"""거래량 급증 — log1p(recent/baseline)."""

import numpy as np
import pandas as pd

from .base import ScoreNode, percentile_rank


class VolumeSurge(ScoreNode):
    name  = "volume_surge"
    label = "거래량 급증"
    default_params = {"baseline_days": 20, "eval_days": 3}
    param_schema = {
        "type": "object",
        "properties": {
            "baseline_days": {"type": "integer", "minimum": 5, "maximum": 60, "default": 20},
            "eval_days":     {"type": "integer", "minimum": 1, "maximum": 10, "default": 3},
        },
    }

    def compute(self, ctx, params: dict) -> pd.Series:
        baseline = int(params.get("baseline_days", 20))
        eval_d   = int(params.get("eval_days", 3))
        prices = ctx.prices
        if prices.empty:
            return pd.Series(dtype=float)

        ordered = prices.sort_values("date")
        last_recent = ordered.groupby("ticker").tail(eval_d).groupby("ticker")["volume"].mean()
        last_baseline = (
            ordered.groupby("ticker")
                   .tail(baseline + eval_d)
                   .groupby("ticker")
                   .head(baseline)
                   .groupby("ticker")["volume"]
                   .mean()
        )
        ratio = last_recent / last_baseline.replace(0, pd.NA)
        raw = np.log1p(ratio.astype(float))
        return percentile_rank(raw).fillna(50.0)