diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/lib/function_base.py | 2 | ||||
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 10 | ||||
| -rw-r--r-- | numpy/random/mtrand/mtrand.pyx | 7 |
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 b05d86747..1c07ae2cd 100644 --- a/numpy/random/mtrand/mtrand.pyx +++ b/numpy/random/mtrand/mtrand.pyx @@ -5003,6 +5003,10 @@ 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 @@ -5019,8 +5023,7 @@ 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) |