def test_Spatial_Empirical_Bayes(self): stl = pysal.open(pysal.examples.get_path('stl_hom.csv'), 'r') stl_e, stl_b = np.array(stl[:, 10]), np.array(stl[:, 13]) stl_w = pysal.open(pysal.examples.get_path('stl.gal'), 'r').read() if not stl_w.id_order_set: stl_w.id_order = range(1, len(stl) + 1) s_eb = sm.Spatial_Empirical_Bayes(stl_e, stl_b, stl_w) s_ebr10 = np.array([4.01485749e-05, 3.62437513e-05, 4.93034844e-05, 5.09387329e-05, 3.72735210e-05, 3.69333797e-05, 5.40245456e-05, 2.99806055e-05, 3.73034109e-05, 3.47270722e-05]) np.testing.assert_array_almost_equal(s_ebr10, s_eb.r[:10])
def test_Spatial_Empirical_Bayes_tabular(self): s_eb = sm.Spatial_Empirical_Bayes(self.stl_df[self.stl_ename], self.stl_df[self.stl_bname], self.stl_w).r self.assertIsInstance(s_eb, np.ndarray) np.testing.assert_allclose(self.s_ebr10, s_eb[:10]) s_eb = sm.Spatial_Empirical_Bayes.by_col(self.stl_df, self.stl_ename, self.stl_bname, self.stl_w) outcol = '{}-{}_spatial_empirical_bayes'.format( self.stl_ename, self.stl_bname) r = s_eb[outcol].values self.assertIsInstance(r, np.ndarray) np.testing.assert_allclose(self.s_ebr10, r[:10].reshape(-1, 1))
def test_Spatial_Empirical_Bayes(self): s_eb = sm.Spatial_Empirical_Bayes(self.stl_e, self.stl_b, self.stl_w) np.testing.assert_allclose(self.s_ebr10, s_eb.r[:10], rtol=RTOL, atol=ATOL)