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BUG/MAINT/ENH: Allow viewing where only the last axis is contiguous #9497

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BUG/MAINT/ENH: Allow viewing where only the last axis is contiguous #9497

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9f30e12
MAINT/BUG: Improve error messages for dtype reassigment, fix missing …
eric-wieser Jul 30, 2017
9009102
ENH: Allow view to reshape arrays with only the last axis contiguous
eric-wieser Jul 30, 2017
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6 changes: 6 additions & 0 deletions doc/release/1.14.0-notes.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -104,6 +104,12 @@ By default, ``np.einsum`` will also attempt optimization as the overhead is
small relative to the potential improvement in speed.


``.view`` now works on arrays where only the last axis is contiguous
--------------------------------------------------------------------
Previously it only worked on C-contiguous arrays when the new dtype was a
different size.


Changes
=======

Expand Down
113 changes: 62 additions & 51 deletions numpy/core/src/multiarray/getset.c
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Original file line number Diff line number Diff line change
Expand Up @@ -438,8 +438,7 @@ array_descr_set(PyArrayObject *self, PyObject *arg)
{
PyArray_Descr *newtype = NULL;
npy_intp newdim;
int i;
char *msg = "new type not compatible with array.";
int axis;
PyObject *safe;
static PyObject *checkfunc = NULL;

Expand All @@ -461,14 +460,13 @@ array_descr_set(PyArrayObject *self, PyObject *arg)
if (_may_have_objects(PyArray_DESCR(self)) || _may_have_objects(newtype)) {
npy_cache_import("numpy.core._internal", "_view_is_safe", &checkfunc);
if (checkfunc == NULL) {
return -1;
goto fail;
}

safe = PyObject_CallFunction(checkfunc, "OO",
PyArray_DESCR(self), newtype);
if (safe == NULL) {
Py_DECREF(newtype);
return -1;
goto fail;
}
Py_DECREF(safe);
}
Expand All @@ -492,58 +490,71 @@ array_descr_set(PyArrayObject *self, PyObject *arg)
}


if ((newtype->elsize != PyArray_DESCR(self)->elsize) &&
(PyArray_NDIM(self) == 0 ||
!PyArray_ISONESEGMENT(self) ||
PyDataType_HASSUBARRAY(newtype))) {
goto fail;
}
/* Changing the size of the dtype results in a shape change */
if (newtype->elsize != PyArray_DESCR(self)->elsize) {
/* forbidden cases */
if (PyArray_NDIM(self) == 0) {
PyErr_SetString(PyExc_ValueError,
"Changing the dtype of a 0d array is only supported "
"if the itemsize is unchanged");
goto fail;
}
else if (PyDataType_HASSUBARRAY(newtype)) {
PyErr_SetString(PyExc_ValueError,
"Changing the dtype to a subarray type is only supported "
"if the total itemsize is unchanged");
goto fail;
}

/* Deprecate not C contiguous and a dimension changes */
if (newtype->elsize != PyArray_DESCR(self)->elsize &&
!PyArray_IS_C_CONTIGUOUS(self)) {
/* 11/27/2015 1.11.0 */
if (DEPRECATE("Changing the shape of non-C contiguous array by\n"
"descriptor assignment is deprecated. To maintain\n"
"the Fortran contiguity of a multidimensional Fortran\n"
"array, use 'a.T.view(...).T' instead") < 0) {
return -1;
/* determine which axis to resize */
if (PyArray_IS_F_CONTIGUOUS(self) &&
!PyArray_IS_C_CONTIGUOUS(self)) {
/* 2015-11-27 1.11.0 */
if (DEPRECATE("Changing the shape of an F-contiguous array by "
"descriptor assignment is deprecated. To maintain "
"the Fortran contiguity of a multidimensional Fortran "
"array, use 'a.T.view(...).T' instead") < 0) {
goto fail;
}
axis = 0;
}
else {
axis = PyArray_NDIM(self) - 1;
if (PyArray_STRIDES(self)[axis] != PyArray_DESCR(self)->elsize) {
PyErr_SetString(PyExc_ValueError,
"To change the size of the dtype, the array must be "
"contiguous in the last dimension");
goto fail;
}
}
}

if (PyArray_IS_C_CONTIGUOUS(self)) {
i = PyArray_NDIM(self) - 1;
}
else {
i = 0;
}
if (newtype->elsize < PyArray_DESCR(self)->elsize) {
/*
* if it is compatible increase the size of the
* dimension at end (or at the front for NPY_ARRAY_F_CONTIGUOUS)
*/
if (PyArray_DESCR(self)->elsize % newtype->elsize != 0) {
goto fail;
if (newtype->elsize < PyArray_DESCR(self)->elsize) {
/* if it is compatible, increase the size of the relevant axis */
if (PyArray_DESCR(self)->elsize % newtype->elsize != 0) {
PyErr_SetString(PyExc_ValueError,
"When changing to a smaller dtype, its size must be a "
"divisor of the size of original dtype");
goto fail;
}
newdim = PyArray_DESCR(self)->elsize / newtype->elsize;
PyArray_DIMS(self)[axis] *= newdim;
PyArray_STRIDES(self)[axis] = newtype->elsize;
}
newdim = PyArray_DESCR(self)->elsize / newtype->elsize;
PyArray_DIMS(self)[i] *= newdim;
PyArray_STRIDES(self)[i] = newtype->elsize;
}
else if (newtype->elsize > PyArray_DESCR(self)->elsize) {
/*
* Determine if last (or first if NPY_ARRAY_F_CONTIGUOUS) dimension
* is compatible
*/
newdim = PyArray_DIMS(self)[i] * PyArray_DESCR(self)->elsize;
if ((newdim % newtype->elsize) != 0) {
goto fail;
else if (newtype->elsize > PyArray_DESCR(self)->elsize) {
/* if it is compatible, decrease the size of the relevant axis */
newdim = PyArray_DIMS(self)[axis] * PyArray_DESCR(self)->elsize;
if ((newdim % newtype->elsize) != 0) {
PyErr_SetString(PyExc_ValueError,
"When changing to a larger dtype, its size must be a "
"multiple of the size of original dtype");
goto fail;
}
PyArray_DIMS(self)[axis] = newdim / newtype->elsize;
PyArray_STRIDES(self)[axis] = newtype->elsize;
}
PyArray_DIMS(self)[i] = newdim / newtype->elsize;
PyArray_STRIDES(self)[i] = newtype->elsize;
}

/* fall through -- adjust type*/
Py_DECREF(PyArray_DESCR(self));
/* Viewing as a subarray increases the number of dimensions */
if (PyDataType_HASSUBARRAY(newtype)) {
/*
* create new array object from data and update
Expand Down Expand Up @@ -573,12 +584,12 @@ array_descr_set(PyArrayObject *self, PyObject *arg)
Py_DECREF(temp);
}

Py_DECREF(PyArray_DESCR(self));
((PyArrayObject_fields *)self)->descr = newtype;
PyArray_UpdateFlags(self, NPY_ARRAY_UPDATE_ALL);
return 0;

fail:
PyErr_SetString(PyExc_ValueError, msg);
Py_DECREF(newtype);
return -1;
}
Expand Down
18 changes: 18 additions & 0 deletions numpy/ma/tests/test_core.py
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Expand Up @@ -4434,6 +4434,24 @@ def test_view(self):
assert_equal(test, data)
assert_(isinstance(test, np.matrix))

def test_view_last_contiguous(self):
# gh-9496
arr = np.arange(24, dtype=np.float64).reshape(3, 4, 2)
arr2 = arr[:,::2,:]
arr_c = arr2.view(np.complex128)
assert_equal(arr_c,
np.array([[
[ 0 +1j],
[ 4 +5j]],

[[ 8 +9j],
[ 12+13j]],

[[ 16+17j],
[ 20+21j]]
])
)

def test_getitem(self):
ndtype = [('a', float), ('b', float)]
a = array(list(zip(np.random.rand(10), np.arange(10))), dtype=ndtype)
Expand Down