code: def optimize(solver, target="rosen", **kwds):
      if target == "rosen":  # 3d-rosenbrock
          # Rosenbrock function
          from dejong import rosen as the_model
  
          ndim = 3
          actual_coeffs = [1.0] * ndim
          pprint = list
      else:  # 4th-order chebyshev
          # Chebyshev cost function
          from poly import chebyshev4cost as the_model
          from poly import chebyshev4coeffs as actual_coeffs
  
          ndim = len(actual_coeffs)
          from mystic.math import poly1d as pprint
  
      # number of trials
      print("One trial:")
      print("===============")
  
      # initial guess
      import random
  
      x0 = [random.uniform(-100, 100) for i in range(ndim)]
  
      # minimize the function
      results = the_solver(the_model, x0, **kwds)
  
      print("===============")
      print("Actual params:\n %s" % pprint(actual_coeffs))
      print("Solved params:\n %s" % pprint(results[0]))
      print("Function value: %s" % results[1])
      print("Total function evals: %s" % results[3])
      return
  
label_desc: Use image node_id 1 for calling a global function with example usage: optimize(solver, target) without return types