code: def _evaluate_hodograph(s, nodes):
      r
      _, num_nodes = np.shape(nodes)
      first_deriv = nodes[:, 1:] - nodes[:, :-1]
      return (num_nodes - 1) * evaluate_multi(
          first_deriv, np.asfortranarray([s])
      )
docs: r"""Evaluate the Hodograph curve at a point :math:`s`.
  
      The Hodograph (first derivative) of a B |eacute| zier curve
      degree :math:`d = n - 1` and is given by
  
      .. math::
  
         B'(s) = n \sum_{j = 0}^{d} \binom{d}{j} s^j
         (1 - s)^{d - j} \cdot \Delta v_j
  
      where each forward difference is given by
      :math:`\Delta v_j = v_{j + 1} - v_j`.
  
      .. note::
  
         There is also a Fortran implementation of this function, which
         will be used if it can be built.
  
      Args:
          nodes (numpy.ndarray): The nodes of a curve.
          s (float): A parameter along the curve at which the Hodograph
              is to be evaluated.
  
      Returns:
          numpy.ndarray: The point on the Hodograph curve (as a two
          dimensional NumPy array with a single row).