MAINT: Add comments and rename methods in PerformanceTracker.

The function that handles a market close for daily frequency changed from
`handle_market_close` to `handle_market_close_daily`.

The function that is called at on the closing minute each day when running
minutely changed from `handle_intraday_close` to
`handle_intraday_market_close`.

tests/test_perf_tracking.py

@@ -88,7 +88,7 @@ def calculate_results(host, events):
             if event.type == DATASOURCE_TYPE.BENCHMARK:
                 bm_updated = True
         if bm_updated:
-            msg = perf_tracker.handle_market_close()
+            msg = perf_tracker.handle_market_close_daily()
             results.append(msg)
             bm_updated = False
     return results
@@ -1259,7 +1259,7 @@ class TestPerformanceTracker(unittest.TestCase):
         for date, group in grouped_events:
             for event in group:
                 perf_tracker.process_event(event)
-            msg = perf_tracker.handle_market_close()
+            msg = perf_tracker.handle_market_close_daily()
             perf_messages.append(msg)
 
         self.assertEqual(perf_tracker.txn_count, len(txns))

zipline/finance/performance/tracker.py

@@ -305,7 +305,17 @@ class PerformanceTracker(object):
         if dt == self.market_close:
             self.returns[todays_date] = self.todays_performance.returns
 
-    def handle_intraday_close(self, new_mkt_open, new_mkt_close):
+    def handle_intraday_market_close(self, new_mkt_open, new_mkt_close):
+        """
+        Function called at market close only when emitting at minutely
+        frequency.
+
+        TODO_SS: Why dont' we call this if we're emitting at daily frequency
+                 but running with a minutely datasource?  Is that just not a
+                 valid combination? If so, why do we draw a distinction between
+                 emission rate and data frequency?
+        """
+
         # update_performance should have been called in handle_minute_close
         # so it is not repeated here.
         self.intraday_risk_metrics = \
@@ -315,7 +325,11 @@ class PerformanceTracker(object):
         self.market_open = new_mkt_open
         self.market_close = new_mkt_close
 
-    def handle_market_close(self):
+    def handle_market_close_daily(self):
+        """
+        Function called after handle_data when running with daily emission
+        rate.
+        """
         self.update_performance()
         # add the return results from today to the returns series
         todays_date = normalize_date(self.market_close)

zipline/gens/tradesimulation.py

@@ -153,8 +153,10 @@ class AlgorithmSimulator(object):
                                     # If at the end of backtest history,
                                     # skip advancing market close.
                                     pass
-                                self.algo.perf_tracker.handle_intraday_close(
-                                    mkt_open, mkt_close)
+                                self.algo.perf_tracker\
+                                         .handle_intraday_market_close(
+                                             mkt_open,
+                                             mkt_close)
 
                     self.algo.portfolio_needs_update = True
 
@@ -236,16 +238,19 @@ class AlgorithmSimulator(object):
         self.algo.blotter.new_orders = []
         return orders
 
-    def get_message(self, date):
+    def get_message(self, dt):
+        """
+        Get a perf message for the given datetime.
+        """
         rvars = self.algo.recorded_vars
         if self.algo.perf_tracker.emission_rate == 'daily':
             perf_message = \
-                self.algo.perf_tracker.handle_market_close()
+                self.algo.perf_tracker.handle_market_close_daily()
             perf_message['daily_perf']['recorded_vars'] = rvars
             return perf_message
 
         elif self.algo.perf_tracker.emission_rate == 'minute':
-            self.algo.perf_tracker.handle_minute_close(date)
+            self.algo.perf_tracker.handle_minute_close(dt)
             perf_message = self.algo.perf_tracker.to_dict()
             perf_message['minute_perf']['recorded_vars'] = rvars
             return perf_message