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