"""stats 包测试。

原则（见 docs/02-architecture.md §5）：**测已知解析解，不测实现细节**。
"""

from __future__ import annotations

import numpy as np
import pytest

pytestmark = pytest.mark.skip(reason="未实现：见 docs/03-roadmap.md L1")


def test_bootstrap_ci_matches_normal_theory_on_large_n(rng):
    """大样本下 bootstrap 百分位区间应逼近正态解析区间（±10% 容差）。"""
    from mcm_toolkit.stats import bootstrap_ci

    x = rng.normal(10, 2, size=5000)
    r = bootstrap_ci(x, statistic=np.mean, confidence=0.95, n_resamples=5000, random_state=0)
    se = x.std(ddof=1) / np.sqrt(x.size)
    assert abs((r.params["high"] - r.params["low"]) - 2 * 1.96 * se) < 0.1 * 2 * 1.96 * se


def test_bootstrap_ci_works_for_arbitrary_statistic(rng):
    """bootstrap 的核心价值：任意统计量都能给区间（这里用中位数）。"""
    from mcm_toolkit.stats import bootstrap_ci

    x = rng.lognormal(0, 1, size=2000)
    r = bootstrap_ci(x, statistic=np.median, random_state=0)
    assert r.params["low"] < r.params["high"]
    assert r.params["low"] < np.median(x) < r.params["high"]


def test_bootstrap_ci_is_reproducible(rng):
    from mcm_toolkit.stats import bootstrap_ci

    x = rng.normal(size=500)
    a = bootstrap_ci(x, statistic=np.mean, random_state=123)
    b = bootstrap_ci(x, statistic=np.mean, random_state=123)
    assert a.params["low"] == b.params["low"]


def test_confidence_interval_matches_scipy(rng):
    from scipy import stats

    from mcm_toolkit.stats import confidence_interval

    x = rng.normal(5, 1, size=50)
    lo, hi = confidence_interval(x, confidence=0.95, method="t")
    ref = stats.t.interval(0.95, len(x) - 1, loc=x.mean(), scale=stats.sem(x))
    assert np.allclose([lo, hi], ref, rtol=1e-6)


def test_correlation_matrix_diagonal_is_one(rng):
    from mcm_toolkit.stats import correlation_matrix

    x = rng.normal(size=(200, 4))
    c = correlation_matrix(x)
    assert np.allclose(np.diag(np.asarray(c)), 1.0)


def test_describe_reports_expected_keys(rng):
    from mcm_toolkit.stats import describe

    table = describe(rng.normal(size=(100, 3)))
    for key in ["mean", "std", "min", "max", "median"]:
        assert key in table.index