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# 本代码由可视化策略环境自动生成 2022年12月29日 11:28
# 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='2017-01-01',
    end_date='2022-11-30',
    market='CN_FUTURE',
    instrument_list='',
    max_count=0
)

m4 = M.futures_forward_extractor.v11(
    input_1=m2.data,
    before_days=0,
    product_filter=["BB", "LR", "JR", "FB", "RI",
 "WR", "RS", "PM", "WT", "TC",
 "RO", "ER", "WS", "B", "FU",
 "LU", "SC", "L", "ME", "WH"],
    if_CFX=True,
    set_enable_trade=False,
    output_type='主力连续'
)

m6 = M.use_datasource.v2(
    instruments=m4.data_2,
    datasource_id='bar1d_CN_FUTURE',
    start_date='',
    end_date='',
    before_start_days=0
)

m3 = M.input_features.v1(
    features="""close
open
high
low
amount
volume
open_intl"""
)

m5 = M.derived_feature_extractor.v3(
    input_data=m6.data,
    features=m3.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=False,
    remove_extra_columns=False,
    user_functions={}
)

m7 = M.genetic_algorithm.v1(
    instruments=m4.data_2,
    feature_datas=m5.data,
    market='CN_FUTURE',
    freq='daily',
    all_start_date='',
    all_end_date='',
    short_date_range_ratio=0.7,
    return_field='close',
    rebalance_period=5,
    train_test_ratio=0.75,
    train_validate_ratio=0.75,
    mtime=100,
    init_ind_num=20,
    ngen=5,
    fitness_func='future_longshort_sharpe',
    train_fitness=1.5,
    test_fitness=1.2,
    ir_type='ir',
    cxpb=0.5,
    mutpb=0.3,
    mutspb=0.3,
    mutnrpb=0.3,
    constant='1,11',
    pool_processes_limit=10
)