class_docstr: Test the RadViz visualizer
class_docstr_tok: ["Test","the","RadViz","visualizer"]
docstr: Test the static normalization method on the RadViz class
docstr_tok: ["Test","the","static","normalization","method","on","the","RadViz","class"]
code: def test_normalize_x(self):
      """
      Test the static normalization method on the RadViz class
      """
      # Original data
      X = np.array(
          [
              [2.318, 2.727, 4.260, 7.212, 4.792],
              [2.315, 2.726, 4.295, 7.140, 4.783],
              [2.315, 2.724, 4.260, 7.135, 4.779],
              [2.110, 3.609, 4.330, 7.985, 5.595],
              [2.110, 3.626, 4.330, 8.203, 5.621],
              [2.110, 3.620, 4.470, 8.210, 5.612],
          ]
      )
  
      # Expected result
      Xe = np.array(
          [
              [1.0, 0.00332594, 0.0, 0.07162791, 0.01543943],
              [
                  0.98557692,
                  0.00221729,
                  0.16666667,
                  0.00465116,
                  0.00475059,
              ],
              [0.98557692, 0.0, 0.0, 0.0, 0.0],
              [0.0, 0.98115299, 0.33333333, 0.79069767, 0.96912114],
              [0.0, 1.0, 0.33333333, 0.99348837, 1.0],
              [0.0, 0.99334812, 1.0, 1.0, 0.98931116],
          ]
      )
  
      # Xprime (transformed X)
      Xp = RadViz.normalize(X)
      npt.assert_array_almost_equal(Xp, Xe)
  
file_path: yellowbrick/tests/test_features/test_radviz.py
imports: import sys
  import pytest
  import numpy.testing
  from tests.base import IS_WINDOWS_OR_CONDA, VisualTestCase
  from ..fixtures import Dataset
  from sklearn.datasets import make_classification
  from yellowbrick.datasets import load_occupancy
  from yellowbrick.features.radviz import *
label_desc: Use image node_id 1 for calling the TestRadViz obj's underlying member method code with example usage: obj.test_normalize_x() without return types