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# 本代码由可视化策略环境自动生成 2021年12月14日 10:20
# 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 timex(df,s,x):
    return s * x


m2_user_functions_bigquant_run = {
    'timex' : timex
}

m1 = M.input_features.v1(
    features="""
# #号开始的表示注释，注释需单独一行
# 多个特征，每行一个，可以包含基础特征和衍生特征，特征须为本平台特征
return_5
timex = timex(close_0,open_0)
MA5 = mean(close_0, 5)
"""
)

m4 = M.instruments.v2(
    start_date='2021-01-01',
    end_date='2021-12-01',
    market='CN_STOCK_A',
    instrument_list='',
    max_count=0
)

m3 = M.general_feature_extractor.v7(
    instruments=m4.data,
    features=m1.data,
    start_date='',
    end_date='',
    before_start_days=90
)

m2 = M.derived_feature_extractor.v3(
    input_data=m3.data,
    features=m1.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=False,
    remove_extra_columns=False,
    user_functions=m2_user_functions_bigquant_run
)

[2021-12-10 14:24:26.803629] INFO: moduleinvoker: input_features.v1 开始运行..

[2021-12-10 14:24:27.152923] INFO: moduleinvoker: input_features.v1 运行完成[0.348894s].

[2021-12-10 14:24:27.158333] INFO: moduleinvoker: instruments.v2 开始运行..

[2021-12-10 14:24:27.166766] INFO: moduleinvoker: 命中缓存

[2021-12-10 14:24:27.169285] INFO: moduleinvoker: instruments.v2 运行完成[0.010952s].

[2021-12-10 14:24:27.194995] INFO: moduleinvoker: general_feature_extractor.v7 开始运行..

[2021-12-10 14:24:27.203957] INFO: moduleinvoker: 命中缓存

[2021-12-10 14:24:27.205564] INFO: moduleinvoker: general_feature_extractor.v7 运行完成[0.01063s].

[2021-12-10 14:24:27.217399] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..

[2021-12-10 14:24:29.609870] INFO: derived_feature_extractor: 提取完成 timex = timex(close_0,open_0), 0.018s

[2021-12-10 14:24:30.507352] INFO: derived_feature_extractor: 提取完成 MA5=mean(close_0, 5), 0.896s

[2021-12-10 14:24:31.023130] INFO: derived_feature_extractor: /y_2020, 243745

[2021-12-10 14:24:32.470429] INFO: derived_feature_extractor: /y_2021, 959220

[2021-12-10 14:24:33.355363] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[6.137948s].