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# scipy.interpolate.spalde

scipy.interpolate.spalde(x, tck)

  Evaluate all derivatives of a B-spline.

  Given the knots and coefficients of a cubic B-spline compute all derivatives up to order k at a point (or set of points).

  Parameters:
    x array_like

      A point or a set of points at which to evaluate the derivatives. Note that `t(k) <= x <= t(n-k+1)` must hold for each x.

    tck tuple

      A tuple (t,c,k) containing the vector of knots, the B-spline coefficients, and the degree of the spline.

  Returns:
    results{ndarray, list of ndarrays}

      An array (or a list of arrays) containing all derivatives up to order k inclusive for each point x.

  See also

  `splprep`, `splrep`, `splint`, `sproot`, `splev`, `bisplrep`, `bisplev`
  `UnivariateSpline`, `BivariateSpline`

  References

  [1]

  de Boor C : On calculating with b-splines, J. Approximation Theory 6 (1972) 50-62.

  [2]

  Cox M.G. : The numerical evaluation of b-splines, J. Inst. Maths applics 10 (1972) 134-149.

  [3]

  Dierckx P. : Curve and surface fitting with splines, Monographs on Numerical Analysis, Oxford University Press, 1993.