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-rw-r--r--doc/release/upcoming_changes/14800.improvement.rst14
-rw-r--r--numpy/core/code_generators/generate_umath.py14
-rw-r--r--numpy/core/tests/test_deprecations.py3
-rw-r--r--numpy/core/tests/test_ufunc.py15
-rw-r--r--numpy/core/tests/test_umath.py6
-rw-r--r--numpy/lib/arraysetops.py8
-rw-r--r--numpy/linalg/tests/test_regression.py7
-rw-r--r--numpy/ma/core.py7
8 files changed, 23 insertions, 51 deletions
diff --git a/doc/release/upcoming_changes/14800.improvement.rst b/doc/release/upcoming_changes/14800.improvement.rst
deleted file mode 100644
index 158c31536..000000000
--- a/doc/release/upcoming_changes/14800.improvement.rst
+++ /dev/null
@@ -1,14 +0,0 @@
-Comparison on ``object`` dtypes will prefer ``object`` output
--------------------------------------------------------------
-Comparison ufuncs (``np.equal`` and friends) would return boolean arrays when
-the input array dtype was ``object``. This led to inconsistent behaviour for
-ragged arrays ``a = np.array([1, np.array([1, 2, 3])], dtype=object)``. This
-will now return an object array::
-
- >>> a = np.array([1, np.array([1, 2, 3])], dtype=object)
- >>> np.equal(a, a)
- array([True, array([ True, True, True])], dtype=object)
-
-The old behaviour, which will raise a ``ValueError`` in this case, is still
-available by specifying a dtype as ``np.equal(a, a, dtype=bool)``.
-
diff --git a/numpy/core/code_generators/generate_umath.py b/numpy/core/code_generators/generate_umath.py
index 760b9c919..9e67a45ef 100644
--- a/numpy/core/code_generators/generate_umath.py
+++ b/numpy/core/code_generators/generate_umath.py
@@ -227,6 +227,8 @@ chartoname = {
}
noobj = '?bBhHiIlLqQefdgFDGmM'
+all = '?bBhHiIlLqQefdgFDGOmM'
+
O = 'O'
P = 'P'
ints = 'bBhHiIlLqQ'
@@ -429,7 +431,7 @@ defdict = {
Ufunc(2, 1, None,
docstrings.get('numpy.core.umath.greater'),
'PyUFunc_SimpleBinaryComparisonTypeResolver',
- TD(noobj, out='?', simd=[('avx2', ints)]),
+ TD(all, out='?', simd=[('avx2', ints)]),
[TypeDescription('O', FullTypeDescr, 'OO', 'O')],
TD('O', out='?'),
),
@@ -437,7 +439,7 @@ defdict = {
Ufunc(2, 1, None,
docstrings.get('numpy.core.umath.greater_equal'),
'PyUFunc_SimpleBinaryComparisonTypeResolver',
- TD(noobj, out='?', simd=[('avx2', ints)]),
+ TD(all, out='?', simd=[('avx2', ints)]),
[TypeDescription('O', FullTypeDescr, 'OO', 'O')],
TD('O', out='?'),
),
@@ -445,7 +447,7 @@ defdict = {
Ufunc(2, 1, None,
docstrings.get('numpy.core.umath.less'),
'PyUFunc_SimpleBinaryComparisonTypeResolver',
- TD(noobj, out='?', simd=[('avx2', ints)]),
+ TD(all, out='?', simd=[('avx2', ints)]),
[TypeDescription('O', FullTypeDescr, 'OO', 'O')],
TD('O', out='?'),
),
@@ -453,7 +455,7 @@ defdict = {
Ufunc(2, 1, None,
docstrings.get('numpy.core.umath.less_equal'),
'PyUFunc_SimpleBinaryComparisonTypeResolver',
- TD(noobj, out='?', simd=[('avx2', ints)]),
+ TD(all, out='?', simd=[('avx2', ints)]),
[TypeDescription('O', FullTypeDescr, 'OO', 'O')],
TD('O', out='?'),
),
@@ -461,7 +463,7 @@ defdict = {
Ufunc(2, 1, None,
docstrings.get('numpy.core.umath.equal'),
'PyUFunc_SimpleBinaryComparisonTypeResolver',
- TD(noobj, out='?', simd=[('avx2', ints)]),
+ TD(all, out='?', simd=[('avx2', ints)]),
[TypeDescription('O', FullTypeDescr, 'OO', 'O')],
TD('O', out='?'),
),
@@ -469,7 +471,7 @@ defdict = {
Ufunc(2, 1, None,
docstrings.get('numpy.core.umath.not_equal'),
'PyUFunc_SimpleBinaryComparisonTypeResolver',
- TD(noobj, out='?', simd=[('avx2', ints)]),
+ TD(all, out='?', simd=[('avx2', ints)]),
[TypeDescription('O', FullTypeDescr, 'OO', 'O')],
TD('O', out='?'),
),
diff --git a/numpy/core/tests/test_deprecations.py b/numpy/core/tests/test_deprecations.py
index 9bdcd8241..363ff26db 100644
--- a/numpy/core/tests/test_deprecations.py
+++ b/numpy/core/tests/test_deprecations.py
@@ -175,8 +175,7 @@ class TestComparisonDeprecations(_DeprecationTestCase):
# ragged array comparison returns True/False
a = np.array([1, np.array([1,2,3])], dtype=object)
b = np.array([1, np.array([1,2,3])], dtype=object)
- res = op(a, b)
- assert res.dtype == 'object'
+ self.assert_deprecated(op, args=(a, b), num=None)
def test_string(self):
# For two string arrays, strings always raised the broadcasting error:
diff --git a/numpy/core/tests/test_ufunc.py b/numpy/core/tests/test_ufunc.py
index d9f961581..ba1aee55b 100644
--- a/numpy/core/tests/test_ufunc.py
+++ b/numpy/core/tests/test_ufunc.py
@@ -1090,18 +1090,13 @@ class TestUfunc(object):
return '=='
arr0d = np.array(HasComparisons())
- assert_equal(arr0d == arr0d, '==')
- assert_equal(np.equal(arr0d, arr0d), '==')
- assert_equal(np.equal(arr0d, arr0d, dtype=bool), True)
- assert_equal(np.equal(arr0d, arr0d, dtype=object), '==')
+ assert_equal(arr0d == arr0d, True)
+ assert_equal(np.equal(arr0d, arr0d), True) # normal behavior is a cast
arr1d = np.array([HasComparisons()])
- ret_obj = np.array(['=='], dtype=object)
- ret_bool = np.array([True])
- assert_equal(arr1d == arr1d, ret_obj)
- assert_equal(np.equal(arr1d, arr1d), ret_obj)
- assert_equal(np.equal(arr1d, arr1d, dtype=object), ret_obj)
- assert_equal(np.equal(arr1d, arr1d, dtype=bool), ret_bool)
+ assert_equal(arr1d == arr1d, np.array([True]))
+ assert_equal(np.equal(arr1d, arr1d), np.array([True])) # normal behavior is a cast
+ assert_equal(np.equal(arr1d, arr1d, dtype=object), np.array(['==']))
def test_object_array_reduction(self):
# Reductions on object arrays
diff --git a/numpy/core/tests/test_umath.py b/numpy/core/tests/test_umath.py
index 96a9f1f8b..1d71766ef 100644
--- a/numpy/core/tests/test_umath.py
+++ b/numpy/core/tests/test_umath.py
@@ -173,8 +173,7 @@ class TestComparisons(object):
# Check comparing identical objects whose comparison
# is not a simple boolean, e.g., arrays that are compared elementwise.
a = np.array([np.array([1, 2, 3]), None], dtype=object)
- b = np.equal(a, a.copy())
- assert b.shape == a.shape
+ assert_raises(ValueError, np.equal, a, a)
# Check error raised when comparing identical non-comparable objects.
class FunkyType(object):
@@ -192,8 +191,7 @@ class TestComparisons(object):
# Check comparing identical objects whose comparison
# is not a simple boolean, e.g., arrays that are compared elementwise.
a = np.array([np.array([1, 2, 3]), None], dtype=object)
- b = np.not_equal(a, a.copy())
- assert b.shape == a.shape
+ assert_raises(ValueError, np.not_equal, a, a)
# Check error raised when comparing identical non-comparable objects.
class FunkyType(object):
diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py
index cf45e181b..2309f7e42 100644
--- a/numpy/lib/arraysetops.py
+++ b/numpy/lib/arraysetops.py
@@ -562,15 +562,11 @@ def in1d(ar1, ar2, assume_unique=False, invert=False):
if invert:
mask = np.ones(len(ar1), dtype=bool)
for a in ar2:
- # convert object arrays to bool
- # cannot use np.not_equal until 'S' and 'U' have loops
- mask &= (ar1 != a).astype(bool)
+ mask &= (ar1 != a)
else:
mask = np.zeros(len(ar1), dtype=bool)
for a in ar2:
- # convert object arrays to bool
- # cannot use np.equal until 'S' and 'U' have loops
- mask |= (ar1 == a).astype(bool)
+ mask |= (ar1 == a)
return mask
# Otherwise use sorting
diff --git a/numpy/linalg/tests/test_regression.py b/numpy/linalg/tests/test_regression.py
index 289566109..bd3a45872 100644
--- a/numpy/linalg/tests/test_regression.py
+++ b/numpy/linalg/tests/test_regression.py
@@ -109,9 +109,10 @@ class TestRegression(object):
assert_raises(ValueError, linalg.norm, testvector, ord='nuc')
assert_raises(ValueError, linalg.norm, testvector, ord=np.inf)
assert_raises(ValueError, linalg.norm, testvector, ord=-np.inf)
- # Succeeds, equivalent to "sum(x != 0)"
- r = linalg.norm(testvector, ord=0)
- assert_(r.dtype == 'bool')
+ with warnings.catch_warnings():
+ warnings.simplefilter("error", DeprecationWarning)
+ assert_raises((AttributeError, DeprecationWarning),
+ linalg.norm, testvector, ord=0)
assert_raises(ValueError, linalg.norm, testvector, ord=-1)
assert_raises(ValueError, linalg.norm, testvector, ord=-2)
diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index f98a29d82..bb0d8d412 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -4790,12 +4790,7 @@ class MaskedArray(ndarray):
mask = _check_mask_axis(self._mask, axis, **kwargs)
if out is None:
- r = self.filled(True).all(axis=axis, **kwargs)
- # object dtypes with axis=None return a scalar
- if isinstance(r, bool):
- d = type(self)(r)
- else:
- d = r.view(type(self))
+ d = self.filled(True).all(axis=axis, **kwargs).view(type(self))
if d.ndim:
d.__setmask__(mask)
elif mask:
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