Test var model error (#2217)
* [varLib.models] Add test for modeling rounding error Tests https://github.com/fonttools/fonttools/pull/2214 If you flip demo to True, it does a slower test and demos the new error as well as the error the old code was producing (ie. rounding deltas post-modeling). Indeed, the new error is always capped by 0.5 as expected, whereas the old one was unbounded. Here's the worst-case error of the bad code: ... 240 0.42 4.8 ... 240 is just the line number. 0.42 is new error. 4.8 is old error. * turn test_modeling_error into a parametrized pytest test Like the other test methods in the same module, all those whose name starts with 'test_' are automatically discovered and run by pytest which is our default test runner. So there is no need to call the test method itself in the top-level module scope. One simply runs the test via pytest. To execute this specific test method one can do 'pytest Tests/varLib/models_test.py::test_modeling_error'. * use pytest markers to mark specific test as 'slow' So that one can optionally deselect tests marked with specific marker by passing -m option (e.g. to deselect 'slow' tests, pytest -m 'not slow' ...). https://docs.pytest.org/en/stable/mark.html#registering-marks https://docs.pytest.org/en/stable/example/parametrize.html#set-marks-or-test-id-for-individual-parametrized-test * [varLib/models_test] Comment out non-test code Co-authored-by: Cosimo Lupo <clupo@google.com>
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@ -34,6 +34,40 @@ def test_supportScalar():
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assert supportScalar({'wght':2.5}, {'wght':(0,2,4)}) == 0.75
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assert supportScalar({'wght':2.5}, {'wght':(0,2,4)}) == 0.75
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@pytest.mark.parametrize(
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"numLocations, numSamples", [
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pytest.param(127, 509, marks=pytest.mark.slow),
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(31, 251),
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]
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)
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def test_modeling_error(numLocations, numSamples):
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# https://github.com/fonttools/fonttools/issues/2213
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locations = [{'axis': float(i)/numLocations} for i in range(numLocations)]
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masterValues = [100. if i else 0. for i in range(numLocations)]
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model = VariationModel(locations)
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for i in range(numSamples):
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loc = {'axis': float(i)/numSamples}
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scalars = model.getScalars(loc)
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deltas_float = model.getDeltas(masterValues)
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deltas_round = model.getDeltas(masterValues, round=round)
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expected = model.interpolateFromDeltasAndScalars(deltas_float, scalars)
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actual = model.interpolateFromDeltasAndScalars(deltas_round, scalars)
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err = abs(actual - expected)
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assert err <= .5, (i, err)
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# This is how NOT to round deltas.
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#deltas_late_round = [round(d) for d in deltas_float]
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#bad = model.interpolateFromDeltasAndScalars(deltas_late_round, scalars)
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#err_bad = abs(bad - expected)
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#if err != err_bad:
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# print("{:d} {:.2} {:.2}".format(i, err, err_bad))
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class VariationModelTest(object):
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class VariationModelTest(object):
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@pytest.mark.parametrize(
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@pytest.mark.parametrize(
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@ -52,6 +52,8 @@ filterwarnings =
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ignore:writePlist:DeprecationWarning:plistlib_test
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ignore:writePlist:DeprecationWarning:plistlib_test
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ignore:some_function:DeprecationWarning:fontTools.ufoLib.utils
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ignore:some_function:DeprecationWarning:fontTools.ufoLib.utils
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ignore::DeprecationWarning:fontTools.varLib.designspace
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ignore::DeprecationWarning:fontTools.varLib.designspace
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markers =
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slow: marks tests as slow (deselect with '-m "not slow"')
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[tool:interrogate]
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[tool:interrogate]
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ignore-semiprivate = true
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ignore-semiprivate = true
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