# -*- coding: utf-8 -*-
"""
技术指标：EMA、ATR
"""

from typing import List, Dict, Optional


def ema(series: List[float], period: int) -> List[Optional[float]]:
    """EMA(period)，前 period-1 个为 None"""
    if not series or period < 1:
        return []
    k = 2.0 / (period + 1)
    out: List[Optional[float]] = [None] * (period - 1)
    s = sum(series[:period])
    out.append(s / period)
    for i in range(period, len(series)):
        val = series[i] * k + out[-1] * (1 - k)  # type: ignore
        out.append(val)
    return out


def atr(high: List[float], low: List[float], close: List[float], period: int) -> List[Optional[float]]:
    """ATR(period)，前 period 个为 None"""
    n = len(close)
    if n < period + 1 or len(high) != n or len(low) != n:
        return [None] * n
    tr_list: List[float] = []
    for i in range(n):
        if i == 0:
            tr_list.append(high[0] - low[0])
        else:
            tr = max(
                high[i] - low[i],
                abs(high[i] - close[i - 1]),
                abs(low[i] - close[i - 1])
            )
            tr_list.append(tr)
    return ema(tr_list, period)


def get_ema_atr_from_klines(klines: List[Dict], ema_period: int, atr_period: int
                             ) -> tuple:
    """
    从K线列表计算收盘价 EMA 和 ATR。
    返回 (ema_list, atr_list)，长度与 klines 一致。
    """
    close = [float(k["close"]) for k in klines]
    high = [float(k["high"]) for k in klines]
    low = [float(k["low"]) for k in klines]
    ema_list = ema(close, ema_period)
    atr_list = atr(high, low, close, atr_period)
    return ema_list, atr_list


def align_higher_tf_ema(
    klines_5m: List[Dict],
    klines_higher: List[Dict],
    ema_fast: int,
    ema_slow: int
) -> List[Dict]:
    """
    根据更高周期K线计算 EMA，并按 5 分钟时间对齐。
    返回列表长度与 klines_5m 一致，每项为 {"ema_fast": float, "ema_slow": float} 或 None。
    """
    if not klines_higher or len(klines_higher) < ema_slow:
        return [{}] * len(klines_5m)
    close_hi = [float(k["close"]) for k in klines_higher]
    ema_f = ema(close_hi, ema_fast)
    ema_s = ema(close_hi, ema_slow)
    id_hi = [k["id"] for k in klines_higher]
    result = []
    for k5 in klines_5m:
        t = k5["id"]
        # 当前 5m 时刻所属的更高周期：取 <= t 的最后一根
        idx = -1
        for i, tid in enumerate(id_hi):
            if tid <= t:
                idx = i
            else:
                break
        if idx >= ema_slow - 1 and ema_f[idx] is not None and ema_s[idx] is not None:
            result.append({"ema_fast": ema_f[idx], "ema_slow": ema_s[idx]})
        else:
            result.append({})
    return result