def test_dissolve_with_lists():
assert anc.dissolve([[1, 2], [3, 4]]) == [1, 2, 3, 4]
assert anc.dissolve([[[1]]]) == [1]
assert anc.dissolve(((
1,
2,
), (3, 4))) == [1, 2, 3, 4]
assert anc.dissolve(((1, 2), (1, 2))) == [1, 2, 1, 2]
def replace(inlist, replacement):
outlist = list(inlist)
for old, new, description in replacement:
if old[0] not in outlist:
return outlist
outlist[outlist.index(old[0])] = new
for i in range(1, len(old)):
if old[i] in outlist:
outlist.remove(old[i])
return dissolve(outlist)
def __buildvrt(archives, vrtfile, pattern, vsi, extent, nodata):
locals = [
vsi + x for x in dissolve([finder(x, [pattern]) for x in archives])
]
gdalbuildvrt(src=locals,
dst=vrtfile,
options={
'outputBounds': (extent['xmin'], extent['ymin'],
extent['xmax'], extent['ymax']),
'srcNodata':
nodata
})
def __buildvrt(archives, vrtfile, pattern, vsi, extent, nodata=None, srs=None):
locals = [vsi + x for x in dissolve([finder(x, [pattern]) for x in archives])]
if nodata is None:
with Raster(locals[0]) as ras:
nodata = ras.nodata
opts = {'outputBounds': (extent['xmin'], extent['ymin'],
extent['xmax'], extent['ymax']),
'srcNodata': nodata}
if srs is not None:
opts['outputSRS'] = crsConvert(srs, 'wkt')
gdalbuildvrt(src=locals, dst=vrtfile,
options=opts)
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'):
"""
wrapper function for geocoding SAR images using ESA SNAP
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 <http://spatialreference.org/ref/epsg/4326/>`_.
tr: int or float, optional
The target resolution 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
Note
----
If only one polarization is selected and not extra products are defined the results are directly written to GeoTiff.
Otherwise the results are first written to a folder containing ENVI files and then transformed to GeoTiff files
(one for each polarization/extra product).
If GeoTiff would directly be selected as output format for multiple polarizations then a multilayer GeoTiff
is written by SNAP which is considered an unfavorable format
.. figure:: figures/snap_geocode.png
:scale: 25%
: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, verbose=False, sortkey='start')
id = ids[0]
else:
raise TypeError("'infile' must be of type str, list or pyroSAR.ID")
if id.is_processed(outdir):
print('scene {} already processed'.format(id.outname_base()))
return
# print(os.path.basename(id.scene))
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 = []
######################
# print('- assessing polarization selection')
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
# print('- parsing base workflow')
workflow = parse_recipe('base')
############################################
# Read node configuration
# print('-- configuring Read Node')
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
# print('-- configuring Remove-GRD-Border-Noise Node')
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
# print('-- configuring ThermalNoiseRemoval Node')
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
# print('-- configuring Apply-Orbit-File Node')
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
# print('-- configuring Calibration Node')
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
# print('-- configuring Terrain-Flattening Node')
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 = parse_node('BandMerge')
workflow.insert_node(bm, before=[tf.source, tf.id])
sources = bm.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.parameters['sourceBands'] = bands_long
bm.parameters['geographicError'] = 0.0
############################################
# specify spatial resolution and coordinate reference system of the output dataset
# print('-- configuring CRS')
tc.parameters['pixelSpacingInMeter'] = tr
try:
t_srs = crsConvert(t_srs, 'epsg')
except TypeError:
raise RuntimeError("format of parameter 't_srs' not recognized")
# 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
# print('-- configuring LinearToFromdB Node')
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
# print('-- configuring Subset Node')
if shapefile:
# print('--- read')
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
# print('--- create bbox')
with bbox(ext, 4326) as bounds:
# print('--- intersect')
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
# print('-- configuring 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_write = None
tc_selection = []
for item in export_extra:
if item in tc_options:
if tc_write is None:
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'
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'
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':
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)
# math = parse_node('BandMaths')
# workflow.insert_node(math, before=[tf.id, area_select.id], resetSuccessorSource=False)
math.parameters.clear_variables()
exp = math.parameters['targetBands'][0]
exp['name'] = 'scatteringArea_VV'
exp['type'] = 'float32'
exp['expression'] = 'Beta0_VV / Gamma0_VV'
exp['noDataValue'] = 0.0
area_merge2 = parse_node('BandMerge')
workflow.insert_node(area_merge2,
before=[tf.id, math.id],
resetSuccessorSource=False)
tc.source = area_merge2.id
# modify Terrain-Correction source bands
tc_bands = tc.parameters['sourceBands'] + ',scatteringArea_VV'
tc.parameters['sourceBands'] = tc_bands
# add scattering Area to list of band directly written from Terrain-Correction
tc_selection.append('scatteringArea_VV')
else:
raise RuntimeError(
"ID '{}' not valid for argument 'export_extra'".format(
item))
if len(tc_selection) > 0:
tc_select = parse_node('BandSelect')
workflow.insert_node(tc_select, after=tc_write.id)
tc_select.parameters['sourceBands'] = tc_selection
############################################
############################################
# select DEM type
# print('-- configuring DEM')
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_egm96_lookup()
############################################
############################################
# 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
# print('- 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:
print(str(e))
with open(wf_name.replace('_proc.xml', '_error.log'), 'w') as log:
log.write(str(e))
if returnWF:
return wf_name
def getAuxdata(datasets, scenes):
def getOrbitContentVersions(contentVersion):
content = contentVersion.read().split('\n')
items = [
re.split(r'\s*=\s*', x.strip('\r')) for x in content
if re.search('^[0-9]{4}', x)
]
return dict(items)
auxDataPath = os.path.join(expanduser("~"), '.snap/auxdata')
scenes = [
identify(scene) if isinstance(scene, str) else scene
for scene in scenes
]
sensors = list(set([scene.sensor for scene in scenes]))
for dataset in datasets:
if dataset == 'SRTM 1Sec HGT':
files = [
x.replace('hgt', 'SRTMGL1.hgt.zip') for x in list(
set(dissolve([scene.getHGT() for scene in scenes])))
]
for file in files:
infile = os.path.join(
'https://step.esa.int/auxdata/dem/SRTMGL1', file)
outfile = os.path.join(auxDataPath, 'dem/SRTM 1Sec HGT', file)
if not os.path.isfile(outfile):
print(infile)
try:
input = urlopen(infile)
except HTTPError:
print('-> not available')
continue
with open(outfile, 'wb') as output:
output.write(input.read())
input.close()
elif dataset == 'POEORB':
for sensor in sensors:
if re.search('S1[AB]', sensor):
dates = [(scene.start[:4], scene.start[4:6])
for scene in scenes]
years = list(set([x[0] for x in dates]))
remote_contentVersion = urlopen(
'https://step.esa.int/auxdata/orbits/Sentinel-1/POEORB/remote_contentVersion.txt'
)
versions_remote = getOrbitContentVersions(
remote_contentVersion)
for year in years:
dir_orb = os.path.join(auxDataPath,
'Orbits/Sentinel-1/POEORB',
year)
if not os.path.isdir(dir_orb):
os.makedirs(dir_orb)
contentVersionFile = os.path.join(
dir_orb, 'contentVersion.txt')
if os.path.isfile(contentVersionFile):
contentVersion = open(contentVersionFile, 'r+')
versions_local = getOrbitContentVersions(
contentVersion)
else:
contentVersion = open(contentVersionFile, 'w')
versions_local = {}
combine = dict(
set(versions_local.items())
& set(versions_remote.items()))
dates_select = [x for x in dates if x[0] == year]
months = list(set([x[1] for x in dates_select]))
orb_ids = sorted([
x for x in [
'{}-{}.zip'.format(year, month)
for month in months
] if not x in combine
])
if len(orb_ids) > 0:
contentVersion.write('#\n#{}\n'.format(
strftime('%a %b %d %H:%M:%S %Z %Y', gmtime())))
for orb_id in orb_ids:
orb_remote = urlopen(
'https://step.esa.int/auxdata/orbits/Sentinel-1/POEORB/{}'
.format(orb_id))
orb_remote_stream = zf.ZipFile(
StringIO(orb_remote.read()), 'r')
orb_remote.close()
targets = [
x for x in orb_remote_stream.namelist()
if not os.path.isfile(
os.path.join(dir_orb, x))
]
orb_remote_stream.extractall(dir_orb, targets)
orb_remote_stream.close()
versions_local[orb_id] = versions_remote[
orb_id]
for key, val in versions_local.iteritems():
contentVersion.write('{}={}\n'.format(
key, val))
contentVersion.close()
remote_contentVersion.close()
else:
print('not implemented yet')
elif dataset == 'Delft Precise Orbits':
path_server = 'dutlru2.lr.tudelft.nl'
subdirs = {
'ASAR:': 'ODR.ENVISAT1/eigen-cg03c',
'ERS1': 'ODR.ERS-1/dgm-e04',
'ERS2': 'ODR.ERS-2/dgm-e04'
}
ftp = FTP(path_server)
ftp.login()
for sensor in sensors:
if sensor in subdirs.keys():
path_target = os.path.join('pub/orbits', subdirs[sensor])
path_local = os.path.join(auxDataPath,
'Orbits/Delft Precise Orbits',
subdirs[sensor])
ftp.cwd(path_target)
for item in ftp.nlst():
ftp.retrbinary(
'RETR ' + item,
open(os.path.join(path_local, item), 'wb').write)
ftp.quit()
else:
print('not implemented yet')
def process(cmd,
outdir=None,
logfile=None,
logpath=None,
inlist=None,
void=True,
shellscript=None):
"""
wrapper function to execute GAMMA commands via module :mod:`subprocess`
Parameters
----------
cmd: list
the command line arguments
outdir: str
the directory to execute the command in
logfile: str
a file to write the command log to; overrides parameter logpath
logpath: str
a directory to write logfiles to; the file will be named {GAMMA command}.log, e.g. gc_map.log;
is overridden by parameter logfile
inlist: list
a list of values, which is passed as interactive inputs via stdin
void: bool
return the stdout and stderr messages?
shellscript: str
a file to write the Gamma commands to in shell format
Returns
-------
tuple of str or None
the stdout and stderr messages if void is False, otherwise None
"""
if logfile is not None:
log = logfile
else:
log = os.path.join(logpath,
os.path.basename(cmd[0]) +
'.log') if logpath else None
if shellscript is not None:
if not os.path.isfile(shellscript):
with open(shellscript, 'w') as init:
pass
line = ' '.join([str(x) for x in dissolve(cmd)])
if inlist is not None:
line += ' <<< $"{}"'.format('\n'.join([str(x)
for x in inlist]) + '\n')
with open(shellscript, 'r+') as sh:
if outdir is not None:
content = sh.read()
sh.seek(0)
is_new = re.search(
'this script was created automatically by pyroSAR',
content) is None
if is_new:
ts = datetime.now().strftime('%a %b %d %H:%M:%S %Y')
sh.write(
'# this script was created automatically by pyroSAR on {}\n\n'
.format(ts))
sh.write('export base={}\n\n'.format(outdir))
sh.write(content)
line = line.replace(outdir, '$base')
sh.seek(0, 2) # set pointer to the end of the file
sh.write(line + '\n\n')
# create an environment containing the locations of all GAMMA submodules to be passed ot the subprocess calls
gammaenv = {'GAMMA_HOME': ExamineGamma().home}
for module in ['DIFF', 'DISP', 'IPTA', 'ISP', 'LAT']:
loc = os.path.join(gammaenv['GAMMA_HOME'], module)
if os.path.isdir(loc):
gammaenv[module + '_HOME'] = loc
# execute the command
out, err = run(cmd,
outdir=outdir,
logfile=log,
inlist=inlist,
void=False,
errorpass=True,
env=gammaenv)
gammaErrorHandler(out, err)
if not void:
return out, err
def process(cmd,
outdir=None,
logfile=None,
logpath=None,
inlist=None,
void=True,
shellscript=None):
"""
wrapper function to execute GAMMA commands via module :mod:`subprocess`
Parameters
----------
cmd: list
the command line arguments
outdir: str
the directory to execute the command in
logfile: str
a file to write the command log to; overrides parameter logpath
logpath: str
a directory to write logfiles to; the file will be named {GAMMA command}.log, e.g. gc_map.log;
is overridden by parameter logfile
inlist: list
a list of values, which is passed as interactive inputs via stdin
void: bool
return the stdout and stderr messages?
shellscript: str
a file to write the Gamma commands to in shell format
Returns
-------
tuple of str or None
the stdout and stderr messages if void is False, otherwise None
"""
if logfile is not None:
log = logfile
else:
log = os.path.join(logpath,
os.path.basename(cmd[0]) +
'.log') if logpath else None
if shellscript is not None:
line = ' '.join([str(x) for x in dissolve(cmd)])
if inlist is not None:
line += ' <<< $"{}"'.format('\n'.join([str(x)
for x in inlist]) + '\n')
with open(shellscript, 'a+') as sh:
if outdir is not None:
first = sh.read(1)
if not first:
ts = datetime.now().strftime('%a %b %d %H:%M:%S %Y')
sh.write(
'# this script was created automatically by pyroSAR on {}\n\n'
.format(ts))
sh.write('export base={}\n\n'.format(outdir))
line = line.replace(outdir, '$base')
sh.write(line + '\n\n')
out, err = run(cmd,
outdir=outdir,
logfile=log,
inlist=inlist,
void=False,
errorpass=True)
gammaErrorHandler(out, err)
if not void:
return out, err
