MAINT: Change expected type of treasury curves from load to DataFrame.

Instead of converting the curves back and forth from dictionaries to
DataFrame and back, use the DataFrame format when passing to
environment.

zipline/data/loader.py

@@ -229,17 +229,7 @@ def load_market_data(trading_day=trading_day_nyse,
     else:
         treasury_curves = saved_curves.tz_localize('UTC')
 
-    tr_curves = {}
-    for tr_dt, curve in treasury_curves.T.iteritems():
-        # tr_dt = tr_dt.replace(hour=0, minute=0, second=0, microsecond=0,
-        #                       tzinfo=pytz.utc)
-        tr_curves[tr_dt] = curve.to_dict()
-
-    tr_curves = OrderedDict(sorted(
-        ((dt, c) for dt, c in iteritems(tr_curves)),
-        key=lambda t: t[0]))
-
-    return benchmark_returns, tr_curves
+    return benchmark_returns, treasury_curves
 
 
 def _load_raw_yahoo_data(indexes=None, stocks=None, start=None, end=None):

zipline/finance/trading.py

@@ -92,6 +92,11 @@ class TradingEnvironment(object):
         max_date=None,
         env_trading_calendar=tradingcalendar
     ):
+        """
+        @load is function that returns benchmark_returns and treasury_curves
+        The treasury_curves are expected to be a DataFrame with an index of
+        dates and columns of the curve names, e.g. '10year', '1month', etc.
+        """
         self.trading_day = env_trading_calendar.trading_day.copy()
 
         # `tc_td` is short for "trading calendar trading days"
@@ -116,10 +121,9 @@ class TradingEnvironment(object):
         if not load:
             load = load_market_data
 
-        self.benchmark_returns, treasury_curves_map = \
+        self.benchmark_returns, self.treasury_curves = \
             load(self.trading_day, self.trading_days, self.bm_symbol)
 
-        self.treasury_curves = pd.DataFrame(treasury_curves_map).T
         if max_date:
             tr_c = self.treasury_curves
             # Mask the treasury curves down to the current date.