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