docstr: Test silverman's output for a single dimension list.
docstr_tok: ["Test","silverman","'s","output","for","a","single","dimension","list","."]
code: def test_silverman_singledim_dataset(self):
      """Test silverman's output for a single dimension list."""
      x1 = np.array([-7, -5, 1, 4, 5])
      mygauss = mlab.GaussianKDE(x1, "silverman")
      y_expected = 0.76770389927475502
      assert_almost_equal(mygauss.covariance_factor(), y_expected, 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 4 for calling the TestGaussianKDECustom obj's underlying member method code with example usage: obj.test_silverman_singledim_dataset() without return types