def initialize(self, context):
self.source_product = context.getSourceProduct()
if self.source_product.getProductType() != S3_OLCI_TYPE_STRING:
raise RuntimeError('Source product must be of type "' +
S3_OLCI_TYPE_STRING + '"')
# todo - check if there is a granule
self.toa_band_names = context.getParameter('band_names')
self.rut_algo.k = self.get_k(context)
self.rut_algo.unc_select = self.get_unc_select(context)
scene_width = self.source_product.getSceneRasterWidth()
scene_height = self.source_product.getSceneRasterHeight()
rut_product = snappy.Product(self.source_product.getName() + '_rut',
'S3_OLCI_RUT', scene_width, scene_height)
snappy.ProductUtils.copyGeoCoding(self.source_product, rut_product)
self.sourceBandMap = {}
for name in self.toa_band_names:
source_band = self.source_product.getBand(name)
unc_toa_band = snappy.Band(name + '_rut',
snappy.ProductData.TYPE_UINT8,
source_band.getRasterWidth(),
source_band.getRasterHeight())
unc_toa_band.setDescription('Uncertainty of ' + name +
' (coverage factor k=' +
str(self.rut_algo.k) + ')')
unc_toa_band.setNoDataValue(250)
unc_toa_band.setNoDataValueUsed(True)
rut_product.addBand(unc_toa_band)
self.sourceBandMap[unc_toa_band] = source_band
context.setTargetProduct(rut_product)
def initialize(self, context):
self.source_product = context.getSourceProduct()
if self.source_product.getProductType() != S2_MSI_TYPE_STRING:
raise RuntimeError('Source product must be of type "' +
S2_MSI_TYPE_STRING + '"')
self.product_meta, self.datastrip_meta, granules_meta = self.source_product.getMetadataRoot(
).getElements()
# todo - check if there is a granule
self.toa_band_names = context.getParameter('band_names')
self.rut_algo.u_sun = self.get_u_sun(self.product_meta)
self.rut_algo.quant = self.get_quant(self.product_meta)
tecta = 0.0
for granule_meta in granules_meta.getElements():
tecta += self.get_tecta(granule_meta)
self.rut_algo.tecta = tecta / granules_meta.getNumElements()
self.rut_algo.k = self.get_k(context)
self.rut_algo.unc_select = self.get_unc_select(context)
scene_width = self.source_product.getSceneRasterWidth()
scene_height = self.source_product.getSceneRasterHeight()
rut_product = snappy.Product(self.source_product.getName() + '_rut',
'S2_RUT', scene_width, scene_height)
snappy.ProductUtils.copyGeoCoding(self.source_product, rut_product)
self.sourceBandMap = {}
for name in self.toa_band_names:
source_band = self.source_product.getBand(name)
unc_toa_band = snappy.Band(name + '_rut',
snappy.ProductData.TYPE_UINT8,
source_band.getRasterWidth(),
source_band.getRasterHeight())
unc_toa_band.setDescription('Uncertainty of ' + name +
' (coverage factor k=' +
str(self.rut_algo.k) + ')')
unc_toa_band.setNoDataValue(250)
unc_toa_band.setNoDataValueUsed(True)
rut_product.addBand(unc_toa_band)
self.sourceBandMap[unc_toa_band] = source_band
snappy.ProductUtils.copyGeoCoding(source_band, unc_toa_band)
context.setTargetProduct(rut_product)
def convertComputedBandToBand(computedBand):
"""Work around to convert virtual band to real
https://forum.step.esa.int/t/how-to-convert-virtual-bands-to-real-bands-using-snappy/3628/6
"""
realBand = snappy.Band(
computedBand.getName(),
computedBand.getDataType(),
computedBand.getRasterWidth(),
computedBand.getRasterHeight()
)
realBand.setDescription(computedBand.getDescription())
realBand.setValidPixelExpression(computedBand.getValidPixelExpression())
realBand.setUnit(computedBand.getUnit())
realBand.setSpectralWavelength(computedBand.getSpectralWavelength())
realBand.setGeophysicalNoDataValue(computedBand.getGeophysicalNoDataValue())
realBand.setNoDataValueUsed(computedBand.isNoDataValueUsed())
if (computedBand.isStxSet()):
realBand.setStx(computedBand.getStx())
imageInfo = computedBand.getImageInfo()
if (imageInfo != None):
realBand.setImageInfo(imageInfo.clone())
product = computedBand.getProduct()
# "Check if all the frame with the raster data are close"
# missing some stuff with topComponent
bandGroup = product.getBandGroup()
bandIndex = bandGroup.indexOf(computedBand)
bandGroup.remove(computedBand)
bandGroup.add(bandIndex, realBand)
realBand.setSourceImage(createSourceImage(computedBand, realBand))
def initialize(self, context):
self.source_product = context.getSourceProduct()
if self.source_product.getProductType() != S2_MSI_TYPE_STRING:
raise RuntimeError('Source product must be of type "' + S2_MSI_TYPE_STRING + '"')
self.mask_group = self.source_product.getMaskGroup() # obtain the masks from the product
metadata_root = self.source_product.getMetadataRoot()
self.product_meta = metadata_root.getElement('Level-1C_User_Product')
self.datastrip_meta = metadata_root.getElement('Level-1C_DataStrip_ID')
granules_meta = metadata_root.getElement('Granules')
self.spacecraft = self.datastrip_meta.getElement('General_Info').getElement('Datatake_Info').getAttributeString(
'SPACECRAFT_NAME')
# todo - check if there is a granule
self.toa_band_names = context.getParameter('band_names')
if not self.toa_band_names:
raise RuntimeError(
'No S2 bands were selected. Please select the S2 bands from the "Processing parameters" tab')
self.rut_algo.u_sun = self.get_u_sun(self.product_meta)
self.rut_algo.quant = self.get_quant(self.product_meta)
# tecta = 0.0
# for granule_meta in granules_meta.getElements():
# tecta += self.get_tecta(granule_meta)
# self.rut_algo.tecta = tecta / granules_meta.getNumElements()
self.source_sza = self.get_tecta()
self.rut_algo.k = self.get_k(context)
self.rut_algo.unc_select = self.get_unc_select(context)
self.sourceBandMap = {}
for name in self.toa_band_names:
# TODO - Change the interface so that undesired bands (e.g azimuth) are not shown.
if not name in S2_BAND_NAMES: # The band name is checked to confirm it is valid band.
if ('view_' in name) or ('sun_' in name):
continue # the angular bands are shown in the GUI and we simply jump to the next band if selected
else:
raise RuntimeError('Source band "' + name + '" is not valid and has not been processed')
source_band = self.source_product.getBand(name)
unc_toa_band = snappy.Band(name + '_rut', snappy.ProductData.TYPE_UINT8, source_band.getRasterWidth(),
source_band.getRasterHeight())
unc_toa_band.setDescription('Uncertainty of ' + name + ' (coverage factor k=' + str(self.rut_algo.k) + ')')
unc_toa_band.setNoDataValue(250)
unc_toa_band.setNoDataValueUsed(True)
self.targetBandList.append(unc_toa_band)
self.sourceBandMap[unc_toa_band] = source_band
snappy.ProductUtils.copyGeoCoding(source_band, unc_toa_band)
masterband = self.get_masterband(self.targetBandList)
rut_product = snappy.Product(self.source_product.getName() + '_rut', 'S2_RUT',
masterband.getRasterWidth(), masterband.getRasterHeight()) # in-memory product
snappy.ProductUtils.copyGeoCoding(masterband, rut_product)
for band in self.targetBandList:
rut_product.addBand(band)
# The metadata from the RUT product is defined
self.rut_product_meta = rut_product.getMetadataRoot() # Here we define the product metadata
# SOURCE_PRODUCT
sourceelem = MetadataElement('Source_product')
data = snappy.ProductData.createInstance(self.source_product.getDisplayName())
sourceattr = MetadataAttribute("SOURCE_PRODUCT", snappy.ProductData.TYPE_ASCII, data.getNumElems())
sourceattr.setData(data)
sourceelem.addAttribute(sourceattr)
self.rut_product_meta.addElement(sourceelem)
# COVERAGE_FACTOR
sourceelem = MetadataElement('Coverage_factor')
data = snappy.ProductData.createInstance(str(context.getParameter('coverage_factor')))
sourceattr = MetadataAttribute("COVERAGE_FACTOR", snappy.ProductData.TYPE_ASCII, data.getNumElems())
sourceattr.setData(data)
sourceelem.addAttribute(sourceattr)
self.rut_product_meta.addElement(sourceelem)
# RUT_VERSION
version = context.getSpi().getOperatorDescriptor().getVersion() # returns what written in the *-info.xml file
sourceelem = MetadataElement('Version')
data = snappy.ProductData.createInstance(version)
sourceattr = MetadataAttribute("VERSION", snappy.ProductData.TYPE_ASCII, data.getNumElems())
sourceattr.setData(data)
sourceelem.addAttribute(sourceattr)
self.rut_product_meta.addElement(sourceelem)
# CONTRIBUTOR LIST: List of selected ones
sourceelem = MetadataElement('List_Contributors')
contributors = ["INSTRUMENT_NOISE", "OOF_STRAYLIGHT-SYSTEMATIC", "OOF_STRAYLIGHT-RANDOM", "CROSSTALK",
"ADC_QUANTISATION", "DS_STABILITY", "GAMMA_KNOWLEDGE", "DIFFUSER-ABSOLUTE_KNOWLEDGE",
"DIFFUSER-TEMPORAL_KNOWLEDGE", "DIFFUSER-COSINE_EFFECT", "DIFFUSER-STRAYLIGHT_RESIDUAL",
"L1C_IMAGE_QUANTISATION"]
for i in range(0, len(contributors)):
data = snappy.ProductData.createInstance(str(self.rut_algo.unc_select[i]))
sourceattr = MetadataAttribute(contributors[i], snappy.ProductData.TYPE_ASCII, data.getNumElems())
sourceattr.setData(data)
sourceelem.addAttribute(sourceattr)
self.rut_product_meta.addElement(sourceelem)
# DATE OF PROCESSING
sourceelem = MetadataElement('Processing_datetime')
data = snappy.ProductData.createInstance(str(datetime.datetime.now()))
sourceattr = MetadataAttribute("PROCESSING_DATETIME", snappy.ProductData.TYPE_ASCII, data.getNumElems())
sourceattr.setData(data)
sourceelem.addAttribute(sourceattr)
self.rut_product_meta.addElement(sourceelem)
context.setTargetProduct(rut_product)