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# scipy.interpolate.splev

`scipy.interpolate.``splev`(x, tck, der=0)

  Evaulate a B-spline and its derivatives.

  Description:

  > Given the knots and coefficients of a B-spline representation, evaluate the value of the smoothing polynomial and it’s derivatives. This is a wrapper around the FORTRAN routines splev and splder of FITPACK.

  Inputs:

  > x (u) – a 1-D array of points at which to return the value of the
  >   smoothed spline or its derivatives. If tck was returned from splprep, then the parameter values, u should be given.
  > tck – A sequence of length 3 returned by splrep or splprep containg the
  >   knots, coefficients, and degree of the spline.
  > der – The order of derivative of the spline to compute (must be less than
  >   or equal to k).

  Outputs: (y, )

  > y – an array of values representing the spline function or curve.
  >   If tck was returned from splrep, then this is a list of arrays representing the curve in N-dimensional space.

  See also:

    splprep, splrep, sproot, spalde, splint - evaluation, roots, integral bisplrep, bisplev - bivariate splines UnivariateSpline, BivariateSpline - an alternative wrapping

    > of the FITPACK functions

  Notes:
    de Boor C : On calculating with b-splines, J. Approximation Theory
      6 (1972) 50-62.
    Cox M.G. : The numerical evaluation of b-splines, J. Inst. Maths
      Applics 10 (1972) 134-149.
    Dierckx P. : Curve and surface fitting with splines, Monographs on
      Numerical Analysis, Oxford University Press, 1993.

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