code: def scale_jointly(x, y):
      x, y = np.array(x), np.array(y)
      global_max, global_min = max(x.max(), y.max()), min(
          x.min(), y.min()
      )
      x_scaled = np.zeros(len(x), dtype=float)
      y_scaled = np.zeros(len(y), dtype=float)
      x_scaled[x < 0] = -(x[x < 0] / global_min)
      x_scaled[x > 0] = x[x > 0] / global_max
      y_scaled[y < 0] = -(y[y < 0] / global_min)
      y_scaled[y > 0] = y[y > 0] / global_max
      return Coordinates((x_scaled + 1) / 2, (y_scaled + 1) / 2)
  
imports: from typing import Callable
  import numpy
  import pandas
  from scipy.stats import rankdata
label_desc: Use image node_id 2 for calling a global function with example usage: scale_jointly(x, y) and returns: Coordinates