eoreader.utils.read

read(path: Union[str, cloudpathlib.cloudpath.CloudPath, pathlib.Path], resolution: Optional[Union[tuple, list, float]] = None, size: Optional[Union[list, tuple]] = None, resampling: rasterio.enums.Resampling = <Resampling.nearest: 0>, masked: bool = True, indexes: Optional[Union[int, list]] = None, **kwargs) → xarray.core.dataarray.DataArray[source]

Overload of sertit.rasters.read() managing DASK in EOReader’s way.

`python >>> raster_path = "path\to\raster.tif" >>> xds1 = read(raster_path) >>> # or >>> with rasterio.open(raster_path) as dst: >>>    xds2 = read(dst) >>> xds1 == xds2 True `

Parameters

  • path (Union[str, CloudPath, Path]) – Path to the raster

  • resolution (Union[tuple, list, float]) – Resolution of the wanted band, in dataset resolution unit (X, Y)

  • size (Union[tuple, list]) – Size of the array (width, height). Not used if resolution is provided.

  • resampling (Resampling) – Resampling method

  • masked (bool) – Get a masked array

  • indexes (Union[int, list]) – Indexes to load. Load the whole array if None.

  • **kwargs – Optional keyword arguments to pass into rioxarray.open_rasterio().

Returns

Masked xarray corresponding to the raster data and its meta data

Return type

Union[XDS_TYPE]