adding type as variable to create_test_panel

tests/test_sources.py

@@ -47,14 +47,16 @@ class TestDataFrameSource(TestCase):
             "DataFrameSource should only stream selected sid 0, not sid 1."
 
     def test_panel_source(self):
-        source, panel = factory.create_test_panel_source()
+        source, panel = factory.create_test_panel_source(source_type=5)
         assert isinstance(source.start, pd.lib.Timestamp)
         assert isinstance(source.end, pd.lib.Timestamp)
         for event in source:
             self.assertTrue('sid' in event)
             self.assertTrue('arbitrary' in event)
+            self.assertTrue('type' in event)
             self.assertTrue(hasattr(event, 'volume'))
             self.assertTrue(hasattr(event, 'price'))
+            self.assertEquals(event['type'], 5)
             self.assertEquals(event['arbitrary'], 1.)
             self.assertEquals(event['sid'], 0)
             self.assertTrue(isinstance(event['volume'], int))

zipline/finance/performance/tracker.py

@@ -339,7 +339,8 @@ class PerformanceTracker(object):
 
     def process_close_position(self, event):
         txn = self.position_tracker.create_close_position_transaction(event)
-        self.process_transaction(txn)
+        if txn:
+            self.process_transaction(txn)
 
     def check_upcoming_dividends(self, midnight_of_date_that_just_ended):
         """

zipline/utils/factory.py

@@ -315,7 +315,7 @@ def create_test_df_source(sim_params=None, bars='daily'):
     return DataFrameSource(df), df
 
 
-def create_test_panel_source(sim_params=None):
+def create_test_panel_source(sim_params=None, source_type=None):
     start = sim_params.first_open \
         if sim_params else pd.datetime(1990, 1, 3, 0, 0, 0, 0, pytz.utc)
 
@@ -329,12 +329,17 @@ def create_test_panel_source(sim_params=None):
 
     price = np.arange(0, len(index))
     volume = np.ones(len(index)) * 1000
+
     arbitrary = np.ones(len(index))
 
     df = pd.DataFrame({'price': price,
                        'volume': volume,
                        'arbitrary': arbitrary},
                       index=index)
+    if source_type:
+        source_types = np.full(len(index), source_type)
+        df['type'] = source_types
+
     panel = pd.Panel.from_dict({0: df})
 
     return DataPanelSource(panel), panel