Method interp

xarray/core/dataset.py:3733–4040

Interpolate a Dataset onto new coordinates. Performs univariate or multivariate interpolation of a Dataset onto new coordinates, utilizing either NumPy or SciPy interpolation routines. Out-of-range values are filled with NaN, unless specified otherwise via `kwargs`

(
        self,
        coords: Mapping[Any, Any] | None = None,
        method: InterpOptions = "linear",
        assume_sorted: bool = False,
        kwargs: Mapping[str, Any] | None = None,
        method_non_numeric: str = "nearest",
        **coords_kwargs: Any,
    )

        )

    def interp(
        self,
        coords: Mapping[Any, Any] | None = None,
        method: InterpOptions = "linear",
        assume_sorted: bool = False,
        kwargs: Mapping[str, Any] | None = None,
        method_non_numeric: str = "nearest",
        **coords_kwargs: Any,
    ) -> Self:
        """
        Interpolate a Dataset onto new coordinates.

        Performs univariate or multivariate interpolation of a Dataset onto new coordinates,
        utilizing either NumPy or SciPy interpolation routines.

        Out-of-range values are filled with NaN, unless specified otherwise via `kwargs` to the numpy/scipy interpolant.

        Parameters
        ----------
        coords : dict, optional
            Mapping from dimension names to the new coordinates.
            New coordinate can be a scalar, array-like or DataArray.
            If DataArrays are passed as new coordinates, their dimensions are
            used for the broadcasting. Missing values are skipped.
        method : { "linear", "nearest", "zero", "slinear", "quadratic", "cubic", \
            "quintic", "polynomial", "pchip", "barycentric", "krogh", "akima", "makima" }
            Interpolation method to use (see descriptions above).
        assume_sorted : bool, default: False
            If False, values of coordinates that are interpolated over can be
            in any order and they are sorted first. If True, interpolated
            coordinates are assumed to be an array of monotonically increasing
            values.
        kwargs : dict, optional
            Additional keyword arguments passed to the interpolator. Valid
            options and their behavior depend which interpolant is used.
        method_non_numeric : {"nearest", "pad", "ffill", "backfill", "bfill"}, optional
            Method for non-numeric types. Passed on to :py:meth:`Dataset.reindex`.
            ``"nearest"`` is used by default.
        **coords_kwargs : {dim: coordinate, ...}, optional
            The keyword arguments form of ``coords``.
            One of coords or coords_kwargs must be provided.


        Returns
        -------
        interpolated : Dataset
            New dataset on the new coordinates.

        Notes
        -----
        - SciPy is required for certain interpolation methods.
        - When interpolating along multiple dimensions with methods `linear` and `nearest`,
            the process attempts to decompose the interpolation into independent interpolations
            along one dimension at a time.
        - The specific interpolation method and dimensionality determine which
            interpolant is used:

            1. **Interpolation along one dimension of 1D data (`method='linear'`)**