[Add]run ga optimization in CtaBacktester

.flake8

@@ -5,3 +5,4 @@ ignore =
     W503 line break before binary operator
     W293 blank line contains whitespace
     W291 trailing whitespace
+    W391 blank line at end of file

tests/backtesting/turtle.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -54,11 +54,62 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2019-05-03 16:19:04.193703\t开始运行遗传算法，每代族群总数：11, 优良品种筛选个数：8，迭代次数：30，交叉概率：0.95，突变概率：0.050000000000000044\n",
+      "gen\tnevals\tmean        \tstd         \tmin         \tmax        \n",
+      "0  \t11    \t[0.58423524]\t[0.30377007]\t[0.13231977]\t[1.2382818]\n",
+      "1  \t11    \t[0.90248989]\t[0.15747112]\t[0.68707859]\t[1.2382818]\n",
+      "2  \t11    \t[1.09406088]\t[0.18860523]\t[0.86284921]\t[1.46762684]\n",
+      "3  \t11    \t[1.21413386]\t[0.12138014]\t[1.02072108]\t[1.46762684]\n",
+      "4  \t11    \t[1.29561806]\t[0.09930932]\t[1.2382818] \t[1.46762684]\n",
+      "5  \t11    \t[1.41029058]\t[0.09930932]\t[1.2382818] \t[1.46762684]\n",
+      "6  \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "7  \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "8  \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "9  \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "10 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "11 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "12 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "13 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "14 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "15 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "16 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "17 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "18 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "19 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "20 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "21 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "22 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "23 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "24 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "25 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "26 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "27 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "28 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "29 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "30 \t11    \t[1.46762684]\t[0.]        \t[1.46762684]\t[1.46762684]\n",
+      "2019-05-03 16:19:58.256354\t遗传算法优化完成，耗时54秒\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[({'atr_length': 38, 'atr_ma_length': 25}, 1.4676268402266743)]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "setting = OptimizationSetting()\n",
     "setting.set_target(\"sharpe_ratio\")\n",

vnpy/app/cta_backtester/engine.py

@@ -222,20 +222,25 @@ class BacktesterEngine(BaseEngine):
         return strategy_class.get_class_parameters()
 
     def run_optimization(
-            self,
+        self,
-            class_name: str,
+        class_name: str,
-            vt_symbol: str,
+        vt_symbol: str,
-            interval: str,
+        interval: str,
-            start: datetime,
+        start: datetime,
-            end: datetime,
+        end: datetime,
-            rate: float,
+        rate: float,
-            slippage: float,
+        slippage: float,
-            size: int,
+        size: int,
-            pricetick: float,
+        pricetick: float,
-            capital: int,
+        capital: int,
-            optimization_setting: OptimizationSetting):
+        optimization_setting: OptimizationSetting,
+        use_ga: bool
+    ):
         """"""
-        self.write_log("开始多进程参数优化")
+        if use_ga:
+            self.write_log("开始遗传算法参数优化")
+        else:
+            self.write_log("开始多进程参数优化")
 
         self.result_values = None
 
@@ -260,10 +265,16 @@ class BacktesterEngine(BaseEngine):
             {}
         )
 
-        self.result_values = engine.run_optimization(
+        if use_ga:
-            optimization_setting,
+            self.result_values = engine.run_ga_optimization(
-            output=False
+                optimization_setting,
-        )
+                output=False
+            )
+        else:
+            self.result_values = engine.run_optimization(
+                optimization_setting,
+                output=False
+            )
 
         # Clear thread object handler.
         self.thread = None
@@ -285,7 +296,8 @@ class BacktesterEngine(BaseEngine):
         size: int,
         pricetick: float,
         capital: int,
-        optimization_setting: OptimizationSetting
+        optimization_setting: OptimizationSetting,
+        use_ga: bool
     ):
         if self.thread:
             self.write_log("已有任务在运行中，请等待完成")
@@ -305,7 +317,8 @@ class BacktesterEngine(BaseEngine):
                 size,
                 pricetick,
                 capital,
-                optimization_setting
+                optimization_setting,
+                use_ga
             )
         )
         self.thread.start()

vnpy/app/cta_backtester/ui/widget.py

@@ -240,7 +240,7 @@ class BacktesterManager(QtWidgets.QWidget):
         if i != dialog.Accepted:
             return
 
-        optimization_setting = dialog.get_setting()
+        optimization_setting, use_ga = dialog.get_setting()
         self.target_display = dialog.target_display
 
         self.backtester_engine.start_optimization(
@@ -254,7 +254,8 @@ class BacktesterManager(QtWidgets.QWidget):
             size,
             pricetick,
             capital,
-            optimization_setting
+            optimization_setting,
+            use_ga
         )
 
         self.result_button.setEnabled(False)
@@ -592,6 +593,7 @@ class OptimizationSettingEditor(QtWidgets.QDialog):
         self.edits = {}
 
         self.optimization_setting = None
+        self.use_ga = False
 
         self.init_ui()
 
@@ -642,12 +644,27 @@ class OptimizationSettingEditor(QtWidgets.QDialog):
 
             row += 1
 
-        button = QtWidgets.QPushButton("确定")
+        parallel_button = QtWidgets.QPushButton("多进程优化")
-        button.clicked.connect(self.generate_setting)
+        parallel_button.clicked.connect(self.generate_parallel_setting)
-        grid.addWidget(button, row, 0, 1, 4)
+        grid.addWidget(parallel_button, row, 0, 1, 4)
+
+        row += 1
+        ga_button = QtWidgets.QPushButton("遗传算法优化")
+        ga_button.clicked.connect(self.generate_ga_setting)
+        grid.addWidget(ga_button, row, 0, 1, 4)
 
         self.setLayout(grid)
 
+    def generate_ga_setting(self):
+        """"""
+        self.use_ga = True
+        self.generate_setting()
+
+    def generate_parallel_setting(self):
+        """"""
+        self.use_ga = False
+        self.generate_setting()
+
     def generate_setting(self):
         """"""
         self.optimization_setting = OptimizationSetting()
@@ -676,7 +693,7 @@ class OptimizationSettingEditor(QtWidgets.QDialog):
 
     def get_setting(self):
         """"""
-        return self.optimization_setting
+        return self.optimization_setting, self.use_ga
 
 
 class OptimizationResultMonitor(QtWidgets.QDialog):

vnpy/app/cta_strategy/backtesting.py

@@ -601,8 +601,12 @@ class BacktestingEngine:
         # toolbox.register("map", pool.map)
 
         # Run ga optimization
-        msg = "开始运行遗传算法，每代族群总数：%s, 优良品种筛选个数：%s，迭代次数：%s，交叉概率：%s，突变概率：%s" % (pop_size, mu, ngen, cxpb, mutpb)
+        self.output(f"参数优化空间：{total_size}")
-        self.output(msg)
+        self.output(f"每代族群总数：{pop_size}")
+        self.output(f"优良筛选个数：{mu}")
+        self.output(f"迭代次数：{ngen}")
+        self.output(f"交叉概率：{cxpb:.0%}")
+        self.output(f"突变概率：{mutpb:.0%}")
 
         start = time()
 
@@ -617,7 +621,7 @@ class BacktestingEngine:
             stats,
             halloffame=hof
         )    
-
+        
         end = time()
         cost = int((end - start))
 
@@ -630,7 +634,7 @@ class BacktestingEngine:
         for parameter_values in hof:
             setting = dict(zip(parameter_keys, parameter_values))
             target_value = ga_optimize(parameter_values)[0]
-            results.append((setting, target_value))
+            results.append((setting, target_value, {}))
         
         return results
 
@@ -1059,12 +1063,13 @@ def optimize(
     pricetick: float,
     capital: int,
     end: datetime,
-    mode: BacktestingMode,
+    mode: BacktestingMode
 ):
     """
     Function for running in multiprocessing.pool
     """
     engine = BacktestingEngine()
+    
     engine.set_parameters(
         vt_symbol=vt_symbol,
         interval=interval,