"""VCP-lite — 단기/장기 일중 변동성 비율 기반 수축률."""

import pandas as pd

from .base import ScoreNode, percentile_rank


class VcpLite(ScoreNode):
    name  = "vcp_lite"
    label = "VCP-lite (변동성 수축)"
    default_params = {"short_window": 40, "long_window": 252}
    param_schema = {
        "type": "object",
        "properties": {
            "short_window": {"type": "integer", "minimum": 10, "maximum": 120, "default": 40},
            "long_window":  {"type": "integer", "minimum": 60, "maximum": 504, "default": 252},
        },
    }

    def compute(self, ctx, params: dict) -> pd.Series:
        short_w = int(params.get("short_window", 40))
        long_w  = int(params.get("long_window", 252))
        prices = ctx.prices
        if prices.empty:
            return pd.Series(dtype=float)

        ordered = prices.sort_values("date").copy()
        ordered["range_pct"] = (ordered["high"] - ordered["low"]) / ordered["close"]

        def _ratio(s: pd.Series) -> float:
            if len(s) < long_w:
                return float("nan")
            short_vol = s.tail(short_w).mean()
            long_vol  = s.tail(long_w).mean()
            if long_vol == 0 or pd.isna(long_vol):
                return float("nan")
            return 1 - (short_vol / long_vol)

        raw = ordered.groupby("ticker", group_keys=False)["range_pct"].apply(_ratio)
        return percentile_rank(raw).fillna(50.0)