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In [9]:

# 本代码由可视化策略环境自动生成 2022年11月30日 17:06
# 本代码单元只能在可视化模式下编辑。您也可以拷贝代码，粘贴到新建的代码单元或者策略，然后修改。


def cal_max_ret(df,close,open,benchmark_close,benchmark_open,N):
    ret = df.groupby('instrument',as_index=False,sort=False,group_keys=False).apply(lambda x:(pd.concat([x['close'].shift(-i)/ x['open']- x['benchmark_close'].shift(-i)/ x['benchmark_open'] for i in range(N)],axis=1))
    return ret
        
def cal_max_ret_dateldf,close,open,benchmark_close,benchmark_open,N):
    ret = df.groupby ('instrument',as_index=False,sort=False,group_keys=False).apply(lambda x:(pd.concat([x['close'].shift(-i)/ x['open']- x['benchmark_close'].shift(-i)/ x['benchmark_open'] for i in range(N)],axis=1))
    return np.nanargmax(np.array(ret),axis=1)
m2_user_functions_bigquant_run={'cal_max_ret':cal_max_ret,'cal_max_ret_date': cal_max_ret_date}

m1 = M.instruments.v2(
    start_date='2022-01-01',
    end_date='2022-05-01',
    market='CN_STOCK_A',
    instrument_list='',
    max_count=0
)

m2 = M.advanced_auto_labeler.v2(
    instruments=m1.data,
    label_expr="""# #号开始的表示注释
# 0. 每行一个，顺序执行，从第二个开始，可以使用label字段
# 1. 可用数据字段见 https://bigquant.com/docs/develop/datasource/deprecated/history_data.html
#   添加benchmark_前缀，可使用对应的benchmark数据
# 2. 可用操作符和函数见 `表达式引擎 <https://bigquant.com/docs/develop/bigexpr/usage.html>`_

# # 计算收益：5日收盘价(作为卖出价格)除以明日开盘价(作为买入价格)
# shift(close, -5) / shift(open, -1)

# # 极值处理：用1%和99%分位的值做clip
# clip(label, all_quantile(label, 0.01), all_quantile(label, 0.99))

# # 将分数映射到分类，这里使用20个分类
# all_wbins(label, 20)

# # 过滤掉一字涨停的情况 (设置label为NaN，在后续处理和训练中会忽略NaN的label)
# where(shift(high, -1) == shift(low, -1), NaN, label)
#未来5日最大相对收益率
shift(cal_max_ret(close,open,benchmark_close,benchmark_open,5),-1)
#未来5日最大相对收益率所在天数
# shift(cal_max_ret_date(close，open, benchmark_close, benchmark_open，5)，-1)+ 1""",
    start_date='',
    end_date='',
    benchmark='000300.SHA',
    drop_na_label=True,
    cast_label_int=True,
    user_functions=m2_user_functions_bigquant_run
)

  File "<ipython-input-9-91d92071f87b>", line 7
    return ret
    ^
SyntaxError: invalid syntax