code: def test_augmentations():
      """Test the signature module augmentations."""
      # Build an array X, note that this is [n_sample, n_channels, length] shape.
      X = np.array([[1, 2], [1, 1], [1, 4]]).reshape(-1, 3, 2)
      X = np.swapaxes(X, 1, 2)
  
      # Leadlag
      leadlag = np.array(
          [
              [
                  [1, 2, 1, 2],
                  [1, 1, 1, 2],
                  [1, 1, 1, 1],
                  [1, 4, 1, 1],
                  [1, 4, 1, 4],
              ]
          ]
      )
      leadlag = np.swapaxes(leadlag, 1, 2)
      assert np.allclose(_LeadLag().fit_transform(X), leadlag)
  
      # Add time
      addtime = np.array(
          [[[0.0, 1.0, 2.0], [0.5, 1.0, 1.0], [1.0, 1.0, 4.0]]]
      )
      addtime = np.swapaxes(addtime, 1, 2)
      assert np.allclose(_AddTime().fit_transform(X), addtime)
  
      # Basepoint
      basepoint = np.array(
          [[[0.0, 0.0], [1.0, 2.0], [1.0, 1.0], [1.0, 4.0]]]
      )
      basepoint = np.swapaxes(basepoint, 1, 2)
      assert np.allclose(_BasePoint().fit_transform(X), basepoint)
  
      # Invisibility reset
      ir = np.array(
          [
              [
                  [1.0, 1.0, 2.0],
                  [1.0, 1.0, 1.0],
                  [1.0, 1.0, 4.0],
                  [0.0, 1.0, 4.0],
                  [0.0, 0.0, 0.0],
              ]
          ]
      )
      ir = np.swapaxes(ir, 1, 2)
      assert np.allclose(_InvisibilityReset().fit_transform(X), ir)
  
      # Cumulative sum
      cumsum = np.array([[[1, 2], [2, 3], [3, 7]]])
      cumsum = np.swapaxes(cumsum, 1, 2)
      assert np.allclose(_CumulativeSum().fit_transform(X), cumsum)
  
      # Test multiple augmentations
      pipeline = _make_augmentation_pipeline(["leadlag", "addtime"])
      lladdtime = np.array(
          [
              [
                  [0.0, 1.0, 2.0, 1.0, 2.0],
                  [0.25, 1.0, 1.0, 1.0, 2.0],
                  [0.5, 1.0, 1.0, 1.0, 1.0],
                  [0.75, 1.0, 4.0, 1.0, 1.0],
                  [1.0, 1.0, 4.0, 1.0, 4.0],
              ]
          ]
      )
      lladdtime = np.swapaxes(lladdtime, 1, 2)
      assert np.allclose(pipeline.fit_transform(X), lladdtime)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_augmentations() without return types