From 821da97126b53508f0df8c13972f7c0d28780a52 Mon Sep 17 00:00:00 2001
From: Wes McKinney <wesmckinn@gmail.com>
Date: Fri, 7 Sep 2012 14:47:36 -0400
Subject: [PATCH] BUG: fix sqrt(negative number) issue in rolling_std close
 #1840

---
 RELEASE.rst                        |  2 ++
 pandas/stats/moments.py            | 20 +++++++++++++++++---
 pandas/stats/tests/test_moments.py | 16 ++++++++++++++++
 3 files changed, 35 insertions(+), 3 deletions(-)

diff --git a/RELEASE.rst b/RELEASE.rst
index 2518669fe1a9d..428802f952dcb 100644
--- a/RELEASE.rst
+++ b/RELEASE.rst
@@ -98,6 +98,8 @@ pandas 0.8.2
     right time zone (#1777)
   - Fix DST issues with generating anchored date ranges (#1778)
   - Fix issue calling sort on result of Series.unique (#1807)
+  - Fix numerical issue leading to square root of negative number in
+    rolling_std (#1840)
 
 pandas 0.8.1
 ============
diff --git a/pandas/stats/moments.py b/pandas/stats/moments.py
index 29df509832ea6..f96ce98eaba4a 100644
--- a/pandas/stats/moments.py
+++ b/pandas/stats/moments.py
@@ -309,7 +309,7 @@ def ewmstd(arg, com=None, span=None, min_periods=0, bias=False,
            time_rule=None):
     result = ewmvar(arg, com=com, span=span, time_rule=time_rule,
                     min_periods=min_periods, bias=bias)
-    return np.sqrt(result)
+    return _zsqrt(result)
 
 ewmvol = ewmstd
 
@@ -343,7 +343,21 @@ def ewmcorr(arg1, arg2, com=None, span=None, min_periods=0,
     mean = lambda x: ewma(x, com=com, span=span, min_periods=min_periods)
     var = lambda x: ewmvar(x, com=com, span=span, min_periods=min_periods,
                            bias=True)
-    return (mean(X*Y) - mean(X)*mean(Y)) / np.sqrt(var(X) * var(Y))
+    return (mean(X*Y) - mean(X)*mean(Y)) / _zsqrt(var(X) * var(Y))
+
+
+def _zsqrt(x):
+    result = np.sqrt(x)
+    mask = x < 0
+
+    if isinstance(x, DataFrame):
+        if mask.values.any():
+            result[mask] = 0
+    else:
+        if mask.any():
+            result[mask] = 0
+
+    return result
 
 def _prep_binary(arg1, arg2):
     if not isinstance(arg2, type(arg1)):
@@ -406,7 +420,7 @@ def call_cython(arg, window, minp, **kwds):
 rolling_mean = _rolling_func(lib.roll_mean, 'Moving mean')
 rolling_median = _rolling_func(lib.roll_median_cython, 'Moving median')
 
-_ts_std = lambda *a, **kw: np.sqrt(lib.roll_var(*a, **kw))
+_ts_std = lambda *a, **kw: _zsqrt(lib.roll_var(*a, **kw))
 rolling_std = _rolling_func(_ts_std, 'Unbiased moving standard deviation',
                             check_minp=_require_min_periods(2))
 rolling_var = _rolling_func(lib.roll_var, 'Unbiased moving variance',
diff --git a/pandas/stats/tests/test_moments.py b/pandas/stats/tests/test_moments.py
index 1d80cb167b4cd..c4f623c34166f 100644
--- a/pandas/stats/tests/test_moments.py
+++ b/pandas/stats/tests/test_moments.py
@@ -89,6 +89,22 @@ def test_rolling_std(self):
         self._check_moment_func(functools.partial(mom.rolling_std, ddof=0),
                                 lambda x: np.std(x, ddof=0))
 
+    def test_rolling_std_neg_sqrt(self):
+        # unit test from Bottleneck
+
+        # Test move_nanstd for neg sqrt.
+
+        a = np.array([0.0011448196318903589,
+                      0.00028718669878572767,
+                      0.00028718669878572767,
+                      0.00028718669878572767,
+                      0.00028718669878572767])
+        b = mom.rolling_std(a, window=3)
+        self.assert_(np.isfinite(b[2:]).all())
+
+        b = mom.ewmstd(a, span=3)
+        self.assert_(np.isfinite(b[2:]).all())
+
     def test_rolling_var(self):
         self._check_moment_func(mom.rolling_var,
                                 lambda x: np.var(x, ddof=1))