Chan/ChanMacro/scoring/oi_matrix.py

"""
scoring/oi_matrix.py — OI × Price 2×2 state machine.

Discrete states, NOT a continuous score:
  NEW_LONGS:       Price↑ OI↑  → new money entering, trend continuation
  SHORT_COVERING:  Price↑ OI↓  → shorts covering, rally fragile
  NEW_SHORTS:      Price↓ OI↑  → new shorts entering, trend continuation
  LONG_EXIT:       Price↓ OI↓  → longs stopping out, panic (possible bottom)
  NEUTRAL:         flat        → noise, don't force classification
"""

from datetime import date as Date
import sqlite3

from .base import BaseScorer
from .constants import OI_PRICE_THRESHOLD, OI_OI_THRESHOLD, OI_STATE_SCORES
from models import FactorScore, OIMatrixScore, OIState, MacroDirection
from config import config


class OIMatrixScorer(BaseScorer):
    """Classifies OI × Price state and assigns score."""

    def compute(self, target_date: Date) -> OIMatrixScore:
        conn = self.get_connection()
        try:
            row = conn.execute(
                "SELECT * FROM derivatives WHERE date = ? AND symbol = 'BTC/USDT:USDT'",
                (str(target_date),)
            ).fetchone()

            if row is None:
                return OIMatrixScore(
                    name="OI Matrix",
                    score=50.0,
                    label="No Data",
                    oi_state=OIState.NEUTRAL,
                )

            row = dict(row)
            oi_change = row.get("oi_24h_change_pct") or 0

            # Get price change from OHLCV
            price_change = self._get_price_change(conn, str(target_date))

            # Classify state
            oi_state = self._classify(price_change, oi_change)

            # Score from state
            score = OI_STATE_SCORES.get(oi_state.value, 50)

            # Direction
            if oi_state == OIState.NEW_LONGS:
                direction = MacroDirection.BULLISH
            elif oi_state == OIState.SHORT_COVERING:
                direction = MacroDirection.BULLISH  # bullish but fragile
            elif oi_state == OIState.NEW_SHORTS:
                direction = MacroDirection.BEARISH
            elif oi_state == OIState.LONG_EXIT:
                direction = MacroDirection.BEARISH  # bearish but possible bottom
            else:
                direction = MacroDirection.NEUTRAL

            # Narrative
            narrative = self._build_narrative(oi_state, price_change, oi_change)

            return OIMatrixScore(
                name="OI Matrix",
                score=float(score),
                label=oi_state.value,
                direction=direction,
                oi_state=oi_state,
                price_change_pct=round(price_change, 2),
                oi_change_pct=round(oi_change, 2),
                sub_scores={
                    "price_change_pct": round(price_change, 2),
                    "oi_change_pct": round(oi_change, 2),
                },
                narrative=narrative,
            )
        finally:
            conn.close()

    def _get_price_change(self, conn: sqlite3.Connection, date_str: str) -> float:
        """Get BTC 24h price change % for a given date."""
        row = conn.execute(
            "SELECT close FROM ohlcv_daily WHERE date = ? AND symbol = 'BTC/USDT:USDT'",
            (date_str,)
        ).fetchone()
        if row is None:
            return 0.0

        # Get previous day close
        prev = conn.execute(
            "SELECT close FROM ohlcv_daily WHERE date < ? AND symbol = 'BTC/USDT:USDT' ORDER BY date DESC LIMIT 1",
            (date_str,)
        ).fetchone()

        if prev is None:
            return 0.0

        current_close = float(row["close"])
        prev_close = float(prev["close"])
        if prev_close == 0:
            return 0.0

        return (current_close - prev_close) / prev_close * 100

    @staticmethod
    def _classify(price_change_pct: float, oi_change_pct: float) -> OIState:
        """Classify OI × Price into discrete state."""
        price_up = price_change_pct > OI_PRICE_THRESHOLD
        price_down = price_change_pct < -OI_PRICE_THRESHOLD
        oi_up = oi_change_pct > OI_OI_THRESHOLD
        oi_down = oi_change_pct < -OI_OI_THRESHOLD

        if price_up and oi_up:
            return OIState.NEW_LONGS
        elif price_up and oi_down:
            return OIState.SHORT_COVERING
        elif price_down and oi_up:
            return OIState.NEW_SHORTS
        elif price_down and oi_down:
            return OIState.LONG_EXIT
        else:
            return OIState.NEUTRAL

    @staticmethod
    def _build_narrative(state: OIState, price_chg: float, oi_chg: float) -> str:
        mapping = {
            OIState.NEW_LONGS: f"新多进场: 价格+{price_chg:.1f}%, OI+{oi_chg:.1f}%, 真金白银推动",
            OIState.SHORT_COVERING: f"空头回补: 价格+{price_chg:.1f}%, OI{oi_chg:.1f}%, 上涨脆弱",
            OIState.NEW_SHORTS: f"新空进场: 价格{price_chg:.1f}%, OI+{oi_chg:.1f}%, 趋势延续",
            OIState.LONG_EXIT: f"多头止损: 价格{price_chg:.1f}%, OI{oi_chg:.1f}%, 恐慌(可能见底)",
            OIState.NEUTRAL: "OI/价格变化不显著, 噪音区",
        }
        return mapping.get(state, "Unknown")