Module « scipy.interpolate »

Fonction interpn - module scipy.interpolate

Signature de la fonction interpn

def interpn(points, values, xi, method='linear', bounds_error=True, fill_value=nan) 

Description

interpn.__doc__

    Multidimensional interpolation on regular grids.

    Parameters
    ----------
    points : tuple of ndarray of float, with shapes (m1, ), ..., (mn, )
        The points defining the regular grid in n dimensions.

    values : array_like, shape (m1, ..., mn, ...)
        The data on the regular grid in n dimensions.

    xi : ndarray of shape (..., ndim)
        The coordinates to sample the gridded data at

    method : str, optional
        The method of interpolation to perform. Supported are "linear" and
        "nearest", and "splinef2d". "splinef2d" is only supported for
        2-dimensional data.

    bounds_error : bool, optional
        If True, when interpolated values are requested outside of the
        domain of the input data, a ValueError is raised.
        If False, then `fill_value` is used.

    fill_value : number, optional
        If provided, the value to use for points outside of the
        interpolation domain. If None, values outside
        the domain are extrapolated.  Extrapolation is not supported by method
        "splinef2d".

    Returns
    -------
    values_x : ndarray, shape xi.shape[:-1] + values.shape[ndim:]
        Interpolated values at input coordinates.

    Notes
    -----

    .. versionadded:: 0.14

    Examples
    --------
    Evaluate a simple example function on the points of a regular 3-D grid:

    >>> from scipy.interpolate import interpn
    >>> def value_func_3d(x, y, z):
    ...     return 2 * x + 3 * y - z
    >>> x = np.linspace(0, 4, 5)
    >>> y = np.linspace(0, 5, 6)
    >>> z = np.linspace(0, 6, 7)
    >>> points = (x, y, z)
    >>> values = value_func_3d(*np.meshgrid(*points, indexing='ij'))

    Evaluate the interpolating function at a point

    >>> point = np.array([2.21, 3.12, 1.15])
    >>> print(interpn(points, values, point))
    [12.63]

    See also
    --------
    NearestNDInterpolator : Nearest neighbor interpolation on unstructured
                            data in N dimensions

    LinearNDInterpolator : Piecewise linear interpolant on unstructured data
                           in N dimensions

    RegularGridInterpolator : Linear and nearest-neighbor Interpolation on a
                              regular grid in arbitrary dimensions

    RectBivariateSpline : Bivariate spline approximation over a rectangular mesh