diff options
Diffstat (limited to 'numpy/core/tests/test_regression.py')
| -rw-r--r-- | numpy/core/tests/test_regression.py | 61 |
1 files changed, 33 insertions, 28 deletions
diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py index c3b9dab69..841144790 100644 --- a/numpy/core/tests/test_regression.py +++ b/numpy/core/tests/test_regression.py @@ -12,7 +12,7 @@ from numpy.testing import ( assert_, assert_equal, IS_PYPY, assert_almost_equal, assert_array_equal, assert_array_almost_equal, assert_raises, assert_raises_regex, assert_warns, suppress_warnings, - _assert_valid_refcount, HAS_REFCOUNT, IS_PYSTON + _assert_valid_refcount, HAS_REFCOUNT, IS_PYSTON, IS_WASM ) from numpy.testing._private.utils import _no_tracing, requires_memory from numpy.compat import asbytes, asunicode, pickle @@ -128,10 +128,7 @@ class TestRegression: assert_(a[1] == 'auto') assert_(a[0] != 'auto') b = np.linspace(0, 10, 11) - # This should return true for now, but will eventually raise an error: - with suppress_warnings() as sup: - sup.filter(FutureWarning) - assert_(b != 'auto') + assert_array_equal(b != 'auto', np.ones(11, dtype=bool)) assert_(b[0] != 'auto') def test_unicode_swapping(self): @@ -295,7 +292,7 @@ class TestRegression: def test_unicode_string_comparison(self): # Ticket #190 - a = np.array('hello', np.unicode_) + a = np.array('hello', np.str_) b = np.array('world') a == b @@ -326,6 +323,7 @@ class TestRegression: assert_raises(ValueError, bfa) assert_raises(ValueError, bfb) + @pytest.mark.xfail(IS_WASM, reason="not sure why") @pytest.mark.parametrize("index", [np.ones(10, dtype=bool), np.arange(10)], ids=["boolean-arr-index", "integer-arr-index"]) @@ -457,7 +455,7 @@ class TestRegression: test_data = [ # (original, py2_pickle) - (np.unicode_('\u6f2c'), + (np.str_('\u6f2c'), b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n" b"(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\n" b"I0\ntp6\nbS',o\\x00\\x00'\np7\ntp8\nRp9\n."), @@ -518,22 +516,15 @@ class TestRegression: def test_method_args(self): # Make sure methods and functions have same default axis # keyword and arguments - funcs1 = ['argmax', 'argmin', 'sum', ('product', 'prod'), - ('sometrue', 'any'), - ('alltrue', 'all'), 'cumsum', ('cumproduct', 'cumprod'), - 'ptp', 'cumprod', 'prod', 'std', 'var', 'mean', - 'round', 'min', 'max', 'argsort', 'sort'] + funcs1 = ['argmax', 'argmin', 'sum', 'any', 'all', 'cumsum', + 'ptp', 'cumprod', 'prod', 'std', 'var', 'mean', + 'round', 'min', 'max', 'argsort', 'sort'] funcs2 = ['compress', 'take', 'repeat'] for func in funcs1: arr = np.random.rand(8, 7) arr2 = arr.copy() - if isinstance(func, tuple): - func_meth = func[1] - func = func[0] - else: - func_meth = func - res1 = getattr(arr, func_meth)() + res1 = getattr(arr, func)() res2 = getattr(np, func)(arr2) if res1 is None: res1 = arr @@ -1338,8 +1329,8 @@ class TestRegression: # Ticket #1058 a = np.fromiter(list(range(10)), dtype='b') b = np.fromiter(list(range(10)), dtype='B') - assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) - assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) + assert_(np.all(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) + assert_(np.all(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) def test_array_from_sequence_scalar_array(self): # Ticket #1078: segfaults when creating an array with a sequence of @@ -1517,8 +1508,8 @@ class TestRegression: def test_fromiter_comparison(self): a = np.fromiter(list(range(10)), dtype='b') b = np.fromiter(list(range(10)), dtype='B') - assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) - assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) + assert_(np.all(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) + assert_(np.all(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) def test_fromstring_crash(self): # Ticket #1345: the following should not cause a crash @@ -1537,9 +1528,12 @@ class TestRegression: for y in dtypes: c = a.astype(y) try: - np.dot(b, c) + d = np.dot(b, c) except TypeError: failures.append((x, y)) + else: + if d != 0: + failures.append((x, y)) if failures: raise AssertionError("Failures: %r" % failures) @@ -1689,7 +1683,7 @@ class TestRegression: # number 2, and the exception hung around until something checked # PyErr_Occurred() and returned an error. assert_equal(np.dtype('S10').itemsize, 10) - np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_) + np.array([['abc', 2], ['long ', '0123456789']], dtype=np.bytes_) assert_equal(np.dtype('S10').itemsize, 10) def test_any_float(self): @@ -1958,7 +1952,7 @@ class TestRegression: # Python2 output for pickle.dumps(...) datas = [ # (original, python2_pickle, koi8r_validity) - (np.unicode_('\u6bd2'), + (np.str_('\u6bd2'), (b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n" b"(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n" b"tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."), @@ -2082,7 +2076,7 @@ class TestRegression: # Ticket #1578, the mismatch only showed up when running # python-debug for python versions >= 2.7, and then as # a core dump and error message. - a = np.array(['abc'], dtype=np.unicode_)[0] + a = np.array(['abc'], dtype=np.str_)[0] del a def test_refcount_error_in_clip(self): @@ -2229,7 +2223,7 @@ class TestRegression: def test_pickle_empty_string(self): # gh-3926 for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): - test_string = np.string_('') + test_string = np.bytes_('') assert_equal(pickle.loads( pickle.dumps(test_string, protocol=proto)), test_string) @@ -2350,7 +2344,7 @@ class TestRegression: values = { np.void: b"a", np.bytes_: b"a", - np.unicode_: "a", + np.str_: "a", np.datetime64: "2017-08-25", } for sctype in scalar_types: @@ -2557,3 +2551,14 @@ class TestRegression: f"Unexpected types order of ufunc in {operation}" f"for {order}. Possible fix: Use signed before unsigned" "in generate_umath.py") + + def test_nonbool_logical(self): + # gh-22845 + # create two arrays with bit patterns that do not overlap. + # needs to be large enough to test both SIMD and scalar paths + size = 100 + a = np.frombuffer(b'\x01' * size, dtype=np.bool_) + b = np.frombuffer(b'\x80' * size, dtype=np.bool_) + expected = np.ones(size, dtype=np.bool_) + assert_array_equal(np.logical_and(a, b), expected) + |