MAINT: Move ignore_nanwarnings to numpy_utils.

zipline/pipeline/factors/technical.py

@@ -23,7 +23,7 @@ from numexpr import evaluate
 
 from zipline.pipeline.data import USEquityPricing
 from zipline.pipeline.mixins import SingleInputMixin
-from zipline.utils.control_flow import ignore_nanwarnings
+from zipline.utils.numpy_utils import ignore_nanwarnings
 from zipline.utils.input_validation import expect_types
 from zipline.utils.math_utils import (
     nanargmax,

zipline/utils/control_flow.py

@@ -2,10 +2,6 @@
 Control flow utilities.
 """
 from six import iteritems
-from warnings import (
-    catch_warnings,
-    filterwarnings,
-)
 
 
 class nullctx(object):
@@ -23,40 +19,6 @@ class nullctx(object):
         return False
 
 
-class WarningContext(object):
-    """
-    Re-entrant contextmanager for contextually managing warnings.
-    """
-    def __init__(self, *warning_specs):
-        self._warning_specs = warning_specs
-        self._catchers = []
-
-    def __enter__(self):
-        catcher = catch_warnings()
-        catcher.__enter__()
-        self._catchers.append(catcher)
-        for args, kwargs in self._warning_specs:
-            filterwarnings(*args, **kwargs)
-        return catcher
-
-    def __exit__(self, *exc_info):
-        catcher = self._catchers.pop()
-        return catcher.__exit__(*exc_info)
-
-
-def ignore_nanwarnings():
-    """
-    Helper for building a WarningContext that ignores warnings from numpy's
-    nanfunctions.
-    """
-    return WarningContext(
-        (
-            ('ignore',),
-            {'category': RuntimeWarning, 'module': 'numpy.lib.nanfunctions'},
-        )
-    )
-
-
 def invert(d):
     """
     Invert a dictionary into a dictionary of sets.

zipline/utils/numpy_utils.py

@@ -2,6 +2,11 @@
 Utilities for working with numpy arrays.
 """
 from datetime import datetime
+from warnings import (
+    catch_warnings,
+    filterwarnings,
+)
+
 from numpy import (
     broadcast,
     busday_count,
@@ -219,3 +224,37 @@ def busday_count_mask_NaT(begindates,
     # Fill in entries where either comparison was NaT with nan in the output.
     out[beginmask | endmask] = nan
     return out
+
+
+class WarningContext(object):
+    """
+    Re-usable contextmanager for contextually managing warnings.
+    """
+    def __init__(self, *warning_specs):
+        self._warning_specs = warning_specs
+        self._catchers = []
+
+    def __enter__(self):
+        catcher = catch_warnings()
+        catcher.__enter__()
+        self._catchers.append(catcher)
+        for args, kwargs in self._warning_specs:
+            filterwarnings(*args, **kwargs)
+        return self
+
+    def __exit__(self, *exc_info):
+        catcher = self._catchers.pop()
+        return catcher.__exit__(*exc_info)
+
+
+def ignore_nanwarnings():
+    """
+    Helper for building a WarningContext that ignores warnings from numpy's
+    nanfunctions.
+    """
+    return WarningContext(
+        (
+            ('ignore',),
+            {'category': RuntimeWarning, 'module': 'numpy.lib.nanfunctions'},
+        )
+    )