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conversion

darts_export.conversion

Collection of conversion functions to translate data for export and processing.

numpy_to_gdal 

numpy_to_gdal(
    nparray: numpy.ndarray,
    rio_georef: xarray.DataArray | xarray.Dataset,
) -> osgeo.gdal.Dataset

Convert a numpy ndarray into a gdal Dataset.

Georeference is to be passed in terms of an xarray object augmented by the rioxarray module, meaning the '.rio' accessor is available.

Parameters:

Returns:

  • osgeo.gdal.Dataset –

    gdal.Dataset: description

Source code in darts-export/src/darts_export/conversion.py 
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def numpy_to_gdal(nparray: np.ndarray, rio_georef: xarray.DataArray | xarray.Dataset) -> gdal.Dataset:
    """Convert a numpy ndarray into a gdal Dataset.

    Georeference is to be passed in terms
    of an xarray object augmented by the rioxarray module, meaning the '.rio' accessor is
    available.

    Args:
        nparray (np.ndarray): The data to convert
        rio_georef (xarray.DataArray | xarray.Dataset): an xarray with rio accessor as georeference

    Returns:
        gdal.Dataset: _description_

    """
    # convert the xarray to a gdal dataset
    dta = gdal_array.OpenArray(nparray)

    # copy over the geodata
    # the transform object of rasterio has to be converted into a tuple
    affine_transform = rio_georef.rio.transform()
    geotransform = (
        affine_transform.c,
        affine_transform.a,
        affine_transform.b,
        affine_transform.f,
        affine_transform.d,
        affine_transform.e,
    )
    dta.SetGeoTransform(geotransform)
    dta.SetProjection(rio_georef.rio.crs.to_wkt())
    return dta

ogrlyr_to_geopandas 

ogrlyr_to_geopandas(
    ogr_layer: osgeo.ogr.Layer,
) -> geopandas.GeoDataFrame

Convert a GDAL/OGR layer object to a geopandas dataframe.

Parameters:

  • ogr_layer (osgeo.ogr.Layer) –

    the ogr layer object to convert

Returns:

  • geopandas.GeoDataFrame –

    gpd.GeoDataFrame: the resulting GeoDataFrame

Source code in darts-export/src/darts_export/conversion.py 
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def ogrlyr_to_geopandas(ogr_layer: ogr.Layer) -> gpd.GeoDataFrame:
    """Convert a GDAL/OGR layer object to a geopandas dataframe.

    Args:
        ogr_layer (ogr.Layer): the ogr layer object to convert

    Returns:
        gpd.GeoDataFrame: the resulting GeoDataFrame

    """
    # Initialize an empty list to store geometries and attributes
    features = []

    # Iterate over OGR features in the layer
    for feature in ogr_layer:
        geom = feature.GetGeometryRef()
        # geom_json = geom.ExportToJson()  # Convert to GeoJSON format
        geom_wkt = geom.ExportToWkt()  # Convert to Well-Known Text (WKT)
        attributes = feature.items()  # Get attribute data as a dictionary

        # Append a tuple (geometry, attributes)
        features.append((geom_wkt, attributes))

    # Create a GeoDataFrame from the geometries and attributes
    gdf = gpd.GeoDataFrame(
        [attr for geom, attr in features], geometry=gpd.GeoSeries.from_wkt([geom for geom, attr in features])
    )

    return gdf

rioxarrayds_to_gdal 

rioxarrayds_to_gdal(
    rix: xarray.DataArray,
) -> osgeo.gdal.Dataset

Convert a rioxarray object to a gdal dataset.

Parameters:

Returns:

  • osgeo.gdal.Dataset –

    gdal.Dataset: the converted data

Source code in darts-export/src/darts_export/conversion.py 
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def rioxarrayds_to_gdal(rix: xarray.DataArray) -> gdal.Dataset:
    """Convert a rioxarray object to a gdal dataset.

    Args:
        rix (xarray.DataArray): data to convert

    Returns:
        gdal.Dataset: the converted data

    """
    return numpy_to_gdal(rix.to_numpy(), rix)