Merge a20696e into 15fe38c

setup.py

@@ -115,6 +115,11 @@ def window_specialization(typename):
         'zipline.data._resample',
         ['zipline/data/_resample.pyx']
     ),
+    Extension(
+        'zipline.pipeline.loaders.blaze._core',
+        ['zipline/pipeline/loaders/blaze/_core.pyx'],
+        depends=['zipline/lib/adjustment.pxd'],
+    ),
 ]
 
 

tests/pipeline/test_classifier.py

@@ -1,11 +1,12 @@
 from functools import reduce
-from operator import or_
+import operator as op
 
 import numpy as np
 import pandas as pd
 
 from zipline.lib.labelarray import LabelArray
 from zipline.pipeline import Classifier
+from zipline.pipeline.expression import methods_to_ops
 from zipline.testing import parameter_space
 from zipline.testing.fixtures import ZiplineTestCase
 from zipline.testing.predicates import assert_equal
@@ -404,7 +405,7 @@ class C(Classifier):
         for choices in [(0,), (0, 1), (0, 1, 2)]:
             terms[str(choices)] = c.element_of(choices)
             expected[str(choices)] = reduce(
-                or_,
+                op.or_,
                 (data == elem for elem in choices),
                 np.zeros_like(data, dtype=bool),
             )
@@ -584,6 +585,27 @@ class C(Classifier):
         )
         self.assertEqual(result, expected)
 
+    @parameter_space(
+        compare_op=[op.gt, op.ge, op.le, op.lt],
+        dtype_and_missing=[(int64_dtype, 0), (categorical_dtype, '')],
+    )
+    def test_bad_compare(self, compare_op, dtype_and_missing):
+        class C(Classifier):
+            inputs = ()
+            window_length = 0
+            dtype = dtype_and_missing[0]
+            missing_value = dtype_and_missing[1]
+
+        with self.assertRaises(TypeError) as e:
+            compare_op(C(), object())
+
+        self.assertEqual(
+            str(e.exception),
+            'cannot compare classifiers with %s' % (
+                methods_to_ops['__%s__' % compare_op.__name__],
+            ),
+        )
+
 
 class TestPostProcessAndToWorkSpaceValue(ZiplineTestCase):
     def test_reversability_categorical(self):

zipline/lib/adjusted_array.py

@@ -35,7 +35,7 @@
 
 NOMASK = None
 BOOL_DTYPES = frozenset(
-    map(dtype, [bool_]),
+    map(dtype, [bool_, uint8]),
 )
 FLOAT_DTYPES = frozenset(
     map(dtype, [float32, float64]),
@@ -103,7 +103,7 @@ def _normalize_array(data, missing_value):
         return data, {}
 
     data_dtype = data.dtype
-    if data_dtype == bool_:
+    if data_dtype in BOOL_DTYPES:
         return data.astype(uint8), {'dtype': dtype(bool_)}
     elif data_dtype in FLOAT_DTYPES:
         return data.astype(float64), {'dtype': dtype(float64)}