diff options
Diffstat (limited to 'numpy/core')
| -rw-r--r-- | numpy/core/src/multiarray/common.c | 3 | ||||
| -rw-r--r-- | numpy/core/src/umath/ufunc_object.c | 17 | ||||
| -rw-r--r-- | numpy/core/tests/test_multiarray.py | 14 | ||||
| -rw-r--r-- | numpy/core/tests/test_ufunc.py | 16 |
4 files changed, 47 insertions, 3 deletions
diff --git a/numpy/core/src/multiarray/common.c b/numpy/core/src/multiarray/common.c index c216daa95..bd566b77b 100644 --- a/numpy/core/src/multiarray/common.c +++ b/numpy/core/src/multiarray/common.c @@ -476,6 +476,9 @@ PyArray_DTypeFromObjectHelper(PyObject *obj, int maxdims, * __len__ is not defined. */ if (maxdims == 0 || !PySequence_Check(obj) || PySequence_Size(obj) < 0) { + // clear any PySequence_Size error, which corrupts further calls to it + PyErr_Clear(); + if (*out_dtype == NULL || (*out_dtype)->type_num != NPY_OBJECT) { Py_XDECREF(*out_dtype); *out_dtype = PyArray_DescrFromType(NPY_OBJECT); diff --git a/numpy/core/src/umath/ufunc_object.c b/numpy/core/src/umath/ufunc_object.c index a472cf9f0..c4a2b8560 100644 --- a/numpy/core/src/umath/ufunc_object.c +++ b/numpy/core/src/umath/ufunc_object.c @@ -3270,17 +3270,22 @@ PyUFunc_Accumulate(PyUFuncObject *ufunc, PyArrayObject *arr, PyArrayObject *out, NPY_BEGIN_THREADS_NDITER(iter); do { - dataptr_copy[0] = dataptr[0]; dataptr_copy[1] = dataptr[1]; dataptr_copy[2] = dataptr[0]; /* Copy the first element to start the reduction */ if (otype == NPY_OBJECT) { + /* + * Input (dataptr[0]) and output (dataptr[1]) may point + * to the same memory (i.e. np.add.accumulate(a, out=a)). + * In that case need to incref before decref to avoid the + * possibility of the reference count being zero temporarily. + */ + Py_XINCREF(*(PyObject **)dataptr_copy[1]); Py_XDECREF(*(PyObject **)dataptr_copy[0]); *(PyObject **)dataptr_copy[0] = *(PyObject **)dataptr_copy[1]; - Py_XINCREF(*(PyObject **)dataptr_copy[0]); } else { memcpy(dataptr_copy[0], dataptr_copy[1], itemsize); @@ -3333,10 +3338,16 @@ PyUFunc_Accumulate(PyUFuncObject *ufunc, PyArrayObject *arr, PyArrayObject *out, /* Copy the first element to start the reduction */ if (otype == NPY_OBJECT) { + /* + * Input (dataptr[0]) and output (dataptr[1]) may point + * to the same memory (i.e. np.add.accumulate(a, out=a, axis=0)). + * In that case need to incref before decref to avoid the + * possibility of the reference count being zero temporarily. + */ + Py_XINCREF(*(PyObject **)dataptr_copy[1]); Py_XDECREF(*(PyObject **)dataptr_copy[0]); *(PyObject **)dataptr_copy[0] = *(PyObject **)dataptr_copy[1]; - Py_XINCREF(*(PyObject **)dataptr_copy[0]); } else { memcpy(dataptr_copy[0], dataptr_copy[1], itemsize); diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py index a6c8489ef..14a902b9c 100644 --- a/numpy/core/tests/test_multiarray.py +++ b/numpy/core/tests/test_multiarray.py @@ -716,6 +716,20 @@ class TestCreation(TestCase): assert_raises(ValueError, np.array, C()) # segfault? + def test_failed_len_sequence(self): + # gh-7393 + class A(object): + def __init__(self, data): + self._data = data + def __getitem__(self, item): + return type(self)(self._data[item]) + def __len__(self): + return len(self._data) + + # len(d) should give 3, but len(d[0]) will fail + d = A([1,2,3]) + assert_equal(len(np.array(d)), 3) + class TestStructured(TestCase): def test_subarray_field_access(self): diff --git a/numpy/core/tests/test_ufunc.py b/numpy/core/tests/test_ufunc.py index eb0985386..ab8cecff0 100644 --- a/numpy/core/tests/test_ufunc.py +++ b/numpy/core/tests/test_ufunc.py @@ -649,6 +649,22 @@ class TestUfunc(TestCase): assert_equal(np.array([[1]], dtype=object).sum(), 1) assert_equal(np.array([[[1, 2]]], dtype=object).sum((0, 1)), [1, 2]) + def test_object_array_accumulate_inplace(self): + # Checks that in-place accumulates work, see also gh-7402 + arr = np.ones(4, dtype=object) + arr[:] = [[1] for i in range(4)] + # Twice reproduced also for tuples: + np.add.accumulate(arr, out=arr) + np.add.accumulate(arr, out=arr) + assert_array_equal(arr, np.array([[1]*i for i in [1, 3, 6, 10]])) + + # And the same if the axis argument is used + arr = np.ones((2, 4), dtype=object) + arr[0, :] = [[2] for i in range(4)] + np.add.accumulate(arr, out=arr, axis=-1) + np.add.accumulate(arr, out=arr, axis=-1) + assert_array_equal(arr[0, :], np.array([[2]*i for i in [1, 3, 6, 10]])) + def test_object_scalar_multiply(self): # Tickets #2469 and #4482 arr = np.matrix([1, 2], dtype=object) |