code: def test_gaussian_kde_covariance_caching(self):
      x1 = np.array([-7, -5, 1, 4, 5], dtype=float)
      xs = np.linspace(-10, 10, num=5)
      # These expected values are from scipy 0.10, before some changes to
      # gaussian_kde. They were not compared with any external reference.
      y_expected = [
          0.02463386,
          0.04689208,
          0.05395444,
          0.05337754,
          0.01664475,
      ]
  
      # set it to the default bandwidth.
      kde2 = mlab.GaussianKDE(x1, "scott")
      y2 = kde2(xs)
  
      np.testing.assert_array_almost_equal(y_expected, y2, decimal=7)
  
imports: from numpy.testing import assert_allclose, assert_almost_equal, assert_array_equal, assert_array_almost_equal_nulp
  import numpy
  import pytest
  from matplotlib import mlab
label_desc: Use image node_id 2 for calling the TestGaussianKDE obj's underlying member method code with example usage: obj.test_gaussian_kde_covariance_caching() without return types