scipy.interpolate.krogh_interpolate¶
- scipy.interpolate.krogh_interpolate(xi, yi, x, der=0, axis=0)[source]¶
Convenience function for polynomial interpolation.
See KroghInterpolator for more details.
Parameters: xi : array_like
Known x-coordinates.
yi : array_like
Known y-coordinates, of shape (xi.size, R). Interpreted as vectors of length R, or scalars if R=1.
x : array_like
Point or points at which to evaluate the derivatives.
der : int or list, optional
How many derivatives to extract; None for all potentially nonzero derivatives (that is a number equal to the number of points), or a list of derivatives to extract. This number includes the function value as 0th derivative.
axis : int, optional
Axis in the yi array corresponding to the x-coordinate values.
Returns: d : ndarray
If the interpolator’s values are R-dimensional then the returned array will be the number of derivatives by N by R. If x is a scalar, the middle dimension will be dropped; if the yi are scalars then the last dimension will be dropped.
See also
Notes
Construction of the interpolating polynomial is a relatively expensive process. If you want to evaluate it repeatedly consider using the class KroghInterpolator (which is what this function uses).