feat(ga): generation summary stats (median/max/p90/entropy)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

tests/unit/test_ga_summary.py

@@ -0,0 +1,26 @@
+import math
+
+import pytest
+
+from multi_swarm.ga.summary import generation_summary
+
+
+def test_summary_basic_stats():
+    fitnesses = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
+    s = generation_summary(fitnesses, n_bins=5)
+    assert s["median"] == pytest.approx(0.45, abs=0.05)
+    assert s["max"] == pytest.approx(0.9)
+    assert 0.0 <= s["entropy"] <= math.log(5) + 0.01
+
+
+def test_summary_uniform_high_entropy():
+    fitnesses = [0.1 * i for i in range(20)]
+    s_uniform = generation_summary(fitnesses, n_bins=5)
+    s_concentrated = generation_summary([0.5] * 20, n_bins=5)
+    assert s_uniform["entropy"] > s_concentrated["entropy"]
+
+
+def test_summary_p90():
+    fitnesses = list(range(100))
+    s = generation_summary([float(x) for x in fitnesses], n_bins=10)
+    assert 88.0 <= s["p90"] <= 91.0