Supertrend about technical

[hroff-1902]

^^ formatted

[tarantula3535]

hi i add ATR type in the code..and update it.

def SuperTrend(dataframe, period = 10, multiplier = 3, atrtype=1):
    import talib.abstract as ta
    df = dataframe.copy()
    atr = 'ATR_' + str(period)
    df[atr]=ta.ATR(df , timeperiod = period)
    st = 'ST_' + str(period) + '_' + str(multiplier)
    stx = 'STX_' + str(period) + '_' + str(multiplier)
    # Compute basic upper and lower bands
    if atrtype==1:
        df['basic_ub'] = (df["high"] + df["low"]) / 2 + multiplier * df[atr]
        df['basic_lb'] = (df["high"] + df["low"]) / 2 - multiplier * df[atr]
    elif atrtype==2:
        df['basic_ub'] = (df["high"] + df["low"] + df["close"]) / 3 + multiplier * df[atr]
        df['basic_lb'] = (df["high"] + df["low"] + df["close"]) / 3 - multiplier * df[atr]
    elif atrtype==3:
        df['basic_ub'] = (df["high"] + df["low"]+df["open"] + df["close"]) / 4 + multiplier * df[atr]
        df['basic_lb'] = (df["high"] + df["low"]+df["open"] + df["close"]) / 4 - multiplier * df[atr]
    # Compute final upper and lower bands
    df['final_ub'] = 0.00
    df['final_lb'] = 0.00
    for i in range(period, len(df)):
        df['final_ub'].iat[i] = df['basic_ub'].iat[i] if df['basic_ub'].iat[i] < df['final_ub'].iat[i - 1] or df['close'].iat[i - 1] > df['final_ub'].iat[i - 1] else df['final_ub'].iat[i - 1]
        df['final_lb'].iat[i] = df['basic_lb'].iat[i] if df['basic_lb'].iat[i] > df['final_lb'].iat[i - 1] or df['close'].iat[i - 1] < df['final_lb'].iat[i - 1] else df['final_lb'].iat[i - 1]
    # Set the Supertrend value
    df[st] = 0.00
    for i in range(period, len(df)):
        df[st].iat[i] = df['final_ub'].iat[i] if df[st].iat[i - 1] == df['final_ub'].iat[i - 1] and df['close'].iat[i] <= df['final_ub'].iat[i] else \
                        df['final_lb'].iat[i] if df[st].iat[i - 1] == df['final_ub'].iat[i - 1] and df['close'].iat[i] >  df['final_ub'].iat[i] else \
                        df['final_lb'].iat[i] if df[st].iat[i - 1] == df['final_lb'].iat[i - 1] and df['close'].iat[i] >= df['final_lb'].iat[i] else \
                        df['final_ub'].iat[i] if df[st].iat[i - 1] == df['final_lb'].iat[i - 1] and df['close'].iat[i] <  df['final_lb'].iat[i] else 0.00 
    # Mark the trend direction up/down
    df[stx] = np.where((df[st] > 0.00), np.where((df['close'] < df[st]), 'down',  'up'), np.NaN)
    # Remove basic and final bands from the columns
    df.drop(['basic_ub', 'basic_lb', 'final_ub', 'final_lb'], inplace=True, axis=1)
    df.fillna(0, inplace=True)
    return df