From 7fc0dd6d97025602950d23b3870dbeaa326a2955 Mon Sep 17 00:00:00 2001
From: Scott Sanderson <ssanderson@quantopian.com>
Date: Tue, 16 Aug 2016 19:51:54 -0400
Subject: [PATCH] MAINT: Use `numpy_utils.as_column` in more places.

---
 zipline/assets/assets.py          |  3 ++-
 zipline/pipeline/engine.py        |  8 ++++++--
 zipline/pipeline/loaders/frame.py |  3 ++-
 zipline/testing/core.py           | 10 ++++++----
 4 files changed, 16 insertions(+), 8 deletions(-)

diff --git a/zipline/assets/assets.py b/zipline/assets/assets.py
index f8620ddc..8ca34629 100644
--- a/zipline/assets/assets.py
+++ b/zipline/assets/assets.py
@@ -59,6 +59,7 @@ from .asset_db_schema import (
 )
 from zipline.utils.control_flow import invert
 from zipline.utils.memoize import lazyval
+from zipline.utils.numpy_utils import as_column
 from zipline.utils.sqlite_utils import group_into_chunks
 
 log = Logger('assets.py')
@@ -1096,7 +1097,7 @@ class AssetFinder(object):
             self._asset_lifetimes = self._compute_asset_lifetimes()
         lifetimes = self._asset_lifetimes
 
-        raw_dates = dates.asi8[:, None]
+        raw_dates = as_column(dates.asi8)
         if include_start_date:
             mask = lifetimes.start <= raw_dates
         else:
diff --git a/zipline/pipeline/engine.py b/zipline/pipeline/engine.py
index dcda762a..2fc54c5a 100644
--- a/zipline/pipeline/engine.py
+++ b/zipline/pipeline/engine.py
@@ -18,7 +18,11 @@ from toolz.curried.operator import getitem
 
 from zipline.lib.adjusted_array import ensure_adjusted_array, ensure_ndarray
 from zipline.errors import NoFurtherDataError
-from zipline.utils.numpy_utils import repeat_first_axis, repeat_last_axis
+from zipline.utils.numpy_utils import (
+    as_column,
+    repeat_first_axis,
+    repeat_last_axis,
+)
 from zipline.utils.pandas_utils import explode
 
 from .term import AssetExists, InputDates, LoadableTerm
@@ -181,7 +185,7 @@ class SimplePipelineEngine(object):
             assets,
             initial_workspace={
                 self._root_mask_term: root_mask_values,
-                self._root_mask_dates_term: dates.values[:, None],
+                self._root_mask_dates_term: as_column(dates.values)
             },
         )
 
diff --git a/zipline/pipeline/loaders/frame.py b/zipline/pipeline/loaders/frame.py
index 77d4bd91..ba7d9383 100644
--- a/zipline/pipeline/loaders/frame.py
+++ b/zipline/pipeline/loaders/frame.py
@@ -15,6 +15,7 @@ from pandas import (
 )
 from zipline.lib.adjusted_array import AdjustedArray
 from zipline.lib.adjustment import make_adjustment_from_labels
+from zipline.utils.numpy_utils import as_column
 from zipline.utils.pandas_utils import sort_values
 from .base import PipelineLoader
 
@@ -169,7 +170,7 @@ class DataFrameLoader(PipelineLoader):
                 # Pull out requested columns/rows from our baseline data.
                 data=self.baseline[ix_(date_indexer, assets_indexer)],
                 # Mask out requested columns/rows that didnt match.
-                mask=(good_assets & good_dates[:, None]) & mask,
+                mask=(good_assets & as_column(good_dates)) & mask,
                 adjustments=self.format_adjustments(dates, assets),
                 missing_value=column.missing_value,
             ),
diff --git a/zipline/testing/core.py b/zipline/testing/core.py
index 9701fc30..65a6caa0 100644
--- a/zipline/testing/core.py
+++ b/zipline/testing/core.py
@@ -47,9 +47,11 @@ from zipline.pipeline.engine import SimplePipelineEngine
 from zipline.pipeline.factors import CustomFactor
 from zipline.pipeline.loaders.testing import make_seeded_random_loader
 from zipline.utils import security_list
-from zipline.utils.input_validation import expect_dimensions
-from zipline.utils.sentinel import sentinel
 from zipline.utils.calendars import get_calendar
+from zipline.utils.input_validation import expect_dimensions
+from zipline.utils.numpy_utils import as_column
+from zipline.utils.sentinel import sentinel
+
 import numpy as np
 from numpy import float64
 
@@ -308,11 +310,11 @@ def make_trade_data_for_asset_info(dates,
     price_sid_deltas = np.arange(len(sids), dtype=float64) * price_step_by_sid
     price_date_deltas = (np.arange(len(dates), dtype=float64) *
                          price_step_by_date)
-    prices = (price_sid_deltas + price_date_deltas[:, None]) + price_start
+    prices = (price_sid_deltas + as_column(price_date_deltas)) + price_start
 
     volume_sid_deltas = np.arange(len(sids)) * volume_step_by_sid
     volume_date_deltas = np.arange(len(dates)) * volume_step_by_date
-    volumes = (volume_sid_deltas + volume_date_deltas[:, None]) + volume_start
+    volumes = volume_sid_deltas + as_column(volume_date_deltas) + volume_start
 
     for j, sid in enumerate(sids):
         start_date, end_date = asset_info.loc[sid, ['start_date', 'end_date']]