Date bookkeeping fixes in perf and risk

Issues appeared when we were close to the end of our
historical data.

Yielding DONE event with both perf and risk messages now

tests/test_algorithm.py

@@ -39,7 +39,8 @@ class TestTransformAlgorithm(TestCase):
         )
         self.source = SpecificEquityTrades(event_list=trade_history)
 
-        self.df_source, self.df = factory.create_test_df_source()
+        self.df_source, self.df = \
+            factory.create_test_df_source(self.trading_environment)
 
     def test_source_as_input(self):
         algo = TestRegisterTransformAlgorithm(sids=[133])

tests/test_perf_tracking.py

@@ -18,10 +18,14 @@ import copy
 import random
 import datetime
 import pytz
+import itertools
+from operator import attrgetter
 
 import zipline.utils.factory as factory
 import zipline.finance.performance as perf
 from zipline.utils.protocol_utils import ndict
+from zipline.gens.sort import date_sort
+from zipline.protocol import DATASOURCE_TYPE
 
 from zipline.finance.trading import TradingEnvironment
 
@@ -539,7 +543,8 @@ shares in position"
             price_list,
             volume,
             trade_time_increment,
-            self.trading_environment
+            self.trading_environment,
+            source_id="factory1"
         )
 
         sid2 = 134
@@ -550,13 +555,18 @@ shares in position"
             price2_list,
             volume,
             trade_time_increment,
-            self.trading_environment
+            self.trading_environment,
+            source_id="factory2"
         )
 
         trade_history.extend(trade_history2)
 
         self.trading_environment.period_start = trade_history[0].dt
         self.trading_environment.period_end = trade_history[-1].dt
+        self.trading_environment.first_open = \
+            self.trading_environment.calculate_first_open()
+        self.trading_environment.last_close = \
+            self.trading_environment.calculate_last_close()
         self.trading_environment.capital_base = 1000.0
         self.trading_environment.frame_index = [
             'sid',
@@ -568,21 +578,26 @@ shares in position"
             self.trading_environment
         )
 
-        for event in trade_history:
-            #create a transaction for all but
-            #first trade in each sid, to simulate None transaction
-            if(event.dt != self.trading_environment.period_start):
-                txn = ndict({
-                    'sid': event.sid,
-                    'amount': -25,
-                    'dt': event.dt,
-                    'price': 10.0,
-                    'commission': 0.50
-                })
-            else:
-                txn = None
-            event['TRANSACTION'] = txn
-            perf_tracker.process_event(event)
+        # date_sort requires 'DONE' messages from each source
+        events = itertools.chain(trade_history,
+                                 [ndict({
+                                        'source_id': 'factory1',
+                                        'dt': 'DONE',
+                                        'type': DATASOURCE_TYPE.TRADE
+                                        }),
+                                  ndict({
+                                        'source_id': 'factory2',
+                                        'dt': 'DONE',
+                                        'type': DATASOURCE_TYPE.TRADE
+                                        })])
+        events = date_sort(events, ('factory1', 'factory2'))
+        events = itertools.chain(events,
+                                 [ndict({'dt': 'DONE'})])
+
+        events = [self.event_with_txn(event) for event in events]
+
+        list(perf_tracker.transform(
+            itertools.groupby(events, attrgetter('dt'))))
 
         #we skip two trades, to test case of None transaction
         txn_count = len(trade_history) - 2
@@ -592,6 +607,23 @@ shares in position"
         expected_size = txn_count / 2 * -25
         self.assertEqual(cumulative_pos.amount, expected_size)
 
-        self.assertEqual(perf_tracker.period_end.
-                         replace(hour=0, minute=0, second=0),
+        self.assertEqual(perf_tracker.last_close,
                          perf_tracker.cumulative_risk_metrics.end_date)
+
+    def event_with_txn(self, event):
+        #create a transaction for all but
+        #first trade in each sid, to simulate None transaction
+        if event.dt != self.trading_environment.period_start \
+                and event.dt != 'DONE':
+            txn = ndict({
+                'sid': event.sid,
+                'amount': -25,
+                'dt': event.dt,
+                'price': 10.0,
+                'commission': 0.50
+            })
+        else:
+            txn = None
+        event['TRANSACTION'] = txn
+
+        return event

tests/test_risk_compare_batch_iterative.py

@@ -87,10 +87,10 @@ class RiskCompareIterativeToBatch(unittest.TestCase):
                 #assert that when original raises exception, same
                 #exception is raised by risk_metrics_refactor
                 np.testing.assert_raises(
-                    type(e), risk_metrics_refactor.update, ret)
+                    type(e), risk_metrics_refactor.update, todays_date, ret)
                 continue
 
-            risk_metrics_refactor.update(ret)
+            risk_metrics_refactor.update(todays_date, ret)
 
             self.assertEqual(
                 risk_metrics_original.start_date,