t returns the 'distance' between two points, with
        inputs as arrays of positions (x, y, z, ...), and an output as an
        array of distance. E.g., the default: 'euclidean', such that the result
        is a matrix of the distances from each point in ``x1`` to each point in
        ``x2``. For more options, see documentation of
        `scipy.spatial.distances.cdist`.
    mode : str, optional
        Mode of the interpolation, can be '1-D' (default) or 'N-D'. When it is
        '1-D' the data `d` will be considered as 1-D and flattened
        internally. When it is 'N-D' the data `d` is assumed to be an array of
        shape (n_samples, m), where m is the dimension of the target domain.


    Attributes
    ----------
    N : int
        The number of data points (as determined by the input arrays).
    di : ndarray
        The 1-D array of data values at each of the data coordinates `xi`.
    xi : ndarray
        The 2-D array of data coordinates.
    function : str or callable
        The radial basis function. See description under Parameters.
    epsilon : float
        Parameter used by gaussian or multiquadrics functions. See Parameters.
    smooth : float
        Smoothing parameter. See description under Parameters.
    norm : str or callable
        The distance function. See description under Parameters.
    mode : str
        Mode of the interpolation. See description under Parameters.
    nodes : ndarray
        A 1-D array of node values for the interpolation.
    A : internal property, do not use

    See Also
    --------
    RBFInterpolator

    Examples
    --------
    >>> import numpy as np
    >>> from scipy.interpolate import Rbf
    >>> rng = np.random.default_rng()
    >>> x, y, z, d = rng.random((4, 50))
    >>> rbfi = Rbf(x, y, z, d)  # radial basis function interpolator instance
    >>> xi = yi = zi = np.linspace(0, 1, 20)
    >>> di = rbfi(xi, yi, zi)   # interpolated values
    >>> di.shape
    (20,)

    c