ite.
    dydx : array_like
        Array containing derivatives of the dependent variable. It can have
        arbitrary number of dimensions, but the length along ``axis``
        (see below) must match the length of ``x``. Values must be finite.
    axis : int, optional
        Axis along which `y` is assumed to be varying. Meaning that for
        ``x[i]`` the corresponding values are ``np.take(y, i, axis=axis)``.
        Default is 0.
    extrapolate : {bool, 'periodic', None}, optional
        If bool, determines whether to extrapolate to out-of-bounds points
        based on first and last intervals, or to return NaNs. If 'periodic',
        periodic extrapolation is used. If None (default), it is set to True.

    Attributes
    ----------
    x : ndarray, shape (n,)
        Breakpoints. The same ``x`` which was passed to the constructor.
    c : ndarray, shape (4, n-1, ...)
        Coefficients of the polynomials on each segment. The trailing
        dimensions match the dimensions of `y`, excluding ``axis``.
        For example, if `y` is 1-D, then ``c[k, i]`` is a coefficient for
        ``(x-x[i])**(3-k)`` on the segment between ``x[i]`` and ``x[i+1]``.
    axis : int
        Interpolation axis. The same axis which was passed to the
        constructor.

    Methods
    -------
    __call__
    derivative
    antiderivative
    integrate
    roots

    See Also
    --------
    Akima1DInterpolator : Akima 1D interpolator.
    PchipInterpolator : PCHIP 1-D monotonic cubic interpolator.
    CubicSpline : Cubic spline data interpolator.
    PPoly : Piecewise polynomial in terms of coefficients and breakpoints

    Notes
    -----
    If you want to create a higher-order spline matching higher-order
    derivatives, use `BPoly.from_derivatives`.

    References
    ----------
    .. [1] `Cubic Hermite spline
            <https://en.wikipedia.org/wiki/Cubic_Hermite_spline>`_
            on Wikipedia.
    r