code: def read_raster_window(
      input_files,
      tile,
      indexes=None,
      resampling="nearest",
      src_nodata=None,
      dst_nodata=None,
      gdal_opts=None
  ):
      
      with rasterio.Env(
          **get_gdal_options(
              gdal_opts,
              is_remote=path_is_remote(
                  input_files[0] if isinstance(input_files, list) else input_files, s3=True
              )
          )
      ) as env:
          logger.debug("reading %s with GDAL options %s", input_files, env.options)
          return _read_raster_window(
              input_files,
              tile,
              indexes=indexes,
              resampling=resampling,
              src_nodata=src_nodata,
              dst_nodata=dst_nodata
          )
docs: Return NumPy arrays from an input raster.
  
      NumPy arrays are reprojected and resampled to tile properties from input
      raster. If tile boundaries cross the antimeridian, data on the other side
      of the antimeridian will be read and concatenated to the numpy array
      accordingly.
  
      Parameters
      ----------
      input_files : string or list
          path to a raster file or list of paths to multiple raster files readable by
          rasterio.
      tile : Tile
          a Tile object
      indexes : list or int
          a list of band numbers; None will read all.
      resampling : string
          one of "nearest", "average", "bilinear" or "lanczos"
      src_nodata : int or float, optional
          if not set, the nodata value from the source dataset will be used
      dst_nodata : int or float, optional
          if not set, the nodata value from the source dataset will be used
      gdal_opts : dict
          GDAL options passed on to rasterio.Env()
  
      Returns
      -------
      raster : MaskedArray