xarray.DataArray.interp¶
-
DataArray.
interp
(coords=None, method='linear', assume_sorted=False, kwargs=None, **coords_kwargs)¶ Multidimensional interpolation of variables.
- Parameters
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 coordinates, their dimensions are used for the broadcasting. Missing values are skipped.method (
str
, default:"linear"
) – The method used to interpolate. Choose from{“linear”, “nearest”} for multidimensional array,
{“linear”, “nearest”, “zero”, “slinear”, “quadratic”, “cubic”} for 1-dimensional array.
assume_sorted (
bool
, 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 (
dict
) – Additional keyword arguments passed to scipy’s interpolator. Valid options and their behavior depend on if 1-dimensional or multi-dimensional interpolation is used.**coords_kwargs (
{dim: coordinate, ...}
, optional) – The keyword arguments form ofcoords
. One of coords or coords_kwargs must be provided.
- Returns
interpolated – New dataarray on the new coordinates.
- Return type
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.) Coordinates: x float64 0.5