diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/src/multiarray/buffer.c | 12 | ||||
| -rw-r--r-- | numpy/ma/core.py | 19 | ||||
| -rw-r--r-- | numpy/ma/tests/test_core.py | 12 |
3 files changed, 35 insertions, 8 deletions
diff --git a/numpy/core/src/multiarray/buffer.c b/numpy/core/src/multiarray/buffer.c index 7f7607e1f..5fa3ba95b 100644 --- a/numpy/core/src/multiarray/buffer.c +++ b/numpy/core/src/multiarray/buffer.c @@ -629,8 +629,6 @@ array_getbuffer(PyObject *obj, Py_buffer *view, int flags) { PyArrayObject *self; _buffer_info_t *info = NULL; - int i; - Py_ssize_t sd; self = (PyArrayObject*)obj; @@ -715,15 +713,19 @@ array_getbuffer(PyObject *obj, Py_buffer *view, int flags) * regenerate strides from shape. */ if (PyArray_CHKFLAGS(self, NPY_ARRAY_C_CONTIGUOUS) && - !((flags & PyBUF_F_CONTIGUOUS) == PyBUF_F_CONTIGUOUS)) { - sd = view->itemsize; + !((flags & PyBUF_F_CONTIGUOUS) == PyBUF_F_CONTIGUOUS)) { + Py_ssize_t sd = view->itemsize; + int i; + for (i = view->ndim-1; i >= 0; --i) { view->strides[i] = sd; sd *= view->shape[i]; } } else if (PyArray_CHKFLAGS(self, NPY_ARRAY_F_CONTIGUOUS)) { - sd = view->itemsize; + Py_ssize_t sd = view->itemsize; + int i; + for (i = 0; i < view->ndim; ++i) { view->strides[i] = sd; sd *= view->shape[i]; diff --git a/numpy/ma/core.py b/numpy/ma/core.py index 807b28c5b..9cc1a1272 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -2684,6 +2684,8 @@ class MaskedArray(ndarray): _defaultmask = nomask _defaulthardmask = False _baseclass = ndarray + # Maximum number of elements per axis used when printing an array. + _print_width = 100 def __new__(cls, data=None, mask=nomask, dtype=None, copy=False, subok=True, ndmin=0, fill_value=None, @@ -3701,7 +3703,7 @@ class MaskedArray(ndarray): if m is nomask: res = self._data else: - if m.shape == (): + if m.shape == () and m.itemsize==len(m.dtype): if m.dtype.names: m = m.view((bool, len(m.dtype))) if m.any(): @@ -3716,8 +3718,19 @@ class MaskedArray(ndarray): # convert to object array to make filled work names = self.dtype.names if names is None: - res = self._data.astype("O") - res.view(ndarray)[m] = f + data = self._data + mask = m + # For big arrays, to avoid a costly conversion to the + # object dtype, extract the corners before the conversion. + for axis in range(self.ndim): + if data.shape[axis] > self._print_width: + ind = self._print_width // 2 + arr = np.split(data, (ind, -ind), axis=axis) + data = np.concatenate((arr[0], arr[2]), axis=axis) + arr = np.split(mask, (ind, -ind), axis=axis) + mask = np.concatenate((arr[0], arr[2]), axis=axis) + res = data.astype("O") + res.view(ndarray)[mask] = f else: rdtype = _recursive_make_descr(self.dtype, "O") res = self._data.astype(rdtype) diff --git a/numpy/ma/tests/test_core.py b/numpy/ma/tests/test_core.py index cab5abb33..2fdd00484 100644 --- a/numpy/ma/tests/test_core.py +++ b/numpy/ma/tests/test_core.py @@ -634,6 +634,18 @@ class TestMaskedArray(TestCase): control = "[(--, (2, --)) (4, (--, 6.0))]" assert_equal(str(test), control) + # Test 0-d array with multi-dimensional dtype + t_2d0 = masked_array(data = (0, [[0.0, 0.0, 0.0], + [0.0, 0.0, 0.0]], + 0.0), + mask = (False, [[True, False, True], + [False, False, True]], + False), + dtype = "int, (2,3)float, float") + control = "(0, [[--, 0.0, --], [0.0, 0.0, --]], 0.0)" + assert_equal(str(t_2d0), control) + + def test_flatten_structured_array(self): # Test flatten_structured_array on arrays # On ndarray |