datacube.api.GridWorkflow.load

static GridWorkflow.load(tile, measurements=None, dask_chunks=None, fuse_func=None, resampling=None, skip_broken_datasets=False)[source]

Load data for a cell/tile.

The data to be loaded is defined by the output of list_tiles().

This is a static function and does not use the index. This can be useful when running as a worker in a distributed environment and you wish to minimize database connections.

See the documentation on using xarray with dask for more information.

Parameters:
  • tile (Tile) – The tile to load.
  • measurements (list(str)) – The names of measurements to load
  • dask_chunks (dict) –

    If the data should be loaded as needed using dask.array.Array, specify the chunk size in each output direction.

    See the documentation on using xarray with dask for more information.

  • fuse_func – Function to fuse together a tile that has been pre-grouped by calling list_cells() with a group_by parameter.
  • resampling (str|dict) –

    The resampling method to use if re-projection is required, could be configured per band using a dictionary (:meth: load_data)

    Valid values are: 'nearest', 'cubic', 'bilinear', 'cubic_spline', 'lanczos', 'average'

    Defaults to 'nearest'.

  • skip_broken_datasets (bool) – If True, ignore broken datasets and continue processing with the data that can be loaded. If False, an exception will be raised on a broken dataset. Defaults to False.
Return type:

xarray.Dataset