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# 本代码由可视化策略环境自动生成 2022年8月12日 17:27
# 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='2022-01-01',
    end_date='2022-08-01',
    market='CN_STOCK_A',
    instrument_list='',
    max_count=0
)

m2 = M.input_features.v1(
    features="""returns = close_0 / shift(close_0, 22)

# return_Nm1 = close_0 / shift(close_0, 120)

# wgt_return_Nm = mean(turn_0 * return_0, 22)

# exp_wgt_return_Nm = ' + '.join(['shift(turn_0,{})*exp(-{}/1/4)'.format(k, k) for k in range(22)])"""
)

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

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

m9 = M.instruments.v2(
    start_date='2022-01-01',
    end_date='2022-08-01',
    market='CN_STOCK_A',
    instrument_list='000001.HIX',
    max_count=0
)

m10 = M.input_features.v1(
    features="""bm_close = bar1d_index_CN_STOCK_A__close
bm_return = bm_close / shift(bm_close, 22)"""
)

m11 = M.general_feature_extractor.v7(
    instruments=m9.data,
    features=m10.data,
    start_date='',
    end_date='',
    before_start_days=0
)

m14 = M.derived_feature_extractor.v3(
    input_data=m11.data,
    features=m10.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=True,
    remove_extra_columns=True,
    user_functions={}
)

m13 = M.select_columns.v3(
    input_ds=m14.data,
    columns='date,bm_return',
    reverse_select=False
)

m12 = M.join.v3(
    data1=m13.data,
    data2=m16.data,
    on='date',
    how='inner',
    sort=True
)

m15 = M.input_features.v1(
    features='intercept = ols("intercept", returns, bm_return, 22)'
)

m4 = M.derived_feature_extractor.v3(
    input_data=m12.data,
    features=m15.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=False,
    remove_extra_columns=False,
    user_functions={},
    m_cached=False
)

[2022-08-12 17:23:01.324366] INFO: moduleinvoker: instruments.v2 开始运行..

[2022-08-12 17:23:01.334136] INFO: moduleinvoker: 命中缓存

[2022-08-12 17:23:01.336621] INFO: moduleinvoker: instruments.v2 运行完成[0.012281s].

[2022-08-12 17:23:01.345729] INFO: moduleinvoker: input_features.v1 开始运行..

[2022-08-12 17:23:01.359037] INFO: moduleinvoker: 命中缓存

[2022-08-12 17:23:01.361301] INFO: moduleinvoker: input_features.v1 运行完成[0.015765s].

[2022-08-12 17:23:01.412860] INFO: moduleinvoker: general_feature_extractor.v7 开始运行..

[2022-08-12 17:23:01.423905] INFO: moduleinvoker: 命中缓存

[2022-08-12 17:23:01.426896] INFO: moduleinvoker: general_feature_extractor.v7 运行完成[0.014136s].

[2022-08-12 17:23:01.443282] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..

[2022-08-12 17:23:02.982888] INFO: derived_feature_extractor: 提取完成 returns = close_0 / shift(close_0, 22), 0.094s

[2022-08-12 17:23:04.249727] INFO: derived_feature_extractor: /y_2022, 661306

[2022-08-12 17:23:04.531149] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[3.08786s].

[2022-08-12 17:23:04.540687] INFO: moduleinvoker: instruments.v2 开始运行..

[2022-08-12 17:23:04.555246] INFO: moduleinvoker: 命中缓存

[2022-08-12 17:23:04.559171] INFO: moduleinvoker: instruments.v2 运行完成[0.018469s].

[2022-08-12 17:23:04.579291] INFO: moduleinvoker: input_features.v1 开始运行..

[2022-08-12 17:23:04.604030] INFO: moduleinvoker: 命中缓存

[2022-08-12 17:23:04.608139] INFO: moduleinvoker: input_features.v1 运行完成[0.028854s].

[2022-08-12 17:23:04.634835] INFO: moduleinvoker: general_feature_extractor.v7 开始运行..

[2022-08-12 17:23:04.655916] INFO: moduleinvoker: 命中缓存

[2022-08-12 17:23:04.658087] INFO: moduleinvoker: general_feature_extractor.v7 运行完成[0.023281s].

[2022-08-12 17:23:04.696280] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..

[2022-08-12 17:23:04.776954] INFO: derived_feature_extractor: 提取完成 bm_close = bar1d_index_CN_STOCK_A__close, 0.001s

[2022-08-12 17:23:04.783507] INFO: derived_feature_extractor: 提取完成 bm_return = bm_close / shift(bm_close, 22), 0.004s

[2022-08-12 17:23:04.864629] INFO: derived_feature_extractor: /y_2022, 139

[2022-08-12 17:23:04.987955] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[0.291699s].

[2022-08-12 17:23:05.016163] INFO: moduleinvoker: select_columns.v3 开始运行..

[2022-08-12 17:23:05.331167] INFO: moduleinvoker: select_columns.v3 运行完成[0.31504s].

[2022-08-12 17:23:05.348617] INFO: moduleinvoker: join.v3 开始运行..

[2022-08-12 17:23:06.795696] INFO: join: /y_2022, 行数=554157/554157, 耗时=1.240558s

[2022-08-12 17:23:06.884539] INFO: join: 最终行数: 554157

[2022-08-12 17:23:06.899157] INFO: moduleinvoker: join.v3 运行完成[1.550535s].

[2022-08-12 17:23:06.909500] INFO: moduleinvoker: input_features.v1 开始运行..

[2022-08-12 17:23:06.926522] INFO: moduleinvoker: 命中缓存

[2022-08-12 17:23:06.929345] INFO: moduleinvoker: input_features.v1 运行完成[0.019861s].

[2022-08-12 17:23:06.941449] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..

[2022-08-12 17:27:19.888171] INFO: derived_feature_extractor: 提取完成 intercept = ols("intercept", returns, bm_return, 22), 251.462s

[2022-08-12 17:27:21.453362] INFO: derived_feature_extractor: /y_2022, 554157

[2022-08-12 17:27:21.722355] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[254.780889s].

列： ['date', 'bm_return']
/y_2022: 117