2017-06-02 07:56:21 +00:00
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# encoding: UTF-8
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"""
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展示如何执行参数优化。
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"""
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from __future__ import division
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2018-05-07 16:37:09 +00:00
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from __future__ import print_function
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2017-06-02 07:56:21 +00:00
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from vnpy.trader.app.ctaStrategy.ctaBacktesting import BacktestingEngine, MINUTE_DB_NAME, OptimizationSetting
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if __name__ == '__main__':
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from vnpy.trader.app.ctaStrategy.strategy.strategyAtrRsi import AtrRsiStrategy
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# 创建回测引擎
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engine = BacktestingEngine()
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# 设置引擎的回测模式为K线
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engine.setBacktestingMode(engine.BAR_MODE)
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# 设置回测用的数据起始日期
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engine.setStartDate('20120101')
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# 设置产品相关参数
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engine.setSlippage(0.2) # 股指1跳
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engine.setRate(0.3/10000) # 万0.3
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engine.setSize(300) # 股指合约大小
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engine.setPriceTick(0.2) # 股指最小价格变动
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# 设置使用的历史数据库
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engine.setDatabase(MINUTE_DB_NAME, 'IF0000')
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# 跑优化
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setting = OptimizationSetting() # 新建一个优化任务设置对象
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setting.setOptimizeTarget('capital') # 设置优化排序的目标是策略净盈利
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setting.addParameter('atrLength', 12, 20, 2) # 增加第一个优化参数atrLength，起始12，结束20，步进2
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setting.addParameter('atrMa', 20, 30, 5) # 增加第二个优化参数atrMa，起始20，结束30，步进5
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setting.addParameter('rsiLength', 5) # 增加一个固定数值的参数
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# 性能测试环境：I7-3770，主频3.4G, 8核心，内存16G，Windows 7 专业版
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# 测试时还跑着一堆其他的程序，性能仅供参考
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import time
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start = time.time()
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# 运行单进程优化函数，自动输出结果，耗时：359秒
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#engine.runOptimization(AtrRsiStrategy, setting)
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# 多进程优化，耗时：89秒
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engine.runParallelOptimization(AtrRsiStrategy, setting)
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2018-05-07 16:37:09 +00:00
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print(u'耗时：%s' %(time.time()-start))
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