BUG: History no longer fails on length-1 '1m' price-only HistorySpecs

The bug occurred because there is a special case in the initial window setup
code for handling the case where only a length-1 history is used for a given
frequency.  Previously, the code was incorrectly calculating the period end
using a hard-coded expression for the end of the day (the correct behavior for
a length-1 '1d' history), and then using the frequency object to calculate the
period start for the window.  In the case of length 1 '1m' data, this resulted
in an initial window whose start and end was the last minute of the day rather
than the first minute of the day.  For non-price fields, this error doesn't
matter, because the window is only used for rolling digests (which doesn't
happen when there's only a length-1 history), and for the forward-filling logic
(which only happens on price fields).  For a length-1 '1m' price, however, the
incorrect window causes us to attempt to forward-fill an empty panel, resulting
in an IndexError when we do an iloc[0] on a length-0 axis.

tests/history_cases.py

@@ -44,6 +44,9 @@ def mixed_frequency_expected_data(count, frequency):
 MIXED_FREQUENCY_MINUTES = TradingEnvironment.instance().market_minute_window(
     to_utc('2013-07-03 9:31AM'), 600,
 )
+ONE_MINUTE_PRICE_ONLY_SPECS = [
+    HistorySpec(1, '1m', 'price', True),
+]
 DAILY_OPEN_CLOSE_SPECS = [
     HistorySpec(3, '1d', 'open_price', False),
     HistorySpec(3, '1d', 'close_price', False),
@@ -77,6 +80,55 @@ HISTORY_CONTAINER_TEST_CASES = {
     # 23 24 25 26 27 28 29
     # 30
 
+    'test one minute price only': {
+        # A list of HistorySpec objects.
+        'specs': ONE_MINUTE_PRICE_ONLY_SPECS,
+        # Sids for the test.
+        'sids': [1],
+        # Start date for test.
+        'dt': to_utc('2013-06-21 9:31AM'),
+        # Sequency of updates to the container
+        'updates': [
+            BarData(
+                {
+                    1: {
+                        'price': 5,
+                        'dt': to_utc('2013-06-21 9:31AM'),
+                    },
+                },
+            ),
+            BarData(
+                {
+                    1: {
+                        'price': 6,
+                        'dt': to_utc('2013-06-21 9:32AM'),
+                    },
+                },
+            ),
+        ],
+        # Expected results
+        'expected': {
+            ONE_MINUTE_PRICE_ONLY_SPECS[0].key_str: [
+                pd.DataFrame(
+                    data={
+                        1: [5],
+                    },
+                    index=[
+                        to_utc('2013-06-21 9:31AM'),
+                    ],
+                ),
+                pd.DataFrame(
+                    data={
+                        1: [6],
+                    },
+                    index=[
+                        to_utc('2013-06-21 9:32AM'),
+                    ],
+                ),
+            ],
+        },
+    },
+
     'test daily open close': {
         # A list of HistorySpec objects.
         'specs': DAILY_OPEN_CLOSE_SPECS,

zipline/history/history_container.py

@@ -23,7 +23,6 @@ from . history import (
     index_at_dt,
 )
 
-from zipline.finance import trading
 from zipline.utils.data import RollingPanel
 
 
@@ -206,13 +205,14 @@ class HistoryContainer(object):
             # requiring the largest number of bars.
             largest_spec = specs[-1]
             if largest_spec.bar_count == 1:
+
                 # No need to allocate a digest panel; this frequency will only
                 # ever use data drawn from self.buffer_panel.
-                env = trading.environment
-                first_window_closes[freq] = \
-                    env.get_open_and_close(initial_dt)[1]
-                first_window_starts[freq] = \
-                    freq.window_open(first_window_closes[freq])
+                first_window_starts[freq] = freq.window_open(initial_dt)
+                first_window_closes[freq] = freq.window_close(
+                    first_window_starts[freq]
+                )
+
                 continue
 
             initial_dates = index_at_dt(largest_spec, initial_dt)