"""C1 因子相关性分析测试：横截面 Spearman 相关矩阵（对角线=1、正/负相关符号）。"""

from __future__ import annotations

from datetime import date

import numpy as np
import pandas as pd
import pytest
from app.api import deps
from app.infrastructure.persistence.sqlalchemy.base import Base
from app.infrastructure.persistence.sqlalchemy.repositories.market_impl import (
    SqlAlchemyDailyBarRepository,
    SqlAlchemyStockRepository,
)
from app.main import app
from app.quant.evaluation import factor_correlation_report
from fastapi.testclient import TestClient
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker

from conftest_quant import bars_dataframe_to_daily_bars, synthetic_daily

_SYMS = ["60000" + str(i) + ".SH" for i in range(5)]


def _panel(dates, symbols, drift) -> pd.DataFrame:
    rng = np.random.default_rng(7)
    arr = np.zeros((len(dates), len(symbols)))
    for j in range(len(symbols)):
        base = np.cumsum(rng.normal(0, 0.5, len(dates)))
        arr[:, j] = base + drift * np.arange(len(dates)) / 100
    return pd.DataFrame(arr, index=dates, columns=symbols)


class TestCorrelationReportUnit:
    def test_diag_and_sign(self) -> None:
        dates = pd.bdate_range("2024-01-01", periods=120)
        pa = _panel(dates, _SYMS, 2.0)
        pb = pa * 0.98 + 0.2  # 近线性正相关
        pc = -pa  # 完全负相关
        rep = factor_correlation_report({"a": pa, "b": pb, "c": pc}, min_symbols=3)
        assert rep.factors == ["a", "b", "c"]
        assert rep.corr_matrix["a"]["a"] == 1.0
        assert rep.corr_matrix["a"]["b"] > 0.9
        assert rep.corr_matrix["a"]["c"] < -0.9
        # 对称
        assert abs(rep.corr_matrix["a"]["b"] - rep.corr_matrix["b"]["a"]) < 1e-3
        assert rep.sample_days == 120

    def test_no_common_dates(self) -> None:
        d1 = pd.bdate_range("2024-01-01", periods=10)
        d2 = pd.bdate_range("2023-01-01", periods=10)
        rep = factor_correlation_report(
            {"x": _panel(d1, _SYMS, 0), "y": _panel(d2, _SYMS, 0)}
        )
        assert rep.sample_days == 0 and rep.corr_matrix["x"]["y"] == 0.0


class TestCorrelationApi:
    @pytest.fixture()
    def client(self, tmp_path):
        engine = create_engine(f"sqlite:///{tmp_path / 'corr.db'}", future=True)
        Base.metadata.create_all(engine)
        Session = sessionmaker(bind=engine, expire_on_commit=False)
        df = synthetic_daily({s: 0.004 - 0.001 * i for i, s in enumerate(_SYMS)}, n=320)
        with Session() as session:
            SqlAlchemyStockRepository(session).upsert_many(
                [
                    __import__("app.domain.entities.market", fromlist=["Stock"]).Stock(
                        symbol=s, name=f"测试{i}", list_date=date(1999, 1, 1)
                    )
                    for i, s in enumerate(_SYMS)
                ]
            )
            SqlAlchemyDailyBarRepository(session).upsert_many(bars_dataframe_to_daily_bars(df))
            session.commit()

        def _override():
            with Session() as s:
                yield s

        app.dependency_overrides[deps.get_session] = _override
        with TestClient(app) as c:
            yield c
        app.dependency_overrides.clear()

    def test_factor_correlations(self, client) -> None:
        resp = client.post(
            "/api/factor-correlations",
            json={
                "universe": {"exclude_st": False, "min_listing_days": 0},
                "factors": [
                    {"name": "momentum_20", "weight": 1},
                    {"name": "momentum_60", "weight": 1},
                    {"name": "volatility_60", "weight": 1},
                ],
                "period": ["2024-03-01", "2024-12-31"],
            },
        )
        assert resp.status_code == 200
        body = resp.json()
        assert len(body["factors"]) == 3
        assert body["corr_matrix"]["momentum_20"]["momentum_20"] == 1.0
        assert "momentum_60" in body["corr_matrix"]