code: def test_cdf_X_transformer():
      """Test CDF transformer on Gaussian normal dataset."""
      target = np.array(np.transpose(np.linspace(0.0, 1.0, 1001)))
      target = np.transpose(
          np.array(np.append([target], [target], axis=0))
      )
      gaussian_dataset = load_gaussian_cdf_data()
      bins = 1001
      cdf_transformer = dc.trans.CDFTransformer(
          transform_X=True, dataset=gaussian_dataset, bins=bins
      )
      _, y, w, ids = (
          gaussian_dataset.X,
          gaussian_dataset.y,
          gaussian_dataset.w,
          gaussian_dataset.ids,
      )
      gaussian_dataset = cdf_transformer.transform(gaussian_dataset)
      X_t, y_t, w_t, ids_t = (
          gaussian_dataset.X,
          gaussian_dataset.y,
          gaussian_dataset.w,
          gaussian_dataset.ids,
      )
  
      # Check ids are unchanged.
      for id_elt, id_t_elt in zip(ids, ids_t):
          assert id_elt == id_t_elt
      # Check y is unchanged since this is an X transformer
      np.testing.assert_allclose(y, y_t)
      # Check w is unchanged since this is an X transformer
      np.testing.assert_allclose(w, w_t)
      # Check X is now holding the proper values when sorted.
      sorted = np.sort(X_t, axis=0)
      np.testing.assert_allclose(sorted, target)
  
imports: import os
  import numpy
  import deepchem
label_desc: Use image node_id 2 for calling a global function with example usage: test_cdf_X_transformer() without return types