xarray.DataArray.interp

DataArray.interp(coords: Mapping[Hashable, Any] = None, method: str = 'linear', assume_sorted: bool = False, kwargs: Mapping[str, Any] = None, **coords_kwargs) → xarray.core.dataarray.DataArray

Multidimensional interpolation of variables.

coords : dict, optional
Mapping from dimension names to the new coordinates. new coordinate can be an scalar, array-like or DataArray. If DataArrays are passed as new coordates, their dimensions are used for the broadcasting.
method: {‘linear’, ‘nearest’} for multidimensional array,
{‘linear’, ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, ‘cubic’} for 1-dimensional array.
assume_sorted: boolean, optional
If False, values of x can be in any order and they are sorted first. If True, x has to be an array of monotonically increasing values.
kwargs: dictionary
Additional keyword passed to scipy’s interpolator.
**coords_kwargs : {dim: coordinate, …}, optional
The keyword arguments form of coords. One of coords or coords_kwargs must be provided.
Returns:interpolated – New dataarray on the new coordinates.
Return type:xr.DataArray

Notes

scipy is required.

See also

scipy.interpolate.interp1d(), scipy.interpolate.interpn()

Examples

>>> da = xr.DataArray([1, 3], [("x", np.arange(2))])
>>> da.interp(x=0.5)
<xarray.DataArray ()>
array(2.0)
Coordinates:
    x        float64 0.5