xarray.ones_like#

xarray.ones_like(other, dtype=None, *, chunks=None, chunked_array_type=None, from_array_kwargs=None)[source]#

Return a new object of ones with the same shape and type as a given dataarray or dataset.

Parameters:
  • other (DataArray, Dataset, or Variable) – The reference object. The output will have the same dimensions and coordinates as this object.

  • dtype (dtype, optional) – dtype of the new array. If omitted, it defaults to other.dtype.

  • chunks (int, "auto", tuple of int or mapping of Hashable to int, optional) – Chunk sizes along each dimension, e.g., 5, "auto", (5, 5) or {"x": 5, "y": 5}.

  • chunked_array_type (str, optional) – Which chunked array type to coerce the underlying data array to. Defaults to β€˜dask’ if installed, else whatever is registered via the ChunkManagerEnetryPoint system. Experimental API that should not be relied upon.

  • from_array_kwargs (dict, optional) – Additional keyword arguments passed on to the ChunkManagerEntrypoint.from_array method used to create chunked arrays, via whichever chunk manager is specified through the chunked_array_type kwarg. For example, with dask as the default chunked array type, this method would pass additional kwargs to dask.array.from_array(). Experimental API that should not be relied upon.

Returns:

out (same as object) – New object of ones with the same shape and type as other.

Examples

>>> x = xr.DataArray(
...     np.arange(6).reshape(2, 3),
...     dims=["lat", "lon"],
...     coords={"lat": [1, 2], "lon": [0, 1, 2]},
... )
>>> x
<xarray.DataArray (lat: 2, lon: 3)>
array([[0, 1, 2],
       [3, 4, 5]])
Coordinates:
  * lat      (lat) int64 1 2
  * lon      (lon) int64 0 1 2
>>> xr.ones_like(x)
<xarray.DataArray (lat: 2, lon: 3)>
array([[1, 1, 1],
       [1, 1, 1]])
Coordinates:
  * lat      (lat) int64 1 2
  * lon      (lon) int64 0 1 2

See also

zeros_like, full_like