67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
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import numpy as np
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from mixer import normalize_rms, mix_streams, soft_limit
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TARGET_DBFS = -20
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class TestNormalizeRms:
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def test_silence_stays_silent(self, silence):
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result = normalize_rms(silence, TARGET_DBFS)
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assert np.allclose(result, 0.0)
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def test_quiet_tone_gets_louder(self, quiet_tone):
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original_rms = np.sqrt(np.mean(quiet_tone ** 2))
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result = normalize_rms(quiet_tone, TARGET_DBFS)
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result_rms = np.sqrt(np.mean(result ** 2))
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assert result_rms > original_rms
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def test_loud_tone_gets_quieter(self, loud_tone):
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original_rms = np.sqrt(np.mean(loud_tone ** 2))
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result = normalize_rms(loud_tone, TARGET_DBFS)
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result_rms = np.sqrt(np.mean(result ** 2))
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assert result_rms < original_rms
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def test_normalized_to_target(self, loud_tone):
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result = normalize_rms(loud_tone, TARGET_DBFS)
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result_rms = np.sqrt(np.mean(result ** 2))
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result_dbfs = 20 * np.log10(result_rms + 1e-10)
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assert abs(result_dbfs - TARGET_DBFS) < 1.0 # within 1 dB
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class TestMixStreams:
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def test_single_stream_unchanged(self, loud_tone):
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result = mix_streams([loud_tone])
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assert np.allclose(result, loud_tone)
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def test_two_streams_summed(self, loud_tone):
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result = mix_streams([loud_tone, loud_tone])
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# Two identical streams summed should be louder
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assert np.max(np.abs(result)) > np.max(np.abs(loud_tone))
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def test_empty_list_returns_silence(self, silence):
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result = mix_streams([])
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assert result.shape[0] == 960
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assert np.allclose(result, 0.0)
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def test_different_lengths_uses_shortest(self):
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short = np.ones(480, dtype=np.float32) * 0.5
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long = np.ones(960, dtype=np.float32) * 0.5
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result = mix_streams([short, long])
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assert result.shape[0] == 480
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class TestSoftLimit:
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def test_quiet_signal_unchanged(self, quiet_tone):
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result = soft_limit(quiet_tone)
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assert np.allclose(result, quiet_tone, atol=0.001)
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def test_clipping_signal_contained(self, clipping_tone):
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result = soft_limit(clipping_tone)
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assert np.max(np.abs(result)) <= 1.0
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def test_preserves_sign(self, clipping_tone):
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result = soft_limit(clipping_tone)
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# Signs should match where input is non-zero
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nonzero = np.abs(clipping_tone) > 0.01
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assert np.all(np.sign(result[nonzero]) == np.sign(clipping_tone[nonzero]))
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