import numpy as np
import pandas as pd
from dataclasses import dataclass
from scipy.stats import kurtosis, skew
from datetime import time, timedelta

from typing import List, Tuple, Optional

from src.core_data import Bar


@dataclass
class ProfileStats:
    """封装剖面图的所有核心统计量。"""
    vah: float
    val: float
    poc: float


def calculate_profile_from_bars(bars: List[Bar], tick_size: float, va_percentage: int = 70) -> Optional[ProfileStats]:
    """
    [全局核心函数] 从给定的K线列表计算剖面图统计量 (VAH, VAL, POC)。
    """
    if not bars:
        return None

    data = []
    for bar in bars:
        price_range = np.arange(bar.low, bar.high + tick_size, tick_size)
        if len(price_range) == 0 or bar.volume == 0: continue
        volume_per_tick = bar.volume / len(price_range)
        for price in price_range:
            data.append({'price': price, 'volume': volume_per_tick})
    if not data: return None
    df = pd.DataFrame(data)
    if df.empty: return None
    price_volume_dist = df.groupby('price')['volume'].sum().sort_index()

    if price_volume_dist.empty or len(price_volume_dist) < 3: return None

    poc = price_volume_dist.idxmax()
    total_volume = price_volume_dist.sum()
    value_area_volume_target = total_volume * (va_percentage / 100.0)
    current_va_volume = price_volume_dist.loc[poc]
    vah, val = poc, poc
    prices_above = price_volume_dist.index[price_volume_dist.index > poc]
    prices_below = price_volume_dist.index[price_volume_dist.index < poc].sort_values(ascending=False)
    idx_above, idx_below = 0, 0
    while current_va_volume < value_area_volume_target:
        vol_above = price_volume_dist.loc[prices_above[idx_above]] if idx_above < len(prices_above) else 0
        vol_below = price_volume_dist.loc[prices_below[idx_below]] if idx_below < len(prices_below) else 0
        if vol_above == 0 and vol_below == 0: break
        if vol_above > vol_below:
            current_va_volume += vol_above
            vah = prices_above[idx_above]
            idx_above += 1
        else:
            current_va_volume += vol_below
            val = prices_below[idx_below]
            idx_below += 1

    return ProfileStats(vah=vah, val=val, poc=poc)