blob: 9c33704f8e22c4eb38219f104315f36e79f60ebd [file] [log] [blame]
From 0d25dc4175e00cdaf9545e8b1b1a5b879cf67248 Mon Sep 17 00:00:00 2001
From: Ethan Kruse <eakruse@uw.edu>
Date: Mon, 19 Oct 2015 13:29:01 -0700
Subject: [PATCH 1/2] Potential fix for #6462
---
numpy/lib/function_base.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 555d083..fef69df 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -3339,7 +3339,7 @@ def _median(a, axis=None, out=None, overwrite_input=False):
indexer[axis] = slice(index-1, index+1)
# Check if the array contains any nan's
- if np.issubdtype(a.dtype, np.inexact):
+ if np.issubdtype(a.dtype, np.inexact) and sz > 0:
# warn and return nans like mean would
rout = mean(part[indexer], axis=axis, out=out)
part = np.rollaxis(part, axis, part.ndim)
From 59d859fb2160950ac93267d7461ad952145c8724 Mon Sep 17 00:00:00 2001
From: Ethan Kruse <eakruse@uw.edu>
Date: Tue, 20 Oct 2015 11:40:49 -0700
Subject: [PATCH 2/2] Added tests for median of empty arrays
---
numpy/lib/tests/test_function_base.py | 30 ++++++++++++++++++++++++++++++
1 file changed, 30 insertions(+)
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index 4516c92..aa41c1f 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -2597,6 +2597,36 @@ def test_nan_behavior(self):
assert_equal(np.median(a, (0, 2)), b)
assert_equal(len(w), 1)
+ def test_empty(self):
+ # empty arrays
+ a = np.array([], dtype=float)
+ with warnings.catch_warnings(record=True) as w:
+ warnings.filterwarnings('always', '', RuntimeWarning)
+ assert_equal(np.median(a), np.nan)
+ assert_(w[0].category is RuntimeWarning)
+
+ # multiple dimensions
+ a = np.array([], dtype=float, ndmin=3)
+ # no axis
+ with warnings.catch_warnings(record=True) as w:
+ warnings.filterwarnings('always', '', RuntimeWarning)
+ assert_equal(np.median(a), np.nan)
+ assert_(w[0].category is RuntimeWarning)
+
+ # axis 0 and 1
+ b = np.array([], dtype=float, ndmin=2)
+ with warnings.catch_warnings(record=True) as w:
+ warnings.filterwarnings('always', '', RuntimeWarning)
+ assert_equal(np.median(a, axis=0), b)
+ assert_equal(np.median(a, axis=1), b)
+
+ # axis 2
+ b = np.array(np.nan, dtype=float, ndmin=2)
+ with warnings.catch_warnings(record=True) as w:
+ warnings.filterwarnings('always', '', RuntimeWarning)
+ assert_equal(np.median(a, axis=2), b)
+ assert_(w[0].category is RuntimeWarning)
+
def test_object(self):
o = np.arange(7.)
assert_(type(np.median(o.astype(object))), float)