diff options
| -rw-r--r-- | doc/release/upcoming_changes/14255.improvement.rst | 4 | ||||
| -rw-r--r-- | numpy/lib/arraysetops.py | 4 | ||||
| -rw-r--r-- | numpy/lib/tests/test_arraysetops.py | 7 |
3 files changed, 11 insertions, 4 deletions
diff --git a/doc/release/upcoming_changes/14255.improvement.rst b/doc/release/upcoming_changes/14255.improvement.rst new file mode 100644 index 000000000..d3385522c --- /dev/null +++ b/doc/release/upcoming_changes/14255.improvement.rst @@ -0,0 +1,4 @@ +`unique` has consistent axes order (except the chosen one) when `axis` is not None +---------------------------------------------------------------------------------- +Using `moveaxis` instead of `swapaxes` when implementation, so that the ordering +of axes except the axis in arguments will not be broken. diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py index f3f4bc17e..c3e833f74 100644 --- a/numpy/lib/arraysetops.py +++ b/numpy/lib/arraysetops.py @@ -264,7 +264,7 @@ def unique(ar, return_index=False, return_inverse=False, # axis was specified and not None try: - ar = np.swapaxes(ar, axis, 0) + ar = np.moveaxis(ar, axis, 0) except np.AxisError: # this removes the "axis1" or "axis2" prefix from the error message raise np.AxisError(axis, ar.ndim) @@ -285,7 +285,7 @@ def unique(ar, return_index=False, return_inverse=False, def reshape_uniq(uniq): uniq = uniq.view(orig_dtype) uniq = uniq.reshape(-1, *orig_shape[1:]) - uniq = np.swapaxes(uniq, 0, axis) + uniq = np.moveaxis(uniq, 0, axis) return uniq output = _unique1d(consolidated, return_index, diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py index dd8a38248..fd21a7f76 100644 --- a/numpy/lib/tests/test_arraysetops.py +++ b/numpy/lib/tests/test_arraysetops.py @@ -600,8 +600,11 @@ class TestUnique(object): assert_array_equal(unique(data, axis=1), result.astype(dtype), msg) msg = 'Unique with 3d array and axis=2 failed' - data3d = np.dstack([data] * 3) - result = data3d[..., :1] + data3d = np.array([[[1, 1], + [1, 0]], + [[0, 1], + [0, 0]]]).astype(dtype) + result = np.take(data3d, [1, 0], axis=2) assert_array_equal(unique(data3d, axis=2), result, msg) uniq, idx, inv, cnt = unique(data, axis=0, return_index=True, |