"""
Tests for quant/regimes.py and quant/walkforward.py.
"""
import numpy as np
from quant.regimes import RegimeClassifier, classify_regime, conditional_performance


class TestRegimeClassifier:
    def test_initial_state(self):
        rc = RegimeClassifier()
        assert rc.current_regime == "unknown"

    def test_classify_trending(self):
        """Rising prices with low volatility → trending_up."""
        regime = classify_regime(
            returns_20=0.15,   # +15% over 20 bars
            vol_20=0.02,       # 2% vol
            vol_ratio=1.0,     # normal volume
        )
        assert regime == "trending_up"

    def test_classify_ranging(self):
        """Flat prices with low volatility → ranging."""
        regime = classify_regime(
            returns_20=0.005,  # near flat
            vol_20=0.01,
            vol_ratio=1.0,
        )
        assert regime == "ranging"

    def test_classify_volatile(self):
        """High volatility regardless of direction → volatile."""
        regime = classify_regime(
            returns_20=0.02,
            vol_20=0.08,       # high vol
            vol_ratio=2.5,     # volume spike
        )
        assert regime == "volatile"

    def test_classify_trending_down(self):
        """Falling prices → trending_down."""
        regime = classify_regime(
            returns_20=-0.12,  # -12%
            vol_20=0.03,
            vol_ratio=1.0,
        )
        assert regime == "trending_down"

    def test_feed_updates_regime(self):
        rc = RegimeClassifier(window=20)
        # Feed 21 downtrend bars (need window+1 for first classification)
        for i in range(21):
            px = 100 - i * 2
            rc.feed(px, close=px, open_px=px - 0.5, vol=10)
        assert rc.current_regime == "trending_down"

        # Feed 21 uptrend bars
        for i in range(21):
            px = 58 + i * 3
            rc.feed(px, close=px, open_px=px + 0.5, vol=10)
        assert rc.current_regime == "trending_up"

    def test_regime_counts(self):
        rc = RegimeClassifier(window=20)
        for i in range(100):
            if i < 30:
                px = 100 + i
            elif i < 60:
                px = 130 - (i - 30) * 0.5
            else:
                px = 115 + (i - 60) * 2
            rc.feed(px, close=px, open_px=px, vol=10)
        counts = rc.regime_counts()
        assert sum(counts.values()) > 0

    def test_conditional_performance(self):
        """Verify per-regime statistics computation."""
        trades = [
            {"time": "2026-01-01T00:00:00", "pnl_net": 100, "pnl_gross": 120},
            {"time": "2026-01-02T00:00:00", "pnl_net": -50, "pnl_gross": -40},
            {"time": "2026-01-03T00:00:00", "pnl_net": 200, "pnl_gross": 220},
        ]
        # 3 trades all in trending_up regime
        result = conditional_performance(trades, {"trending_up": 3, "volatile": 0})
        assert result["regimes"]["trending_up"]["count"] == 3
        assert result["regimes"]["trending_up"]["avg_pnl"] > 0
        assert result["best_regime"] == "trending_up"