| 144 | @pytest.mark.parametrize("T_A, T_B", test_data) |
| 145 | @pytest.mark.parametrize("percentages", percentages) |
| 146 | def test_scraamp_A_B_join(T_A, T_B, percentages): |
| 147 | m = 3 |
| 148 | |
| 149 | for p in [1.0, 2.0, 3.0]: |
| 150 | for percentage in percentages: |
| 151 | seed = np.random.randint(100000) |
| 152 | |
| 153 | np.random.seed(seed) |
| 154 | ref_P, ref_I, ref_left_I, ref_right_I = naive.scraamp( |
| 155 | T_A, m, T_B, percentage, None, False, None, p=p |
| 156 | ) |
| 157 | |
| 158 | np.random.seed(seed) |
| 159 | approx = scraamp( |
| 160 | T_A, |
| 161 | m, |
| 162 | T_B, |
| 163 | ignore_trivial=False, |
| 164 | percentage=percentage, |
| 165 | pre_scraamp=False, |
| 166 | p=p, |
| 167 | ) |
| 168 | approx.update() |
| 169 | comp_P = approx.P_ |
| 170 | comp_I = approx.I_ |
| 171 | comp_left_I = approx.left_I_ |
| 172 | comp_right_I = approx.right_I_ |
| 173 | |
| 174 | naive.replace_inf(ref_P) |
| 175 | naive.replace_inf(comp_P) |
| 176 | |
| 177 | npt.assert_almost_equal(ref_P, comp_P) |
| 178 | npt.assert_almost_equal(ref_I, comp_I) |
| 179 | npt.assert_almost_equal(ref_left_I, comp_left_I) |
| 180 | npt.assert_almost_equal(ref_right_I, comp_right_I) |
| 181 | |
| 182 | |
| 183 | @pytest.mark.parametrize("T_A, T_B", test_data) |