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gportal.file

GCOMCFile

GCOM-C HDF5 file reader.

Attributes:

Name Type Description
h5_file h5py.File

h5py.File object.
Source code in gportal/file/gcomc.py 
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class GCOMCFile:
    """GCOM-C HDF5 file reader.

    Attributes:
        h5_file: [`h5py.File`][h5py.File] object.
    """

    def __init__(self, h5_file: h5py.File):
        self.h5_file: h5py.File = h5_file

    @classmethod
    def open(cls, path: str) -> "GCOMCFile":
        """Opens a GCOM-C HDF5 file.

        Args:
            path: Path to a GCOM-C HDF5 file.

        Returns:
            An instance of [`GCOMCFile`][gportal.file.gcomc.GCOMCFile].
        """
        h5_file = h5py.File(path)

        if "Global_attributes" not in h5_file:
            raise ValueError("Not a GCOM-C file.")

        satellite = h5_file["Global_attributes"].attrs.get("Satellite")
        if not satellite or satellite[0] != b"Global Change Observation Mission - Climate (GCOM-C)":
            raise ValueError("Not a GCOM-C file.")

        return cls(h5_file)

    def close(self) -> None:
        """Closes the file."""
        self.h5_file.close()

    def __enter__(self):
        return self

    def __exit__(self, exc_type, exc_value, traceback):
        self.close()

    @property
    def attrs(self) -> dict[str, Union[int, float, str]]:
        """Global attributes."""
        return {
            k: v[0].decode() if isinstance(v[0], bytes) else v[0]
            for k, v in self.h5_file["Global_attributes"].attrs.items()
        }

    @property
    def granule_id(self) -> str:
        """Granule ID."""
        return Path(str(self.attrs["Product_file_name"])).stem

    @property
    def geometry_attrs(self) -> dict[str, Union[int, float, str]]:
        """Geometry data attributes."""
        return {
            k: v[0].decode() if isinstance(v[0], bytes) else v[0]
            for k, v in self.h5_file["Geometry_data"].attrs.items()
        }

    @property
    def geometry_data(self) -> dict[str, h5py.Dataset]:
        """Geometry data."""
        geometry_data = self.h5_file["Geometry_data"]

        if not isinstance(geometry_data, h5py.Group):
            raise GCOMCFileError(f"Geometry_data is not a group: {type(geometry_data)}")

        return {k: v for k, v in geometry_data.items()}

    @property
    def image_data(self) -> dict[str, h5py.Dataset]:
        """Image data."""
        image_data = self.h5_file["Image_data"]

        if not isinstance(image_data, h5py.Group):
            raise GCOMCFileError(f"Image_data is not a group: {type(image_data)}")

        return {k: v for k, v in image_data.items()}

    def save_as_geotiff(self, output_dir: str = ".", targets: Optional[list[str]] = None) -> dict[str, str]:
        """Saves the file as GeoTIFF.

        Args:
            output_dir: Directory to save the GeoTIFF files.
            targets: Image data names to save. If not provided, all image data are saved.

        Returns:
            Dictionary of image data names and paths to the saved GeoTIFF files.
        """
        if targets is None:
            targets = [k for k in self.image_data.keys()]

        results = {}
        for image_data_name in targets:
            dataset = self.image_data[image_data_name]
            if dataset.ndim != 2:
                # Skip not 2D data, like Line_tai93.
                continue

            output_path = Path(output_dir) / f"{self.granule_id}-{image_data_name}.tif"
            results[image_data_name] = str(output_path)

            raw_error_dn = dataset.attrs.get("Error_DN")
            error_dn = raw_error_dn[0] if isinstance(raw_error_dn, np.ndarray) else None

            raw_offset = dataset.attrs.get("Offset")
            offset = raw_offset[0] if isinstance(raw_offset, np.ndarray) else 0

            raw_slope = dataset.attrs.get("Slope")
            slope = raw_slope[0] if isinstance(raw_slope, np.ndarray) else 1

            crs, transform, gcps = self._build_projection(dataset.shape)

            with rasterio.open(
                output_path,
                mode="w",
                driver="GTiff",
                width=dataset.shape[1],
                height=dataset.shape[0],
                count=1,
                dtype=dataset.dtype,
                crs=crs,
                transform=transform,
                nodata=error_dn,
            ) as dst:
                dst.offsets = (offset,)
                dst.scales = (slope,)

                if gcps is not None:
                    dst.gcps = (gcps, crs)

                dst.write(dataset, 1)

        return results

    def save_as_multiband_geotiff(
        self,
        bands: list[str],
        output_path: Optional[Union[str, Path]] = None,
    ) -> str:
        """Saves the file as a multiband GeoTIFF.

        Args:
            bands: List of image data names for each band.
            output_path: Path to save the GeoTIFF file.

        Returns:
            Path to the saved GeoTIFF file.
        """
        datasets = [self.image_data[band] for band in bands]

        shape = datasets[0].shape
        for dataset in datasets[1:]:
            if dataset.shape != shape:
                raise ValueError("All bands must have the same shape.")

        if output_path is None:
            output_path = Path.cwd() / f"{self.granule_id}.tif"

        dtypes = []
        error_dns = []
        offsets = []
        scales = []
        crs = None
        transform = None
        gcps = None
        for i, dataset in enumerate(datasets):
            dtypes.append(dataset.dtype)

            raw_error_dn = dataset.attrs.get("Error_DN")
            error_dns.append(raw_error_dn[0] if isinstance(raw_error_dn, np.ndarray) else None)

            raw_offset = dataset.attrs.get("Offset")
            offsets.append(raw_offset[0] if isinstance(raw_offset, np.ndarray) else 0)

            raw_slope = dataset.attrs.get("Slope")
            scales.append(raw_slope[0] if isinstance(raw_slope, np.ndarray) else 1)

            crs, transform, gcps = self._build_projection(dataset.shape)

        with rasterio.open(
            output_path,
            mode="w",
            driver="GTiff",
            width=shape[1],
            height=shape[0],
            count=len(datasets),
            dtype=np.find_common_type(dtypes, []),
            crs=crs,
            transform=transform,
            nodata=error_dns[0] if len(np.unique(error_dns)) == 1 else None,
        ) as dst:
            dst.offsets = offsets
            dst.scales = scales

            if gcps is not None:
                dst.gcps = (crs, gcps)

            for i, dataset in enumerate(datasets, start=1):
                dst.write(dataset, i)

        return str(output_path)

    def _build_projection(
        self, shape: tuple[int, int]
    ) -> tuple[
        rasterio.crs.CRS, Optional[rasterio.transform.Affine], Optional[list[rasterio.control.GroundControlPoint]]
    ]:
        # https://shikisai.jaxa.jp/faq/faq0062.html?006

        geometry_attrs = self.geometry_attrs
        projection = self.geometry_attrs["Image_projection"]

        if projection == "L1B reference grid":  # FIXME: 経度方向の投影がおかしい？
            lat = self.geometry_data["Latitude"]
            lon = self.geometry_data["Longitude"]

            row_interval = shape[0] / (lat.shape[0] - 1)
            col_interval = shape[1] / (lat.shape[1] - 1)

            gcps = [
                rasterio.control.GroundControlPoint(
                    row=index[0] * row_interval,
                    col=index[1] * col_interval,
                    x=lon[index],
                    y=lat[index],
                )
                for index in np.ndindex(lat.shape)
                # Reduce the points to avoid the error: `TIFFFetchNormalTag:Incorrect count for "GeoTiePoints"`
                if index[0] % 10 == 0 and index[1] % 10 == 0
            ]

            crs = rasterio.CRS.from_epsg(4326)

            return crs, None, gcps

        elif projection == "EQA (sinusoidal equal area) projection from 0-deg longitude":
            crs = rasterio.CRS.from_authority("ESRI", 53008)

            (west, east), (north, south) = rasterio.warp.transform(  # type: ignore
                src_crs=rasterio.CRS.from_epsg(4326),
                dst_crs=crs,
                xs=[geometry_attrs["Upper_left_longitude"], geometry_attrs["Lower_right_longitude"]],
                ys=[geometry_attrs["Upper_left_latitude"], geometry_attrs["Lower_right_latitude"]],
            )

            transform = rasterio.transform.from_bounds(
                west=west,
                south=south,
                east=east,
                north=north,
                width=shape[1],
                height=shape[0],
            )

            return crs, transform, None

        elif projection == "Equal Rectangular projection":
            crs = rasterio.CRS.from_epsg(4326)
            transform = rasterio.transform.from_bounds(
                west=geometry_attrs["Upper_left_longitude"],
                south=geometry_attrs["Lower_right_latitude"],
                east=geometry_attrs["Lower_right_longitude"],
                north=geometry_attrs["Upper_left_latitude"],
                width=shape[1],
                height=shape[0],
            )
            return crs, transform, None

        else:
            raise NotImplementedError(f"Projection {projection} is not supported.")

open(path) classmethod

Opens a GCOM-C HDF5 file.

Parameters:

Name Type Description Default
path str

Path to a GCOM-C HDF5 file.

 required

Returns:

Type Description
GCOMCFile

An instance of GCOMCFile.
Source code in gportal/file/gcomc.py 
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@classmethod
def open(cls, path: str) -> "GCOMCFile":
    """Opens a GCOM-C HDF5 file.

    Args:
        path: Path to a GCOM-C HDF5 file.

    Returns:
        An instance of [`GCOMCFile`][gportal.file.gcomc.GCOMCFile].
    """
    h5_file = h5py.File(path)

    if "Global_attributes" not in h5_file:
        raise ValueError("Not a GCOM-C file.")

    satellite = h5_file["Global_attributes"].attrs.get("Satellite")
    if not satellite or satellite[0] != b"Global Change Observation Mission - Climate (GCOM-C)":
        raise ValueError("Not a GCOM-C file.")

    return cls(h5_file)

close()

Closes the file.

Source code in gportal/file/gcomc.py 
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def close(self) -> None:
    """Closes the file."""
    self.h5_file.close()

attrs: dict[str, Union[int, float, str]] property

Global attributes.

granule_id: str property

Granule ID.

geometry_attrs: dict[str, Union[int, float, str]] property

Geometry data attributes.

geometry_data: dict[str, h5py.Dataset] property

Geometry data.

image_data: dict[str, h5py.Dataset] property

Image data.

save_as_geotiff(output_dir='.', targets=None)

Saves the file as GeoTIFF.

Parameters:

Name Type Description Default
output_dir str

Directory to save the GeoTIFF files.

 '.'
targets Optional[list[str]]

Image data names to save. If not provided, all image data are saved.

 None

Returns:

Type Description
dict[str, str]

Dictionary of image data names and paths to the saved GeoTIFF files.
Source code in gportal/file/gcomc.py 
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def save_as_geotiff(self, output_dir: str = ".", targets: Optional[list[str]] = None) -> dict[str, str]:
    """Saves the file as GeoTIFF.

    Args:
        output_dir: Directory to save the GeoTIFF files.
        targets: Image data names to save. If not provided, all image data are saved.

    Returns:
        Dictionary of image data names and paths to the saved GeoTIFF files.
    """
    if targets is None:
        targets = [k for k in self.image_data.keys()]

    results = {}
    for image_data_name in targets:
        dataset = self.image_data[image_data_name]
        if dataset.ndim != 2:
            # Skip not 2D data, like Line_tai93.
            continue

        output_path = Path(output_dir) / f"{self.granule_id}-{image_data_name}.tif"
        results[image_data_name] = str(output_path)

        raw_error_dn = dataset.attrs.get("Error_DN")
        error_dn = raw_error_dn[0] if isinstance(raw_error_dn, np.ndarray) else None

        raw_offset = dataset.attrs.get("Offset")
        offset = raw_offset[0] if isinstance(raw_offset, np.ndarray) else 0

        raw_slope = dataset.attrs.get("Slope")
        slope = raw_slope[0] if isinstance(raw_slope, np.ndarray) else 1

        crs, transform, gcps = self._build_projection(dataset.shape)

        with rasterio.open(
            output_path,
            mode="w",
            driver="GTiff",
            width=dataset.shape[1],
            height=dataset.shape[0],
            count=1,
            dtype=dataset.dtype,
            crs=crs,
            transform=transform,
            nodata=error_dn,
        ) as dst:
            dst.offsets = (offset,)
            dst.scales = (slope,)

            if gcps is not None:
                dst.gcps = (gcps, crs)

            dst.write(dataset, 1)

    return results

save_as_multiband_geotiff(bands, output_path=None)

Saves the file as a multiband GeoTIFF.

Parameters:

Name Type Description Default
bands list[str]

List of image data names for each band.

 required
output_path Optional[Union[str, Path]]

Path to save the GeoTIFF file.

 None

Returns:

Type Description
str

Path to the saved GeoTIFF file.
Source code in gportal/file/gcomc.py 
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def save_as_multiband_geotiff(
    self,
    bands: list[str],
    output_path: Optional[Union[str, Path]] = None,
) -> str:
    """Saves the file as a multiband GeoTIFF.

    Args:
        bands: List of image data names for each band.
        output_path: Path to save the GeoTIFF file.

    Returns:
        Path to the saved GeoTIFF file.
    """
    datasets = [self.image_data[band] for band in bands]

    shape = datasets[0].shape
    for dataset in datasets[1:]:
        if dataset.shape != shape:
            raise ValueError("All bands must have the same shape.")

    if output_path is None:
        output_path = Path.cwd() / f"{self.granule_id}.tif"

    dtypes = []
    error_dns = []
    offsets = []
    scales = []
    crs = None
    transform = None
    gcps = None
    for i, dataset in enumerate(datasets):
        dtypes.append(dataset.dtype)

        raw_error_dn = dataset.attrs.get("Error_DN")
        error_dns.append(raw_error_dn[0] if isinstance(raw_error_dn, np.ndarray) else None)

        raw_offset = dataset.attrs.get("Offset")
        offsets.append(raw_offset[0] if isinstance(raw_offset, np.ndarray) else 0)

        raw_slope = dataset.attrs.get("Slope")
        scales.append(raw_slope[0] if isinstance(raw_slope, np.ndarray) else 1)

        crs, transform, gcps = self._build_projection(dataset.shape)

    with rasterio.open(
        output_path,
        mode="w",
        driver="GTiff",
        width=shape[1],
        height=shape[0],
        count=len(datasets),
        dtype=np.find_common_type(dtypes, []),
        crs=crs,
        transform=transform,
        nodata=error_dns[0] if len(np.unique(error_dns)) == 1 else None,
    ) as dst:
        dst.offsets = offsets
        dst.scales = scales

        if gcps is not None:
            dst.gcps = (crs, gcps)

        for i, dataset in enumerate(datasets, start=1):
            dst.write(dataset, i)

    return str(output_path)