code: def test_pdf_non_fft(self):
      kde = nparam.KDEUnivariate(self.noise)
      kde.fit(fft=False, bw="scott")
  
      grid = kde.support
      testx = [grid[10 * i] for i in range(6)]
  
      # Test against values from R 'ks' package
      kde_expected = [
          0.00016808277984236013,
          0.030759614592368954,
          0.14123404934759243,
          0.28807147408162409,
          0.25594519303876273,
          0.056593973915651047,
      ]
  
      kde_vals0 = kde.density[10 * np.arange(6)]
      kde_vals = kde.evaluate(testx)
  
      npt.assert_allclose(kde_vals, kde_expected, atol=1e-6)
      npt.assert_allclose(kde_vals0, kde_expected, atol=1e-6)
  
imports: import numpy
  import numpy.testing
  import pytest
  from numpy.testing import assert_allclose, assert_equal
  import statsmodels.api
label_desc: Use image node_id 1 for calling the TestKDEUnivariate obj's underlying member method code with example usage: obj.test_pdf_non_fft() without return types