[Add]增加参数优化的其他统计数据输出

examples/CtaBacktesting/.ipynb_checkpoints/backtesting_IF-checkpoint.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -11,7 +11,7 @@
     "%matplotlib inline\n",
     "\n",
     "from vnpy.trader.app.ctaStrategy.ctaBacktesting import BacktestingEngine, OptimizationSetting, MINUTE_DB_NAME\n",
-    "#from vnpy.trader.app.ctaStrategy.strategy.strategyAtrRsi import AtrRsiStrategy\n",
+    "from vnpy.trader.app.ctaStrategy.strategy.strategyAtrRsi import AtrRsiStrategy\n",
     "#from vnpy.trader.app.ctaStrategy.strategy.strategyMultiTimeframe import MultiTimeframeStrategy\n",
     "from vnpy.trader.app.ctaStrategy.strategy.strategyMultiSignal import MultiSignalStrategy"
    ]
@@ -39,14 +39,14 @@
     "# 设置回测使用的数据\n",
     "engine.setBacktestingMode(engine.BAR_MODE)    # 设置引擎的回测模式为K线\n",
     "engine.setDatabase(MINUTE_DB_NAME, 'IF0000')  # 设置使用的历史数据库\n",
-    "engine.setStartDate('20100101')               # 设置回测用的数据起始日期"
+    "engine.setStartDate('20130101')               # 设置回测用的数据起始日期"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
@@ -60,7 +60,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -75,25 +75,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
+   "outputs": [],
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2017-12-15 23:01:54.728000\t开始载入数据\n",
-      "2017-12-15 23:01:54.765000\t载入完成，数据量：0\n",
-      "2017-12-15 23:01:54.765000\t开始回测\n",
-      "2017-12-15 23:01:54.765000\t策略初始化完成\n",
-      "2017-12-15 23:01:54.765000\t策略启动完成\n",
-      "2017-12-15 23:01:54.765000\t开始回放数据\n",
-      "2017-12-15 23:01:54.766000\t数据回放结束\n"
-     ]
-    }
-   ],
    "source": [
     "# 运行回测\n",
     "engine.runBacktesting()          # 运行回测"
@@ -139,23 +125,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2018-01-08 17:21:35.783000\t------------------------------\n",
+      "2018-01-08 17:21:35.784000\t优化结果：\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 20, 'atrLength': 12}，目标：0\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 25, 'atrLength': 12}，目标：0\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 30, 'atrLength': 12}，目标：0\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 20, 'atrLength': 14}，目标：0\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 25, 'atrLength': 14}，目标：0\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 30, 'atrLength': 14}，目标：0\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 20, 'atrLength': 16}，目标：0\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 25, 'atrLength': 16}，目标：0\n",
+      "2018-01-08 17:21:35.784000\t参数：{'rsiLength': 5, 'atrMa': 30, 'atrLength': 16}，目标：0\n",
+      "耗时：214.858999968\n"
+     ]
+    }
+   ],
    "source": [
     "# 优化配置\n",
     "setting = OptimizationSetting()                 # 新建一个优化任务设置对象\n",
-    "setting.setOptimizeTarget('capital')            # 设置优化排序的目标是策略净盈利\n",
+    "setting.setOptimizeTarget('totalNetPnl')        # 设置优化排序的目标是策略净盈利\n",
-    "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\n",
+    "setting.addParameter('atrLength', 12, 16, 2)    # 增加第一个优化参数atrLength，起始12，结束20，步进2\n",
     "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\n",
     "setting.addParameter('rsiLength', 5)            # 增加一个固定数值的参数\n",
     "\n",
     "# 执行多进程优化\n",
     "import time\n",
     "start = time.time()\n",
-    "engine.runParallelOptimization(AtrRsiStrategy, setting)\n",
+    "resultList = engine.runParallelOptimization(AtrRsiStrategy, setting)\n",
     "print u'耗时：%s' %(time.time()-start)"
    ]
   },
@@ -166,7 +171,11 @@
     "collapsed": true
    },
    "outputs": [],
-   "source": []
+   "source": [
+    "# 显示优化的所有统计数据\n",
+    "for result in resultList:\n",
+    "    print u'参数：%s，目标：%s，统计数据：%s' %(result[0], result[1], result[2])"
+   ]
   }
  ],
  "metadata": {

vnpy/trader/app/ctaStrategy/ctaBacktesting.py

@@ -876,15 +876,15 @@ class BacktestingEngine(object):
                 targetValue = d[targetName]
             except KeyError:
                 targetValue = 0
-            resultList.append(([str(setting)], targetValue))
+            resultList.append(([str(setting)], targetValue, d))
         
         # 显示结果
         resultList.sort(reverse=True, key=lambda result:result[1])
         self.output('-' * 30)
         self.output(u'优化结果：')
         for result in resultList:
-            self.output(u'%s: %s' %(result[0], result[1]))
+            self.output(u'参数：%s，目标：%s' %(result[0], result[1]))    
-        return result
+        return resultList
             
     #----------------------------------------------------------------------
     def runParallelOptimization(self, strategyClass, optimizationSetting):
@@ -916,7 +916,9 @@ class BacktestingEngine(object):
         self.output('-' * 30)
         self.output(u'优化结果：')
         for result in resultList:
-            self.output(u'%s: %s' %(result[0], result[1]))    
+            self.output(u'参数：%s，目标：%s' %(result[0], result[1]))    
+            
+        return resultList
 
     #----------------------------------------------------------------------
     def updateDailyClose(self, dt, price):
@@ -1270,5 +1272,5 @@ def optimize(strategyClass, setting, targetName,
         targetValue = d[targetName]
     except KeyError:
         targetValue = 0            
-    return (str(setting), targetValue)    
+    return (str(setting), targetValue, d)    
     

vnpy/trader/app/ctaStrategy/ctaEngine.py

@@ -600,7 +600,7 @@ class CtaEngine(object):
         syncData = self.mainEngine.dbQuery(POSITION_DB_NAME, strategy.className, flt)
         
         if not syncData:
-            continue
+            return
         
         d = syncData[0]