Merge pull request #7279 from madphysicist/percentile-tests

TST: Fixed elements being shuffled

3 files changed, 11 insertions, 8 deletions

diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 7f80e424c..12fa4049b 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -3277,7 +3277,7 @@ def _ureduce(a, func, **kwargs):
     a : array_like
         Input array or object that can be converted to an array.
     func : callable
-        Reduction function Kapable of receiving an axis argument.
+        Reduction function capable of receiving a single axis argument.
         It is is called with `a` as first argument followed by `kwargs`.
      kwargs : keyword arguments
         additional keyword arguments to pass to `func`.
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index 782c1399a..235b7f2fe 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -2389,8 +2389,8 @@ class TestPercentile(TestCase):
         assert_equal(np.percentile(x, [25, 60], axis=(0,)),
                      np.percentile(x, [25, 60], axis=0))
 
-        d = np.arange(3 * 5 * 7 * 11).reshape(3, 5, 7, 11)
-        np.random.shuffle(d)
+        d = np.arange(3 * 5 * 7 * 11).reshape((3, 5, 7, 11))
+        np.random.shuffle(d.ravel())
         assert_equal(np.percentile(d, 25,  axis=(0, 1, 2))[0],
                      np.percentile(d[:,:,:, 0].flatten(), 25))
         assert_equal(np.percentile(d, [10, 90], axis=(0, 1, 3))[:, 1],
@@ -2617,7 +2617,7 @@ class TestMedian(TestCase):
                         [3,  4])
 
         a4 = np.arange(3 * 4 * 5, dtype=np.float32).reshape((3, 4, 5))
-        map(np.random.shuffle, a4)
+        np.random.shuffle(a4.ravel())
         assert_allclose(np.median(a4, axis=None),
                         np.median(a4.copy(), axis=None, overwrite_input=True))
         assert_allclose(np.median(a4, axis=0),
@@ -2765,8 +2765,8 @@ class TestMedian(TestCase):
         assert_equal(np.median(x, axis=(0, )), np.median(x, axis=0))
         assert_equal(np.median(x, axis=(-1, )), np.median(x, axis=-1))
 
-        d = np.arange(3 * 5 * 7 * 11).reshape(3, 5, 7, 11)
-        np.random.shuffle(d)
+        d = np.arange(3 * 5 * 7 * 11).reshape((3, 5, 7, 11))
+        np.random.shuffle(d.ravel())
         assert_equal(np.median(d, axis=(0, 1, 2))[0],
                      np.median(d[:,:,:, 0].flatten()))
         assert_equal(np.median(d, axis=(0, 1, 3))[1],
diff --git a/numpy/random/mtrand/mtrand.pyx b/numpy/random/mtrand/mtrand.pyx
index 964129a8c..db4ea13e6 100644
--- a/numpy/random/mtrand/mtrand.pyx
+++ b/numpy/random/mtrand/mtrand.pyx
@@ -5021,6 +5021,10 @@ cdef class RandomState:
 
         Modify a sequence in-place by shuffling its contents.
 
+        This function only shuffles the array along the first axis of a
+        multi-dimensional array. The order of sub-arrays is changed but
+        their contents remains the same.
+
         Parameters
         ----------
         x : array_like
@@ -5037,8 +5041,7 @@ cdef class RandomState:
         >>> arr
         [1 7 5 2 9 4 3 6 0 8]
 
-        This function only shuffles the array along the first index of a
-        multi-dimensional array:
+        Multi-dimensional arrays are only shuffled along the first axis:
 
         >>> arr = np.arange(9).reshape((3, 3))
         >>> np.random.shuffle(arr)