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""" assert_fn.py """ |
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import numpy as np |
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def assert_notes_almost_equal(actual_notes, predicted_notes, delta=5e-3): |
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""" |
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Asserts that the given lists of Note instances are equal up to a small |
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floating-point tolerance, similar to `assertAlmostEqual` of `unittest`. |
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Tolerance is 5e-3 by default, which is 5 ms for 100 ticks-per-second. |
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""" |
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assert len(actual_notes) == len(predicted_notes) |
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for actual_note, predicted_note in zip(actual_notes, predicted_notes): |
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assert abs(actual_note.onset - predicted_note.onset) < delta |
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assert abs(actual_note.offset - predicted_note.offset) < delta |
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assert actual_note.pitch == predicted_note.pitch |
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if actual_note.is_drum is False and predicted_note.is_drum is False: |
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assert actual_note.program == predicted_note.program |
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assert actual_note.is_drum == predicted_note.is_drum |
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assert actual_note.velocity == predicted_note.velocity |
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def assert_note_events_almost_equal(actual_note_events, |
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predicted_note_events, |
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ignore_time=False, |
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ignore_activity=True, |
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delta=5.1e-3): |
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""" |
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Asserts that the given lists of Note instances are equal up to a small |
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floating-point tolerance, similar to `assertAlmostEqual` of `unittest`. |
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Tolerance is 5e-3 by default, which is 5 ms for 100 ticks-per-second. |
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If `ignore_time` is True, then the time field is ignored. (useful for |
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comparing tie note events, default is False) |
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If `ignore_activity` is True, then the activity field is ignored (default |
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is True). |
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""" |
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assert len(actual_note_events) == len(predicted_note_events) |
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for j, (actual_note_event, |
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predicted_note_event) in enumerate(zip(actual_note_events, predicted_note_events)): |
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if ignore_time is False: |
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assert abs(actual_note_event.time - predicted_note_event.time) <= delta |
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assert actual_note_event.is_drum == predicted_note_event.is_drum |
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if actual_note_event.is_drum is False and predicted_note_event.is_drum is False: |
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assert actual_note_event.program == predicted_note_event.program |
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assert actual_note_event.pitch == predicted_note_event.pitch |
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assert actual_note_event.velocity == predicted_note_event.velocity |
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if ignore_activity is False: |
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assert actual_note_event.activity == predicted_note_event.activity |
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def assert_track_metrics_score1(metrics) -> None: |
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for k, v in metrics.items(): |
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if np.isnan(v) is False: |
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assert v == 1.0 |
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