code: def schaffer(p):
      """
      This function has plenty of local minimum, with strong shocks
      global minimum at (0,0) with value 0
      https://en.wikipedia.org/wiki/Test_functions_for_optimization
      """
      x1, x2 = p
      part1 = np.square(x1) - np.square(x2)
      part2 = np.square(x1) + np.square(x2)
      return 0.5 + (np.square(np.sin(part1)) - 0.5) / np.square(
          1 + 0.001 * part2
      )
  
imports: import numpy
  from sko.GA import GA
  import pandas
  import matplotlib.pyplot
label_desc: Use image node_id 1 for calling a global function with example usage: schaffer(p) and returns: unknown