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