Python编程自动化：紫气东来/寻龙起爆通达信公式源码

import pandas as pd
import numpy as np
import talib
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

def calculate_winner(close, window=250):
    winner = np.zeros(len(close))
    for i in range(len(close)):
        if i < window:
            winner[i] = np.nan
            continue
        current_price = close[i]
        window_prices = close[i - window:i]
        # 计算在窗口内低于当前价格的比例
        winner[i] = np.sum(window_prices <= current_price) / len(window_prices)
    return winner

def calculate_zshjj_zzljj(df):
    """计算紫气东来/寻龙起爆主力控盘和散户套牢指标"""
    # 计算获利盘比例
    df['winner_close'] = calculate_winner(df['close'])
    
    # 计算10%区间内的筹码
    df['winner_high'] = calculate_winner(df['close'] * 1.1)
    df['winner_low'] = calculate_winner(df['close'] * 0.9)
    df['winner_band'] = df['winner_high'] - df['winner_low']
    
    # 计算主力筹码和散户筹码
    df['ZLCM'] = talib.EMA(df['winner_close'] * 70, timeperiod=3)
    df['SHCM'] = talib.EMA(df['winner_band'] * 80, timeperiod=3)
    
    # 计算筹码系数
    df['ZSHTL'] = df['SHCM'] / (df['ZLCM'] + df['SHCM']) * 100
    df['ZZLKP'] = df['ZLCM'] / (df['ZLCM'] + df['SHCM']) * 100
    
    # 计算55日警戒线
    df['ZSHJJ'] = talib.EMA(df['ZSHTL'], timeperiod=55)
    df['ZZLJJ'] = talib.EMA(df['ZZLKP'], timeperiod=55)
    
    # 机构持仓比例
    df[


    
'institutional_holding'] = df['ZZLKP']
    
    # 散户持仓比例
    df['retail_holding'] = df['ZSHTL'].astype(int)
    
    return df

def plot_chip_indicators(df):
    """绘制紫气东来/寻龙起爆筹码分布指标图"""
    fig, ax = plt.subplots(figsize=(14, 7))
    
    # 设置x轴为日期
    ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
    plt.xticks(rotation=45)
    
    # 1. 绘制散户套牢筹码（灰色区域）
    ax.bar(df.index, df['ZSHTL'], color='gray', width=1, label='Retail Holding')
    
    # 2. 绘制主力控盘筹码（蓝色）
    mask_blue = df['ZZLKP'] > 20
    ax.bar(df.index, df['ZZLKP'], width=1, color='blue', alpha=0.6, label='Main Control')
    
    # 3. 绘制主力警戒线（黄色）
    ax.plot(df.index, df['ZZLJJ'], color='yellow', linewidth=2, label='Main Alert')
    
    # 4. 绘制散户警戒线（浅灰色）
    ax.plot(df.index, df['ZSHJJ'], color='lightgray', linestyle='--', label='Retail Alert')
    
    mask_top = df['ZZLKP'] > 95
    ax.bar(df.index[mask_top], df['ZZLKP'][mask_top], width=1, color='green', alpha=0.5, label='Top Risk')
    
    mask_pit = df['ZZLKP'] <= 10
    ax.bar(df.index[mask_pit], df['ZZLKP'][mask_pit], width=1, color='purple', alpha=0.7, label='Bottom Pit')
    
    # 设置图例和标题
    ax.set_title('Main Control and Retail Chips Distribution')
    ax.set_ylabel('Percentage (%)')
    ax.legend(loc='upper left')
    
    plt.tight_layout()
    plt.show()

if __name__ == "__main__":
    dates = pd.date_range(start='2023-01-01', periods=300, freq='D')
    np.random.seed(42)
    prices = np.cumprod(1 + np.random.randn(300) * 0.01) * 100
    
    df = pd.DataFrame({
        'date'


    
: dates,
        'close': prices
    }).set_index('date')
    
    # 计算指标
    df = calculate_zshjj_zzljj(df)
    
    # 显示最后几行数据
    print("机构持仓比例:", df['institutional_holding'].iloc[-1])
    print("散户持仓比例:", df['retail_holding'].iloc[-1])
    
    # 绘制图表
    plot_chip_indicators(df[-100:])  # 仅显示最后100个数据点