made executors to return turn over

alphamind/execution/baseexecutor.py

@@ -7,14 +7,24 @@ Created on 2017-9-22
 
 
 import abc
+from typing import Tuple
+import numpy as np
 import pandas as pd
 
 
 class ExecutorBase(metaclass=abc.ABCMeta):
 
     def __init__(self):
-        pass
+        self.current_pos = pd.DataFrame()
 
     @abc.abstractmethod
     def execute(self, target_pos: pd.DataFrame) -> pd.DataFrame:
-        pass
+        pass
\ No newline at end of file
+
+    @staticmethod
+    def calc_turn_over(target_pos: pd.DataFrame, current_pos: pd.DataFrame) -> float:
+        pos_merged = pd.merge(target_pos, current_pos, on=['code'], how='outer')
+        pos_merged.fillna(0, inplace=True)
+        pos_merged['industry'] = pos_merged['industry_x'].where(pos_merged['industry_x'] != 0, pos_merged['industry_y'])
+        turn_over = np.abs(pos_merged.weight_x - pos_merged.weight_y).sum()
+        return turn_over

alphamind/execution/naiveexecutor.py

@@ -5,6 +5,7 @@ Created on 2017-9-22
 @author: cheng.li
 """
 
+from typing import Tuple
 import pandas as pd
 from alphamind.execution.baseexecutor import ExecutorBase
 
@@ -14,5 +15,10 @@ class NaiveExecutor(ExecutorBase):
     def __init__(self):
         super().__init__()
 
-    def execute(self, target_pos: pd.DataFrame) -> pd.DataFrame:
-        return target_pos.copy()
+    def execute(self, target_pos: pd.DataFrame) -> Tuple[float, pd.DataFrame]:
+        if self.current_pos.empty:
+            turn_over = target_pos.weight.sum()
+        else:
+            turn_over = self.calc_turn_over(target_pos, self.current_pos)
+        self.current_pos = target_pos.copy()
+        return turn_over, target_pos.copy()

alphamind/execution/thresholdexecutor.py

@@ -5,7 +5,7 @@ Created on 2017-9-22
 @author: cheng.li
 """
 
-import numpy as np
+from typing import Tuple
 import pandas as pd
 from alphamind.execution.baseexecutor import ExecutorBase
 
@@ -17,19 +17,16 @@ class ThresholdExecutor(ExecutorBase):
         self.threshold = turn_over_threshold
         self.current_pos = pd.DataFrame()
 
-    def execute(self, target_pos: pd.DataFrame) -> pd.DataFrame:
+    def execute(self, target_pos: pd.DataFrame) -> Tuple[float, pd.DataFrame]:
 
         if self.current_pos.empty:
             self.current_pos = target_pos.copy()
-            return target_pos.copy()
+            return target_pos.weight.sum(), target_pos.copy()
         else:
-            pos_merged = pd.merge(target_pos, self.current_pos, on=['code'], how='outer')
-            pos_merged.fillna(0, inplace=True)
-            pos_merged['industry'] = pos_merged['industry_x'].where(pos_merged['industry_x'] != 0, pos_merged['industry_y'])
-            turn_over = np.abs(pos_merged.weight_x - pos_merged.weight_y).sum()
+            turn_over = self.calc_turn_over(target_pos, self.current_pos)
 
             if turn_over >= self.threshold:
                 self.current_pos = target_pos.copy()
-                return self.current_pos.copy()
+                return turn_over, self.current_pos.copy()
             else:
-                return self.current_pos.copy()
+                return 0., self.current_pos.copy()

alphamind/tests/execution/test_thresholdexecutor.py

@@ -21,24 +21,27 @@ class TestThresholdExecutor(unittest.TestCase):
         executor = ThresholdExecutor(turn_over_threshold=0.5)
 
         # 1st round
-        executed_pos = executor.execute(target_pos)
+        turn_over, executed_pos = executor.execute(target_pos)
         self.assertTrue(target_pos.equals(executed_pos))
+        self.assertAlmostEqual(turn_over, target_pos.weight.sum())
 
         # 2nd round
         target_pos = pd.DataFrame({'code': [1, 2, 4],
                                    'weight': [0.3, 0.2, 0.5],
                                    'industry': ['a', 'b', 'd']})
 
-        executed_pos = executor.execute(target_pos)
+        turn_over, executed_pos = executor.execute(target_pos)
         self.assertTrue(target_pos.equals(executed_pos))
         self.assertTrue(executed_pos.equals(executor.current_pos))
+        self.assertAlmostEqual(turn_over, 1.2)
 
         # 3nd round
         target_pos = pd.DataFrame({'code': [1, 3, 4],
                                    'weight': [0.3, 0.2, 0.5],
                                    'industry': ['a', 'c', 'd']})
-        executed_pos2 = executor.execute(target_pos)
+        turn_over, executed_pos2 = executor.execute(target_pos)
         self.assertTrue(executed_pos.equals(executed_pos2))
+        self.assertAlmostEqual(turn_over, 0.)
 
 
 if __name__ == '__main__':