克隆策略

    {"Description":"实验创建于2017/8/26","Summary":"","Graph":{"EdgesInternal":[{"DestinationInputPortId":"-1242:input_1","SourceOutputPortId":"-1232:data"},{"DestinationInputPortId":"-1255:input_data","SourceOutputPortId":"-1242:data_1"}],"ModuleNodes":[{"Id":"-1232","ModuleId":"BigQuantSpace.use_datasource.use_datasource-v1","ModuleParameters":[{"Name":"datasource_id","Value":"trading_days","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"start_date","Value":"","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"end_date","Value":"","ValueType":"Literal","LinkedGlobalParameter":null}],"InputPortsInternal":[{"DataSourceId":null,"TrainedModelId":null,"TransformModuleId":null,"Name":"instruments","NodeId":"-1232"},{"DataSourceId":null,"TrainedModelId":null,"TransformModuleId":null,"Name":"features","NodeId":"-1232"}],"OutputPortsInternal":[{"Name":"data","NodeId":"-1232","OutputType":null}],"UsePreviousResults":true,"moduleIdForCode":1,"Comment":"","CommentCollapsed":true},{"Id":"-1242","ModuleId":"BigQuantSpace.cached.cached-v3","ModuleParameters":[{"Name":"run","Value":"def bigquant_run(input_1):\n df = input_1.read()\n df = df[df.country_code == 'CN']\n df = df.set_index('date')\n df = pd.DataFrame({'交易天数': df.resample('M').size()})\n data_1 = DataSource.write_df(df)\n return Outputs(data_1=data_1)\n","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"post_run","Value":"# 后处理函数，可选。输入是主函数的输出，可以在这里对数据做处理，或者返回更友好的outputs数据格式。此函数输出不会被缓存。\ndef bigquant_run(outputs):\n return outputs\n","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"input_ports","Value":"","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"params","Value":"{}","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"output_ports","Value":"","ValueType":"Literal","LinkedGlobalParameter":null}],"InputPortsInternal":[{"DataSourceId":null,"TrainedModelId":null,"TransformModuleId":null,"Name":"input_1","NodeId":"-1242"},{"DataSourceId":null,"TrainedModelId":null,"TransformModuleId":null,"Name":"input_2","NodeId":"-1242"},{"DataSourceId":null,"TrainedModelId":null,"TransformModuleId":null,"Name":"input_3","NodeId":"-1242"}],"OutputPortsInternal":[{"Name":"data_1","NodeId":"-1242","OutputType":null},{"Name":"data_2","NodeId":"-1242","OutputType":null},{"Name":"data_3","NodeId":"-1242","OutputType":null}],"UsePreviousResults":true,"moduleIdForCode":2,"Comment":"","CommentCollapsed":true},{"Id":"-1255","ModuleId":"BigQuantSpace.plot_dataframe.plot_dataframe-v1","ModuleParameters":[{"Name":"title","Value":"交易天数统计","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"chart_type","Value":"line","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"x","Value":"","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"y","Value":"交易天数","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"options","Value":"{\n 'chart': {\n 'height': 400\n }\n}","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"candlestick","Value":"False","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"pane_1","Value":"","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"pane_2","Value":"","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"pane_3","Value":"","ValueType":"Literal","LinkedGlobalParameter":null},{"Name":"pane_4","Value":"","ValueType":"Literal","LinkedGlobalParameter":null}],"InputPortsInternal":[{"DataSourceId":null,"TrainedModelId":null,"TransformModuleId":null,"Name":"input_data","NodeId":"-1255"}],"OutputPortsInternal":[],"UsePreviousResults":false,"moduleIdForCode":3,"Comment":"","CommentCollapsed":true}],"SerializedClientData":"<?xml version='1.0' encoding='utf-16'?><DataV1 xmlns:xsd='http://www.w3.org/2001/XMLSchema' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance'><Meta /><NodePositions><NodePosition Node='-1232' Position='501.78192138671875,59.84046936035156,200,200'/><NodePosition Node='-1242' Position='471.6534729003906,183.52542114257812,200,200'/><NodePosition Node='-1255' Position='479.58209228515625,307.2103271484375,200,200'/></NodePositions><NodeGroups /></DataV1>"},"IsDraft":true,"ParentExperimentId":null,"WebService":{"IsWebServiceExperiment":false,"Inputs":[],"Outputs":[],"Parameters":[{"Name":"交易日期","Value":"","ParameterDefinition":{"Name":"交易日期","FriendlyName":"交易日期","DefaultValue":"","ParameterType":"String","HasDefaultValue":true,"IsOptional":true,"ParameterRules":[],"HasRules":false,"MarkupType":0,"CredentialDescriptor":null}}],"WebServiceGroupId":null,"SerializedClientData":"<?xml version='1.0' encoding='utf-16'?><DataV1 xmlns:xsd='http://www.w3.org/2001/XMLSchema' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance'><Meta /><NodePositions></NodePositions><NodeGroups /></DataV1>"},"DisableNodesUpdate":false,"Category":"user","Tags":[],"IsPartialRun":true}
    In [21]:
    # 本代码由可视化策略环境自动生成 2019年9月4日 23:10
# 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 m2_run_bigquant_run(input_1):
    df = input_1.read()
    df = df[df.country_code == 'CN']
    df = df.set_index('date')
    df = pd.DataFrame({'交易天数': df.resample('M').size()})
    data_1 = DataSource.write_df(df)
    return Outputs(data_1=data_1)

# 后处理函数，可选。输入是主函数的输出，可以在这里对数据做处理，或者返回更友好的outputs数据格式。此函数输出不会被缓存。
def m2_post_run_bigquant_run(outputs):
    return outputs


m1 = M.use_datasource.v1(
    datasource_id='trading_days',
    start_date='',
    end_date=''
)

m2 = M.cached.v3(
    input_1=m1.data,
    run=m2_run_bigquant_run,
    post_run=m2_post_run_bigquant_run,
    input_ports='',
    params='{}',
    output_ports=''
)

m3 = M.plot_dataframe.v1(
    input_data=m2.data_1,
    title='交易天数统计',
    chart_type='line',
    x='',
    y='交易天数',
    options={
    'chart': {
        'height': 400
    }
},
    candlestick=False,
    pane_1='',
    pane_2='',
    pane_3='',
    pane_4=''
)