliceAssembly operator outdir: str The directory to write the final files to. t_srs: int, str or osr.SpatialReference A target geographic reference system in WKT, EPSG, PROJ4 or OPENGIS format. See function :func:`spatialist.auxil.crsConvert()` for details. Default: `4326 <https://spatialreference.org/ref/epsg/4326/>`_. tr: int or float, optional The target pixel spacing in meters. Default is 20 polarizations: list or str The polarizations to be processed; can be a string for a single polarization, e.g. 'VV', or a list of several polarizations, e.g. ['VV', 'VH']. With the special value 'all' (default) all available polarizations are processed. shapefile: str or :py:class:`~spatialist.vector.Vector` or dict or None A vector geometry for subsetting the SAR scene to a test site. scaling: {'dB', 'db', 'linear'}, optional Should the output be in linear or decibel scaling? Default is 'dB'. geocoding_type: {'Range-Doppler', 'SAR simulation cross correlation'}, optional The type of geocoding applied; can be either 'Range-Doppler' (default) or 'SAR simulation cross correlation' removeS1BorderNoise: bool, optional Enables removal of S1 GRD border noise (default). removeS1BorderNoiseMethod: str the border noise removal method to be applied, See :func:`pyroSAR.S1.removeGRDBorderNoise` for details; one of the following: - 'ESA': the pure implementation as described by ESA - 'pyroSAR': the ESA method plus the custom pyroSAR refinement removeS1ThermalNoise: bool, optional Enables removal of S1 thermal noise (default). offset: tuple, optional A tuple defining offsets for left, right, top and bottom in pixels, e.g. (100, 100, 0, 0); this variable is overridden if a shapefile is defined. Default is None. allow_RES_OSV: bool (only applies to Sentinel-1) Also allow the less accurate RES orbit files to be used? The function first tries to download a POE file for the scene. If this fails and RES files are allowed, it will download the RES file. The selected OSV type is written to the workflow XML file. Processing is aborted if the correction fails (Apply-Orbit-File parameter continueOnFail set to false). demName: str the name of the auto-download DEM. Default is 'SRTM 1Sec HGT'. Is ignored when `externalDEMFile` is not None. externalDEMFile: str or None, optional The absolute path to an external DEM file. Default is None. Overrides `demName`. externalDEMNoDataValue: int, float or None, optional The no data value of the external DEM. If not specified (default) the function will try to read it from the specified external DEM. externalDEMApplyEGM: bool, optional Apply Earth Gravitational Model to external DEM? Default is True. terrainFlattening: bool apply topographic normalization on the data? basename_extensions: list of str or None names of additional parameters to append to the basename, e.g. ['orbitNumber_rel'] test: bool, optional If set to True the workflow xml file is only written and not executed. Default is False. export_extra: list or None a list of image file IDs to be exported to outdir. The following IDs are currently supported: - incidenceAngleFromEllipsoid - localIncidenceAngle - projectedLocalIncidenceAngle - DEM - layoverShadowMask - scatteringArea groupsize: int the number of workers executed together in one gpt call cleanup: bool should all files written to the temporary directory during function execution be deleted after processing? tmpdir: str or None path of custom temporary directory, useful to separate output folder and temp folder. If `None`, the `outdir` location will be used. The created subdirectory will be deleted after processing. gpt_exceptions: dict or None a dictionary to override the configured GPT executable for certain operators; each (sub-)workflow containing this operator will be executed with the define executable; - e.g. ``{'Terrain-Flattening': '/home/user/snap/bin/gpt'}`` gpt_args: list or None a list of additional arguments to be passed to the gpt call - e.g. ``['-x', '-c', '2048M']`` for increased tile cache size and intermediate clearing returnWF: bool return the full name of the written workflow XML file? nodataValueAtSea: bool mask pixels acquired over sea? The sea mask depends on the selected DEM. demResamplingMethod: str one of the following: - 'NEAREST_NEIGHBOUR' - 'BILINEAR_INTERPOLATION' - 'CUBIC_CONVOLUTION' - 'BISINC_5_POINT_INTERPOLATION' - 'BISINC_11_POINT_INTERPOLATION' - 'BISINC_21_POINT_INTERPOLATION' - 'BICUBIC_INTERPOLATION' imgResamplingMethod: str the resampling method for geocoding the SAR image; the options are identical to demResamplingMethod speckleFilter: str one of the following: - 'Boxcar' - 'Median' - 'Frost' - 'Gamma Map' - 'Refined Lee' - 'Lee' - 'Lee Sigma' refarea: str or list 'sigma0', 'gamma0' or a list of both alignToStandardGrid: bool align all processed images to a common grid? standardGridOriginX: int or float the x origin value for grid alignment standardGridOriginY: int or float the y origin value for grid alignment Returns ------- str or None either the name of the workflow file if ``returnWF == True`` or None otherwise .. figure:: figures/snap_geocode.svg :align: center Workflow diagram for function geocode for processing a Sentinel-1 Ground Range Detected (GRD) scene to radiometrically terrain corrected (RTC) backscatter. An additional `Subset` node might be inserted in case a vector geometry is provided. Examples -------- geocode a Sentinel-1 scene and export the local incidence angle map with it >>> from pyroSAR.snap import geocode >>> filename = 'S1A_IW_GRDH_1SDV_20180829T170656_20180829T170721_023464_028DE0_F7BD.zip' >>> geocode(infile=filename, outdir='outdir', tr=20, scaling='dB', >>> export_extra=['DEM', 'localIncidenceAngle'], t_srs=4326) See Also -------- :class:`pyroSAR.drivers.ID`, :class:`spatialist.vector.Vector`, :func:`spatialist.auxil.crsConvert()` """ if isinstance(infile, pyroSAR.ID): id = infile elif isinstance(infile, str): id = pyroSAR.identify(infile) elif isinstance(infile, list): ids = pyroSAR.identify_many(infile, sortkey='start') id = ids[0] else: raise TypeError("'infile' must be of type str, list or pyroSAR.ID") if id.is_processed(outdir): log.info('scene {} already processed'.format(id.outname_base())) return if not os.path.isdir(outdir): os.makedirs(outdir) ############################################ # general setup if id.sensor in ['ASAR', 'ERS1', 'ERS2']: formatName = 'ENVISAT' elif id.sensor in ['S1A', 'S1B']: if id.product == 'SLC': raise RuntimeError('Sentinel-1 SLC data is not supported yet') formatName = 'SENTINEL-1' else: raise RuntimeError('sensor not supported (yet)') # several options like resampling are modified globally for the whole workflow at the end of this function # this list gathers IDs of nodes for which this should not be done because they are configured individually resampling_exceptions = [] ###################### if isinstance(polarizations, str): if polarizations == 'all': polarizations = id.polarizations else: if polarizations in id.polarizations: polarizations = [polarizations] else: raise RuntimeError('polarization {} does not exists in the source product'.format(polarizations)) elif isinstance(polarizations, list): polarizations = [x for x in polarizations if x in id.polarizations] else: raise RuntimeError('polarizations must be of type str or list') bandnames = dict() bandnames['int'] = ['Intensity_' + x for x in polarizations] bandnames['beta0'] = ['Beta0_' + x for x in polarizations] bandnames['gamma0'] = ['Gamma0_' + x for x in polarizations] bandnames['sigma0'] = ['Sigma0_' + x for x in polarizations] ############################################ ############################################ # parse base workflow workflow = parse_recipe('base') ############################################ # Read node configuration read = workflow['Read'] read.parameters['file'] = id.scene read.parameters['formatName'] = formatName readers = [read.id] if isinstance(infile, list): for i in range(1, len(infile)): readn = parse_node('Read') readn.parameters['file'] = ids[i].scene readn.parameters['formatName'] = formatName workflow.insert_node(readn, before=read.id, resetSuccessorSource=False) readers.append(readn.id) sliceAssembly = parse_node('SliceAssembly') sliceAssembly.parameters['selectedPolarisations'] = polarizations workflow.insert_node(sliceAssembly, before=readers) read = sliceAssembly ############################################ # Remove-GRD-Border-Noise node configuration if id.sensor in ['S1A', 'S1B'] and removeS1BorderNoise: bn = parse_node('Remove-GRD-Border-Noise') workflow.insert_node(bn, before=read.id) bn.parameters['selectedPolarisations'] = polarizations ############################################ # ThermalNoiseRemoval node configuration if id.sensor in ['S1A', 'S1B'] and removeS1ThermalNoise: for reader in readers: tn = parse_node('ThermalNoiseRemoval') workflow.insert_node(tn, before=reader) tn.parameters['selectedPolarisations'] = polarizations ############################################ # orbit file application node configuration orbit_lookup = {'ENVISAT': 'DELFT Precise (ENVISAT, ERS1&2) (Auto Download)', 'SENTINEL-1': 'Sentinel Precise (Auto Download)'} orbitType = orbit_lookup[formatName] if formatName == 'ENVISAT' and id.acquisition_mode == 'WSM': orbitType = 'DORIS Precise VOR (ENVISAT) (Auto Download)' if formatName == 'SENTINEL-1': match = id.getOSV(osvType='POE', returnMatch=True) if match is None and allow_RES_OSV: id.getOSV(osvType='RES') orbitType = 'Sentinel Restituted (Auto Download)' orb = workflow['Apply-Orbit-File'] orb.parameters['orbitType'] = orbitType orb.parameters['continueOnFail'] = False ############################################ # calibration node configuration cal = workflow['Calibration'] cal.parameters['selectedPolarisations'] = polarizations cal.parameters['sourceBands'] = bandnames['int'] if isinstance(refarea, str): refarea = [refarea] if terrainFlattening: if 'gamma0' not in refarea: raise RuntimeError('if terrain flattening is applied refarea must be gamma0') cal.parameters['outputBetaBand'] = True if 'sigma0' in refarea: cal.parameters['outputSigmaBand'] = True else: refarea_options = ['sigma0', 'gamma0'] for opt in refarea: if opt not in refarea_options: message = '{0} must be one of the following:\n- {1}' raise ValueError(message.format('refarea', '\n- '.join(refarea_options))) cal.parameters['output{}Band'.format(opt[:-1].capitalize())] = True last = cal.id ############################################ # terrain flattening node configuration if terrainFlattening: tf = parse_node('Terrain-Flattening') workflow.insert_node(tf, before=last) if id.sensor in ['ERS1', 'ERS2'] or (id.sensor == 'ASAR' and id.acquisition_mode != 'APP'): tf.parameters['sourceBands'] = 'Beta0' else: tf.parameters['sourceBands'] = bandnames['beta0'] if 'reGridMethod' in tf.parameters.keys(): if externalDEMFile is None: tf.parameters['reGridMethod'] = True else: tf.parameters['reGridMethod'] = False last = tf.id ############################################ # speckle filtering node configuration speckleFilter_options = ['Boxcar', 'Median', 'Frost', 'Gamma Map', 'Refined Lee', 'Lee', 'Lee Sigma'] if speckleFilter: message = '{0} must be one of the following:\n- {1}' if speckleFilter not in speckleFilter_options: raise ValueError(message.format('speckleFilter', '\n- '.join(speckleFilter_options))) sf = parse_node('Speckle-Filter') workflow.insert_node(sf, before=last) sf.parameters['sourceBands'] = None sf.parameters['filter'] = speckleFilter last = sf.id ############################################ # configuration of node sequence for specific geocoding approaches bands = dissolve([bandnames[opt] for opt in refarea]) if geocoding_type == 'Range-Doppler': tc = parse_node('Terrain-Correction') workflow.insert_node(tc, before=last) tc.parameters['sourceBands'] = bands elif geocoding_type == 'SAR simulation cross correlation': sarsim = parse_node('SAR-Simulation') workflow.insert_node(sarsim, before=last) sarsim.parameters['sourceBands'] = bands workflow.insert_node(parse_node('Cross-Correlation'), before='SAR-Simulation') tc = parse_node('SARSim-Terrain-Correction') workflow.insert_node(tc, before='Cross-Correlation') else: raise RuntimeError('geocode_type not recognized') tc.parameters['alignToStandardGrid'] = alignToStandardGrid tc.parameters['standardGridOriginX'] = standardGridOriginX tc.parameters['standardGridOriginY'] = standardGridOriginY ############################################ # Multilook node configuration try: image_geometry = id.meta['image_geometry'] incidence = id.meta['incidence'] except KeyError: raise RuntimeError('This function does not yet support sensor {}'.format(id.sensor)) rlks, azlks = multilook_factors(sp_rg=id.spacing[0], sp_az=id.spacing[1], tr_rg=tr, tr_az=tr, geometry=image_geometry, incidence=incidence) if azlks > 1 or rlks > 1: workflow.insert_node(parse_node('Multilook'), before='Calibration') ml = workflow['Multilook'] ml.parameters['nAzLooks'] = azlks ml.parameters['nRgLooks'] = rlks ml.parameters['sourceBands'] = None ############################################ # merge sigma0 and gamma0 bands to pass them to Terrain-Correction if len(refarea) > 1 and terrainFlattening: bm_tc = parse_node('BandMerge') workflow.insert_node(bm_tc, before=[tf.source, tf.id]) sources = bm_tc.source gamma_index = sources.index('Terrain-Flattening') sigma_index = abs(gamma_index - 1) s1_id = os.path.basename(os.path.splitext(id.scene)[0]) bands_long = [] for band in bands: comp = [band + '::'] if shapefile is not None: comp.append('Subset_') comp.append(s1_id) if band.startswith('Gamma'): comp.append('_' + workflow.suffix(stop=sources[gamma_index])) else: comp.append('_' + workflow.suffix(stop=sources[sigma_index])) bands_long.append(''.join(comp)) bm_tc.parameters['sourceBands'] = bands_long bm_tc.parameters['geographicError'] = 0.0 ############################################ # specify spatial resolution and coordinate reference system of the output dataset tc.parameters['pixelSpacingInMeter'] = tr try: # try to convert the CRS into EPSG code (for readability in the workflow XML) t_srs = crsConvert(t_srs, 'epsg') except TypeError: raise RuntimeError("format of parameter 't_srs' not recognized") except RuntimeError: # this error can occur when the CRS does not have a corresponding EPSG code # in this case the original CRS representation is written to the workflow pass # the EPSG code 4326 is not supported by SNAP and thus the WKT string has to be defined; # in all other cases defining EPSG:{code} will do if t_srs == 4326: t_srs = 'GEOGCS["WGS84(DD)",' \ 'DATUM["WGS84",' \ 'SPHEROID["WGS84", 6378137.0, 298.257223563]],' \ 'PRIMEM["Greenwich", 0.0],' \ 'UNIT["degree", 0.017453292519943295],' \ 'AXIS["Geodetic longitude", EAST],' \ 'AXIS["Geodetic latitude", NORTH]]' else: t_srs = 'EPSG:{}'.format(t_srs) tc.parameters['mapProjection'] = t_srs ############################################ # (optionally) add node for conversion from linear to db scaling if scaling not in ['dB', 'db', 'linear']: raise RuntimeError('scaling must be a string of either "dB", "db" or "linear"') if scaling in ['dB', 'db']: lin2db = parse_node('LinearToFromdB') workflow.insert_node(lin2db, before=tc.id) lin2db.parameters['sourceBands'] = bands ############################################ # (optionally) add subset node and add bounding box coordinates of defined shapefile if shapefile: if isinstance(shapefile, dict): ext = shapefile else: if isinstance(shapefile, Vector): shp = shapefile.clone() elif isinstance(shapefile, str): shp = Vector(shapefile) else: raise TypeError("argument 'shapefile' must be either a dictionary, a Vector object or a string.") # reproject the geometry to WGS 84 latlon shp.reproject(4326) ext = shp.extent shp.close() # add an extra buffer of 0.01 degrees buffer = 0.01 ext['xmin'] -= buffer ext['ymin'] -= buffer ext['xmax'] += buffer ext['ymax'] += buffer with bbox(ext, 4326) as bounds: inter = intersect(id.bbox(), bounds) if not inter: raise RuntimeError('no bounding box intersection between shapefile and scene') inter.close() wkt = bounds.convert2wkt()[0] subset = parse_node('Subset') workflow.insert_node(subset, before=read.id) subset.parameters['region'] = [0, 0, id.samples, id.lines] subset.parameters['geoRegion'] = wkt subset.parameters['copyMetadata'] = True ############################################ # (optionally) configure subset node for pixel offsets if offset and not shapefile: subset = parse_node('Subset') workflow.insert_node(subset, before=read.id) # left, right, top and bottom offset in pixels l, r, t, b = offset subset_values = [l, t, id.samples - l - r, id.lines - t - b] subset.parameters['region'] = subset_values subset.parameters['geoRegion'] = '' ############################################ # parametrize write node # create a suffix for the output file to identify processing steps performed in the workflow suffix = workflow.suffix() if tmpdir is None: tmpdir = outdir basename = os.path.join(tmpdir, id.outname_base(basename_extensions)) outname = basename + '_' + suffix write = workflow['Write'] write.parameters['file'] = outname write.parameters['formatName'] = 'ENVI' ############################################ ############################################ if export_extra is not None: tc_options = ['incidenceAngleFromEllipsoid', 'localIncidenceAngle', 'projectedLocalIncidenceAngle', 'DEM'] tc_selection = [] for item in export_extra: if item in tc_options: key = 'save{}{}'.format(item[0].upper(), item[1:]) tc.parameters[key] = True tc_selection.append(item) elif item == 'layoverShadowMask': sarsim = parse_node('SAR-Simulation') sarsim.parameters['saveLayoverShadowMask'] = True workflow.insert_node(sarsim, after=tc.id, resetSuccessorSource=False) sarsim_select = parse_node('BandSelect') sarsim_select.parameters['sourceBands'] = 'layover_shadow_mask' workflow.insert_node(sarsim_select, before=sarsim.id, resetSuccessorSource=False) sarsim_tc = parse_node('Terrain-Correction') workflow.insert_node(sarsim_tc, before=sarsim_select.id) sarsim_tc.parameters['alignToStandardGrid'] = alignToStandardGrid sarsim_tc.parameters['standardGridOriginX'] = standardGridOriginX sarsim_tc.parameters['standardGridOriginY'] = standardGridOriginY sarsim_tc.parameters['imgResamplingMethod'] = 'NEAREST_NEIGHBOUR' sarsim_tc.parameters['pixelSpacingInMeter'] = tr sarsim_tc.parameters['mapProjection'] = t_srs resampling_exceptions.append(sarsim_tc.id) sarsim_write = parse_node('Write') sarsim_write.parameters['file'] = outname sarsim_write.parameters['formatName'] = 'ENVI' workflow.insert_node(sarsim_write, before=sarsim_tc.id, resetSuccessorSource=False) elif item == 'scatteringArea': if not terrainFlattening: raise RuntimeError('scatteringArea can only be created if terrain flattening is performed') area_select = parse_node('BandSelect') workflow.insert_node(area_select, before=tf.source, resetSuccessorSource=False) area_select.parameters['sourceBands'] = bandnames['beta0'] area_merge1 = parse_node('BandMerge') workflow.insert_node(area_merge1, before=[tf.id, area_select.id], resetSuccessorSource=False) math = parse_node('BandMaths') math.element.attrib['class'] = '"com.bc.ceres.binding.dom.XppDomElement"' workflow.insert_node(math, before=area_merge1.id, resetSuccessorSource=False) pol = polarizations[0] # the result will be the same for each polarization area = 'scatteringArea_{0}'.format(pol) expression = 'Beta0_{0} / Gamma0_{0}'.format(pol) math.parameters.clear_variables() exp = math.parameters['targetBands'][0] exp['name'] = area exp['type'] = 'float32' exp['expression'] = expression exp['noDataValue'] = 0.0 if len(refarea) > 1: bm_tc.source = bm_tc.source + [math.id] else: bm_tc = parse_node('BandMerge') workflow.insert_node(bm_tc, before=[tf.id, math.id], resetSuccessorSource=False) tc.source = bm_tc.id # modify Terrain-Correction source bands tc_bands = tc.parameters['sourceBands'] + ',' + area tc.parameters['sourceBands'] = tc_bands # add scattering Area to list of band directly written from Terrain-Correction tc_selection.append(area) else: raise RuntimeError("ID '{}' not valid for argument 'export_extra'".format(item)) # directly write export_extra layers to avoid dB scaling if scaling == 'dB' and len(tc_selection) > 0: tc_write = parse_node('Write') workflow.insert_node(tc_write, before=tc.id, resetSuccessorSource=False) tc_write.parameters['file'] = outname tc_write.parameters['formatName'] = 'ENVI' tc_select = parse_node('BandSelect') workflow.insert_node(tc_select, after=tc_write.id) tc_select.parameters['sourceBands'] = tc_selection ############################################ ############################################ # select DEM type dempar = {'externalDEMFile': externalDEMFile, 'externalDEMApplyEGM': externalDEMApplyEGM} if externalDEMFile is not None: if os.path.isfile(externalDEMFile): if externalDEMNoDataValue is None: with Raster(externalDEMFile) as dem: dempar['externalDEMNoDataValue'] = dem.nodata if dempar['externalDEMNoDataValue'] is None: raise RuntimeError('Cannot read NoData value from DEM file. ' 'Please specify externalDEMNoDataValue') else: dempar['externalDEMNoDataValue'] = externalDEMNoDataValue dempar['reGridMethod'] = False else: raise RuntimeError('specified externalDEMFile does not exist') dempar['demName'] = 'External DEM' else: dempar['demName'] = demName dempar['externalDEMFile'] = None dempar['externalDEMNoDataValue'] = 0 for key, value in dempar.items(): workflow.set_par(key, value) # download the EGM lookup table if necessary if dempar['externalDEMApplyEGM']: get_egm_lookup(geoid='EGM96', software='SNAP') ############################################ ############################################ # configure the resampling methods options = ['NEAREST_NEIGHBOUR', 'BILINEAR_INTERPOLATION', 'CUBIC_CONVOLUTION', 'BISINC_5_POINT_INTERPOLATION', 'BISINC_11_POINT_INTERPOLATION', 'BISINC_21_POINT_INTERPOLATION', 'BICUBIC_INTERPOLATION'] message = '{0} must be one of the following:\n- {1}' if demResamplingMethod not in options: raise ValueError(message.format('demResamplingMethod', '\n- '.join(options))) if imgResamplingMethod not in options: raise ValueError(message.format('imgResamplingMethod', '\n- '.join(options))) workflow.set_par('demResamplingMethod', demResamplingMethod) workflow.set_par('imgResamplingMethod', imgResamplingMethod, exceptions=resampling_exceptions) ############################################ ############################################ # additional parameter settings applied to the whole workflow workflow.set_par('nodataValueAtSea', nodataValueAtSea) ############################################ ############################################ # write workflow to file and optionally execute it log.debug('writing workflow to file') wf_name = outname.replace(tmpdir, outdir) + '_proc.xml' workflow.write(wf_name) # execute the newly written workflow if not test: try: groups = groupbyWorkers(wf_name, groupsize) gpt(wf_name, groups=groups, cleanup=cleanup, gpt_exceptions=gpt_exceptions, gpt_args=gpt_args, removeS1BorderNoiseMethod=removeS1BorderNoiseMethod, outdir=outdir) except RuntimeError as e: log.info(str(e)) with open(wf_name.replace('_proc.xml', '_error.log'), 'w') as logfile: logfile.write(str(e)) if returnWF: return wf_name