MAINT: Switch PanelBarReader to take trading calendar and freq args

tests/test_panel_daily_bar_reader.py

@@ -22,13 +22,12 @@ from zipline.data.us_equity_pricing import PanelBarReader
 from zipline.testing import ExplodingObject
 from zipline.testing.fixtures import (
     WithAssetFinder,
-    WithNYSETradingDays,
     ZiplineTestCase,
 )
+from zipline.utils.calendars import get_calendar
 
 
 class TestPanelDailyBarReader(WithAssetFinder,
-                              WithNYSETradingDays,
                               ZiplineTestCase):
 
     START_DATE = pd.Timestamp('2006-01-03', tz='utc')
@@ -39,10 +38,13 @@ class TestPanelDailyBarReader(WithAssetFinder,
         super(TestPanelDailyBarReader, cls).init_class_fixtures()
 
         finder = cls.asset_finder
-        days = cls.trading_days
+        trading_calendar = get_calendar('NYSE')
 
         items = finder.retrieve_all(finder.sids)
-        major_axis = days
+        major_axis = trading_calendar.sessions_in_range(
+            cls.START_DATE,
+            cls.END_DATE
+        )
         minor_axis = ['open', 'high', 'low', 'close', 'volume']
 
         shape = tuple(map(len, [items, major_axis, minor_axis]))
@@ -55,7 +57,7 @@ class TestPanelDailyBarReader(WithAssetFinder,
             minor_axis=minor_axis,
         )
 
-        cls.reader = PanelBarReader(days, cls.panel)
+        cls.reader = PanelBarReader(trading_calendar, cls.panel, 'daily')
 
     def test_spot_price(self):
         panel = self.panel
@@ -83,7 +85,7 @@ class TestPanelDailyBarReader(WithAssetFinder,
         for axis_order in permutations((0, 1, 2)):
             transposed = panel.transpose(*axis_order)
             with self.assertRaises(ValueError) as e:
-                PanelBarReader(unused, transposed)
+                PanelBarReader(unused, transposed, 'daily')
 
             expected = (
                 "Duplicate entries in Panel.{name}: ['a', 'b'].".format(

zipline/algorithm.py

@@ -619,8 +619,12 @@ class TradingAlgorithm(object):
                 # to be inferred.
                 if overwrite_sim_params:
                     self.sim_params = self.sim_params.create_new(
-                        normalize_date(data.major_axis[0]),
-                        normalize_date(data.major_axis[-1])
+                        self.trading_calendar.minute_to_session_label(
+                            data.major_axis[0]
+                        ),
+                        self.trading_calendar.minute_to_session_label(
+                            data.major_axis[-1]
+                        ),
                     )
 
                     # Assume data is daily if timestamp times are
@@ -649,11 +653,13 @@ class TradingAlgorithm(object):
 
                 if self.sim_params.data_frequency == 'daily':
                     equity_reader_arg = 'equity_daily_reader'
-                    calendar = self.trading_calendar.all_sessions
                 elif self.sim_params.data_frequency == 'minute':
                     equity_reader_arg = 'equity_minute_reader'
-                    calendar = self.trading_calendar.all_minutes
-                equity_reader = PanelBarReader(calendar, copy_panel)
+                equity_reader = PanelBarReader(
+                    self.trading_calendar,
+                    copy_panel,
+                    self.sim_params.data_frequency,
+                )
 
                 self.data_portal = DataPortal(
                     self.asset_finder,

zipline/data/us_equity_pricing.py

@@ -43,7 +43,6 @@ from pandas import (
     NaT,
     DatetimeIndex
 )
-from pandas.core.datetools import normalize_date
 from pandas.tslib import iNaT
 from six import (
     iteritems,
@@ -770,15 +769,34 @@ class PanelBarReader(DailyBarReader):
         The first trading day in the dataset.
     """
     @preprocess(panel=call(verify_indices_all_unique))
-    def __init__(self, calendar, panel):
+    @expect_element(data_frequency={'daily', 'minute'})
+    def __init__(self, trading_calendar, panel, data_frequency):
 
         panel = panel.copy()
         if 'volume' not in panel.minor_axis:
             # Fake volume if it does not exist.
             panel.loc[:, :, 'volume'] = int(1e9)
 
-        self.first_trading_day = normalize_date(panel.major_axis[0])
-        self._calendar = calendar
+        self.trading_calendar = trading_calendar
+        self.first_trading_day = trading_calendar.minute_to_session_label(
+            panel.major_axis[0]
+        )
+        last_trading_day = trading_calendar.minute_to_session_label(
+            panel.major_axis[-1]
+        )
+
+        self._sessions = trading_calendar.sessions_in_range(
+            self.first_trading_day,
+            last_trading_day
+        )
+
+        if data_frequency == 'daily':
+            self._calendar = self._sessions
+        elif data_frequency == 'minute':
+            self._calendar = trading_calendar.minutes_for_sessions_in_range(
+                self.first_trading_day,
+                last_trading_day
+            )
 
         self.panel = panel
 
@@ -788,18 +806,9 @@ class PanelBarReader(DailyBarReader):
 
     @property
     def last_available_dt(self):
-        # Returns the last Panel index that is on the calendar.
-        # The slice end is converted from dt to date string so that
-        # dts on the last day of the calendar get included.
-        return self.panel.major_axis[
-            self.panel.major_axis.slice_indexer(
-                end=self._calendar[-1].strftime('%Y-%m-%d')
-            )
-        ][-1]
+        return self._calendar[-1]
 
-    @property
-    def trading_calendar(self):
-        return None
+    trading_calendar = None
 
     def load_raw_arrays(self, columns, start_dt, end_dt, assets):
         cal = self._calendar