code: def test_ks_regular_drift_scaled():
      # Scaling (changes in actual y values) should not affect KS, only the distribution of the values:
      dist1 = np.random.normal(0, 1, 10000) * 100
      dist2 = np.random.normal(1, 1, 10000) * 100
      res = kolmogorov_smirnov(dist1=dist1, dist2=dist2)
      assert_that(res, close_to(0.382, 0.01))
  
imports: import numpy
  from hamcrest import assert_that, calling, close_to, equal_to, raises
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.utils.distribution.drift import cramers_v, earth_movers_distance, kolmogorov_smirnov
label_desc: Use image node_id 24 for calling a global function with example usage: test_ks_regular_drift_scaled() without return types