{"description":"实验创建于2020/2/23","graph":{"edges":[{"to_node_id":"-96:instruments","from_node_id":"-11:data"},{"to_node_id":"-24:features","from_node_id":"-19:data"},{"to_node_id":"-96:features","from_node_id":"-19:data"},{"to_node_id":"-24:input_data","from_node_id":"-96:data"}],"nodes":[{"node_id":"-11","module_id":"BigQuantSpace.instruments.instruments-v2","parameters":[{"name":"start_date","value":"2021-02-10","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"2021-04-15","type":"Literal","bound_global_parameter":null},{"name":"market","value":"CN_STOCK_A","type":"Literal","bound_global_parameter":null},{"name":"instrument_list","value":"000001.SZA\n300023.SZA","type":"Literal","bound_global_parameter":null},{"name":"max_count","value":0,"type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"rolling_conf","node_id":"-11"}],"output_ports":[{"name":"data","node_id":"-11"}],"cacheable":true,"seq_num":2,"comment":"","comment_collapsed":true},{"node_id":"-19","module_id":"BigQuantSpace.input_features.input_features-v1","parameters":[{"name":"features","value":"\n# #号开始的表示注释，注释需单独一行\n# 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\navg_amount=mean(bar1d_CN_STOCK_A__amount, 2)\nclose_1=shift(bar1d_CN_STOCK_A__close, 1)\nclose_avg=(bar1d_CN_STOCK_A__close + bar1d_CN_STOCK_A__open)/2\npb_lf=market_value_CN_STOCK_A__pb_lf\npe_ttm=market_value_CN_STOCK_A__pe_ttm\n","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"features_ds","node_id":"-19"}],"output_ports":[{"name":"data","node_id":"-19"}],"cacheable":true,"seq_num":3,"comment":"","comment_collapsed":true},{"node_id":"-24","module_id":"BigQuantSpace.derived_feature_extractor.derived_feature_extractor-v3","parameters":[{"name":"date_col","value":"date","type":"Literal","bound_global_parameter":null},{"name":"instrument_col","value":"instrument","type":"Literal","bound_global_parameter":null},{"name":"drop_na","value":"False","type":"Literal","bound_global_parameter":null},{"name":"remove_extra_columns","value":"True","type":"Literal","bound_global_parameter":null},{"name":"user_functions","value":"{}","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"input_data","node_id":"-24"},{"name":"features","node_id":"-24"}],"output_ports":[{"name":"data","node_id":"-24"}],"cacheable":true,"seq_num":4,"comment":"","comment_collapsed":true},{"node_id":"-96","module_id":"BigQuantSpace.general_feature_extractor.general_feature_extractor-v7","parameters":[{"name":"start_date","value":"","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"","type":"Literal","bound_global_parameter":null},{"name":"before_start_days","value":"0","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"instruments","node_id":"-96"},{"name":"features","node_id":"-96"}],"output_ports":[{"name":"data","node_id":"-96"}],"cacheable":false,"seq_num":1,"comment":"","comment_collapsed":true}],"node_layout":"<node_postions><node_position Node='-11' Position='317,149,200,200'/><node_position Node='-19' Position='555,232,200,200'/><node_position Node='-24' Position='424,396,200,200'/><node_position Node='-96' Position='323,321,200,200'/></node_postions>"},"nodes_readonly":false,"studio_version":"v2"}

# 本代码由可视化策略环境自动生成 2021年10月16日08:11
# 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。


m2 = M.instruments.v2(
    start_date='2021-02-10',
    end_date='2021-04-15',
    market='CN_STOCK_A',
    instrument_list="""000001.SZA
300023.SZA""",
    max_count=0
)

m3 = 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
avg_amount=mean(bar1d_CN_STOCK_A__amount, 2)
close_1=shift(bar1d_CN_STOCK_A__close, 1)
close_avg=(bar1d_CN_STOCK_A__close + bar1d_CN_STOCK_A__open)/2
pb_lf=market_value_CN_STOCK_A__pb_lf
pe_ttm=market_value_CN_STOCK_A__pe_ttm
"""
)

m1 = M.general_feature_extractor.v7(
    instruments=m2.data,
    features=m3.data,
    start_date='',
    end_date='',
    before_start_days=0,
    m_cached=False
)

m4 = M.derived_feature_extractor.v3(
    input_data=m1.data,
    features=m3.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=False,
    remove_extra_columns=True,
    user_functions={}
)

[2021-10-16 08:11:45.046378] INFO: moduleinvoker: instruments.v2 开始运行..

[2021-10-16 08:11:45.114119] INFO: moduleinvoker: instruments.v2 运行完成[0.067761s].

[2021-10-16 08:11:45.120052] INFO: moduleinvoker: input_features.v1 开始运行..

[2021-10-16 08:11:45.159444] INFO: moduleinvoker: input_features.v1 运行完成[0.039391s].

[2021-10-16 08:11:45.238000] INFO: moduleinvoker: general_feature_extractor.v7 开始运行..

[2021-10-16 08:11:45.563631] INFO: 基础特征抽取: 年份 2021, 特征行数=82

[2021-10-16 08:11:45.618177] INFO: 基础特征抽取: 总行数: 82

[2021-10-16 08:11:45.619948] INFO: moduleinvoker: general_feature_extractor.v7 运行完成[0.381958s].

[2021-10-16 08:11:45.631708] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..

[2021-10-16 08:11:45.692378] INFO: derived_feature_extractor: 提取完成 avg_amount=mean(bar1d_CN_STOCK_A__amount, 2), 0.005s

[2021-10-16 08:11:45.699161] INFO: derived_feature_extractor: 提取完成 close_1=shift(bar1d_CN_STOCK_A__close, 1), 0.005s

[2021-10-16 08:11:45.701672] INFO: derived_feature_extractor: 提取完成 close_avg=(bar1d_CN_STOCK_A__close + bar1d_CN_STOCK_A__open)/2, 0.001s

[2021-10-16 08:11:45.703306] INFO: derived_feature_extractor: 提取完成 pb_lf=market_value_CN_STOCK_A__pb_lf, 0.001s

[2021-10-16 08:11:45.704921] INFO: derived_feature_extractor: 提取完成 pe_ttm=market_value_CN_STOCK_A__pe_ttm, 0.001s

[2021-10-16 08:11:45.740615] INFO: derived_feature_extractor: /y_2021, 82

[2021-10-16 08:11:45.784562] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[0.152833s].