e.
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.
c