Misc

tests/pipeline/test_engine.py

@@ -1253,8 +1253,6 @@ def test_correlation_factors(self, returns_length, correlation_length):
         num_days = end_date_index - start_date_index + 1
         num_assets = len(assets)
 
-        returns = Returns(window_length=returns_length)
-
         cascading_mask = \
             AssetIDPlusDay() < (sids[-1] + dates[start_date_index].day)
         expected_cascading_mask_result = make_cascading_boolean_array(
@@ -1313,6 +1311,7 @@ def test_correlation_factors(self, returns_length, correlation_length):
             # (correlation_length - 1) days prior to our start date. This is
             # because we need (correlation_length - 1) extra days of returns to
             # compute our expected correlations.
+            returns = Returns(window_length=returns_length)
             results = self.engine.run_pipeline(
                 Pipeline(columns={'returns': returns}),
                 dates[start_date_index - (correlation_length - 1)],
@@ -1371,8 +1370,6 @@ def test_regression_of_returns_factor(self,
         num_days = end_date_index - start_date_index + 1
         num_assets = len(assets)
 
-        returns = Returns(window_length=returns_length)
-
         cascading_mask = \
             AssetIDPlusDay() < (sids[-1] + dates[start_date_index].day)
         expected_cascading_mask_result = make_cascading_boolean_array(
@@ -1435,6 +1432,7 @@ def test_regression_of_returns_factor(self,
             # prior to our start date. This is because we need
             # (regression_length - 1) extra days of returns to compute our
             # expected regressions.
+            returns = Returns(window_length=returns_length)
             results = self.engine.run_pipeline(
                 Pipeline(columns={'returns': returns}),
                 dates[start_date_index - (regression_length - 1)],

tests/pipeline/test_slice.py

@@ -13,7 +13,7 @@
 from zipline.pipeline import CustomFactor, Pipeline
 from zipline.pipeline.data import USEquityPricing
 from zipline.pipeline.engine import SimplePipelineEngine
-from zipline.pipeline.factors import Returns
+from zipline.pipeline.factors import FactorSlice, Returns
 from zipline.pipeline.loaders.frame import DataFrameLoader
 from zipline.testing import check_arrays
 from zipline.testing.fixtures import WithTradingEnvironment, ZiplineTestCase
@@ -58,6 +58,10 @@ def init_class_fixtures(cls):
         )
 
     def test_slice(self):
+        """
+        Test that slices can be created by indexing into a term, and that they
+        have the correct shape when used as inputs.
+        """
         my_asset_column = 0
         start_date_index = 5
         end_date_index = 9
@@ -68,6 +72,7 @@ def test_slice(self):
 
         returns = Returns(window_length=2)
         returns_slice = returns[my_asset]
+        self.assertIsInstance(returns_slice, FactorSlice)
 
         class UsesSlicedInput(CustomFactor):
             window_length = 3
@@ -92,7 +97,12 @@ def compute(self, today, assets, out, returns, returns_slice):
             pipe, self.dates[start_date_index], self.dates[end_date_index],
         )
 
-        # Test that slices cannot be added as a pipeline column.
+    def test_adding_slice_column(self):
+        """
+        Test that slices cannot be added as a pipeline column.
+        """
+        my_asset = self.asset_finder.retrieve_asset(self.sids[0])
+
         with self.assertRaises(UnsupportedPipelineColumn):
             pipe = Pipeline(columns={'open_slice': OpenPrice()[my_asset]})
 
@@ -101,6 +111,9 @@ def compute(self, today, assets, out, returns, returns_slice):
             pipe.add(OpenPrice()[my_asset], 'open_slice')
 
     def test_single_column_output(self):
+        """
+        Tests for custom factors that compute a 1D out.
+        """
         start_date_index = 5
         end_date_index = 9
         alternating_mask = (AssetIDPlusDay() % 2).eq(0)

zipline/errors.py

@@ -639,6 +639,6 @@ class NonExistentAssetInTimeFrame(ZiplineError):
 
 class UnsupportedPipelineColumn(ZiplineError):
     msg = (
-        "Adding single-column terms as pipeline columns is not currently "
-        "supported."
+        "{termname} cannot be added as a column. Adding single-column terms "
+        "as pipeline columns is not currently supported."
     )

zipline/pipeline/factors/factor.py

@@ -628,18 +628,37 @@ def rank(self, method='ordinal', ascending=True, mask=NotSpecified):
         """
         return Rank(self, method=method, ascending=ascending, mask=mask)
 
-    def rolling_pearson(self,
-                        target_slice,
-                        correlation_length,
-                        mask=NotSpecified):
-        return RollingPearson(self, target_slice, correlation_length, mask)
-
-    def rolling_spearman(self,
+    @expect_types(
+        target_slice=Slice,
+        correlation_length=int,
+        mask=(Filter, NotSpecifiedType),
+    )
+    def rolling_pearsonr(self,
                          target_slice,
                          correlation_length,
                          mask=NotSpecified):
+        """
+        """
+        return RollingPearson(self, target_slice, correlation_length, mask)
+
+    @expect_types(
+        target_slice=Slice,
+        correlation_length=int,
+        mask=(Filter, NotSpecifiedType),
+    )
+    def rolling_spearmanr(self,
+                          target_slice,
+                          correlation_length,
+                          mask=NotSpecified):
+        """
+        """
         return RollingSpearman(self, target_slice, correlation_length, mask)
 
+    @expect_types(
+        target_slice=Slice,
+        regression_length=int,
+        mask=(Filter, NotSpecifiedType),
+    )
     def rolling_linear_regression(self,
                                   target_slice,
                                   regression_length,

zipline/pipeline/pipeline.py

@@ -41,7 +41,7 @@ def __init__(self, columns=None, screen=None):
             columns = {}
         for term in columns.values():
             if term.ndim == 1:
-                raise UnsupportedPipelineColumn()
+                raise UnsupportedPipelineColumn(termname=type(term).__name__)
         self._columns = columns
         self._screen = screen
 
@@ -78,7 +78,7 @@ def add(self, term, name, overwrite=False):
             named `name`.
         """
         if term.ndim == 1:
-            raise UnsupportedPipelineColumn()
+            raise UnsupportedPipelineColumn(termname=type(term).__name__)
 
         columns = self.columns
         if name in columns: