Ejemplo n.º 1
0
    def initialize(self, filename, working_dir, has_snow):
        file_hdr = os.path.splitext(filename)[0] + ".HDR"
        file_dbl = os.path.splitext(filename)[0] + ".DBL"
        file_dbldir = os.path.splitext(filename)[0] + ".DBL.DIR"
        LOGGER.info("AUX_REFDE2 filename: " + filename)
        # uncompress dbl
        uncompress_dbl_product(file_dbl)

        # DEM filenames provider
        list_of_file = os.listdir(file_dbldir)
        nbresol = 0
        for f in list_of_file:
            if "_ALT" in f and "TIF" in os.path.splitext(f)[1]:
                nbresol = nbresol + 1
        LOGGER.info("Nb resolution found " + str(nbresol))
        self.initialize_res_list(nbresol)

        LOGGER.info(
            "DEMFilenamesProvider::Initialize. Nb resolution computed:" +
            str(len(self._resList)))
        for resol in self._resList:
            LOGGER.debug("DEMFilenamesProvider::Initialize. Prefix resol : " +
                         resol)

        handler = EarthExplorerXMLFileHandler(file_hdr)
        list_of_dbl_files = handler.get_list_of_packaged_dbl_files(True, False)
        LOGGER.info("DEMFileNames found " + str(len(list_of_dbl_files)) +
                    " files")

        for i in range(0, len(list_of_dbl_files)):
            if list_of_dbl_files[i].split('.TIF')[-1]:
                raise MajaDataException(
                    "Wrong file extension detected. Delete the file: " +
                    str(list_of_dbl_files[i]))

        # --------------------------------------
        # Find the correct filename
        for fi in list_of_dbl_files:
            # LAIG - FA - MAC - 1610 - CNES
            # ../ CONTEXTES_ANOMALIES / TMA_VENUS_maccs_errors / 4398 / VE_TEST_AUX_REFDE2_BRASCHAT_0001.DBL.DIR / VE_TEST_AUX_REFDE2_BRASCHAT_0001_SLP.TIF
            # Extract the last value -> SLP
            # ../ CONTEXTES_ANOMALIES / TMA_VENUS_maccs_errors / 4398 / VE_TEST_AUX_REFDE2_BRASCHAT_0001.DBL.DIR / VE_TEST_AUX_REFDE2_BRASCHAT_0001_ALT_R1.TIF
            # Extract the last value -> ALT
            l_splitted = (os.path.splitext(os.path.basename(fi))[0]).split("_")
            l_lenghtlistfilenamename = len(l_splitted)
            # Extract the tow last values -> ex: 0001 _SLP or ALT_R1
            l_keytype = l_splitted[-1]
            if l_lenghtlistfilenamename > 2:
                l_keytype = l_splitted[-2] + "_" + l_keytype
            # --------------------------------------
            # Test if the filename is ALC
            if "ALC" in l_keytype:
                self.ALC = fi
            # --------------------------------------
            # Test if the filename is MSK
            elif "MSK" in l_keytype:
                self.MSK = fi
            # --------------------------------------
            # Test if the filename is ASC
            elif "ASC" in l_keytype:
                self.ASC = fi
            # --------------------------------------
            # Test if the filename is SLC
            elif "SLC" in l_keytype:
                self.__SLCInternal = fi
            else:
                # --------------------------------------
                # Lop under resolutions
                for res in self._resList:
                    # --------------------------------------
                    # Test if the filename is SLP
                    if "SLP" in l_keytype:
                        if res in l_keytype:
                            self.__SLPListInternal.append(fi)
                    # --------------------------------------
                    # Test if the filename is ALT
                    elif "ALT" in l_keytype:
                        if res in l_keytype:
                            self.ALTList.append(fi)
                    # --------------------------------------
                    # Test if the filename is ASP
                    elif "ASP" in l_keytype:
                        if res in l_keytype:
                            self.__ASPListInternal.append(fi)
                    else:
                        LOGGER.debug(
                            "Unknown Filename and associated product type.")
                # endloop resol
        # --------------------------------------
        # Check existent of ALC filename
        if not os.path.exists(self.ALC):
            raise MajaDataException("The ALC file '" + self.ALC +
                                    "' of the DTM doesn't exist !")

        # --------------------------------------
        # Check existent of MSK filename
        if not os.path.exists(self.MSK):
            raise MajaDataException("The MSK file '" + self.MSK +
                                    "' of the DTM doesn't exist !")

        # --------------------------------------
        # Check existent of SLC filename
        if not os.path.exists(self.__SLCInternal):
            raise MajaDataException("The SLC file '" + self.__SLCInternal +
                                    "' of the DTM doesn't exist !")
        else:
            LOGGER.debug("Starting multiply " + self.__SLCInternal + " * " +
                         str(self._coeff))
            self.SLC = os.path.join(
                working_dir, "Mul_" + os.path.basename(self.__SLCInternal))
            self._apps.add_otb_app(
                multiply_by_scalar(self.__SLCInternal,
                                   self._coeff,
                                   output_image=self.SLC))
            mtdat = GdalDatasetInfo(self.__SLCInternal)
            self.CoarseArea = Area()
            self.CoarseArea.size = mtdat.size
            self.CoarseArea.origin = mtdat.origin
            self.CoarseArea.spacing = mtdat.pixel_size
            LOGGER.debug("Done")

        # --------------------------------------
        for resol in range(0, len(self._resList)):
            # --------------------------------------
            # Check existent of SLP filename
            if not os.path.exists(self.__SLPListInternal[resol]):
                raise MajaDataException("One of the SLP file '" +
                                        self.__SLPListInternal[resol] +
                                        "' of the DTM doesn't exist !")
            else:
                LOGGER.debug("Starting multiply " +
                             self.__SLPListInternal[resol] + " * " +
                             str(self._coeff))
                tmp = os.path.join(
                    working_dir,
                    "Mul_" + os.path.basename(self.__SLPListInternal[resol]))
                slp_mul_app = multiply_by_scalar(self.__SLPListInternal[resol],
                                                 self._coeff,
                                                 output_image=tmp,
                                                 write_output=False)
                self._apps.add_otb_app(slp_mul_app)
                mtdat = GdalDatasetInfo(self.__SLPListInternal[resol])
                l2area = Area()
                l2area.size = mtdat.size
                l2area.origin = mtdat.origin
                l2area.spacing = mtdat.pixel_size
                self.ProjRef = mtdat.dataset.GetProjectionRef()
                self.L2Areas.append(l2area)
                LOGGER.debug("Done")
                self.SLPList.append(slp_mul_app.getoutput().get("out"))
            # --------------------------------------
            # Check existent of ALT filename
            if not os.path.exists(self.ALTList[resol]):
                raise MajaDataException("One of the ALT file '" +
                                        self.ALTList[resol] +
                                        "' of the DTM doesn't exist !")
            # --------------------------------------
            # Check existent of ASP filename
            if not os.path.exists(self.__ASPListInternal[resol]):
                raise MajaDataException("One of the ASP file '" +
                                        self.__ASPListInternal[resol] +
                                        "' of the DTM doesn't exist !")
            else:
                LOGGER.debug("Starting multiply " +
                             self.__ASPListInternal[resol] + " * " +
                             str(self._coeff))
                tmp = os.path.join(
                    working_dir,
                    "Mul_" + os.path.basename(self.__ASPListInternal[resol]))
                asp_mul_app = multiply_by_scalar(self.__ASPListInternal[resol],
                                                 self._coeff,
                                                 output_image=tmp,
                                                 write_output=False)
                self._apps.add_otb_app(asp_mul_app)
                LOGGER.debug("Done")
                self.ASPList.append(asp_mul_app.getoutput().get("out"))

        # end loop resol

        LOGGER.debug(nbresol)

        l_cartoCode = xml_tools.get_only_value(
            handler.root,
            "//DEM_Information/Cartographic/Coordinate_Reference_System/Code",
            namespaces=handler.nss,
            check=True)
        l_geoCode = xml_tools.get_only_value(
            handler.root,
            "//DEM_Information/Geographic/Coordinate_Reference_System/Code",
            namespaces=handler.nss,
            check=True)
        if l_cartoCode is not None:
            self.ProjCode = l_cartoCode.text
            self.ProjType = "PROJECTED"
        elif l_geoCode is not None:
            self.ProjCode = l_geoCode.text
            self.ProjType = "GEOGRAPHIC"
        else:
            raise MajaDataException("Unknown DEM type")

        LOGGER.debug("DEM Projection Code: " + self.ProjCode)
        LOGGER.debug("DEM Projection Type: " + self.ProjType)

        self.Site = xml_tools.get_xml_string_value(
            handler.root,
            "//Specific_Product_Header/Instance_Id/Applicable_Site_Nick_Name",
            namespaces=handler.nss)

        if nbresol != 0:
            param_stats = {"im": self.ALTList[0]}
            stat_app = stats(self.ALTList[0])
            self.ALT_Mean = stat_app.getoutput().get("mean")
            self.ALT_Max = stat_app.getoutput().get("max")
            self.ALT_Min = stat_app.getoutput().get("min")
            self.ALT_Stdv = stat_app.getoutput().get("stdv")
            self.ALT_LogicalName = "LOCAL=" + os.path.splitext(
                os.path.basename(file_hdr))[0]
            LOGGER.info("DEM Mean : " + str(self.ALT_Mean))
            LOGGER.info("DEM Max : " + str(self.ALT_Max))
            LOGGER.info("DEM Min : " + str(self.ALT_Min))
            LOGGER.info("DEM Stdv : " + str(self.ALT_Stdv))
Ejemplo n.º 2
0
    def initialize(self, product_filename, validate=False, schema_path=None, tile_id=None):
        self.ProductFileName = product_filename
        self.PluginName = "SENTINEL2"
        LOGGER.info("Start Sentinel2 L1 ImageInformationProvider " + product_filename + "...")
        # detect correctly formatted
        if (("_MTD_SAFL1C_" not in product_filename and "MTD_MSIL1C" not in product_filename) or
                os.path.splitext(product_filename)[1] != ".xml"):
            return False

        try:
            headerHandler = MajaSentinel2L1MainXmlReader(product_filename, validate, schema_path,tile_id=tile_id)
        except Exception as e:
            LOGGER.info(e)
            return False
        self.HeaderHandler = headerHandler
        self.Satellite = headerHandler.satellite_name.upper()
        self.SatelliteID = self.Satellite.upper().replace("-","")
        self.UniqueSatellite = "SENTINEL-2_"
        self.LevelType = "L1VALD"
        self.FileCategory = "SSC"

        granule_id_split = headerHandler.granule_id.split("_")
        self.FileClass = granule_id_split[1]
        self.HeaderFilename = headerHandler.main_xml_file
        self.Prefix = granule_id_split[0]
        self.L1NoData = headerHandler.get_no_data()
        self.ReflectanceQuantification = 1.0 / headerHandler.quantification_value
        self.RealL1NoData = self.L1NoData * self.ReflectanceQuantification
        self.xmlTileFilename = headerHandler.XmlTileFileName
        LOGGER.info("Tile xml filename : " + self.xmlTileFilename)
        tile_handler = MajaSentinel2L1GranuleXmlReader(self.xmlTileFilename)
        self.TileHandler = tile_handler
        LOGGER.debug("TileId: " + self.HeaderHandler.TileId)
        self.Site = maja_utils.get_formated_site(self.HeaderHandler.TileId)
        self.TileHandler.TileId = self.Site

        self.ProductDate = date_utils.get_datetime_from_utc("UTC=" + tile_handler.sensing_time)
        self.ProductDateStr = self.ProductDate.strftime('%Y%m%d')
        LOGGER.debug("Product Date: " + self.ProductDateStr)
        self.ProductId = headerHandler.get_string_value_of("ProductURI")
        LOGGER.debug("ProductID: "+self.ProductId)

        self.GenerationDateStr = headerHandler.get_string_value_of("GenerationTime")
        self.AcquisitionStart = headerHandler.get_string_value_of("ProductStartTime")

        self.OrbitNumber = headerHandler.get_string_value_of("OrbitNumber")

        l_datastrip_split = tile_handler.datastrip_id.split("_")
        l_start_date_str = l_datastrip_split[-3]
        l_stop_date_str = l_datastrip_split[-2][1:]
        l_start_date_time = date_utils.get_datetime_from_yyyymmddthhmmss(l_start_date_str)
        l_stop_date_time = date_utils.get_datetime_from_yyyymmddthhmmss(l_stop_date_str)
        self.UTCValidityStart = date_utils.get_utc_from_datetime(l_start_date_time)
        LOGGER.debug("UTCValidityStart : " + self.UTCValidityStart)
        self.UTCValidityStop = date_utils.get_utc_from_datetime(l_stop_date_time)
        LOGGER.debug("UTCValidityStop : " + self.UTCValidityStop)

        self.ReferenceSiteDefinitionId = "UNKNOWN"

        # Not available in S2
        self.SOLHeaderFileName = ""
        self.SOLImageFileName = ""
        self.VIEHeaderFileName = ""
        self.VIEImageFileName = ""
        self.ListOfViewingAnglesPerBandAtL2Resolution = []
        self.ListOfViewingAnglesPerBandAtL2CoarseResolution = []
        self.ListOfViewingZenithAnglesPerBandAtL2CoarseResolution = []
        self.ListOfViewingAzimuthAnglesPerBandAtL2CoarseResolution = []
        l_MeanViewingZenithalAngles = []
        l_MeanViewingAzimuthalAngles = []
        for f in range(0, len(tile_handler.angles.viewing_incidence_angle.incidence_angles_mean)):
            angles = tile_handler.angles.viewing_incidence_angle.incidence_angles_mean[str(f)]
            self.ListOfViewingAnglesPerBandAtL2CoarseResolution.append(angles)
            self.ListOfViewingZenithAnglesPerBandAtL2CoarseResolution.append(angles["incidence_zenith_angle"])
            self.ListOfViewingAzimuthAnglesPerBandAtL2CoarseResolution.append(angles["incidence_azimuth_angle"])
            l_MeanViewingZenithalAngles.append(float(angles["incidence_zenith_angle"]))
            l_MeanViewingAzimuthalAngles.append(float(angles["incidence_azimuth_angle"]))
        self.ViewingAngle = {
            "incidence_zenith_angle": str(statistics.mean(l_MeanViewingZenithalAngles)),
            "incidence_azimuth_angle": str(statistics.mean(l_MeanViewingAzimuthalAngles))
            }
        l_bandsdefinition = MajaSentinel2Plugin().BandsDefinitions
        l_nbRes = len(l_bandsdefinition.ListOfL2Resolution)
        for r in range(0, l_nbRes):
            l_res = l_bandsdefinition.ListOfL2Resolution[r]
            l_l2bandcodes = l_bandsdefinition.get_list_of_l2_band_code(l_res)
            l_l2bandidx = [l_bandsdefinition.get_band_id_in_l2_coarse(b) for b in l_l2bandcodes]
            for b in l_l2bandidx:
                self.ListOfViewingAnglesPerBandAtL2Resolution.append(
                    self.ListOfViewingAnglesPerBandAtL2CoarseResolution[b])

        self.ViewingAngleGrids = []
        for grid in tile_handler.angles.viewing_incidence_angle.list_of_viewing_angles_grid:
            self.ViewingAngleGrids.append({
                "StepUnit":grid.step_unit,
                "ColStep":grid.col_step,
                "RowStep":grid.row_step,
                "Band":grid.band_id,
                "Detector":grid.detector_id,
                "Azimuth":grid.azimuth_values,
                "Zenith":grid.zenith_values
                })
        self.SolarAngle = tile_handler.angles.sun_angles.sun_angles_mean

        self.SolarAngleGrid["StepUnit"] = tile_handler.angles.sun_angles.step_unit
        self.SolarAngleGrid["ColStep"] = tile_handler.angles.sun_angles.col_step
        self.SolarAngleGrid["RowStep"] = tile_handler.angles.sun_angles.row_step
        self.SolarAngleGrid["Azimuth"] = tile_handler.angles.sun_angles.azimuth_angle_list_string_values
        self.SolarAngleGrid["Zenith"] = tile_handler.angles.sun_angles.zenith_angle_list_string_values

        # Area by resolution
        self.AreaByResolution = []
        for res in l_bandsdefinition.ListOfL2Resolution:
            res_m = l_bandsdefinition.get_l1_resolution(res)
            l_ul = tile_handler.get_geoposition_upperleftcorner(res_m)
            l_spa = tile_handler.get_geoposition_dims(res_m)
            l_size = tile_handler.get_size(res_m)
            curArea = Area()
            curArea.origin = (
                str(l_ul.x),
                str(l_ul.y))
            curArea.spacing = (
                str(l_spa.x),
                str(l_spa.y))
            curArea.size = (
                str(l_size.x),
                str(l_size.y))
            self.AreaByResolution.append(curArea)
        
        # Spectral information
        self.SpectralInfo = []
        l_pathGain = "//Product_Image_Characteristics/PHYSICAL_GAINS[@bandId='{}']"
        l_pathRadiance = "//Solar_Irradiance_List/SOLAR_IRRADIANCE[@bandId='{}']"
        l_pathWavelength = "//Spectral_Information_List/Spectral_Information[@bandId='{}']/Wavelength/{}"
        l_pathResponse = "//Spectral_Information_List/Spectral_Information[@bandId='{}']/Spectral_Response/{}"
        for b, bidx in l_bandsdefinition.L1BandMap.items():
            self.SpectralInfo.append({
                "Band":b,
                "PhysicalGain":float(headerHandler.get_string_value(l_pathGain.format(bidx))),
                "SolarIrradiance":headerHandler.get_string_value(l_pathRadiance.format(bidx)),
                "WavelengthMin":headerHandler.get_string_value(l_pathWavelength.format(bidx, "MIN")),
                "WavelengthMax":headerHandler.get_string_value(l_pathWavelength.format(bidx, "MAX")),
                "WavelengthCentral":headerHandler.get_string_value(l_pathWavelength.format(bidx, "CENTRAL")),
                "ResponseStep":headerHandler.get_string_value(l_pathResponse.format(bidx, "STEP")),
                "ResponseValues":headerHandler.get_string_value(l_pathResponse.format(bidx, "VALUES"))
                })

        # TODO CenterCorner
        l_resolution = 10
        l_boundingbox = tile_handler.get_geoposition_boundingbox(l_resolution)
        LOGGER.info("Geoposition BoundingBox computed: xmin, ymin, xmax, ymax: " + str(l_boundingbox.xmin) + ", "
                    + str(l_boundingbox.ymin) + ", " + str(l_boundingbox.xmax) + ", " + str(l_boundingbox.ymax) + ".")

        # Transform in Lat / Long coordinates
        # -------------------------------------------------------------------------
        # CSCode = EPSG:32615
        cs_code = tile_handler.reference_system_code
        cs_code = maja_utils.split_string(cs_code, ':')[-1]

        # Estimation of the coordinate of the central point
        l_inputpoint_0 = l_boundingbox.xmin + (l_boundingbox.xmax - l_boundingbox.xmin) / 2.0
        l_inputpoint_1 = l_boundingbox.ymin + (l_boundingbox.ymax - l_boundingbox.ymin) / 2.0
        LOGGER.debug(
            "Geoposition BoundingBox central point computed: x, y: " + str(l_inputpoint_0) + ", " + str(l_inputpoint_1))

        LOGGER.debug("Start Conversion ToWKT with the EPSG '" + cs_code + "'...")
        param_conv = {"carto.x": l_inputpoint_0,
                      "carto.y": l_inputpoint_1,
                      "mapproj": "epsg",
                      "mapproj.epsg.code": int(cs_code)
                      }
        conv_app = OtbAppHandler("ConvertCartoToGeoPoint", param_conv)
        LOGGER.debug("Start Conversion ToWKT done.")

        self.CenterCorner.longitude = conv_app.getoutput()["long"]
        self.CenterCorner.latitude = conv_app.getoutput()["lat"]
        self.CenterCorner.column = 0
        self.CenterCorner.line = 0
        conv_app = None

        return True
    def initialize(self, product_filename, validate=False, schema_path=None):
        LOGGER.info("Start Venus L1 Initialize on product " + product_filename)
        l_hdrfilename = os.path.splitext(product_filename)[0] + ".HDR"
        l_CanLoad = xml_tools.can_load_file(l_hdrfilename)
        if not l_CanLoad:
            return False

        rootNode = xml_tools.get_root_xml(l_hdrfilename, deannotate=True)
        self.Satellite = xml_tools.get_xml_string_value(rootNode, "//Mission")
        if not self._plugin.is_valid_with_satellite(self.Satellite):
            LOGGER.debug("The L1 product '" + product_filename + "' with satellite '" + self.Satellite + "' is not a VENUS product !")
        self.SatelliteID = self.Satellite.upper()
        self.PluginName = self._plugin.PluginName
        self.Prefix = "VE"
        l_File_Type = xml_tools.get_xml_string_value(rootNode, "//File_Type")
        filenamekey = l_File_Type.split("_")
        self.FileCategory = filenamekey[0]
        self.LevelType = filenamekey[1]
        self.FileClass = xml_tools.get_xml_string_value(rootNode, "//File_Class")
        self.Site = xml_tools.get_xml_string_value(rootNode, "//Instance_Id/Nick_Name")
        self.ReferenceSiteDefinitionId = xml_tools.get_xml_string_value(rootNode, "//Reference_SiteDefinition_Id")
        l_AcquisitionDateTime = xml_tools.get_xml_string_value(rootNode, "//Product_Information/Acquisition_Date_Time")
        self.ProductDate = date_utils.get_datetime_from_utc(l_AcquisitionDateTime)
        self.ProductDateStr = self.ProductDate.strftime('%Y%m%d')
        LOGGER.debug("Product Date: " + self.ProductDateStr)

        self.ProductId = xml_tools.get_xml_string_value(rootNode, "//Fixed_Header/File_Name")


        genDate = xml_tools.get_xml_string_value(rootNode, "//Processing_Information/Date_Time")
        genDate = genDate[4:]
        if genDate[-1] != 'Z':
            genDate = genDate + 'Z'
        self.GenerationDateStr = genDate
        self.AcquisitionStart = l_AcquisitionDateTime[4:]

        self.OrbitNumber = xml_tools.get_xml_string_value(rootNode, "//Product_Information/Acquisition_Orbit_Number")
        self.SpectralContent = "XS"

        self.FilenamesProvider.initialize(l_hdrfilename, validate=validate, schema_path=schema_path)
        self.HeaderFilename = self.FilenamesProvider.m_hdrfilename
        self.SOLImageFileName = self.FilenamesProvider.m_SOLImageFileName
        self.SOLHeaderFileName = self.FilenamesProvider.m_SOLHeaderFileName
        self.VIEImageFileName = self.FilenamesProvider.m_VIEImageFileName
        self.VIEHeaderFileName = self.FilenamesProvider.m_VIEHeaderFileName

        self.HeaderHandler = VenusL1HeaderImageEarthExplorerXMLFileHandler(l_hdrfilename)
        # Estimation of the coordinate of the central point
        self.CenterCorner.longitude = self.HeaderHandler.get_useful_image_geo_coverage_center_corner_long()
        self.CenterCorner.latitude = self.HeaderHandler.get_useful_image_geo_coverage_center_corner_lat()
        self.CenterCorner.column = self.HeaderHandler.get_useful_image_geo_coverage_center_corner_column()
        self.CenterCorner.line = self.HeaderHandler.get_useful_image_geo_coverage_center_corner_line()

        # Initialize the Validity Start/Stop
        self.UTCValidityStart = l_AcquisitionDateTime
        self.UTCValidityStop = l_AcquisitionDateTime
        # Initialize the Viewing angles for each detectors (Zenith and Azimuth)
        self.ListOfViewingZenithAnglesPerBandAtL2CoarseResolution = []
        self.ListOfViewingAzimuthAnglesPerBandAtL2CoarseResolution = []

        l_meanViewingZenith = 0.0
        l_meanViewingAzimuth = 0.0
        l_count = 0.0
        l_BandsDefinitions = self._plugin.BandsDefinitions
        for det in l_BandsDefinitions.DetectorMap:
            l_Zenith = self.HeaderHandler.get_useful_image_center_view_angle_zenith(det)
            l_Azimuth = self.HeaderHandler.get_useful_image_center_view_angle_azimuth(det)
            l_meanViewingZenith += l_Zenith
            l_meanViewingAzimuth += l_Azimuth
            l_count += 1.0
            self.ListOfViewingZenithAnglesPerBandAtL2CoarseResolution.append(str(l_Zenith))
            self.ListOfViewingAzimuthAnglesPerBandAtL2CoarseResolution.append(str(l_Azimuth))
            self.ListOfViewingAnglesPerBandAtL2CoarseResolution.append(
              { "incidence_zenith_angle": str(l_Zenith),
                "incidence_azimuth_angle": str(l_Azimuth)
              })

        self.ViewingAngle = {
            "incidence_zenith_angle": str(l_meanViewingZenith / l_count),
            "incidence_azimuth_angle": str(l_meanViewingAzimuth / l_count)
            }

        # Fill the L2 resolution angles
        self.ListOfViewingAnglesPerBandAtL2Resolution = self.ListOfViewingAnglesPerBandAtL2CoarseResolution
        # Solar Angles
        self.SolarAngle = {
            "sun_zenith_angle": self.HeaderHandler.get_useful_image_image_center_solar_angle_zenith(),
            "sun_azimuth_angle": self.HeaderHandler.get_useful_image_image_center_solar_angle_azimuth()
        }

        # Detect pixel size and product size
        originX = xml_tools.get_xml_float_value(rootNode, "//Geo_Referencing_Information/Product_Coverage/Cartographic/Upper_Left_Corner/X")
        originY = xml_tools.get_xml_float_value(rootNode, "//Geo_Referencing_Information/Product_Coverage/Cartographic/Upper_Left_Corner/Y")
        pixSizeX = xml_tools.get_xml_float_value(rootNode, "//Product_Sampling/By_Column")
        pixSizeY = xml_tools.get_xml_float_value(rootNode, "//Product_Sampling/By_Line")
        nbCol = xml_tools.get_xml_int_value(rootNode, "//Image_Information/Size/Columns")
        nbRow = xml_tools.get_xml_int_value(rootNode, "//Image_Information/Size/Lines")
        gridColStep = (nbCol - 1.0) * pixSizeX
        gridRowStep = (nbRow - 1.0) * pixSizeY

        gridColStepStr = f"{gridColStep:.1f}"
        gridRowStepStr = f"{gridRowStep:.1f}"
        
        # Solar angle grid
        ula = xml_tools.get_xml_string_value(rootNode, "//Solar_Angles/Product/Upper_Left_Corner/Azimuth")
        ulz = xml_tools.get_xml_string_value(rootNode, "//Solar_Angles/Product/Upper_Left_Corner/Zenith")
        ura = xml_tools.get_xml_string_value(rootNode, "//Solar_Angles/Product/Upper_Right_Corner/Azimuth")
        urz = xml_tools.get_xml_string_value(rootNode, "//Solar_Angles/Product/Upper_Right_Corner/Zenith")
        lla = xml_tools.get_xml_string_value(rootNode, "//Solar_Angles/Product/Lower_Left_Corner/Azimuth")
        llz = xml_tools.get_xml_string_value(rootNode, "//Solar_Angles/Product/Lower_Left_Corner/Zenith")
        lra = xml_tools.get_xml_string_value(rootNode, "//Solar_Angles/Product/Lower_Right_Corner/Azimuth")
        lrz = xml_tools.get_xml_string_value(rootNode, "//Solar_Angles/Product/Lower_Right_Corner/Zenith")
        self.SolarAngleGrid["StepUnit"] = "m"
        self.SolarAngleGrid["ColStep"] = gridColStepStr
        self.SolarAngleGrid["RowStep"] = gridRowStepStr
        self.SolarAngleGrid["Azimuth"] = [ula+' '+ura, lla+' '+lra]
        self.SolarAngleGrid["Zenith"] = [ulz+' '+urz, llz+' '+lrz]
        
        # Viewing angle grids
        detectors = [1,2,3,4]
        self.ViewingAngleGrids = []
        l_pathView = "//List_of_Viewing_Angles/Viewing_Angles[@sn='{}']/Product/{}"
        for det in detectors:
            ula = xml_tools.get_xml_string_value(rootNode, l_pathView.format(det,"Upper_Left_Corner/Azimuth"))
            ulz = xml_tools.get_xml_string_value(rootNode, l_pathView.format(det,"Upper_Left_Corner/Zenith"))
            ura = xml_tools.get_xml_string_value(rootNode, l_pathView.format(det,"Upper_Right_Corner/Azimuth"))
            urz = xml_tools.get_xml_string_value(rootNode, l_pathView.format(det,"Upper_Right_Corner/Zenith"))
            lla = xml_tools.get_xml_string_value(rootNode, l_pathView.format(det,"Lower_Left_Corner/Azimuth"))
            llz = xml_tools.get_xml_string_value(rootNode, l_pathView.format(det,"Lower_Left_Corner/Zenith"))
            lra = xml_tools.get_xml_string_value(rootNode, l_pathView.format(det,"Lower_Right_Corner/Azimuth"))
            lrz = xml_tools.get_xml_string_value(rootNode, l_pathView.format(det,"Lower_Right_Corner/Zenith"))
            self.ViewingAngleGrids.append({
                "StepUnit":"m",
                "ColStep":gridColStepStr,
                "RowStep":gridRowStepStr,
                "Detector":str(det),
                "Azimuth":[ula+' '+ura, lla+' '+lra],
                "Zenith":[ulz+' '+urz, llz+' '+lrz]
                })

        # Set Area by resolution
        curArea = Area()
        curArea.origin = (
            f"{originX:.1f}",
            f"{originY:.1f}")
        curArea.spacing = (
            f"{pixSizeX:.1f}",
            f"{-pixSizeY:.1f}")
        curArea.size = (
            str(nbCol),
            str(nbRow))
        self.AreaByResolution = [curArea]

        # Gather spectral information
        l_resol = l_BandsDefinitions.ListOfL1Resolution[0]
        l_pathAk = "//List_of_Aks/Ak[@sk='{}']"
        l_pathPolarCoef = "//List_of_Polarization_Coefficients/Polarization_Coefficient[@sk='{}']"
        l_pathWavelenghCentral = "//List_of_Band_Central_Wavelength/Band_Central_Wavelength[@sk='{}']"
        self.SpectralInfo = []
        for b, bidx in l_BandsDefinitions.L1BandMap.items():
            bcode = l_BandsDefinitions.L1ListOfBandsMap[l_resol][bidx]
            self.SpectralInfo.append({
                "Band":b.replace("B0", "B"),
                "Ak":xml_tools.get_xml_string_value(rootNode,l_pathAk.format(bcode)) ,
                "PolarizationCoefficient":xml_tools.get_xml_string_value(rootNode,l_pathPolarCoef.format(bcode)),
                "WavelengthCentral": xml_tools.get_xml_string_value(rootNode,l_pathWavelenghCentral.format(bcode))
                })

        # 4.2: New
        # Set the L1 no data value
        self.L1NoData = self.HeaderHandler.get_no_data_value_as_int()
        # Set the reflectance quantification value
        self.ReflectanceQuantification = self.HeaderHandler.get_reflectance_quantification_value()
        # Computes the real value of the L1 NoData
        self.RealL1NoData = self.L1NoData * self.ReflectanceQuantification

        return True
    def read(self, product_info, app_handler, l2comm, dem, pReadL1Mode):
        """product_info,plugin, l2comm,mode

        :param product_info: L1ImageInformationsBase
        :param pReadL1Mode: ReadL1ModeType
        :return:
        """
        LOGGER.debug("Start Venus L1 ImageFileReader ...")
        product_filename = product_info.HeaderFilename
        LOGGER.debug("Start Venus L1 ImageFileReader with the filename: " +
                     product_filename)
        self._plugin.initialize(app_handler)
        self.headerHandler = product_info.HeaderHandler
        self._dem = dem
        # working_dir = get_working_directory("L1Read_", app_handler.get_working_directory())
        working_dir = app_handler.get_directory_manager(
        ).get_temporary_directory("L1Read_", do_always_remove=True)
        self.ReadL1Mode = pReadL1Mode
        self._GIPPL2COMMHandler = l2comm
        l_BandsDefinitions = self._plugin.BandsDefinitions
        # --------------------------------------
        # Initialize the Image filename provider
        l_FilenameProvider = VenusL1ImageFilenames()
        #product_info.FilenamesProvider
        IsValidSatellite = (l_FilenameProvider.initialize(product_filename)
                            is not False)
        if not IsValidSatellite:
            raise MajaPluginVenusException(
                "The file <{}> is not a valid Venus L1 product.".format(
                    product_filename))

        # *********************************************************************************************************
        # Register the Header o the Input image file
        # *********************************************************************************************************
        LOGGER.debug("Load the Venus L1 Header file : '" + product_filename +
                     "'")
        l_L1XMLHandler = HeaderImageEarthExplorerXMLFileHandler(
            product_filename)

        # *********************************************************************************************************
        # TOA Reader connection
        # *********************************************************************************************************
        l_L1NoData = l_L1XMLHandler.get_no_data_value_as_double()
        l_ReflectanceQuantificationValue = l_L1XMLHandler.get_reflectance_quantification_value(
        )
        l_reflectanceMultiplicationValues = []

        if xml_tools.as_bool(l2comm.get_value("CalAdjustOption")):
            l_factor = xml_tools.as_float_list(
                l2comm.get_value("CalAdjustFactor"))
            if len(l_factor) != (VenusL1ImageFileReader.TOALastChannel -
                                 VenusL1ImageFileReader.TOAFirstChannel + 1):
                raise MajaPluginVenusException(
                    "Not the same number of Calibration coeffs than L1 bands")
            for i in range(0, len(l_factor)):
                l_reflectanceMultiplicationValues.append(
                    l_ReflectanceQuantificationValue * l_factor[i])
        else:
            for i in range(VenusL1ImageFileReader.TOALastChannel -
                           VenusL1ImageFileReader.TOAFirstChannel + 1):
                l_reflectanceMultiplicationValues.append(
                    l_ReflectanceQuantificationValue)

        l_RealL1NoData = l_L1NoData * l_ReflectanceQuantificationValue

        # *********************************************************************************************************
        # L1 TOA image pipeline connection
        # *********************************************************************************************************
        if not l_FilenameProvider.m_TOAImageFileName:
            raise MajaPluginVenusException(
                "VenusL1ImageFileReader : The TOA image does not exist !")

        tmp_l1toa_roi = os.path.join(working_dir, "l1toa_roi.tif")
        app_l1_toa_roi = extract_roi(l_FilenameProvider.m_TOAImageFileName, [
            channel
            for channel in range(VenusL1ImageFileReader.TOALastChannel -
                                 VenusL1ImageFileReader.TOAFirstChannel + 1)
        ],
                                     tmp_l1toa_roi,
                                     write_output=False)
        self._l1toa_pipeline.add_otb_app(app_l1_toa_roi)

        tmp_sat_roi = os.path.join(working_dir, "sat_roi.tif")
        app_sat_roi = extract_roi(l_FilenameProvider.m_TOAImageFileName,
                                  [VenusL1ImageFileReader.SATChannel - 1],
                                  tmp_sat_roi,
                                  write_output=False)
        self._sat_pipeline.add_otb_app(app_sat_roi)
        #Multiply scalar by quantif
        tmp_l1toa_mbs = os.path.join(working_dir, "l1toa.tif")
        app_l1toa_mbs = multiply_by_scalar(
            app_l1_toa_roi.getoutput().get("out"),
            l_ReflectanceQuantificationValue,
            output_image=tmp_l1toa_mbs,
            write_output=False)
        self._l1toa_pipeline.add_otb_app(app_l1toa_mbs)
        # update all extract ROI in once
        write_images([
            app_l1toa_mbs.getoutput().get("out"),
            app_sat_roi.getoutput().get("out")
        ], [tmp_l1toa_mbs, tmp_sat_roi])

        self._toascalar = tmp_l1toa_mbs

        # *********************************************************************************************************
        # L1 PIX image pipeline connection
        # *********************************************************************************************************
        tmp_l1pix_roi = os.path.join(working_dir, "l1pix.tif")
        app_l1_pix_roi = extract_roi(l_FilenameProvider.m_TOAImageFileName,
                                     [VenusL1ImageFileReader.PIXChannel - 1],
                                     tmp_l1pix_roi + ":uint16",
                                     write_output=False)
        self._l1pix_pipeline.add_otb_app(app_l1_pix_roi)
        self._l1pix = app_l1_pix_roi.getoutput().get("out")

        # *********************************************************************************************************
        #                                     START READ L1 for ALGORITHMS
        # *********************************************************************************************************
        if pReadL1Mode == ReadL1Mode.READ_L1_MODE_FOR_ALGORITHMS:
            # *********************************************************************************************************
            # L2 PIX image pipeline connection
            # *********************************************************************************************************
            # LAIG-FA-MAC-131720-CS : New for 4.2
            # Before resample, binarytovector -> resample -> vectortobinary
            tmp_l2pix_bin2vec = os.path.join(working_dir, "l2pix_bin2vec.tif")
            param_l2pix_bin2vec = {
                "im": app_l1_pix_roi.getoutput().get("out"),
                "out": tmp_l2pix_bin2vec + ":uint8",
                "nbcomp": VenusL1ImageFileReader.PIXNumberOfComponentsPerPixel
            }
            app_l2pix_bin2vec = OtbAppHandler("BinaryToVector",
                                              param_l2pix_bin2vec,
                                              write_output=False)
            self._l2pix_pipeline.add_otb_app(app_l2pix_bin2vec)

            tmp_l2pix_resample = os.path.join(working_dir,
                                              "l2pix_resample.tif")
            app_l2pix_resample = resample(
                app_l2pix_bin2vec.getoutput().get("out"),
                self._dem.ALTList[0],
                tmp_l2pix_resample,
                OtbResampleType.LINEAR_WITH_RADIUS,
                padradius=4.0,
                threshold=0.0,
                write_output=False)
            self._l2pix_pipeline.add_otb_app(app_l2pix_resample)
            #L2 PIX is concatenate
            tmp_l2pix_binconcat = os.path.join(working_dir, "l2pix.tif")
            param_l2pix_binconcat = {
                "im": app_l2pix_resample.getoutput().get("out"),
                "out": tmp_l2pix_binconcat + ":uint16"
            }
            app_l2pix_binconcat = OtbAppHandler("BinaryConcatenate",
                                                param_l2pix_binconcat,
                                                write_output=False)
            self._l2pix = app_l2pix_binconcat.getoutput().get("out")
            self._l2pix_pipeline.add_otb_app(app_l2pix_binconcat)

            # *********************************************************************************************************
            # L2 EDG image pipeline connection
            # *********************************************************************************************************
            tmp_edg_thresholder = os.path.join(working_dir,
                                               "edg_thresholder1.tif")
            param_edg_thresholder1 = {
                "im": self._toascalar,
                "thresholdvalue": l_RealL1NoData,
                "equalvalue": 255,
                "outsidevalue": 0,
                "out": tmp_edg_thresholder + ":uint8"
            }
            app_edg_thresholder1 = OtbAppHandler("OneBandEqualThreshold",
                                                 param_edg_thresholder1,
                                                 write_output=True)
            self._edg_pipeline.add_otb_app(app_edg_thresholder1)

            tmp_edg_resample = os.path.join(working_dir, "edg_resample.tif")
            app_edg_resample = resample(
                app_edg_thresholder1.getoutput().get("out"),
                self._dem.ALTList[0],
                tmp_edg_resample,
                OtbResampleType.BCO,
                padradius=4.0,
                write_output=True)
            self._edg_pipeline.add_otb_app(app_edg_resample)

            # Threshold the output
            out_sub_edg = os.path.join(working_dir, "edg_thresholder2.tif")
            param_edg_thresholder2 = {
                "im": app_edg_resample.getoutput().get("out"),
                "thresholdvalue": 0,
                "equalvalue": 1,
                "outsidevalue": 0,
                "out": out_sub_edg + ":uint8"
            }
            app_edg_thresholder2 = OtbAppHandler("OneBandEqualThreshold",
                                                 param_edg_thresholder2,
                                                 write_output=True)
            self._edg_pipeline.add_otb_app(app_edg_thresholder2)

            # *********************************************************************************************************
            # IPEDGSub image pipeline connection
            # *********************************************************************************************************
            tmp_edgsub_resample = os.path.join(working_dir,
                                               "edgsub_resample.tif")
            app_edgsub_resample = resample(
                app_edg_thresholder1.getoutput().get("out"),
                self._dem.ALC,
                tmp_edgsub_resample,
                OtbResampleType.LINEAR_WITH_RADIUS,
                padradius=12.0,
                write_output=True)
            self._edg_pipeline.add_otb_app(app_edgsub_resample)
            # Threshold the output
            out_sub_edgsub = os.path.join(working_dir, "edgsub.tif")
            param_edgsub_thresholder2 = {
                "im": app_edgsub_resample.getoutput().get("out"),
                "thresholdvalue": 0,
                "equalvalue": 0,
                "outsidevalue": 1,
                "out": out_sub_edgsub + ":uint8"
            }
            app_edgsub_thresholder2 = OtbAppHandler("OneBandEqualThreshold",
                                                    param_edgsub_thresholder2,
                                                    write_output=True)
            self._edgsub = app_edgsub_thresholder2.getoutput().get("out")
            self._edg_pipeline.add_otb_app(app_edgsub_thresholder2)

            # *********************************************************************************************************
            # L2 TOA image pipeline connection
            # *********************************************************************************************************
            tmp_l2toa_resample = os.path.join(working_dir,
                                              "l2toa_resample.tif")
            app_l2toa_resample = resample(self._toascalar,
                                          self._dem.ALTList[0],
                                          tmp_l2toa_resample,
                                          OtbResampleType.BCO,
                                          padradius=4.0,
                                          write_output=False)
            self._l2toa_pipeline.add_otb_app(app_l2toa_resample)
            l2toa_list = []
            l_toathresholdminvalue = 0
            l_toathresholvalue = -10

            #Apply EDG mask on l2toa resampled
            tmp_l2toa = os.path.join(working_dir, "l2toa.tif")
            app_l2toa = apply_mask(app_l2toa_resample.getoutput().get("out"),
                                   app_edg_thresholder2.getoutput().get("out"),
                                   l_toathresholvalue,
                                   tmp_l2toa,
                                   write_output=False)
            self._l2toa = app_l2toa.getoutput().get("out")
            self._l2toa_pipeline.add_otb_app(app_l2toa)

            # *********************************************************************************************************
            # TOA Sub image pipeline connection
            # *********************************************************************************************************
            tmp_toasub_resample = os.path.join(working_dir,
                                               "toasub_resample.tif")
            app_toasub_resample = resample(self._toascalar,
                                           self._dem.ALC,
                                           tmp_toasub_resample,
                                           OtbResampleType.LINEAR_WITH_RADIUS,
                                           padradius=4.0,
                                           write_output=True)
            self._l2toa_pipeline.add_otb_app(app_toasub_resample)

            # Threshold the output
            out_edgsub_threshold = os.path.join(working_dir,
                                                "edgsubthreshold.tif")
            param_edgsub_threshold = {
                "im": app_edgsub_resample.getoutput().get("out"),
                "thresholdvalue": 0,
                "equalvalue": 1,
                "outsidevalue": 0,
                "out": out_edgsub_threshold + ":uint8"
            }
            app_edgsub_threshold = OtbAppHandler("OneBandEqualThreshold",
                                                 param_edgsub_threshold,
                                                 write_output=True)
            self._edg_pipeline.add_otb_app(app_edgsub_threshold)

            tmp_l2subtoa = os.path.join(working_dir, "toasub.tif")
            app_l2subtoa = apply_mask(
                app_toasub_resample.getoutput().get("out"),
                app_edgsub_threshold.getoutput().get("out"),
                l_toathresholvalue,
                tmp_l2subtoa,
                write_output=True)
            self._toasub = app_l2subtoa.getoutput().get("out")
            self._l2toa_pipeline.add_otb_app(app_l2subtoa)

            # *********************************************************************************************************
            # L2EDG - Actualization of the L2 edge mask
            # *********************************************************************************************************
            #tmp_l2edg_threshold = os.path.join(working_dir, "l2edg_threshold.tif")
            #app_l2edg_threshold = binary_threshold(self._edgsub,
            #                                         lower_threshold=0,
            #                                         inside_value=1000,
            #                                         outside_value=0,
            #                                         output_image=tmp_l2edg_threshold + ":uint8",
            #                                         write_output=True)
            #self._l2edg_pipeline.add_otb_app(app_l2edg_threshold)
            tmp_l2edg_resample = os.path.join(working_dir, "l2edg.tif")
            app_l2edg_resample = resample(self._edgsub,
                                          self._dem.ALTList[0],
                                          tmp_l2edg_resample + ":uint8",
                                          OtbResampleType.LINEAR,
                                          padradius=4.0,
                                          threshold=0.001,
                                          write_output=True)
            self._l2edg = app_l2edg_resample.getoutput().get("out")
            self._l2edg_pipeline.add_otb_app(app_l2edg_resample)

            # *********************************************************************************************************
            # SAT image pipeline connection
            # *********************************************************************************************************
            tmp_sat_bin2vec = os.path.join(working_dir, "sat_bin2vec.tif")
            param_sat_bin2vec = {
                "im": tmp_sat_roi,
                "out": tmp_sat_bin2vec + ":uint8",
                "nbcomp": VenusL1ImageFileReader.SATNumberOfComponentsPerPixel
            }
            app_sat_bin2vec = OtbAppHandler("BinaryToVector",
                                            param_sat_bin2vec,
                                            write_output=False)
            self._sat_pipeline.add_otb_app(app_sat_bin2vec)

            l_l2sat_thresholdvalue = l2comm.get_value_f("SaturationThreshold")

            tmp_sat_resample = os.path.join(working_dir, "l2sat.tif")
            app_sat_resample = resample(app_sat_bin2vec.getoutput().get("out"),
                                        self._dem.ALTList[0],
                                        tmp_sat_resample + ":uint8",
                                        OtbResampleType.BCO,
                                        padradius=4.0,
                                        threshold=l_l2sat_thresholdvalue,
                                        write_output=False)
            self._l2sat = app_sat_resample.getoutput().get("out")
            self._sat_pipeline.add_otb_app(app_sat_resample)

            # *********************************************************************************************************
            # IPSAT Sub image pipeline connection
            # *********************************************************************************************************
            l_sat_subthresholdvalue = l2comm.get_value_f(
                "SaturationThresholdSub")
            tmp_satsub_resample = os.path.join(working_dir, "satsub.tif")
            app_satsub_resample = resample(
                app_sat_bin2vec.getoutput().get("out"),
                self._dem.ALC,
                tmp_satsub_resample + ":uint8",
                OtbResampleType.LINEAR_WITH_RADIUS,
                padradius=4.0,
                threshold=l_sat_subthresholdvalue)
            self._satsub = app_satsub_resample.getoutput().get("out")
            self._sat_pipeline.add_otb_app(app_satsub_resample)

            # *********************************************************************************************************
            # CLA image pipeline connection
            # *********************************************************************************************************

            LOGGER.debug(
                "VenusL1ImageFileReader::Initialize - CLA image filename: '" +
                l_FilenameProvider.m_CLAImageFileName + "'")
            if not l_FilenameProvider.m_CLAImageFileName:
                raise MajaPluginVenusException(
                    "The CLA image does not exist !! ")
            self._cla = l_FilenameProvider.m_CLAImageFileName

            # *********************************************************************************************************
            # SOL1 image pipeline connection
            # *********************************************************************************************************
            LOGGER.debug(
                "VenusL1ImageFileReader::Initialize - SOL image filename: '" +
                l_FilenameProvider.m_SOLImageFileName + "'")
            if not l_FilenameProvider.m_SOLImageFileName:
                raise MajaPluginVenusException(
                    "The SOL image does not exist !! ")
            mtdat = GdalDatasetInfo(l_FilenameProvider.m_TOAImageFileName)
            toaarea = Area()
            toaarea.size = mtdat.size
            toaarea.origin = mtdat.origin
            toaarea.spacing = mtdat.pixel_size
            l_SOLHeaderHandler = HeaderImageEarthExplorerXMLFileHandler(
                l_FilenameProvider.m_SOLHeaderFileName)
            l_L1SOLSubsamplingFactor = l_SOLHeaderHandler.get_sampling_factor()
            LOGGER.debug(l_L1SOLSubsamplingFactor)
            # SOL1
            tmp_sol1_b1 = os.path.join(working_dir, "sol1_B1.tif")
            app_sol1_b1 = multiply_by_scalar(
                l_FilenameProvider.m_SOLImageFileName +
                VenusL1ImageFileReader.SOL1ChannelB1,
                toaarea.spacing[0],
                tmp_sol1_b1,
                write_output=False)
            self._sol_pipeline.add_otb_app(app_sol1_b1)

            tmp_sol1_b2 = os.path.join(working_dir, "sol1_B2.tif")
            app_sol1_b2 = multiply_by_scalar(
                l_FilenameProvider.m_SOLImageFileName +
                VenusL1ImageFileReader.SOL1ChannelB2,
                (-1) * toaarea.spacing[1],
                tmp_sol1_b2,
                write_output=False)
            self._sol_pipeline.add_otb_app(app_sol1_b2)
            tmp_sol1_concat = os.path.join(working_dir, "sol1_concat.tif")
            param_sol1_concat = {
                "il": [
                    app_sol1_b1.getoutput().get("out"),
                    app_sol1_b2.getoutput().get("out")
                ],
                "out":
                tmp_sol1_concat
            }
            app_sol1_concat = OtbAppHandler("ConcatenateDoubleImages",
                                            param_sol1_concat)
            update_projection(l_FilenameProvider.m_TOAImageFileName,
                              app_sol1_concat.getoutput().get("out"),
                              l_L1SOLSubsamplingFactor)

            self._sol_pipeline.add_otb_app(app_sol1_concat)

            tmp_sol1_resample = os.path.join(working_dir, "sol1.tif")
            app_sol1_resample = resample(
                app_sol1_concat.getoutput().get("out"),
                self._dem.ALC,
                tmp_sol1_resample,
                OtbResampleType.LINEAR,
                padradius=4.0)
            self._sol1 = app_sol1_resample.getoutput().get("out")
            self._sol_pipeline.add_otb_app(app_sol1_resample)

            # SOL2
            tmp_sol2_b1 = os.path.join(working_dir, "sol2_B1.tif")
            app_sol2_b1 = multiply_by_scalar(
                l_FilenameProvider.m_SOLImageFileName +
                VenusL1ImageFileReader.SOL2ChannelB1,
                toaarea.spacing[0],
                tmp_sol2_b1,
                write_output=False)
            self._sol_pipeline.add_otb_app(app_sol2_b1)
            tmp_sol2_b2 = os.path.join(working_dir, "sol2_B2.tif")
            app_sol2_b2 = multiply_by_scalar(
                l_FilenameProvider.m_SOLImageFileName +
                VenusL1ImageFileReader.SOL2ChannelB2,
                (-1) * toaarea.spacing[1],
                tmp_sol2_b2,
                write_output=False)
            self._sol_pipeline.add_otb_app(app_sol2_b2)

            tmp_sol2_concat = os.path.join(working_dir, "sol2_concat.tif")
            param_sol2_concat = {
                "il": [
                    app_sol2_b1.getoutput().get("out"),
                    app_sol2_b2.getoutput().get("out")
                ],
                "out":
                tmp_sol2_concat
            }
            app_sol2_concat = OtbAppHandler("ConcatenateDoubleImages",
                                            param_sol2_concat)
            update_projection(l_FilenameProvider.m_TOAImageFileName,
                              app_sol2_concat.getoutput().get("out"),
                              l_L1SOLSubsamplingFactor)
            self._sol_pipeline.add_otb_app(app_sol2_concat)

            tmp_sol2_resample = os.path.join(working_dir, "sol2.tif")
            app_sol2_resample = resample(
                app_sol2_concat.getoutput().get("out"),
                self._dem.ALC,
                tmp_sol2_resample,
                OtbResampleType.LINEAR,
                padradius=4.0)
            self._sol2 = app_sol2_resample.getoutput().get("out")
            self._sol_pipeline.add_otb_app(app_sol2_resample)

            # *********************************************************************************************************
            # DTMVIE image pipeline connection
            # *********************************************************************************************************
            LOGGER.debug(
                "VenusL1ImageFileReader::Initialize - VIE image filename: '" +
                l_FilenameProvider.m_VIEImageFileName + "'")

            l_VIEHeaderHandler = HeaderImageEarthExplorerXMLFileHandler(
                l_FilenameProvider.m_VIEHeaderFileName)
            l_L1VIESubsamplingFactor = l_VIEHeaderHandler.get_sampling_factor()
            LOGGER.debug(l_L1VIESubsamplingFactor)

            tmp_vieb5b1_mult = os.path.join(working_dir, "vie5b1_mult.tif")
            app_vieb5b1_mult = multiply_by_scalar(
                l_FilenameProvider.m_VIEImageFileName +
                VenusL1ImageFileReader.VIEB5ChannelB1,
                toaarea.spacing[0],
                tmp_vieb5b1_mult,
                write_output=False)
            self._dtmvie_pipeline.add_otb_app(app_vieb5b1_mult)

            tmp_vieb5b2_mult = os.path.join(working_dir, "vie5b2_mult.tif")
            app_vieb5b2_mult = multiply_by_scalar(
                l_FilenameProvider.m_VIEImageFileName +
                VenusL1ImageFileReader.VIEB5ChannelB2,
                (-1) * toaarea.spacing[1],
                tmp_vieb5b2_mult,
                write_output=False)
            self._dtmvie_pipeline.add_otb_app(app_vieb5b2_mult)

            tmp_vieb6b1_mult = os.path.join(working_dir, "vie6b1_mult.tif")
            app_vieb6b1_mult = multiply_by_scalar(
                l_FilenameProvider.m_VIEImageFileName +
                VenusL1ImageFileReader.VIEB6ChannelB1,
                toaarea.spacing[0],
                tmp_vieb6b1_mult,
                write_output=False)
            self._dtmvie_pipeline.add_otb_app(app_vieb6b1_mult)

            tmp_vieb6b2_mult = os.path.join(working_dir, "vie6b2_mult.tif")
            app_vieb6b2_mult = multiply_by_scalar(
                l_FilenameProvider.m_VIEImageFileName +
                VenusL1ImageFileReader.VIEB6ChannelB2,
                (-1) * toaarea.spacing[1],
                tmp_vieb6b2_mult,
                write_output=False)
            self._dtmvie_pipeline.add_otb_app(app_vieb6b2_mult)

            tmp_dtmvie_concat = os.path.join(working_dir, "dtmvie_concat.tif")
            param_dtmvie_concat = {
                "il": [
                    app_vieb5b1_mult.getoutput().get("out"),
                    app_vieb5b2_mult.getoutput().get("out"),
                    app_vieb6b1_mult.getoutput().get("out"),
                    app_vieb6b2_mult.getoutput().get("out")
                ],
                "out":
                tmp_dtmvie_concat
            }
            app_dtmvie_concat = OtbAppHandler("ConcatenateDoubleImages",
                                              param_dtmvie_concat)
            update_projection(l_FilenameProvider.m_TOAImageFileName,
                              app_dtmvie_concat.getoutput().get("out"),
                              l_L1VIESubsamplingFactor)
            self._dtmvie_pipeline.add_otb_app(app_dtmvie_concat)

            tmp_dtmvie_resample = os.path.join(working_dir, "dtmvie.tif")
            app_dtmvie_resample = resample(
                app_dtmvie_concat.getoutput().get("out"),
                self._dem.ALC,
                tmp_dtmvie_resample,
                OtbResampleType.LINEAR,
                padradius=4.0)
            self._dtmvie = app_dtmvie_resample.getoutput().get("out")
            self._dtmvie_pipeline.add_otb_app(app_dtmvie_resample)

            # *********************************************************************************************************
            # VIE image pipeline connection
            # *********************************************************************************************************
            tmp_shadowvie_concat = os.path.join(working_dir,
                                                "shadowvie_concat.tif")
            param_shadowvie_concat = {
                "il": [
                    app_vieb5b1_mult.getoutput().get("out"),
                    app_vieb5b2_mult.getoutput().get("out")
                ],
                "out":
                tmp_shadowvie_concat
            }
            app_shadowvie_concat = OtbAppHandler("ConcatenateDoubleImages",
                                                 param_shadowvie_concat)
            self._shadowvie_pipeline.add_otb_app(app_shadowvie_concat)
            update_projection(l_FilenameProvider.m_TOAImageFileName,
                              app_shadowvie_concat.getoutput().get("out"),
                              l_L1VIESubsamplingFactor)
            tmp_shadowvie_resample = os.path.join(working_dir, "shadowvie.tif")
            app_shadowvie_resample = resample(
                app_shadowvie_concat.getoutput().get("out"),
                self._dem.ALC,
                tmp_shadowvie_resample,
                OtbResampleType.LINEAR,
                padradius=4.0)
            self._shadowvie = app_shadowvie_resample.getoutput().get("out")
            self._shadowvie_pipeline.add_otb_app(app_shadowvie_resample)

            # Fill the datas
            self.dict_of_vals["IPEDGSubOutput"] = self._edgsub
            self.dict_of_vals["SOL1Image"] = self._sol1
            self.dict_of_vals["SOL2Image"] = self._sol2
            self.dict_of_vals["DTMVIEImage"] = self._dtmvie
            self.dict_of_vals["IPTOASubOutput"] = self._toasub

            self.dict_of_vals["L2TOAImageList"] = [self._l2toa]
            self.dict_of_vals["ViewingZenithMeanMap"] = self._meanZenithMap
            self.dict_of_vals["ViewingAzimuthMeanMap"] = self._meanAzimuthMap
            self.dict_of_vals["CLAImage"] = self._cla
            self.dict_of_vals["IPSATSubOutput"] = self._satsub
            self.dict_of_vals["ShadowVIEImage"] = self._shadowvie
            if self._plugin.CirrusMasking:
                l_CirrusBandCode = l2comm.get_value("CirrusBandCode")
                l_CirrusBandIdx = self._plugin.BandsDefinitions.get_band_id_in_l2_coarse(
                    l_CirrusBandCode)
                tmp = os.path.join(working_dir, "l1toacirrus.tif")
                app = extract_roi(self._toascalar, [l_CirrusBandIdx - 1], tmp)
                self.dict_of_vals["L1TOACirrusImage"] = app.getoutput().get(
                    "out")
            self.dict_of_vals["L2EDGOutputList"] = [self._l2edg]
            self.dict_of_vals["L2SATImageList"] = [self._l2sat]
            self.dict_of_vals["L2PIXImageList"] = [self._l2pix]
            self.dict_of_vals["L1PIXImageList"] = [self._l1pix]
            self.dict_of_vals["L1TOAImageList"] = [self._toascalar]
    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