{"description":"实验创建于11/25/2021","graph":{"edges":[{"to_node_id":"-851:instruments","from_node_id":"-838:data"},{"to_node_id":"-851:features","from_node_id":"-846:data"},{"to_node_id":"-858:features","from_node_id":"-846:data"},{"to_node_id":"-858:input_data","from_node_id":"-851:data"}],"nodes":[{"node_id":"-838","module_id":"BigQuantSpace.instruments.instruments-v2","parameters":[{"name":"start_date","value":"2021-01-01","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"2021-11-01","type":"Literal","bound_global_parameter":null},{"name":"market","value":"CN_STOCK_A","type":"Literal","bound_global_parameter":null},{"name":"instrument_list","value":"","type":"Literal","bound_global_parameter":null},{"name":"max_count","value":0,"type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"rolling_conf","node_id":"-838"}],"output_ports":[{"name":"data","node_id":"-838"}],"cacheable":true,"seq_num":1,"comment":"","comment_collapsed":true},{"node_id":"-846","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\nreturn_5\nreturn_10\nreturn_20\navg_amount_0/avg_amount_5\navg_amount_5/avg_amount_20\nrank_avg_amount_0/rank_avg_amount_5\nrank_avg_amount_5/rank_avg_amount_10\nrank_return_0\nrank_return_5\nrank_return_10\nrank_return_0/rank_return_5\nrank_return_5/rank_return_10\npe_ttm_0\n","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"features_ds","node_id":"-846"}],"output_ports":[{"name":"data","node_id":"-846"}],"cacheable":true,"seq_num":2,"comment":"","comment_collapsed":true},{"node_id":"-851","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":90,"type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"instruments","node_id":"-851"},{"name":"features","node_id":"-851"}],"output_ports":[{"name":"data","node_id":"-851"}],"cacheable":true,"seq_num":3,"comment":"","comment_collapsed":true},{"node_id":"-858","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":"False","type":"Literal","bound_global_parameter":null},{"name":"user_functions","value":"{}","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"input_data","node_id":"-858"},{"name":"features","node_id":"-858"}],"output_ports":[{"name":"data","node_id":"-858"}],"cacheable":true,"seq_num":4,"comment":"","comment_collapsed":true}],"node_layout":"<node_postions><node_position Node='-838' Position='313.9374694824219,106.13540649414062,200,200'/><node_position Node='-846' Position='641.9375,107.13540649414062,200,200'/><node_position Node='-851' Position='455.9375,207.13540649414062,200,200'/><node_position Node='-858' Position='468.9375,308.1354064941406,200,200'/></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11月25日 18:32
# 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。


m1 = M.instruments.v2(
    start_date='2021-01-01',
    end_date='2021-11-01',
    market='CN_STOCK_A',
    instrument_list='',
    max_count=0
)

m2 = 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
return_10
return_20
avg_amount_0/avg_amount_5
avg_amount_5/avg_amount_20
rank_avg_amount_0/rank_avg_amount_5
rank_avg_amount_5/rank_avg_amount_10
rank_return_0
rank_return_5
rank_return_10
rank_return_0/rank_return_5
rank_return_5/rank_return_10
pe_ttm_0
"""
)

m3 = M.general_feature_extractor.v7(
    instruments=m1.data,
    features=m2.data,
    start_date='',
    end_date='',
    before_start_days=90
)

m4 = M.derived_feature_extractor.v3(
    input_data=m3.data,
    features=m2.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=False,
    remove_extra_columns=False,
    user_functions={}
)

[2021-11-25 18:30:43.886858] INFO: moduleinvoker: instruments.v2 开始运行..

[2021-11-25 18:30:43.929606] INFO: moduleinvoker: 命中缓存

[2021-11-25 18:30:43.931965] INFO: moduleinvoker: instruments.v2 运行完成[0.045157s].

[2021-11-25 18:30:43.968619] INFO: moduleinvoker: input_features.v1 开始运行..

[2021-11-25 18:30:43.984692] INFO: moduleinvoker: 命中缓存

[2021-11-25 18:30:43.987466] INFO: moduleinvoker: input_features.v1 运行完成[0.018865s].

[2021-11-25 18:30:44.157782] INFO: moduleinvoker: general_feature_extractor.v7 开始运行..

[2021-11-25 18:30:44.182890] INFO: moduleinvoker: 命中缓存

[2021-11-25 18:30:44.185637] INFO: moduleinvoker: general_feature_extractor.v7 运行完成[0.02789s].

[2021-11-25 18:30:44.291590] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..

[2021-11-25 18:31:04.748435] INFO: derived_feature_extractor: 提取完成 avg_amount_0/avg_amount_5, 0.024s

[2021-11-25 18:31:04.762412] INFO: derived_feature_extractor: 提取完成 avg_amount_5/avg_amount_20, 0.011s

[2021-11-25 18:31:04.785437] INFO: derived_feature_extractor: 提取完成 rank_avg_amount_0/rank_avg_amount_5, 0.021s

[2021-11-25 18:31:04.793220] INFO: derived_feature_extractor: 提取完成 rank_avg_amount_5/rank_avg_amount_10, 0.006s

[2021-11-25 18:31:04.801547] INFO: derived_feature_extractor: 提取完成 rank_return_0/rank_return_5, 0.006s

[2021-11-25 18:31:04.811825] INFO: derived_feature_extractor: 提取完成 rank_return_5/rank_return_10, 0.008s

[2021-11-25 18:31:11.225566] INFO: derived_feature_extractor: /y_2020, 243745

[2021-11-25 18:31:22.956851] INFO: derived_feature_extractor: /y_2021, 858486

[2021-11-25 18:31:28.019889] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[43.728264s].