Python编程学动量自动化：主力趋势力度指标

    
import pandas as pd
import numpy as np

def calculate_indicator(df):
    # 计算LIJIN2
    df['LLV24'] = df['low'].rolling(24).min()
    df['HHV24'] = df['high'].rolling(24).max()
    df['LIJIN2'] = (df['close'] - df['LLV24']) / (df['HHV24'] - df['LLV24']) * 2000
    
    # 计算力道（SMA）
    df['力道'] = df['LIJIN2'].ewm(alpha=1/3, adjust=False).mean()
    
    # 计算LIJIN3
    denominator = (df['high'] - df['low']) * 2 - abs(df['close'] - df['open'])
    df['LIJIN3'] = df['volume'] / np.where(denominator != 0, denominator, 1)
    
    # 计算LIJIN4
    condition1 = df['close'] > df['open']
    condition2 = df['close'] < df['open']
    
    numerator = np.where(
        condition1,
        df['LIJIN3'] * (df['high'] - df['low']),
        np.where(
            condition2,
            df['LIJIN3'] * (df['high'] - df['open'] + df['close'] - df['low']),
            df['volume'] / 2
        )
    )
    
    denominator_part = np.where(
        condition1,
        -df['LIJIN3'] * (df['high'] - df['close'] + df['open'] - df['low']),
        np.where(
            condition2,
            -df['LIJIN3'] * (df['high'] - df['low']),
            -df['volume'] / 2
        )
    )

    df['LIJIN4'] = (numerator / (denominator_part * -1)) - (denominator_part * -1) / numerator
    
    # 计算LIJIN5-LIJIN7
    df['LIJIN5'] = df['amount'] / (100 * df['volume'])
    df['LIJIN6'] = df['LIJIN5'].rolling(40).mean()
    df['LIJIN7'] = 100 * (df['close'] - df['LIJIN6']) / df['LIJIN6']
    
    # 计算底部追击
    df['底部追击'] = np.where(
        (df['LIJIN4'] > 0) & (df['LIJIN7'] -12) & (df['close']/df['open'] > 1.08),
        300,
        200
    )
    
    # 计算LIJIN8-LIJINA
    df['LLV34'] = df['low'].rolling(34).min()
    df['HHV34'] = df['high'].rolling(34).max()
    df['LIJIN8'] = (df['close'] - df['LLV34']) / (df['HHV34'] - df['LLV34']) * 100
    df['LIJIN9'] = df['LIJIN8'].ewm(alpha=1/3, adjust=False).mean()
    df['LIJINA'] = df['LIJIN9'].ewm(alpha=1/3, adjust=False).mean()
    df['D'] = df['LIJINA'].ewm(alpha=1/5, adjust=False).mean() * 20
    
    # 计算趋势线
    window = 55
    sma1 = ((df['close'] - df['low'].rolling(window).min()) / 
           (df['high'].rolling(window).max() - df['low'].rolling(window).min()) * 100)
    sma1 = sma1.rolling(5).mean()
    sma2 = sma1.rolling(3).mean()
    df[


    
'趋势线'] = 3 * sma1 - 2 * sma2
    df['趋势线'] = df['趋势线'].ewm(span=3, adjust=False).mean()
    
    # 计算BB信号
    df['LIJIN12'] = (df['趋势线'] - df['趋势线'].shift(1)) / df['趋势线'].shift(1) * 100
    df['BB'] = (df['趋势线'] <= 13) & (df['LIJIN12'] > 13)
    
    # 计算MACD相关
    ema13 = df['close'].ewm(span=13, adjust=False).mean()
    ema24 = df['close'].ewm(span=24, adjust=False).mean()
    df['LIJINDIF'] = ema13 - ema24
    df['LIJINDEA'] = df['LIJINDIF'].ewm(span=6, adjust=False).mean()
    df['LIJINMACD'] = (df['LIJINDIF'] - df['LIJINDEA']) * 3

    
    return df

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