code: def _fprime(score, x, k_params, alpha):
      """
      The regularized derivative.
      """
      from cvxopt import matrix
  
      x_arr = np.asarray(x)
      params = x_arr[:k_params].ravel()
      # Call the numpy version
      # The derivative just appends a vector of constants
      fprime_arr = np.append(score(params), alpha)
      # Return
      return matrix(fprime_arr, (1, 2 * k_params))
  
imports: import numpy
  import statsmodels.base.l1_solvers_common
label_desc: Use image node_id 3 for calling a global function with example usage: _fprime(score, x, k_params, alpha) and returns: matrix