"""仅用已收盘日线计算指标，避免把盘中未完成的日线混入信号。"""

from dataclasses import dataclass
from datetime import date, datetime
from decimal import Decimal, ROUND_CEILING
import math
from statistics import fmean, pstdev

from .config import ETFConfig


@dataclass(frozen=True)
class Indicators:
    day: str
    ma60: float
    atr: float
    lower: float
    middle: float
    upper: float
    grid: float


def calculate(rows: list[dict], today: date, cfg: ETFConfig) -> Indicators:
    """MA60 + Wilder ATR + BOLL（总体标准差），格距向上取整到 0.001 元。"""
    bars = {}
    for row in rows:
        day = datetime.strptime(str(row['date']), '%Y%m%d').date()
        if day >= today:
            continue
        if day in bars:
            raise ValueError('日线包含重复日期')
        high, low, close = (float(row[key]) for key in ('high', 'low', 'close'))
        if not all(math.isfinite(v) and v > 0 for v in (high, low, close)) or not low <= close <= high:
            raise ValueError('日线价格无效')
        bars[day] = (high, low, close)
    days = sorted(bars)
    if len(days) < max(60, cfg.atr_period + 1, cfg.boll_period):
        raise ValueError('已收盘日线不足，至少需要 60 根且能计算 ATR')
    # 长期停牌或历史缓存未补齐时不使用过期信号；春节等长假允许 15 个自然日。
    if (today - days[-1]).days > 15:
        raise ValueError('最近日线超过 15 个自然日，需补齐行情')
    values = [bars[d] for d in days]
    closes = [v[2] for v in values]
    tr = [max(h - l, abs(h - closes[i - 1]), abs(l - closes[i - 1]))
          for i, (h, l, _) in enumerate(values) if i > 0]
    n = cfg.atr_period
    atr = fmean(tr[:n])
    for value in tr[n:]:
        atr = (atr * (n - 1) + value) / n
    ma = fmean(closes[-60:])
    window = closes[-cfg.boll_period:]
    middle, width = fmean(window), cfg.boll_std * pstdev(window)
    raw_grid = max(atr * cfg.atr_multiplier, ma * cfg.min_grid_pct / 100, 0.001)
    grid = float(Decimal(str(raw_grid)).quantize(Decimal('0.001'), rounding=ROUND_CEILING))
    return Indicators(days[-1].strftime('%Y%m%d'), ma, atr, middle - width, middle, middle + width, grid)