c2a7a62763
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
27 lines
812 B
Python
27 lines
812 B
Python
import math
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import pytest
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from multi_swarm.ga.summary import generation_summary
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def test_summary_basic_stats():
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fitnesses = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
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s = generation_summary(fitnesses, n_bins=5)
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assert s["median"] == pytest.approx(0.45, abs=0.05)
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assert s["max"] == pytest.approx(0.9)
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assert 0.0 <= s["entropy"] <= math.log(5) + 0.01
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def test_summary_uniform_high_entropy():
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fitnesses = [0.1 * i for i in range(20)]
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s_uniform = generation_summary(fitnesses, n_bins=5)
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s_concentrated = generation_summary([0.5] * 20, n_bins=5)
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assert s_uniform["entropy"] > s_concentrated["entropy"]
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def test_summary_p90():
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fitnesses = list(range(100))
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s = generation_summary([float(x) for x in fitnesses], n_bins=10)
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assert 88.0 <= s["p90"] <= 91.0
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