def test_posthoc_quade(self):
results = sp.posthoc_quade(self.df_bn)
p_results = np.array(
[[
-1.00000000, 0.67651326, 0.15432143, 0.17954686, 0.2081421,
0.02267043, 0.2081421
],
[
0.67651326, -1.00000000, 0.29595042, 0.33809987, 0.38443835,
0.0494024, 0.38443835
],
[
0.15432143, 0.29595042, -1.00000000, 0.92586499, 0.85245022,
0.29595042, 0.85245022
],
[
0.17954686, 0.33809987, 0.92586499, -1.00000000, 0.92586499,
0.25789648, 0.92586499
],
[
0.2081421, 0.38443835, 0.85245022, 0.92586499, -1.00000000,
0.22378308, 1.00000000
],
[
0.02267043, 0.0494024, 0.29595042, 0.25789648, 0.22378308,
-1.00000000, 0.22378308
],
[
0.2081421, 0.38443835, 0.85245022, 0.92586499, 1.00000000,
0.22378308, -1.00000000
]])
self.assertTrue(np.allclose(results, p_results))
def test_posthoc_quade_norm(self):
results = sp.posthoc_quade(self.df_bn, dist='normal')
p_results = np.array([[
1.00000000, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan
], [0.5693540320, 1.00000000, np.nan, np.nan, np.nan, np.nan, np.nan],
[
0.0430605548, 0.145913303, 1.00000000,
np.nan, np.nan, np.nan, np.nan
],
[
0.0578705783, 0.184285855, 0.8993796,
1.00000000, np.nan, np.nan, np.nan
],
[
0.0766885196, 0.229662468, 0.8003530,
0.8993796, 1.00000000, np.nan, np.nan
],
[
0.0005066018, 0.003634715, 0.1459133,
0.1139777, 0.08782032, 1.00000000, np.nan
],
[
0.0766885196, 0.229662468, 0.8003530,
0.8993796, 1.00000000, 0.08782032, 1.00000000
]])
tri_upper = np.triu_indices(p_results.shape[0], 1)
p_results[tri_upper] = np.transpose(p_results)[tri_upper]
self.assertTrue(np.allclose(results, p_results))
