MAINT: Rename perfomances intraday_perf to minute_perf.

minute_perf is more precise than intraday_perf as a naming scheme
for the performance packet type.

tests/test_perf_tracking.py

@@ -1098,21 +1098,21 @@ class TestPerformanceTracker(unittest.TestCase):
         msg_1 = messages[foo_event_1.dt]
         msg_2 = messages[foo_event_2.dt]
 
-        self.assertEquals(1, len(msg_1['intraday_perf']['transactions']),
+        self.assertEquals(1, len(msg_1['minute_perf']['transactions']),
                           "The first message should contain one transaction.")
         # Check that transactions aren't emitted for previous events.
-        self.assertEquals(0, len(msg_2['intraday_perf']['transactions']),
+        self.assertEquals(0, len(msg_2['minute_perf']['transactions']),
                           "The second message should have no transactions.")
 
-        self.assertEquals(1, len(msg_1['intraday_perf']['orders']),
+        self.assertEquals(1, len(msg_1['minute_perf']['orders']),
                           "The first message should contain one orders.")
         # Check that orders aren't emitted for previous events.
-        self.assertEquals(0, len(msg_2['intraday_perf']['orders']),
+        self.assertEquals(0, len(msg_2['minute_perf']['orders']),
                           "The second message should have no orders.")
 
         # Ensure that period_close moves through time.
         # Also, ensure that the period_closes are the expected dts.
         self.assertEquals(foo_event_1.dt,
-                          msg_1['intraday_perf']['period_close'])
+                          msg_1['minute_perf']['period_close'])
         self.assertEquals(foo_event_2.dt,
-                          msg_2['intraday_perf']['period_close'])
+                          msg_2['minute_perf']['period_close'])

zipline/finance/performance.py

@@ -278,14 +278,9 @@ class PerformanceTracker(object):
                           'daily_perf':
                           self.todays_performance.to_dict()})
         if emission_type == 'minute':
-            # Currently reusing 'todays_performance' for intraday trading
-            # result, should be analogous, but has the potential for needing
-            # its own configuration down the line.
-            # Naming as intraday to make clear that these results are
-            # being updated per minute
             _dict['intraday_risk_metrics'] = \
                 self.intraday_risk_metrics.to_dict()
-            _dict['intraday_perf'] = self.todays_performance.to_dict(
+            _dict['minute_perf'] = self.todays_performance.to_dict(
                 self.saved_dt)
             _dict['cumulative_risk_metrics'] = \
                 self.cumulative_risk_metrics.to_dict()

zipline/finance/risk.py

@@ -649,7 +649,7 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
         self.algorithm_volatility.append(
             self.calculate_volatility(self.algorithm_returns))
 
-        # caching the treasury rates for the live case is a
+        # caching the treasury rates for the minutely case is a
         # big speedup, because it avoids searching the treasury
         # curves on every minute.
         treasury_end = self.algorithm_returns.index[-1].replace(

zipline/gens/tradesimulation.py

@@ -26,7 +26,7 @@ log = Logger('Trade Simulation')
 class AlgorithmSimulator(object):
 
     EMISSION_TO_PERF_KEY_MAP = {
-        'minute': 'intraday_perf',
+        'minute': 'minute_perf',
         'daily': 'daily_perf'
     }
 
@@ -185,7 +185,7 @@ class AlgorithmSimulator(object):
         elif self.algo.perf_tracker.emission_rate == 'minute':
             self.algo.perf_tracker.handle_minute_close(date)
             perf_message = self.algo.perf_tracker.to_dict()
-            perf_message['intraday_perf']['recorded_vars'] = rvars
+            perf_message['minute_perf']['recorded_vars'] = rvars
             return perf_message
 
     def get_next_close(self, mkt_close):