cupyx.scipy.interpolate.krogh_interpolate(xi, yi, x, der=0, axis=0)[source]#

Convenience function for polynomial interpolation

  • xi (cupy.ndarray) – x-coordinate

  • yi (cupy.ndarray) – y-coordinates, of shape (xi.size, R). Interpreted as vectors of length R, or scalars if R=1

  • x (cupy.ndarray) – 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


d – If the interpolator’s values are R-D 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

Return type: