{"description":"实验创建于2017/8/26","graph":{"edges":[{"to_node_id":"-215:instruments","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8:data"},{"to_node_id":"-215:features","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24:data"},{"to_node_id":"-222:features","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24:data"},{"to_node_id":"-554:data1","from_node_id":"-215:data"},{"to_node_id":"-222:input_data","from_node_id":"-554:data"}],"nodes":[{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8","module_id":"BigQuantSpace.instruments.instruments-v2","parameters":[{"name":"start_date","value":"2010-01-01","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"2022-12-31","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":"287d2cb0-f53c-4101-bdf8-104b137c8601-8"}],"output_ports":[{"name":"data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8"}],"cacheable":true,"seq_num":1,"comment":"","comment_collapsed":true},{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24","module_id":"BigQuantSpace.input_features.input_features-v1","parameters":[{"name":"features","value":"ta_macd(close_0, 'golden_cross')\nta_macd_dif(close_0)\nta_macd_dea(close_0)\nta_macd_hist(close_0)","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"features_ds","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24"}],"output_ports":[{"name":"data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24"}],"cacheable":true,"seq_num":3,"comment":"","comment_collapsed":true},{"node_id":"-215","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":"-215"},{"name":"features","node_id":"-215"}],"output_ports":[{"name":"data","node_id":"-215"}],"cacheable":true,"seq_num":15,"comment":"","comment_collapsed":true},{"node_id":"-222","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":"-222"},{"name":"features","node_id":"-222"}],"output_ports":[{"name":"data","node_id":"-222"}],"cacheable":true,"seq_num":16,"comment":"","comment_collapsed":true},{"node_id":"-554","module_id":"BigQuantSpace.resample.resample-v1","parameters":[{"name":"group","value":"instrument","type":"Literal","bound_global_parameter":null},{"name":"sessions","value":"Q","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"data1","node_id":"-554"}],"output_ports":[{"name":"data","node_id":"-554"}],"cacheable":true,"seq_num":2,"comment":"","comment_collapsed":true}],"node_layout":"<node_postions><node_position Node='287d2cb0-f53c-4101-bdf8-104b137c8601-8' Position='198.51284790039062,24.97765350341797,200,200'/><node_position Node='287d2cb0-f53c-4101-bdf8-104b137c8601-24' Position='551.1575927734375,22.560893058776855,200,200'/><node_position Node='-215' Position='391.92620849609375,247.31396484375,200,200'/><node_position Node='-222' Position='391.24346923828125,450.13751220703125,200,200'/><node_position Node='-554' Position='390.82127380371094,347.7580871582031,200,200'/></node_postions>"},"nodes_readonly":false,"studio_version":"v2"}

# 本代码由可视化策略环境自动生成 2023年4月7日 15:00
# 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='2010-01-01',
    end_date='2022-12-31',
    market='CN_STOCK_A',
    instrument_list='',
    max_count=0
)

m3 = M.input_features.v1(
    features="""ta_macd(close_0, 'golden_cross')
ta_macd_dif(close_0)
ta_macd_dea(close_0)
ta_macd_hist(close_0)"""
)

m15 = M.general_feature_extractor.v7(
    instruments=m1.data,
    features=m3.data,
    start_date='',
    end_date='',
    before_start_days=90
)

m2 = M.resample.v1(
    data1=m15.data,
    group='instrument',
    sessions='Q'
)

m16 = M.derived_feature_extractor.v3(
    input_data=m2.data,
    features=m3.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=False,
    remove_extra_columns=False
)

[2023-04-07 14:59:30.855728] INFO: moduleinvoker: instruments.v2 开始运行..

[2023-04-07 14:59:30.864016] INFO: moduleinvoker: 命中缓存

[2023-04-07 14:59:30.865890] INFO: moduleinvoker: instruments.v2 运行完成[0.010173s].

[2023-04-07 14:59:30.870668] INFO: moduleinvoker: input_features.v1 开始运行..

[2023-04-07 14:59:30.911042] INFO: moduleinvoker: input_features.v1 运行完成[0.04035s].

[2023-04-07 14:59:30.930452] INFO: moduleinvoker: general_feature_extractor.v7 开始运行..

[2023-04-07 14:59:30.938742] INFO: moduleinvoker: 命中缓存

[2023-04-07 14:59:30.940558] INFO: moduleinvoker: general_feature_extractor.v7 运行完成[0.010138s].

[2023-04-07 14:59:30.949895] INFO: moduleinvoker: resample.v1 开始运行..

[2023-04-07 14:59:30.956619] INFO: moduleinvoker: 命中缓存

[2023-04-07 14:59:30.958196] INFO: moduleinvoker: resample.v1 运行完成[0.00831s].

[2023-04-07 14:59:30.966694] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..

[2023-04-07 14:59:48.339093] INFO: derived_feature_extractor: 提取完成 ta_macd(close_0, 'golden_cross'), 16.986s

[2023-04-07 14:59:52.801077] INFO: derived_feature_extractor: 提取完成 ta_macd_dif(close_0), 4.460s

[2023-04-07 14:59:57.272869] INFO: derived_feature_extractor: 提取完成 ta_macd_dea(close_0), 4.470s

[2023-04-07 15:00:02.305213] INFO: derived_feature_extractor: 提取完成 ta_macd_hist(close_0), 5.031s

[2023-04-07 15:00:02.682397] INFO: derived_feature_extractor: /data, 165928

[2023-04-07 15:00:02.832724] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[31.865999s].