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)
