xarray.full_like

xarray.full_like(other, fill_value, dtype: Union[numpy.dtype, str] = None)

Return a new object with the same shape and type as a given object.

Parameters:
  • other (DataArray, Dataset, or Variable) – The reference object in input
  • fill_value (scalar) – Value to fill the new object with before returning it.
  • dtype (dtype, optional) – dtype of the new array. If omitted, it defaults to other.dtype.
Returns:

out – New object with the same shape and type as other, with the data filled with fill_value. Coords will be copied from other. If other is based on dask, the new one will be as well, and will be split in the same chunks.

Return type:

same as object

Examples

>>> import numpy as np
>>> import xarray as xr
>>> 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.full_like(x, 1)
<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
>>> xr.full_like(x, 0.5)
<xarray.DataArray (lat: 2, lon: 3)>
array([[0, 0, 0],
       [0, 0, 0]])
Coordinates:
* lat      (lat) int64 1 2
* lon      (lon) int64 0 1 2
>>> xr.full_like(x, 0.5, dtype=np.double)
<xarray.DataArray (lat: 2, lon: 3)>
array([[0.5, 0.5, 0.5],
       [0.5, 0.5, 0.5]])
Coordinates:
* lat      (lat) int64 1 2
* lon      (lon) int64 0 1 2
>>> xr.full_like(x, np.nan, dtype=np.double)
<xarray.DataArray (lat: 2, lon: 3)>
array([[nan, nan, nan],
       [nan, nan, nan]])
Coordinates:
* lat      (lat) int64 1 2
* lon      (lon) int64 0 1 2