code: def 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.
  
      """
      if isinstance(tck, BSpline):
          raise TypeError("spalde does not accept BSpline instances.")
      else:
          return _impl.spalde(x, tck)
  
file_path: scipy/scipy/interpolate/_fitpack_py.py
imports: import numpy
  from ._fitpack_impl import bisplrep, bisplev, dblint
  from .None import _fitpack_impl
  from ._bsplines import BSpline
label_desc: Use image node_id 6 for calling a global function with example usage: spalde(x, tck) and returns: _impl