Пример #1
0
    def _pre_process_sar(self, resolution: float = None) -> dict:
        """
        Pre-process SAR data (geocoding...)

        Args:
            resolution (float): Resolution

        Returns:
            dict: Dictionary containing {band: path}
        """
        out = {}

        # Create target dir (tmp dir)
        with tempfile.TemporaryDirectory() as tmp_dir:
            # Set command as a list
            target_file = os.path.join(tmp_dir, f"{self.condensed_name}")

            # Use dimap for speed and security (ie. GeoTiff's broken georef)
            pp_target = f"{target_file}"
            pp_dim = pp_target + ".dim"

            # Pre-process graph
            if PP_GRAPH not in os.environ:
                sat = "s1" if self.sat_id == Platform.S1.name else "sar"
                spt = "grd" if self.sar_prod_type == SarProductType.GDRG else "cplx"
                pp_graph = os.path.join(utils.get_data_dir(),
                                        f"{spt}_{sat}_preprocess_default.xml")
            else:
                pp_graph = os.environ[PP_GRAPH]
                if not os.path.isfile(pp_graph) or not pp_graph.endswith(
                        ".xml"):
                    FileNotFoundError(f"{pp_graph} cannot be found.")

            # Command line
            if not os.path.isfile(pp_dim):
                def_res = float(os.environ.get(SAR_DEF_RES, self.resolution))
                res_m = resolution if resolution else def_res
                res_deg = res_m / 10.0 * 8.983152841195215e-5  # Approx
                cmd_list = snap.get_gpt_cli(
                    pp_graph,
                    [
                        f"-Pfile={strings.to_cmd_string(self._snap_path)}",
                        f"-Pout={pp_dim}",
                        f"-Pcrs={self.crs()}",
                        f"-Pres_m={res_m}",
                        f"-Pres_deg={res_deg}",
                    ],
                    display_snap_opt=LOGGER.level == logging.DEBUG,
                )

                # Pre-process SAR images according to the given graph
                LOGGER.debug("Pre-process SAR image")
                misc.run_cli(cmd_list)

            # Convert DIMAP images to GeoTiff
            for pol in self.pol_channels:
                # Speckle image
                out[sbn.from_value(pol)] = self._write_sar(pp_dim, pol.value)

        return out
Пример #2
0
def test_utils():
    root_dir = os.path.abspath(os.path.join(__file__, "..", "..", ".."))
    # Root directory
    src_dir = os.path.join(root_dir, "eoreader")
    data_dir = os.path.join(src_dir, "data")
    assert utils.get_root_dir() == root_dir
    assert utils.get_src_dir() == src_dir
    assert utils.get_data_dir() == data_dir
Пример #3
0
    def _run_s3_gpt_cli(self, out_dim: str, resolution: float = None) -> list:
        """
        Construct GPT command line to reproject S3 images and quality flags

        Args:
            out_dim (str): Out DIMAP name
            resolution (float): Resolution

        Returns:
            list: Processed band name
        """
        # Default resolution
        def_res = os.environ.get(S3_DEF_RES, self.resolution)

        # Construct GPT graph
        graph_path = os.path.join(utils.get_data_dir(), "preprocess_s3.xml")
        snap_bands = ",".join([
            self._get_snap_band_name(band)
            for band, band_nb in self.band_names.items() if band_nb
        ])
        if self._instrument_name == S3Instrument.OLCI:
            sensor = "OLCI"
            fmt = "Sen3"
            snap_bands += ",quality_flags"
        else:
            sensor = "SLSTR_500m"
            fmt = "Sen3_SLSTRL1B_500m"
            exception_bands = ",".join([
                self._get_slstr_quality_flags_name(band)
                for band, band_nb in self.band_names.items() if band_nb
            ])
            snap_bands += f",{exception_bands},cloud_an,cloud_in"

        # Run GPT graph
        cmd_list = snap.get_gpt_cli(
            graph_path,
            [
                f"-Pin={strings.to_cmd_string(self.path)}",
                f"-Pbands={snap_bands}",
                f"-Psensor={sensor}",
                f"-Pformat={fmt}",
                f"-Pno_data={self._snap_no_data}",
                f"-Pres_m={resolution if resolution else def_res}",
                f"-Pout={strings.to_cmd_string(out_dim)}",
            ],
            display_snap_opt=LOGGER.level == logging.DEBUG,
        )
        LOGGER.debug("Converting %s", self.name)
        misc.run_cli(cmd_list)

        return snap_bands.split(",")
Пример #4
0
    def _despeckle_sar(self, band: sbn) -> str:
        """
        Pre-process SAR data (geocode...)

        Args:
            band (sbn): Band to despeckle

        Returns:
            str: Despeckled path
        """
        # Create target dir (tmp dir)
        with tempfile.TemporaryDirectory() as tmp_dir:
            # Out files
            target_file = os.path.join(tmp_dir, f"{self.condensed_name}")
            dspk_dim = target_file + ".dim"

            # Despeckle graph
            if DSPK_GRAPH not in os.environ:
                dspk_graph = os.path.join(utils.get_data_dir(),
                                          "sar_despeckle_default.xml")
            else:
                dspk_graph = os.environ[DSPK_GRAPH]
                if not os.path.isfile(dspk_graph) or not dspk_graph.endswith(
                        ".xml"):
                    FileNotFoundError(f"{dspk_graph} cannot be found.")

            # Create command line and run it
            if not os.path.isfile(dspk_dim):
                path = self.get_band_paths([band])[band]
                cmd_list = snap.get_gpt_cli(
                    dspk_graph,
                    [f"-Pfile={path}", f"-Pout={dspk_dim}"],
                    display_snap_opt=False,
                )

                # Pre-process SAR images according to the given graph
                LOGGER.debug("Despeckle SAR image")
                misc.run_cli(cmd_list)

            # Convert DIMAP images to GeoTiff
            out = self._write_sar(dspk_dim, band.value, dspk=True)

        return out