docstr: Test a scalar's cov factor.
docstr_tok: ["Test","a","scalar","'s","cov","factor","."]
code: def test_scalar_covariance_dataset(self):
      """Test a scalar's cov factor."""
      np.random.seed(8765678)
      n_basesample = 50
      multidim_data = [np.random.randn(n_basesample) for i in range(5)]
  
      kde = mlab.GaussianKDE(multidim_data, bw_method=0.5)
      assert kde.covariance_factor() == 0.5
  
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 8 for calling the TestGaussianKDECustom obj's underlying member method code with example usage: obj.test_scalar_covariance_dataset() without return types