#!/usr/bin/env python3
"""indicators.py — 通用技术指标库（2026-08-11 从 mr_scanner 抽取）

背景：calc_ma/calc_rsi/calc_atr/calc_obv 原定义在 mr_scanner.py，
被 s2_scanner.py import 复用 —— 策略扫描器互相 import 工具函数是坏味道。
抽取到公共模块，供所有策略扫描器（mr/s2/accumulation/p_oversold）共用。

算法与 backtest_framework.py 完全一致（零偏差）。
"""


def calc_ma(series, n):
    """简单移动平均。前 n-1 位返回 None。"""
    result = []
    for i in range(len(series)):
        if i < n - 1:
            result.append(None)
        else:
            result.append(sum(series[i - n + 1:i + 1]) / n)
    return result


def calc_rsi(series, n=14):
    """RSI（相对强弱指数），Wilder 平滑。"""
    deltas = [series[i] - series[i - 1] for i in range(1, len(series))]
    gains = [d if d > 0 else 0 for d in deltas]
    losses = [-d if d < 0 else 0 for d in deltas]
    result = [None] * (n + 1)
    avg_gain = sum(gains[:n]) / n
    avg_loss = sum(losses[:n]) / n
    if avg_loss == 0:
        result.append(100)
    else:
        rs = avg_gain / avg_loss
        result.append(100 - 100 / (1 + rs))
    for i in range(n, len(gains)):
        avg_gain = (avg_gain * (n - 1) + gains[i]) / n
        avg_loss = (avg_loss * (n - 1) + losses[i]) / n
        if avg_loss == 0:
            result.append(100)
        else:
            rs = avg_gain / avg_loss
            result.append(100 - 100 / (1 + rs))
    while len(result) < len(series):
        result.insert(0, None)
    return result[:len(series)]


def calc_atr(klines, n=14):
    """ATR（Average True Range），EMA 平滑——与 backtest_framework.calc_atr 完全一致
    （2026-08-12 统一口径：原 SMA 与回测 EMA 差 3.59%，回测实盘口径分裂）。
    klines: [{high, low, close, ...}]。返回最新 ATR 值（单值）。"""
    if len(klines) < n + 1:
        return None
    highs = [k["high"] for k in klines]
    lows = [k["low"] for k in klines]
    closes = [k["close"] for k in klines]
    # True Range（与 backtest_framework.calc_tr 一致）
    tr = [highs[0] - lows[0]]
    for i in range(1, len(highs)):
        hl = highs[i] - lows[i]
        hc = abs(highs[i] - closes[i - 1])
        lc = abs(lows[i] - closes[i - 1])
        tr.append(max(hl, hc, lc))
    # EMA 平滑（与 backtest_framework.calc_atr 一致：calc_ema(tr, n)）
    k = 2 / (n + 1)
    ema = tr[0]
    for t in tr[1:]:
        ema = t * k + ema * (1 - k)
    return ema


def calc_obv(klines):
    """OBV 能量潮（近20日变化量），资金流向指标。
    klines: [{close, volume, ...}]"""
    if len(klines) < 21:
        return 0
    obv = 0
    for i in range(1, len(klines)):
        if klines[i]["close"] > klines[i - 1]["close"]:
            obv += klines[i]["volume"] * 100  # 手→股
        elif klines[i]["close"] < klines[i - 1]["close"]:
            obv -= klines[i]["volume"] * 100
    # 近20日 OBV 变化
    obv_now = 0
    for i in range(max(1, len(klines) - 20), len(klines)):
        if klines[i]["close"] > klines[i - 1]["close"]:
            obv_now += klines[i]["volume"] * 100
        elif klines[i]["close"] < klines[i - 1]["close"]:
            obv_now -= klines[i]["volume"] * 100
    return obv_now