Module « scipy.interpolate »

Fonction pchip_interpolate - module scipy.interpolate

Signature de la fonction pchip_interpolate

def pchip_interpolate(xi, yi, x, der=0, axis=0) 

Description

pchip_interpolate.__doc__

    Convenience function for pchip interpolation.

    xi and yi are arrays of values used to approximate some function f,
    with ``yi = f(xi)``. The interpolant uses monotonic cubic splines
    to find the value of new points x and the derivatives there.

    See `scipy.interpolate.PchipInterpolator` for details.

    Parameters
    ----------
    xi : array_like
        A sorted list of x-coordinates, of length N.
    yi :  array_like
        A 1-D array of real values. `yi`'s length along the interpolation
        axis must be equal to the length of `xi`. If N-D array, use axis
        parameter to select correct axis.
    x : scalar or array_like
        Of length M.
    der : int or list, optional
        Derivatives to extract. The 0th derivative can be included to
        return the function value.
    axis : int, optional
        Axis in the yi array corresponding to the x-coordinate values.

    See Also
    --------
    PchipInterpolator : PCHIP 1-D monotonic cubic interpolator.

    Returns
    -------
    y : scalar or array_like
        The result, of length R or length M or M by R,

    Examples
    --------
    We can interpolate 2D observed data using pchip interpolation:

    >>> import matplotlib.pyplot as plt
    >>> from scipy.interpolate import pchip_interpolate
    >>> x_observed = np.linspace(0.0, 10.0, 11)
    >>> y_observed = np.sin(x_observed)
    >>> x = np.linspace(min(x_observed), max(x_observed), num=100)
    >>> y = pchip_interpolate(x_observed, y_observed, x)
    >>> plt.plot(x_observed, y_observed, "o", label="observation")
    >>> plt.plot(x, y, label="pchip interpolation")
    >>> plt.legend()
    >>> plt.show()