{"description":"实验创建于2020/2/23","graph":{"edges":[{"to_node_id":"-96:instruments","from_node_id":"-11:data"},{"to_node_id":"-96:features","from_node_id":"-19:data"},{"to_node_id":"-31:features","from_node_id":"-19:data"},{"to_node_id":"-31:input_data","from_node_id":"-96:data"}],"nodes":[{"node_id":"-11","module_id":"BigQuantSpace.instruments.instruments-v2","parameters":[{"name":"start_date","value":"2022-09-10","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"2022-11-08","type":"Literal","bound_global_parameter":null},{"name":"market","value":"CN_STOCK_A","type":"Literal","bound_global_parameter":null},{"name":"instrument_list","value":"003003.SZA\n600519.SHA\n","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":false,"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\n# amount=bar1d_CN_STOCK_A__amount\n#mean(amount, 2)\n#close_1=shift(bar1d_CN_STOCK_A__close, 1)\n#close_avg=(bar1d_CN_STOCK_A__close + bar1d_CN_STOCK_A__open)/2\n# pb_lf=market_value_CN_STOCK_A__pb_lf\n#pe_ttm=market_value_CN_STOCK_A__pe_ttm\n# amount_5\n# rank_amount_5\n# #((close_0-open_0)/open_0)/((close_0-open_4)/open_4)\n# daily_return_3\n# # rank_avg_amount_5\n# avg_amount_5\n# # rank_amount_5\n# rank_amount_0\n# std(turn_0,10)\n# avg_turn_5\n# rank_swing_volatility_60_0\n# fe1=sum(max(0,high_0-delay((high_0+low_0+close_0)/3,1)),26)/sum(max(0,delay((high_0+low_0+close_0)/3,1)-1),26)*100\n# mean(turn_0*(return_0-1),30)\n# std(return_0-1,60)\n# std(return_0-1,15)\n# fe2o=rank(((close_0-sum(min(low_0,delay(close_0,1)),6))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),6)*12*24+(close_0-sum(min(low_0,delay(close_0,1)),12))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),12)*6*24+(close_0-sum(min(low_0,delay(close_0,1)),24))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),24)*6*24)/-20000)\n# # rank_amount_0/rank_avg_amount_5\nfs_roe_0\nclose_0\nfe3=sum((close_0-open_0)/open_0>0.04,20)\nrank_volatility_10_0\nrank_swing_volatility_10_0\n\n\n\n# market_cap_float_0\n#fe2=((close_0-sum(min(low_0,delay(close_0,1)),6))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),6)*12*24+(close_0-sum(min(low_0,delay(close_0,1)),12))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),12)*6*24+(close_0-sum(min(low_0,delay(close_0,1)),24))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),24)*6*24)*100/(6*12+6*24+12*24)","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"features_ds","node_id":"-19"}],"output_ports":[{"name":"data","node_id":"-19"}],"cacheable":false,"seq_num":3,"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":"200","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_id":"-31","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":"-31"},{"name":"features","node_id":"-31"}],"output_ports":[{"name":"data","node_id":"-31"}],"cacheable":true,"seq_num":4,"comment":"","comment_collapsed":true}],"node_layout":"<node_postions><node_position Node='-11' Position='179.75076293945312,142.43533325195312,200,200'/><node_position Node='-19' Position='483.42022705078125,141.44674682617188,200,200'/><node_position Node='-96' Position='345.3276672363281,286.1951599121094,200,200'/><node_position Node='-31' Position='352.2735595703125,384.3444519042969,200,200'/></node_postions>"},"nodes_readonly":false,"studio_version":"v2"}

# 本代码由可视化策略环境自动生成 2022年11月10日 10:47
# 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='2022-09-10',
    end_date='2022-11-08',
    market='CN_STOCK_A',
    instrument_list="""003003.SZA
600519.SHA
""",
    max_count=0,
    m_cached=False
)

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
# amount=bar1d_CN_STOCK_A__amount
#mean(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
# amount_5
# rank_amount_5
# #((close_0-open_0)/open_0)/((close_0-open_4)/open_4)
# daily_return_3
# # rank_avg_amount_5
# avg_amount_5
# # rank_amount_5
# rank_amount_0
# std(turn_0,10)
# avg_turn_5
# rank_swing_volatility_60_0
# fe1=sum(max(0,high_0-delay((high_0+low_0+close_0)/3,1)),26)/sum(max(0,delay((high_0+low_0+close_0)/3,1)-1),26)*100
# mean(turn_0*(return_0-1),30)
# std(return_0-1,60)
# std(return_0-1,15)
# fe2o=rank(((close_0-sum(min(low_0,delay(close_0,1)),6))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),6)*12*24+(close_0-sum(min(low_0,delay(close_0,1)),12))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),12)*6*24+(close_0-sum(min(low_0,delay(close_0,1)),24))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),24)*6*24)/-20000)
# # rank_amount_0/rank_avg_amount_5
fs_roe_0
close_0
fe3=sum((close_0-open_0)/open_0>0.04,20)
rank_volatility_10_0
rank_swing_volatility_10_0



# market_cap_float_0
#fe2=((close_0-sum(min(low_0,delay(close_0,1)),6))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),6)*12*24+(close_0-sum(min(low_0,delay(close_0,1)),12))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),12)*6*24+(close_0-sum(min(low_0,delay(close_0,1)),24))/sum(max(high_0,delay(close_0,1))-min(low_0,delay(close_0,1)),24)*6*24)*100/(6*12+6*24+12*24)""",
    m_cached=False
)

m1 = M.general_feature_extractor.v7(
    instruments=m2.data,
    features=m3.data,
    start_date='',
    end_date='',
    before_start_days=200,
    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=False,
    user_functions={}
)

[2022-11-10 10:43:55.619933] INFO: moduleinvoker: instruments.v2 开始运行..

[2022-11-10 10:43:55.664976] INFO: moduleinvoker: instruments.v2 运行完成[0.045046s].

[2022-11-10 10:43:55.670453] INFO: moduleinvoker: input_features.v1 开始运行..

[2022-11-10 10:43:55.704658] INFO: moduleinvoker: input_features.v1 运行完成[0.034193s].

[2022-11-10 10:43:55.722578] INFO: moduleinvoker: general_feature_extractor.v7 开始运行..

[2022-11-10 10:43:56.036019] INFO: 基础特征抽取: 年份 2022, 特征行数=348

[2022-11-10 10:43:56.062250] INFO: 基础特征抽取: 总行数: 348

[2022-11-10 10:43:56.064218] INFO: moduleinvoker: general_feature_extractor.v7 运行完成[0.341679s].

[2022-11-10 10:43:56.071397] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..

[2022-11-10 10:43:56.116611] INFO: derived_feature_extractor: 提取完成 fe3=sum((close_0-open_0)/open_0>0.04,20), 0.005s

[2022-11-10 10:43:56.156962] INFO: derived_feature_extractor: /y_2022, 348

[2022-11-10 10:43:56.206459] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[0.135034s].