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