code: def splder(tck, n=1):
      """
      Compute the spline representation of the derivative of a given spline
  
      Parameters
      ----------
      tck : tuple of (t, c, k)
          Spline whose derivative to compute
      n : int, optional
          Order of derivative to evaluate. Default: 1
  
      Returns
      -------
      tck_der : tuple of (t2, c2, k2)
          Spline of order k2=k-n representing the derivative
          of the input spline.
  
      Notes
      -----
      .. seealso:: :class:`scipy.interpolate.splder`
  
      See Also
      --------
      splantider, splev, spalde
      """
      if n < 0:
          return splantider(tck, -n)
  
      t, c, k = tck
  
      if n > k:
          raise ValueError(
              (
                  "Order of derivative (n = %r) must be <= "
                  "order of spline (k = %r)"
              )
              % (n, tck[2])
          )
  
      # Extra axes for the trailing dims of the `c` array:
      sh = (slice(None),) + ((None,) * len(c.shape[1:]))
  
      try:
          for j in range(n):
              # See e.g. Schumaker, Spline Functions: Basic Theory, Chapter 5
  
              # Compute the denominator in the differentiation formula.
              # (and append traling dims, if necessary)
              dt = t[k + 1 : -1] - t[1 : -k - 1]
              dt = dt[sh]
              # Compute the new coefficients
              c = (c[1 : -1 - k] - c[: -2 - k]) * k / dt
              # Pad coefficient array to same size as knots (FITPACK
              # convention)
              c = cupy.r_[c, np.zeros((k,) + c.shape[1:])]
              # Adjust knots
              t = t[1:-1]
              k -= 1
      except FloatingPointError as e:
          raise ValueError(
              (
                  "The spline has internal repeated knots "
                  "and is not differentiable %d times"
              )
              % n
          ) from e
  
      return t, c, k
  
imports: import operator
  import cupy
  from cupy._core import internal
  from cupy._core._scalar import get_typename
  from cupyx.scipy.sparse import csr_matrix
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: splder(tck, n) and returns: t,  c,  k, splantider