ENH: Add some tests for supervised FoM #1126
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Could use a review |
kohr-h
approved these changes
Sep 21, 2017
| result = odl.contrib.fom.mean_squared_error(data, true) | ||
| expected = np.mean((true - data) ** 2) | ||
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| assert pytest.approx(result) == expected |
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Slightly weird to have it this way, I prefer result == pytest.approx(expected)
| space = simple_fixture('space', [odl.rn(3), | ||
| odl.uniform_discr(0, 1, 10)]) | ||
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| def test_mean_squared_error(space): |
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Given the recent issue #1136 an additional check that the normalized variants do the right thing would be good. That means checking 0 <= result_normalized <= 1 for random inputs, (x, x) and (x, -x) which are often best and worst case, resp.
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Merging after CI |
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Adds tests for the most used supervised FoM.