MAINT: make_rotating_asset -> make_rotating_equity.

tests/pipeline/test_engine.py

@@ -50,7 +50,7 @@ from zipline.pipeline.factors import (
 )
 from zipline.utils.memoize import lazyval
 from zipline.utils.test_utils import (
-    make_rotating_asset_info,
+    make_rotating_equity_info,
     make_simple_equity_info,
     product_upper_triangle,
     check_arrays,
@@ -608,7 +608,7 @@ class SyntheticBcolzTestCase(TestCase):
         cls.trading_day = day = cls.env.trading_day
         cls.calendar = date_range('2015', '2015-08', tz='UTC', freq=day)
 
-        cls.asset_info = make_rotating_asset_info(
+        cls.asset_info = make_rotating_equity_info(
             num_assets=6,
             first_start=cls.first_asset_start,
             frequency=day,

tests/test_assets.py

@@ -59,8 +59,8 @@ from zipline.errors import (
 from zipline.finance.trading import TradingEnvironment, noop_load
 from zipline.utils.test_utils import (
     all_subindices,
-    make_rotating_asset_info,
-    tmp_assets_db
+    tmp_assets_db,
+    make_rotating_equity_info,
 )
 
 
@@ -105,7 +105,7 @@ def build_lookup_generic_cases(asset_finder_type):
             },
         ],
         index='sid')
-    with tmp_assets_db(frame) as assets_db:
+    with tmp_assets_db(equities=frame) as assets_db:
         finder = asset_finder_type(assets_db)
         dupe_0, dupe_1, unique = assets = [
             finder.retrieve_asset(i)
@@ -774,7 +774,7 @@ class AssetFinderTestCase(TestCase):
         trading_day = self.env.trading_day
         first_start = pd.Timestamp('2015-04-01', tz='UTC')
 
-        frame = make_rotating_asset_info(
+        frame = make_rotating_equity_info(
             num_assets=num_assets,
             first_start=first_start,
             frequency=self.env.trading_day,

zipline/utils/test_utils.py

@@ -233,11 +233,11 @@ def all_subindices(index):
     )
 
 
-def make_rotating_asset_info(num_assets,
-                             first_start,
-                             frequency,
-                             periods_between_starts,
-                             asset_lifetime):
+def make_rotating_equity_info(num_assets,
+                              first_start,
+                              frequency,
+                              periods_between_starts,
+                              asset_lifetime):
     """
     Create a DataFrame representing lifetimes of assets that are constantly
     rotating in and out of existence.