def get_detfoo_index_detector_list(maskFilename, shift):
l_result = {}
# Load the MSK_DETFOO gml file
maskHandler = get_root_xml(maskFilename, deannotate=True)
# Get the mask feature nodes
# as : <eop:MaskFeature gml:id="detector_footprint-B02-10-2">
xnodes = get_all_values(maskHandler,
"//*[local-name(.) = 'MaskFeature']")
# Two indices : the detector index and the feature index
detId = 0
# For each feature
for i in range(len(xnodes)):
feat = xnodes[i]
# Get the attribute of the feature node
# "detector_footprint-B02-10-2"
attribute = list(feat.items())[0][1]
element = attribute.split('-')
# Get the detector index and the feature index
detId = int(element[-2])
featId = int(element[-1])
l_result[featId + shift] = detId
return l_result
def get_no_data(self):
nodata = 0
special_values = xml_tools.get_all_values(self.root, XPATH_MAIN_S2.get("special_values"))
for values in special_values:
if values.findtext("SPECIAL_VALUE_TEXT") == "NODATA":
nodata = int(values.findtext("SPECIAL_VALUE_INDEX"))
return nodata
raise MajaDriverException("NODATA not found in the L1 Header file")
def get_list_of_packaged_dbl_files(self, absolute, check):
nodes = xml_tools.get_all_values(
self.root, EARTH_EXPLORER_HANDLER_XPATH["DBLFilenames"])
list_of_files = [nd.text for nd in nodes]
if absolute:
l_rootbasepath = os.path.dirname(self.main_xml_file)
list_of_files = [
os.path.join(l_rootbasepath, nd.text) for nd in nodes
]
if check:
for fi in list_of_files:
if not os.path.exists(fi):
raise MajaDataException("File " + fi + " does not exists")
return list_of_files
def get_list_of_gipp_files(self):
"""
GetList_of_GIPP_Files
:return:
"""
l_listofgipps = []
for gipp_node in xml_tools.get_all_values(self.root, GIPP_FILE):
one_gipp = dict()
one_gipp["index"] = xml_tools.get_only_value(gipp_node, GIPP_FILE_INDEX)
one_gipp["file_location"] = xml_tools.get_xml_string_value(gipp_node, GIPP_FILE_LOCATION)
one_gipp["nature"] = xml_tools.get_xml_string_value(gipp_node, GIPP_FILE_NATURE)
one_gipp["logical_name"] = xml_tools.get_xml_string_value(gipp_node, GIPP_FILE_LOGICAL_NAME)
l_listofgipps.append(one_gipp)
return l_listofgipps
def get_list_of_zones(self, bandIdx):
list_of_zone = []
# Convert the band index integer value in string
path = "//Viewing_Incidence_Angles_Grids[@bandId='" + str(
bandIdx) + "']"
xnodes = xml_tools.get_all_values(self.root, path)
# Two indices : the detector index and the feature index
detId = 0
# For each feature
for i in range(len(xnodes)):
LOGGER.debug((list(xnodes[i].items())))
list_of_zone.append(xnodes[i].get("detectorId"))
return list_of_zone
def get_detfoo_index_shift(maskFilename):
"""
Get the shift between the detector index and the feature index in the MSK_DETFOO mask
:param maskFilename: string
:return:
"""
shift = 0
# Load the MSK_DETFOO gml file
maskHandler = get_root_xml(maskFilename, deannotate=True)
# Get the mask feature nodes
# as : <eop:MaskFeature gml:id="detector_footprint-B02-10-2">
xnodes = get_all_values(maskHandler,
"//*[local-name(.) = 'MaskFeature']")
# Two indices : the detector index and the feature index
detId = 0
# For each feature
for i in range(len(xnodes)):
feat = xnodes[i]
prevShift = shift
prevDetId = detId
# "detector_footprint-B02-10-2"
attribute = list(feat.items())[0][1]
element = attribute.split('-')
# Get the detector index and the feature index
detId = int(element[-2])
featId = int(element[-1])
# The shift between those two indices must be constant
# because it should not have a gap of detector between to consecutive features
shift = detId - featId
# Check the index values of the next features
if (i > 0) and ((shift != prevShift) or (detId != prevDetId + 1)):
LOGGER.warn(
"Sentinel2L1ImageFileReaderBase::get_detfoo_index_shift: The detector indices are not in ascending order "
"or do not have a constant shift with the feature indices in the MSK_DETFOO "
+ maskFilename + " !")
return False, shift
return True, shift
def get_mask_feature_count(maskFilename, regex=None):
"""
Get the number of layers in a gml file
:param maskFilename:
:return:
"""
maskHandler = get_root_xml(maskFilename, deannotate=True)
xnodes = get_all_values(maskHandler, "//*[local-name(.) = 'MaskFeature']")
if xnodes is not None:
if regex is None:
return len(xnodes)
else:
nb = 0
for x in xnodes:
for a in list(x.items()):
if regex in a[1]:
nb = nb + 1
return nb
else:
return 0
def get_list_of_quality_index(self):
"""
GetListOfQualityIndexes
:return:
"""
l_listofqualityindexes = []
for quality_index_node in xml_tools.get_all_values(self.root, ONE_QUALITY_INDEX):
one_quality_index = dict()
one_quality_index["index"] = xml_tools.get_xml_int_value(quality_index_node, GIPP_FILE_INDEX)
one_quality_index["code"] = xml_tools.get_xml_int_value(quality_index_node, QUALITY_INDEX_CODE)
one_quality_index["value"] = xml_tools.get_xml_int_value(quality_index_node, QUALITY_INDEX_VALUE)
one_quality_index["band_code"] = QUALITY_INDEX_BAND_CODE
l_listofqualityindexes.append(one_quality_index)
LOGGER.debug("Add the quality index [%s] Code=<%s> Value=<%s> Band_Code=<%s> ",
one_quality_index["index"],
one_quality_index["code"],
one_quality_index["value"],
one_quality_index["band_code"])
def muscate_initialize(self,
product_filename,
plugin_base,
validate=False,
schema_path=None):
# Initialize the Image filename provider
if not MajaMuscateL1ImageInformations.is_a_muscate_by_checking_the_filename(
product_filename):
LOGGER.debug("The filename <" + product_filename +
"> is not an 'muscate' L1 header file.")
return False
if not MajaMuscateL1ImageInformations.is_a_muscate_by_checking_the_satellite(
product_filename, plugin_base):
LOGGER.debug(
"The filename <" + product_filename +
"> is not an 'muscate' L1 header file (by reading platform in the xml file)."
)
return False
# Init XML handler
lHandler = MuscateXMLFileHandler(product_filename,
validate=validate,
schema_path=schema_path)
# Store the satellite
self.Satellite = lHandler.get_string_value_of("Platform")
self.SatelliteID = self.Satellite.upper().replace("-", "")
# Store the plugin name
self.PluginName = plugin_base.PluginName
self.ProductFileName = product_filename
self.FileCategory = plugin_base.ShortFileType # LSC
self.LevelType = "L1VALD"
self.Prefix = self.Satellite
self.FileClass = "TEST" # LANDSAT5-TM-XSTH...
self.Site = lHandler.get_string_value_of("ZoneGeo")
self.ProductDateStr = lHandler.get_acquisition_date_formated_yyyymmdd(
) # YYYYMMDD
# LANDSAT5-TM-XSTH_20100118-103000-000_L1C_EU93066200A00B_C_V1-0
self.ProductId = lHandler.get_string_value_of("ProductId")
self.ProductVersion = lHandler.get_string_value_of("ProductVersion")
l_DatePDV = lHandler.get_date_pdv_formated_utc(
) # UTC=2010-01-18T12:00:00
self.ProductDate = date_utils.get_datetime_from_utc(l_DatePDV)
self.GenerationDateStr = lHandler.get_string_value_of("ProductionDate")
self.AcquisitionStart = lHandler.get_string_value_of("AcquisitionDate")
self.OrbitNumber = lHandler.get_string_value_of("OrbitNumber")
self.ReferenceSiteDefinitionId = "UNKNOWN"
self.HeaderFilename = product_filename
self.HeaderHandler = lHandler
if xml_tools.get_only_value(lHandler.root,
"//Product_Characteristics/INSTRUMENT",
check=True) is not None:
self.Instrument = lHandler.get_string_value_of("Instrument")
if xml_tools.get_only_value(
lHandler.root,
"//Product_Characteristics/SPECTRAL_CONTENT",
check=True) is not None:
self.SpectralContent = lHandler.get_string_value_of(
"SpectralContent").replace("+", "")
# VENUS specification
# Store the VIE and SOL filenames (DATA and Headers) to copy in the L2 product
self.SOLHeaderFileName = ""
self.SOLImageFileName = ""
self.VIEHeaderFileName = ""
self.VIEImageFileName = ""
# Initialize the parameters necessary for the core of the algorithms of MACCS
# Get longitude and latitude coordinates of the product
ulc = lHandler.get_upper_left_corner()
lrc = lHandler.get_lower_right_corner()
# Estimation of the coordinate of the central point
center = lHandler.get_center()
#l_Corner.Longitude = ulc[0] + (lrc[0] - ulc[0]) / 2.
#l_Corner.Latitude = ulc[1] + (lrc[1] - ulc[1]) / 2.
self.CenterCorner.longitude = center[0]
self.CenterCorner.latitude = center[1]
self.CenterCorner.column = 0
self.CenterCorner.line = 0
# Initialize the Validity Start/Stop
l_UTCValidity = date_utils.get_utc_from_datetime(self.ProductDate)
if l_UTCValidity.endswith('.000Z'):
l_UTCValidity = l_UTCValidity[:-5]
self.UTCValidityStart = l_UTCValidity
self.UTCValidityStop = l_UTCValidity
# Get the list of bands in a L2 product
l_BandsDefinitions = plugin_base.BandsDefinitions
l_ListOfBandsL2Coarse = l_BandsDefinitions.get_list_of_band_id_in_l2_coarse(
)
l_NbBandsL2Coarse = len(l_ListOfBandsL2Coarse)
LOGGER.debug(
"l_BandsDefinitions->GetListOfBandCodeInL2Coarse -> l_NbBandsL2Coarse: "
+ str(l_NbBandsL2Coarse))
LOGGER.debug(
"MuscateXmllHandler->GetListOfBands -> l_NbBands : "
+ str(len(lHandler.get_list_of_bands())))
self.ListOfViewingAnglesPerBandAtL2Resolution = []
self.ListOfViewingAnglesPerBandAtL2CoarseResolution = []
self.ListOfViewingZenithAnglesPerBandAtL2CoarseResolution = []
self.ListOfViewingAzimuthAnglesPerBandAtL2CoarseResolution = []
# Initialize the Viewing angles for each detectors (Zenith and Azimuth)
# Read the constants values from the Header Envi file name
# The angles must be in degree
if plugin_base.WideFieldSensor:
# Initialize the Viewing angles for each detectors (Zenith and Azimuth)
l_MeanViewingZenithalAngles = lHandler.get_mean_viewing_zenithal_angles(
)
l_MeanViewingAzimuthalAngles = lHandler.get_mean_viewing_azimuthal_angles(
)
self.ViewingAngle = {
"incidence_zenith_angle":
str(statistics.mean(l_MeanViewingZenithalAngles)),
"incidence_azimuth_angle":
str(statistics.mean(l_MeanViewingAzimuthalAngles))
}
# For each bands for EnviProduct
for bd in range(0, len(l_ListOfBandsL2Coarse)):
angles = {
"incidence_zenith_angle":
str(l_MeanViewingZenithalAngles[bd]),
"incidence_azimuth_angle":
str(l_MeanViewingAzimuthalAngles[bd])
}
self.ListOfViewingAnglesPerBandAtL2CoarseResolution.append(
angles)
self.ListOfViewingZenithAnglesPerBandAtL2CoarseResolution.append(
str(angles["incidence_zenith_angle"]))
self.ListOfViewingAzimuthAnglesPerBandAtL2CoarseResolution.append(
str(angles["incidence_azimuth_angle"]))
else:
lViewingAngles = lHandler.get_mean_viewing_angles()
l_ViewAngleZenith = lViewingAngles[0]
l_ViewAngleAzimuth = lViewingAngles[1]
self.ViewingAngle = {
"incidence_zenith_angle": str(l_ViewAngleZenith),
"incidence_azimuth_angle": str(l_ViewAngleAzimuth)
}
# For each bands for EnviProduct
for bd in l_ListOfBandsL2Coarse:
angles = {
"incidence_zenith_angle": str(l_ViewAngleZenith),
"incidence_azimuth_angle": str(l_ViewAngleAzimuth)
}
self.ListOfViewingAnglesPerBandAtL2CoarseResolution.append(
angles)
self.ListOfViewingZenithAnglesPerBandAtL2CoarseResolution.append(
str(angles["incidence_zenith_angle"]))
self.ListOfViewingAzimuthAnglesPerBandAtL2CoarseResolution.append(
str(angles["incidence_azimuth_angle"]))
# Fill the L2 resolution angles
l_nbRes = len(l_BandsDefinitions.ListOfL2Resolution)
for r in range(0, l_nbRes):
l_res = l_BandsDefinitions.ListOfL2Resolution[r]
l_l2bandcodes = l_BandsDefinitions.get_list_of_l2_band_code(l_res)
l_l2bandidx = [
l_BandsDefinitions.get_band_id_in_l2_coarse(b)
for b in l_l2bandcodes
]
for b in l_l2bandidx:
self.ListOfViewingAnglesPerBandAtL2Resolution.append(
self.ListOfViewingAnglesPerBandAtL2CoarseResolution[b])
# Solar Angles
lSolarAngles = lHandler.get_mean_solar_angles()
self.SolarAngle = {
"sun_zenith_angle": lSolarAngles[0],
"sun_azimuth_angle": lSolarAngles[1]
}
if xml_tools.get_only_value(lHandler.root,
"//Angles_Grids_List/Sun_Angles_Grids",
check=True) is not None:
self.SolarAngleGrid["StepUnit"] = xml_tools.get_attribute(
lHandler.root, "//Angles_Grids_List/Sun_Angles_Grids/Zenith",
"step_unit")
self.SolarAngleGrid["ColStep"] = lHandler.get_string_value_of(
"SunAngleColStep")
self.SolarAngleGrid["RowStep"] = lHandler.get_string_value_of(
"SunAngleRowStep")
self.SolarAngleGrid["Azimuth"] = lHandler.get_sun_azimuthal_angles(
)
self.SolarAngleGrid["Zenith"] = lHandler.get_sun_zenithal_angles()
# Viewing angle grids
self.ViewingAngleGrids = []
if len(
xml_tools.get_all_values(
lHandler.root,
"//Angles_Grids_List/Viewing_Incidence_Angles_Grids_List/Band_Viewing_Incidence_Angles_Grids_List"
)):
if lHandler.has_per_band_angles():
for bn, bandid in l_BandsDefinitions.L2CoarseBandMap.items():
zonelist = lHandler.get_list_of_zones(bn)
zenith_values = lHandler.get_viewing_zenithal_angles(bn)
azimuth_values = lHandler.get_viewing_azimuthal_angles(bn)
LOGGER.debug("Viewing Angle grid for band " + str(bn))
for d, det in enumerate(zonelist):
self.ViewingAngleGrids.append({
"StepUnit":
lHandler.get_viewing_grid_step_unit(bn, det),
"ColStep":
lHandler.get_viewing_grid_col_step(bn, det),
"RowStep":
lHandler.get_viewing_grid_row_step(bn, det),
"Band":
str(bandid),
"Detector":
det.lstrip('0'),
"Azimuth":
azimuth_values[d],
"Zenith":
zenith_values[d]
})
else:
zonelist = lHandler.get_list_of_zones("dummy")
for det in zonelist:
LOGGER.debug("Viewing Angle grid for det " + det)
self.ViewingAngleGrids.append({
"StepUnit":
lHandler.get_viewing_grid_step_unit(bandid=None,
det=det),
"ColStep":
lHandler.get_viewing_grid_col_step(bandid=None,
det=det),
"RowStep":
lHandler.get_viewing_grid_row_step(bandid=None,
det=det),
"Detector":
det.lstrip('0'),
"Azimuth":
lHandler.get_viewing_azimuthal_angles(det)[0],
"Zenith":
lHandler.get_viewing_zenithal_angles(det)[0]
})
# Area by resolution
self.AreaByResolution = []
l_grpSuffixes = l_BandsDefinitions.ListOfL2Resolution
if len(l_grpSuffixes) == 1:
l_grpSuffixes = ["XS"]
for res in l_grpSuffixes:
l_path_group_geo = "//Group_Geopositioning_List/Group_Geopositioning[@group_id='{}']/{}"
curArea = Area()
curArea.origin = (xml_tools.get_xml_string_value(
lHandler.root, l_path_group_geo.format(res, "ULX")),
xml_tools.get_xml_string_value(
lHandler.root,
l_path_group_geo.format(res, "ULY")))
curArea.spacing = (xml_tools.get_xml_string_value(
lHandler.root, l_path_group_geo.format(res, "XDIM")),
xml_tools.get_xml_string_value(
lHandler.root,
l_path_group_geo.format(res, "YDIM")))
curArea.size = (xml_tools.get_xml_string_value(
lHandler.root, l_path_group_geo.format(res, "NCOLS")),
xml_tools.get_xml_string_value(
lHandler.root,
l_path_group_geo.format(res, "NROWS")))
self.AreaByResolution.append(curArea)
# Spectral information
self.SpectralInfo = []
l_pathBase = "//Spectral_Band_Informations_List/Spectral_Band_Informations[@band_id='{}']"
l_pathNativeCoeff = "/Calibration_Coefficients_Lists/Native_Coefficients_List/COEFFICIENT[@name='{}']"
l_pathRadiance = "/SOLAR_IRRADIANCE"
l_pathWavelength = "/Wavelength/{}"
l_pathResponse = "/Spectral_Response/{}"
l_pathsSpecInfo = {
'PhysicalGain': l_pathNativeCoeff.format("PhysicalGain"),
'LuminanceMax': l_pathNativeCoeff.format("LuminanceMax"),
'LuminanceMin': l_pathNativeCoeff.format("LuminanceMin"),
'QuantizeCalMax': l_pathNativeCoeff.format("QuantizeCalMax"),
'QuantizeCalMin': l_pathNativeCoeff.format("QuantizeCalMin"),
'RadianceAdd': l_pathNativeCoeff.format("RadianceAdd"),
'RadianceMult': l_pathNativeCoeff.format("RadianceMult"),
'ReflectanceAdd': l_pathNativeCoeff.format("ReflectanceAdd"),
'ReflectanceMult': l_pathNativeCoeff.format("ReflectanceMult"),
'SolarIrradiance': l_pathRadiance,
'WavelengthMin': l_pathWavelength.format("MIN"),
'WavelengthMax': l_pathWavelength.format("MAX"),
'WavelengthCentral': l_pathWavelength.format("CENTRAL"),
'ResponseStep': l_pathResponse.format("STEP"),
'ResponseValues': l_pathResponse.format("VALUES")
}
for b, bidx in l_BandsDefinitions.L1BandMap.items():
specInfo = {"Band": b}
realBase = l_pathBase.format(b)
for measure, pathMeasure in l_pathsSpecInfo.items():
res = xml_tools.get_xml_string_value(lHandler.root,
realBase + pathMeasure,
check=True)
if len(res):
specInfo[measure] = res
if measure == 'PhysicalGain':
specInfo[measure] = float(res)
self.SpectralInfo.append(specInfo)
# -------------------------------------------------------------------------
# 4.2: New
# Set the L1 no data value
self.L1NoData = int(lHandler.get_string_value_of("L1NoData"))
# Set the reflectance quantification value
self.ReflectanceQuantification = 1. / float(
lHandler.get_string_value_of("QuantificationValue"))
# Computes the real value of the L1 NoData
self.RealL1NoData = float(
self.L1NoData) * self.ReflectanceQuantification
# Save metadata related to Muscate format
self.MuscateData["Node_MetadataFormat"] = xml_tools.extract_nodes(
lHandler.root, "//Metadata_Identification/METADATA_FORMAT")
l_NodeOriginalDataDiffuser = xml_tools.extract_nodes(
lHandler.root, "//ORIGINAL_DATA_DIFFUSER")
if l_NodeOriginalDataDiffuser is not None:
self.MuscateData[
"Node_OriginalDataDiffuser"] = l_NodeOriginalDataDiffuser
self.MuscateData[
"Node_Geoposition_Informations"] = xml_tools.extract_nodes(
lHandler.root, "//Geoposition_Informations")
self.MuscateData[
"Node_Geometric_Informations"] = xml_tools.extract_nodes(
lHandler.root, "//Geometric_Informations")
#~ self.MuscateData["Identifier"] = lIdent
self.MuscateData["Authority"] = lHandler.get_string_value_of(
"Authority")
self.MuscateData["Producer"] = lHandler.get_string_value_of("Producer")
self.MuscateData["Project"] = lHandler.get_string_value_of("Project")
self.MuscateData["ZoneGeo"] = lHandler.get_string_value_of("ZoneGeo")
#~ self.MuscateData["Platform"] = self.Satellite
self.MuscateData["AcquisitionDate"] = lHandler.get_string_value_of(
"AcquisitionDate")
self.MuscateData[
"UTCAcquisitionRangeMean"] = lHandler.get_string_value_of(
"UTCAcquisitionRangeMean")
self.MuscateData[
"UTCAcquisitionRangeDatePrecision"] = lHandler.get_string_value_of(
"UTCAcquisitionRangeDatePrecision")
l_NodeSolarAnglesGrid = xml_tools.extract_nodes(
lHandler.root,
"//Data_List/Data[Data_Properties/NATURE='Solar_Angles_Grid']")
if l_NodeSolarAnglesGrid is not None:
self.MuscateData["Node_Solar_Angles_Grid"] = l_NodeSolarAnglesGrid
l_NodeViewingAnglesGrid = xml_tools.extract_nodes(
lHandler.root,
"//Data_List/Data[Data_Properties/NATURE='Viewing_Angles_Grid']")
if l_NodeViewingAnglesGrid is not None:
self.MuscateData[
"Node_Viewing_Angles_Grid"] = l_NodeViewingAnglesGrid
l_NodeUsefulImageInfoFile = xml_tools.extract_nodes(
lHandler.root,
"//Data_List/Data[Data_Properties/NATURE='Useful_Image_Informations_File']"
)
if l_NodeUsefulImageInfoFile is not None:
self.MuscateData[
"Node_Useful_Image_Informations_File"] = l_NodeUsefulImageInfoFile
l_NodeUsefulImage = xml_tools.extract_nodes(
lHandler.root,
"//Mask_List/Mask[Mask_Properties/NATURE='Useful_Image']")
if l_NodeUsefulImage is not None:
self.MuscateData["Node_Useful_Image"] = l_NodeUsefulImage
l_NodeDetFoo = xml_tools.get_only_value(
lHandler.root,
"//Mask_List/Mask/Mask_Properties/NATURE[.='Detector_Footprint']",
check=True)
if l_NodeDetFoo is not None:
self.MuscateData[
"ZoneMaskFileNames"] = lHandler.get_map_list_of_detector_footprint_image_filenames(
)
pix_node = xml_tools.get_only_value(
lHandler.root,
"//Mask_List/Mask/Mask_Properties/NATURE[.='Aberrant_Pixels']",
check=True)
if pix_node is not None:
self.MuscateData[
"PIXImages"] = lHandler.get_list_of_pix_mask_filenames()
self.MuscateData[
"PIXIndices"] = lHandler.get_list_of_pix_mask_indices()
spectral_node = xml_tools.extract_nodes(
lHandler.root,
"//Radiometric_Informations/Spectral_Band_Informations_List")
if spectral_node is not None:
self.MuscateData[
"Node_Spectral_Band_Informations_List"] = spectral_node
qualityGeo_node = xml_tools.extract_nodes(
lHandler.root,
"//Current_Product/Product_Quality_List[@level='Geo']")
if qualityGeo_node is not None:
self.MuscateData["Node_Product_Quality_List_Geo"] = qualityGeo_node
qualityNatif_node = xml_tools.extract_nodes(
lHandler.root,
"//Current_Product/Product_Quality_List[@level='Natif']")
if qualityNatif_node is not None:
self.MuscateData[
"Node_Product_Quality_List_Natif"] = qualityNatif_node
processingJob_node = xml_tools.extract_nodes(
lHandler.root, "//Production_Informations/Processing_Jobs_List")
if processingJob_node is not None:
self.MuscateData["Node_Processing_Jobs_List"] = processingJob_node
return True
def write_public_images(self, p_PublicDirectory, p_L2BaseFilename,
p_ReflectanceQuantificationValue,
p_AOTQuantificationValue, p_AOTNodataValue,
p_VAPQuantificationValue, p_VAPNodataValue,
p_CLDDataBandsSelected, p_CLDCoreAlgorithmsMapBand,
p_WritePublicProduct, p_EnvCorOption, working_dir):
# IF PUBLIC PART OF L2 PRODUCT IS WRITTEN
if p_WritePublicProduct:
l_BandsDefinitions = self._plugin.BandsDefinitions
l_ListOfL2Res = l_BandsDefinitions.ListOfL2Resolution
l_NumberOfResolutions = len(l_ListOfL2Res)
LOGGER.debug(
"L2ImageFileWriterBase::Initialize Number of resolutions: " +
str(l_NumberOfResolutions) + ".")
# Not use the list of XS band because for Landsat8, the band B9 is not
# selected in the L2 resolution (only in L2Coarse resolution)
l_BaseL2FullFilename = os.path.join(p_PublicDirectory,
p_L2BaseFilename)
l_MASKSDirectory = os.path.join(p_PublicDirectory, "MASKS")
l_BaseL2FullMASKSFilename = os.path.join(l_MASKSDirectory,
p_L2BaseFilename)
file_utils.create_directory(l_MASKSDirectory)
resol_QLK = 0
l_RedBandId, l_BlueBandId, l_GreenBandId = l_BandsDefinitions.get_l2_information_for_quicklook_band_code(
self._quicklookredbandcode, self._quicklookgreenbandcode,
self._quicklookbluebandcode)
# *************************************************************************************************************
# **** LOOP on RESOLUTION *********************************************
# *************************************************************************************************************
for resol in range(0, l_NumberOfResolutions):
l_StrResolution = l_BandsDefinitions.ListOfL2Resolution[resol]
# --------------------------------------------------------
# L2 area AreaType l_AreaToL2Resolution
l_AreaFile = self._sre_list[resol]
l_ListOfBand = l_BandsDefinitions.get_list_of_l2_band_code(
l_StrResolution)
l_NumberOfBands = len(l_ListOfBand)
LOGGER.debug(
"L2ImageFileReader::Gen Public image file for the resolution "
+ l_StrResolution + ".")
l_grpSuffix = ""
if l_NumberOfResolutions == 1:
l_grpSuffix = "XS"
else:
l_grpSuffix = l_ListOfL2Res[resol]
l_StrResolution = l_BandsDefinitions.ListOfL2Resolution[resol]
# Read the Coef apply for SRE and FRE images
LOGGER.info(
"SRE and FRE values multiply by the reflectance quantification value "
+ str(p_ReflectanceQuantificationValue) + ".")
# *************************************************************************************************************
# **** PUBLIC DATA ************************************************
# *************************************************************************************************************
# START WRITING SRE Image file DATA
# Initialize the Scalar filter
sre_pipeline = OtbPipelineManager()
#Extract each channel for each file
tmp_l2_filename_list = []
tmp_l2_image_list = []
tmp_sre_scaled = os.path.join(
working_dir,
"tmp_sre_multi_round_" + l_StrResolution + ".tif")
param_scaled_sre = {
"im": self._sre_list[resol],
"coef": p_ReflectanceQuantificationValue,
"out": tmp_sre_scaled
}
scaled_sre_app = OtbAppHandler("RoundImage",
param_scaled_sre,
write_output=False)
sre_pipeline.add_otb_app(scaled_sre_app)
for i in range(l_NumberOfBands):
if resol == resol_QLK and (l_RedBandId == i
or l_GreenBandId == i
or l_BlueBandId == i):
tmp_sre_roi = os.path.join(
working_dir,
"tmp_sre_roi_" + l_ListOfBand[i] + ".tif")
tmp_sre_roi_app = extract_roi(self._sre_list[resol],
[i],
tmp_sre_roi,
write_output=False)
tmp_l2_image_list.append(
tmp_sre_roi_app.getoutput().get("out"))
tmp_l2_filename_list.append(tmp_sre_roi)
if l_RedBandId == i:
self._qckl_red_image = tmp_sre_roi
elif l_GreenBandId == i:
self._qckl_green_image = tmp_sre_roi
elif l_BlueBandId == i:
self._qckl_blue_image = tmp_sre_roi
sre_pipeline.add_otb_app(tmp_sre_roi_app)
tmp_sre_scaled_roi = os.path.join(
working_dir,
"tmp_sre_scaled_roi_" + l_ListOfBand[i] + ".tif")
tmp_sre_scaled_roi_app = extract_roi(
scaled_sre_app.getoutput().get("out"), [i],
tmp_sre_scaled_roi + ":int16",
write_output=False)
tmp_l2_image_list.append(
tmp_sre_scaled_roi_app.getoutput().get("out"))
sre_pipeline.add_otb_app(tmp_sre_scaled_roi_app)
tmp_l2_filename_list.append(
l_BaseL2FullFilename + "_SRE_" + l_ListOfBand[i] +
".tif" + file_utils.
get_extended_filename_write_image_file_standard())
# START WRITING FRE Image file DATA
tmp_tgs_filename = os.path.join(
working_dir, "tmp_tgs_" + l_StrResolution + ".tif")
tmp_stl_filename = os.path.join(
working_dir, "tmp_stl_" + l_StrResolution + ".tif")
fre_pipeline = OtbPipelineManager()
if p_EnvCorOption:
# Initialize the Scalar filter
tmp_fre_scaled = os.path.join(
working_dir,
"tmp_fre_multi_round_" + l_StrResolution + ".tif")
param_scaled_fre = {
"im": self._fre_list[resol],
"coef": p_ReflectanceQuantificationValue,
"out": tmp_fre_scaled
}
scaled_fre_app = OtbAppHandler("RoundImage",
param_scaled_fre,
write_output=False)
fre_pipeline.add_otb_app(scaled_fre_app)
# Extract each channel for each file
for i in range(l_NumberOfBands):
tmp_fre_roi = os.path.join(
working_dir,
"tmp_fre_roi_" + l_ListOfBand[i] + ".tif")
tmp_fre_roi_app = extract_roi(
scaled_fre_app.getoutput().get("out"), [i],
tmp_fre_roi + ":int16",
write_output=False)
tmp_l2_image_list.append(
tmp_fre_roi_app.getoutput().get("out"))
fre_pipeline.add_otb_app(tmp_fre_roi_app)
tmp_l2_filename_list.append(
l_BaseL2FullFilename + "_FRE_" + l_ListOfBand[i] +
".tif" + file_utils.
get_extended_filename_write_image_file_standard())
#Add tgs and stl also provided by the envcorr
tmp_l2_image_list.append(self._tgs_list[resol])
tmp_l2_filename_list.append(tmp_tgs_filename)
tmp_l2_image_list.append(self._stl_list[resol])
tmp_l2_filename_list.append(tmp_stl_filename)
# START WRITING ATB Image file DATA
# Initialize the Scalar filter
# FA1424: Temporary Fix to address cosmetic aspects of FA1424
# VAPThreshold.SetInput(self.GetVAPImageList()[resol))
# VAPThreshold.SetOutsideValue(255. / p_VAPQuantificationValue)
# VAPThreshold.ThresholdAbove(255. / p_VAPQuantificationValue)
# VAPScalar.SetInput(VAPThreshold.GetOutput())
# VAPScalar.SetCoef(p_VAPQuantificationValue)
atb_pipeline = OtbPipelineManager()
tmp_vap = os.path.join(
working_dir, "tmp_vap_scaled_" + l_StrResolution + ".tif")
param_bandmath_vap = {
"il":
[self._l2vapimagelist[resol], self._l2edgimagelist[resol]],
"exp":
"(im2b1 == 1)?" + str(p_VAPNodataValue) + ":" + "im1b1*" +
str(p_VAPQuantificationValue),
"out":
tmp_vap
}
vap_scal_app = OtbAppHandler("BandMathDouble",
param_bandmath_vap,
write_output=False)
atb_pipeline.add_otb_app(vap_scal_app)
tmp_round_vap = os.path.join(
working_dir, "tmp_vap_round_" + l_StrResolution + ".tif")
param_round_vap = {
"im": vap_scal_app.getoutput().get("out"),
"out": tmp_round_vap
}
vap_round_app = OtbAppHandler("RoundImage",
param_round_vap,
write_output=False)
atb_pipeline.add_otb_app(vap_round_app)
tmp_aot = os.path.join(
working_dir, "tmp_aot_scaled_" + l_StrResolution + ".tif")
param_bandmath_aot = {
"il":
[self._l2aotlist[resol], self._l2edgimagelist[resol]],
"exp":
"(im2b1 == 1)?" + str(p_AOTNodataValue) + ":" + "im1b1*" +
str(p_AOTQuantificationValue),
"out":
tmp_aot
}
aot_scal_app = OtbAppHandler("BandMathDouble",
param_bandmath_aot,
write_output=False)
atb_pipeline.add_otb_app(aot_scal_app)
tmp_round_aot = os.path.join(
working_dir, "tmp_aot_round_" + l_StrResolution + ".tif")
param_round_aot = {
"im": aot_scal_app.getoutput().get("out"),
"out": tmp_round_aot
}
aot_round_app = OtbAppHandler("RoundImage",
param_round_aot,
write_output=False)
atb_pipeline.add_otb_app(aot_round_app)
atb_filename = l_BaseL2FullFilename + "_ATB_" + l_grpSuffix + ".tif"
param_atb_concat = {
"il": [
vap_round_app.getoutput().get("out"),
aot_round_app.getoutput().get("out")
],
"out":
atb_filename + ":uint8" + file_utils.
get_extended_filename_write_image_file_standard()
}
atb_binconcat_app = OtbAppHandler("ConcatenateImages",
param_atb_concat,
write_output=False)
#tmp_l2_image_list.append(atb_binconcat_app.getoutput().get("out"))
#tmp_l2_filename_list.append(atb_filename)
atb_pipeline.add_otb_app(atb_binconcat_app)
# START WRITING IAB MASK
iab_pipeline = OtbPipelineManager()
# Create the image list
tmp_iab = os.path.join(
working_dir, "tmp_iab_concat_" + l_StrResolution + ".tif")
param_iab_concat = {
"il":
[self._l2iwcmasklist[resol], self._l2taomasklist[resol]],
"out": tmp_iab + ":uint8"
}
tmp_iab_concat_app = OtbAppHandler("ConcatenateImages",
param_iab_concat,
write_output=False)
iab_pipeline.add_otb_app(tmp_iab_concat_app)
iab_filename = l_BaseL2FullMASKSFilename + "_IAB_" + l_grpSuffix + ".tif"
param_iab_binconcat = {
"im":
tmp_iab_concat_app.getoutput().get("out"),
"out":
iab_filename + ":uint8" + file_utils.
get_extended_filename_write_image_file_standard()
}
iab_binconcat_app = OtbAppHandler("BinaryConcatenate",
param_iab_binconcat,
write_output=False)
iab_pipeline.add_otb_app(iab_binconcat_app)
write_images([
atb_binconcat_app.getoutput().get("out"),
iab_binconcat_app.getoutput().get("out")
], [atb_filename, iab_filename])
#tmp_l2_image_list.append(iab_binconcat_app.getoutput().get("out"))
#tmp_l2_filename_list.append(iab_filename)
# START WRITING EDG Image file DATA
tmp_l2_image_list.append(self._l2edgimagelist[resol])
tmp_l2_filename_list.append(l_BaseL2FullMASKSFilename +
"_EDG_" + l_grpSuffix + ".tif")
#--------------------------
# Write all the images at L2 Reso
write_images(tmp_l2_image_list, tmp_l2_filename_list)
atb_pipeline.free_otb_app()
iab_pipeline.free_otb_app()
fre_pipeline.free_otb_app()
sre_pipeline.free_otb_app()
# --------------------------
#Caching of cloud images needed for MG2
l_cm2_index = p_CLDCoreAlgorithmsMapBand[CLOUD_MASK_ALL_CLOUDS]
l_shadows_index = p_CLDCoreAlgorithmsMapBand[
CLOUD_MASK_SHADOWS]
l_shadvar_index = p_CLDCoreAlgorithmsMapBand[
CLOUD_MASK_SHADVAR]
# START WRITING MG2 Image file DATA
l_mg2_image_list = []
mg2_pipeline = OtbPipelineManager()
# Connect the WAM image
wat_resampled = os.path.join(
working_dir, "wat_resampled_" + l_StrResolution + ".tif")
app_resample_wat = resample(self._wasimage,
self._dtm.ALTList[resol],
wat_resampled,
method=OtbResampleType.LINEAR,
threshold=0.25,
write_output=False)
l_mg2_image_list.append(
app_resample_wat.getoutput().get("out"))
mg2_pipeline.add_otb_app(app_resample_wat)
# Extract the CM2 cloud mask
l_mg2_image_list.append(self._l2cldlist[resol][l_cm2_index])
#Connect the SNW image if any
if self._cld_snow is not None:
LOGGER.debug(
"Snow mask has been successfully computed, adding it to the MG2"
)
snw_resampled = os.path.join(
working_dir,
"snw_resampled_" + l_StrResolution + ".tif")
app_resample_snw = resample(self._cld_snow,
self._dtm.ALTList[resol],
snw_resampled,
method=OtbResampleType.LINEAR,
threshold=0.25,
write_output=False)
l_mg2_image_list.append(
app_resample_snw.getoutput().get("out"))
mg2_pipeline.add_otb_app(app_resample_snw)
else:
# Add a constant mask
tmp_constant_filename = os.path.join(
working_dir, "Const_shd_masks.tif")
cst_snw_app = constant_image(self._dtm.ALTList[resol],
0,
tmp_constant_filename +
":uint8",
write_output=False)
l_mg2_image_list.append(cst_snw_app.getoutput().get("out"))
mg2_pipeline.add_otb_app(cst_snw_app)
# Connect the shadow or mask
tmp_shador_bandmath = os.path.join(
working_dir,
"tmp_shador_bandmath_" + l_StrResolution + ".tif")
tmp_band_math_app = band_math([
self._l2cldlist[resol][l_shadows_index],
self._l2cldlist[resol][l_shadvar_index]
],
"im1b1 || im2b1",
tmp_shador_bandmath + ":uint8",
write_output=False)
l_mg2_image_list.append(
tmp_band_math_app.getoutput().get("out"))
mg2_pipeline.add_otb_app(tmp_band_math_app)
# Connect the HID image
hid_resampled = os.path.join(
working_dir, "hid_resampled_" + l_StrResolution + ".tif")
app_resample_hid = resample(self._dtm_hid,
self._dtm.ALTList[resol],
hid_resampled,
method=OtbResampleType.LINEAR,
threshold=0.25,
write_output=False)
l_mg2_image_list.append(
app_resample_hid.getoutput().get("out"))
mg2_pipeline.add_otb_app(app_resample_hid)
# Connect the SHDimage
shd_resampled = os.path.join(
working_dir, "shd_resampled_" + l_StrResolution + ".tif")
app_resample_shd = resample(self._dtm_shd,
self._dtm.ALTList[resol],
shd_resampled,
method=OtbResampleType.LINEAR,
threshold=0.25,
write_output=False)
mg2_pipeline.add_otb_app(app_resample_shd)
l_mg2_image_list.append(
app_resample_shd.getoutput().get("out"))
if p_EnvCorOption:
# Append STL
l_mg2_image_list.append(tmp_stl_filename)
# Append TGS
l_mg2_image_list.append(tmp_tgs_filename)
else:
# Append STL
l_mg2_image_list.append(self._stl_list[resol])
# Append TGS
l_mg2_image_list.append(self._tgs_list[resol])
# Concatenate all
tmp_mg2 = os.path.join(
working_dir, "tmp_mg2_concat_" + l_StrResolution + ".tif")
param_mg2_concat = {"il": l_mg2_image_list, "out": tmp_mg2}
tmp_mg2_concat_app = OtbAppHandler("ConcatenateImages",
param_mg2_concat,
write_output=False)
param_mg2_binconcat = {
"im":
tmp_mg2_concat_app.getoutput().get("out"),
"out":
l_BaseL2FullMASKSFilename + "_MG2_" + l_grpSuffix +
".tif" + ":uint8" + file_utils.
get_extended_filename_write_image_file_standard()
}
mg2_binconcat_app = OtbAppHandler("BinaryConcatenate",
param_mg2_binconcat,
write_output=True)
mg2_pipeline.add_otb_app(mg2_binconcat_app)
mg2_pipeline.free_otb_app()
# START WRITING SAT Image file DATA
# TODO Create the writer with test on number of bands
param_sat_binconcat = {
"im":
self._l2satimagelist[resol],
"out":
l_BaseL2FullMASKSFilename + "_SAT_" + l_grpSuffix +
".tif" + ":uint8" + file_utils.
get_extended_filename_write_image_file_standard()
}
sat_binconcat_app = OtbAppHandler("BinaryConcatenate",
param_sat_binconcat,
write_output=True)
# START WRITING PIX Image file DATA
if "PIXImages" in self._l1_image_info.MuscateData:
LOGGER.debug(
"The L1 product have 'Aberrant_Pixels' masks. There are writed in the L2 out product..."
)
otb_file_utils.otb_copy_image_to_file(
self._l2piximagelist[resol],
l_BaseL2FullMASKSFilename + "_PIX_" + l_grpSuffix +
".tif")
else:
LOGGER.debug("No PIX node detected to write")
# START WRITING USI Image file DATA
if "Node_Useful_Image" in self._l1_image_info.MuscateData:
LOGGER.debug(
"The L1 product have 'Useful_Image' files. There are copied in the L2 out product..."
)
# Write the USI in the Xml file, in the Useful_Imagenode !
l_XPathRootUSI_In = "//Mask[Mask_Properties/NATURE='Useful_Image']/Mask_File_List/MASK_FILE[@group_id='{}']"
xnodes_in = xml_tools.get_all_values(
self._l1_image_info.MuscateData["Node_Useful_Image"],
l_XPathRootUSI_In.format(l_grpSuffix))
# Get the path in the xml product filename
lPath = os.path.dirname(self._l1_image_info.HeaderFilename)
for node_in in xnodes_in:
l_FullPathFilename = os.path.join(lPath, node_in.text)
# Expand threshold the file
usi_resampled = l_BaseL2FullMASKSFilename + "_USI_" + l_grpSuffix + ".tif"\
+ file_utils.get_extended_filename_write_mask_file_muscate()
resample(l_FullPathFilename,
self._dtm.ALTList[resol],
usi_resampled,
threshold=0.25,
method=OtbResampleType.LINEAR,
write_output=True)
else:
LOGGER.debug(
"No 'Useful_Image' mask detected in the L1 product."
)
# Fin si manage USI
# START WRITING DFP Image file DATA (=DFP in MUSCATE) #TODO
if self._l2dfpimagelist is not None:
param_dfp_binconcat = {
"im":
self._l2dfpimagelist[resol],
"out":
l_BaseL2FullMASKSFilename + "_DFP_" + l_grpSuffix +
".tif"
}
dfp_binconcat_app = OtbAppHandler("BinaryConcatenate",
param_dfp_binconcat,
write_output=True)
else:
LOGGER.debug("DFP Masks not available.")
# START WRITING CLM (CLD) Image file DATA
# Connect the CLD image
# Connect the CLD image
# -------------------------------------
l_cld_uses_filenames = False
for f in self._l2cldlist[resol]:
if not otb_is_swig_pointer(f) and os.path.exists(f):
l_cld_uses_filenames = True
self.write_cld_image(self._l2cldlist[resol],
p_CLDDataBandsSelected,
l_BaseL2FullMASKSFilename + "_CLM_" +
l_grpSuffix + ".tif",
use_filenames=l_cld_uses_filenames)
LOGGER.debug("Writing L2 resolution image done !")