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-rw-r--r--doc/release/upcoming_changes/14942.compatibility.rst5
-rw-r--r--numpy/core/src/multiarray/arraytypes.c.src115
-rw-r--r--numpy/core/src/multiarray/item_selection.c275
-rw-r--r--numpy/core/tests/test_multiarray.py14
4 files changed, 183 insertions, 226 deletions
diff --git a/doc/release/upcoming_changes/14942.compatibility.rst b/doc/release/upcoming_changes/14942.compatibility.rst
new file mode 100644
index 000000000..41a2457e2
--- /dev/null
+++ b/doc/release/upcoming_changes/14942.compatibility.rst
@@ -0,0 +1,5 @@
+Fasttake slot is deprecated and now NULL'ed
+-------------------------------------------
+The fasttake slot for all dtypes is now never used internally
+and always set to NULL. No downstream project should be using
+this, so no compatibility issue is expected.
diff --git a/numpy/core/src/multiarray/arraytypes.c.src b/numpy/core/src/multiarray/arraytypes.c.src
index 077fb0ec8..0f52df486 100644
--- a/numpy/core/src/multiarray/arraytypes.c.src
+++ b/numpy/core/src/multiarray/arraytypes.c.src
@@ -3973,119 +3973,6 @@ static void
#define OBJECT_fastputmask NULL
-/*
- *****************************************************************************
- ** FASTTAKE **
- *****************************************************************************
- */
-
-
-/**begin repeat
- *
- * #name = BOOL,
- * BYTE, UBYTE, SHORT, USHORT, INT, UINT,
- * LONG, ULONG, LONGLONG, ULONGLONG,
- * HALF, FLOAT, DOUBLE, LONGDOUBLE,
- * CFLOAT, CDOUBLE, CLONGDOUBLE,
- * DATETIME, TIMEDELTA#
- * #type = npy_bool,
- * npy_byte, npy_ubyte, npy_short, npy_ushort, npy_int, npy_uint,
- * npy_long, npy_ulong, npy_longlong, npy_ulonglong,
- * npy_half, npy_float, npy_double, npy_longdouble,
- * npy_cfloat, npy_cdouble, npy_clongdouble,
- * npy_datetime, npy_timedelta#
-*/
-static int
-@name@_fasttake(@type@ *dest, @type@ *src, npy_intp *indarray,
- npy_intp nindarray, npy_intp n_outer,
- npy_intp m_middle, npy_intp nelem,
- NPY_CLIPMODE clipmode)
-{
- npy_intp i, j, k, tmp;
- NPY_BEGIN_THREADS_DEF;
-
- NPY_BEGIN_THREADS;
-
- switch(clipmode) {
- case NPY_RAISE:
- for (i = 0; i < n_outer; i++) {
- for (j = 0; j < m_middle; j++) {
- tmp = indarray[j];
- /*
- * We don't know what axis we're operating on,
- * so don't report it in case of an error.
- */
- if (check_and_adjust_index(&tmp, nindarray, -1, _save) < 0) {
- return 1;
- }
- if (NPY_LIKELY(nelem == 1)) {
- *dest++ = *(src + tmp);
- }
- else {
- for (k = 0; k < nelem; k++) {
- *dest++ = *(src + tmp*nelem + k);
- }
- }
- }
- src += nelem*nindarray;
- }
- break;
- case NPY_WRAP:
- for (i = 0; i < n_outer; i++) {
- for (j = 0; j < m_middle; j++) {
- tmp = indarray[j];
- if (tmp < 0) {
- while (tmp < 0) {
- tmp += nindarray;
- }
- }
- else if (tmp >= nindarray) {
- while (tmp >= nindarray) {
- tmp -= nindarray;
- }
- }
- if (NPY_LIKELY(nelem == 1)) {
- *dest++ = *(src+tmp);
- }
- else {
- for (k = 0; k < nelem; k++) {
- *dest++ = *(src+tmp*nelem+k);
- }
- }
- }
- src += nelem*nindarray;
- }
- break;
- case NPY_CLIP:
- for (i = 0; i < n_outer; i++) {
- for (j = 0; j < m_middle; j++) {
- tmp = indarray[j];
- if (tmp < 0) {
- tmp = 0;
- }
- else if (tmp >= nindarray) {
- tmp = nindarray - 1;
- }
- if (NPY_LIKELY(nelem == 1)) {
- *dest++ = *(src + tmp);
- }
- else {
- for (k = 0; k < nelem; k++) {
- *dest++ = *(src + tmp*nelem + k);
- }
- }
- }
- src += nelem*nindarray;
- }
- break;
- }
-
- NPY_END_THREADS;
- return 0;
-}
-/**end repeat**/
-
-#define OBJECT_fasttake NULL
/*
*****************************************************************************
@@ -4446,7 +4333,7 @@ static PyArray_ArrFuncs _Py@NAME@_ArrFuncs = {
NULL,
(PyArray_FastClipFunc*)NULL,
(PyArray_FastPutmaskFunc*)@from@_fastputmask,
- (PyArray_FastTakeFunc*)@from@_fasttake,
+ (PyArray_FastTakeFunc*)NULL,
(PyArray_ArgFunc*)@from@_argmin
};
diff --git a/numpy/core/src/multiarray/item_selection.c b/numpy/core/src/multiarray/item_selection.c
index e2c3ebd00..000ff6ef9 100644
--- a/numpy/core/src/multiarray/item_selection.c
+++ b/numpy/core/src/multiarray/item_selection.c
@@ -21,11 +21,168 @@
#include "lowlevel_strided_loops.h"
#include "array_assign.h"
-#include "item_selection.h"
#include "npy_sort.h"
#include "npy_partition.h"
#include "npy_binsearch.h"
#include "alloc.h"
+#include "arraytypes.h"
+
+
+
+static NPY_GCC_OPT_3 NPY_INLINE int
+npy_fasttake_impl(
+ char *dest, char *src, const npy_intp *indices,
+ npy_intp n, npy_intp m, npy_intp max_item,
+ npy_intp nelem, npy_intp chunk,
+ NPY_CLIPMODE clipmode, npy_intp itemsize, int needs_refcounting,
+ PyArray_Descr *dtype, int axis)
+{
+ NPY_BEGIN_THREADS_DEF;
+ NPY_BEGIN_THREADS_DESCR(dtype);
+ switch (clipmode) {
+ case NPY_RAISE:
+ for (npy_intp i = 0; i < n; i++) {
+ for (npy_intp j = 0; j < m; j++) {
+ npy_intp tmp = indices[j];
+ if (check_and_adjust_index(&tmp, max_item, axis,
+ _save) < 0) {
+ return -1;
+ }
+ char *tmp_src = src + tmp * chunk;
+ if (needs_refcounting) {
+ for (npy_intp k = 0; k < nelem; k++) {
+ PyArray_Item_INCREF(tmp_src, dtype);
+ PyArray_Item_XDECREF(dest, dtype);
+ memmove(dest, tmp_src, itemsize);
+ dest += itemsize;
+ tmp_src += itemsize;
+ }
+ }
+ else {
+ memmove(dest, tmp_src, chunk);
+ dest += chunk;
+ }
+ }
+ src += chunk*max_item;
+ }
+ break;
+ case NPY_WRAP:
+ for (npy_intp i = 0; i < n; i++) {
+ for (npy_intp j = 0; j < m; j++) {
+ npy_intp tmp = indices[j];
+ if (tmp < 0) {
+ while (tmp < 0) {
+ tmp += max_item;
+ }
+ }
+ else if (tmp >= max_item) {
+ while (tmp >= max_item) {
+ tmp -= max_item;
+ }
+ }
+ char *tmp_src = src + tmp * chunk;
+ if (needs_refcounting) {
+ for (npy_intp k = 0; k < nelem; k++) {
+ PyArray_Item_INCREF(tmp_src, dtype);
+ PyArray_Item_XDECREF(dest, dtype);
+ memmove(dest, tmp_src, itemsize);
+ dest += itemsize;
+ tmp_src += itemsize;
+ }
+ }
+ else {
+ memmove(dest, tmp_src, chunk);
+ dest += chunk;
+ }
+ }
+ src += chunk*max_item;
+ }
+ break;
+ case NPY_CLIP:
+ for (npy_intp i = 0; i < n; i++) {
+ for (npy_intp j = 0; j < m; j++) {
+ npy_intp tmp = indices[j];
+ if (tmp < 0) {
+ tmp = 0;
+ }
+ else if (tmp >= max_item) {
+ tmp = max_item - 1;
+ }
+ char *tmp_src = src + tmp * chunk;
+ if (needs_refcounting) {
+ for (npy_intp k = 0; k < nelem; k++) {
+ PyArray_Item_INCREF(tmp_src, dtype);
+ PyArray_Item_XDECREF(dest, dtype);
+ memmove(dest, tmp_src, itemsize);
+ dest += itemsize;
+ tmp_src += itemsize;
+ }
+ }
+ else {
+ memmove(dest, tmp_src, chunk);
+ dest += chunk;
+ }
+ }
+ src += chunk*max_item;
+ }
+ break;
+ }
+
+ NPY_END_THREADS;
+ return 0;
+}
+
+
+/*
+ * Helper function instantiating npy_fasttake_impl in different branches
+ * to allow the compiler to optimize each to the specific itemsize.
+ */
+static NPY_GCC_OPT_3 int
+npy_fasttake(
+ char *dest, char *src, const npy_intp *indices,
+ npy_intp n, npy_intp m, npy_intp max_item,
+ npy_intp nelem, npy_intp chunk,
+ NPY_CLIPMODE clipmode, npy_intp itemsize, int needs_refcounting,
+ PyArray_Descr *dtype, int axis)
+{
+ if (!needs_refcounting) {
+ if (chunk == 1) {
+ return npy_fasttake_impl(
+ dest, src, indices, n, m, max_item, nelem, chunk,
+ clipmode, itemsize, needs_refcounting, dtype, axis);
+ }
+ if (chunk == 2) {
+ return npy_fasttake_impl(
+ dest, src, indices, n, m, max_item, nelem, chunk,
+ clipmode, itemsize, needs_refcounting, dtype, axis);
+ }
+ if (chunk == 4) {
+ return npy_fasttake_impl(
+ dest, src, indices, n, m, max_item, nelem, chunk,
+ clipmode, itemsize, needs_refcounting, dtype, axis);
+ }
+ if (chunk == 8) {
+ return npy_fasttake_impl(
+ dest, src, indices, n, m, max_item, nelem, chunk,
+ clipmode, itemsize, needs_refcounting, dtype, axis);
+ }
+ if (chunk == 16) {
+ return npy_fasttake_impl(
+ dest, src, indices, n, m, max_item, nelem, chunk,
+ clipmode, itemsize, needs_refcounting, dtype, axis);
+ }
+ if (chunk == 32) {
+ return npy_fasttake_impl(
+ dest, src, indices, n, m, max_item, nelem, chunk,
+ clipmode, itemsize, needs_refcounting, dtype, axis);
+ }
+ }
+
+ return npy_fasttake_impl(
+ dest, src, indices, n, m, max_item, nelem, chunk,
+ clipmode, itemsize, needs_refcounting, dtype, axis);
+}
+
/*NUMPY_API
* Take
@@ -35,12 +192,10 @@ PyArray_TakeFrom(PyArrayObject *self0, PyObject *indices0, int axis,
PyArrayObject *out, NPY_CLIPMODE clipmode)
{
PyArray_Descr *dtype;
- PyArray_FastTakeFunc *func;
PyArrayObject *obj = NULL, *self, *indices;
- npy_intp nd, i, j, n, m, k, max_item, tmp, chunk, itemsize, nelem;
+ npy_intp nd, i, n, m, max_item, chunk, itemsize, nelem;
npy_intp shape[NPY_MAXDIMS];
- char *src, *dest, *tmp_src;
- int err;
+
npy_bool needs_refcounting;
indices = NULL;
@@ -122,9 +277,10 @@ PyArray_TakeFrom(PyArrayObject *self0, PyObject *indices0, int axis,
nelem = chunk;
itemsize = PyArray_ITEMSIZE(obj);
chunk = chunk * itemsize;
- src = PyArray_DATA(self);
- dest = PyArray_DATA(obj);
+ char *src = PyArray_DATA(self);
+ char *dest = PyArray_DATA(obj);
needs_refcounting = PyDataType_REFCHK(PyArray_DESCR(self));
+ npy_intp *indices_data = (npy_intp *)PyArray_DATA(indices);
if ((max_item == 0) && (PyArray_SIZE(obj) != 0)) {
/* Index error, since that is the usual error for raise mode */
@@ -133,107 +289,10 @@ PyArray_TakeFrom(PyArrayObject *self0, PyObject *indices0, int axis,
goto fail;
}
- func = PyArray_DESCR(self)->f->fasttake;
- if (func == NULL) {
- NPY_BEGIN_THREADS_DEF;
- NPY_BEGIN_THREADS_DESCR(PyArray_DESCR(self));
- switch(clipmode) {
- case NPY_RAISE:
- for (i = 0; i < n; i++) {
- for (j = 0; j < m; j++) {
- tmp = ((npy_intp *)(PyArray_DATA(indices)))[j];
- if (check_and_adjust_index(&tmp, max_item, axis,
- _save) < 0) {
- goto fail;
- }
- tmp_src = src + tmp * chunk;
- if (needs_refcounting) {
- for (k=0; k < nelem; k++) {
- PyArray_Item_INCREF(tmp_src, PyArray_DESCR(self));
- PyArray_Item_XDECREF(dest, PyArray_DESCR(self));
- memmove(dest, tmp_src, itemsize);
- dest += itemsize;
- tmp_src += itemsize;
- }
- }
- else {
- memmove(dest, tmp_src, chunk);
- dest += chunk;
- }
- }
- src += chunk*max_item;
- }
- break;
- case NPY_WRAP:
- for (i = 0; i < n; i++) {
- for (j = 0; j < m; j++) {
- tmp = ((npy_intp *)(PyArray_DATA(indices)))[j];
- if (tmp < 0) {
- while (tmp < 0) {
- tmp += max_item;
- }
- }
- else if (tmp >= max_item) {
- while (tmp >= max_item) {
- tmp -= max_item;
- }
- }
- tmp_src = src + tmp * chunk;
- if (needs_refcounting) {
- for (k=0; k < nelem; k++) {
- PyArray_Item_INCREF(tmp_src, PyArray_DESCR(self));
- PyArray_Item_XDECREF(dest, PyArray_DESCR(self));
- memmove(dest, tmp_src, itemsize);
- dest += itemsize;
- tmp_src += itemsize;
- }
- }
- else {
- memmove(dest, tmp_src, chunk);
- dest += chunk;
- }
- }
- src += chunk*max_item;
- }
- break;
- case NPY_CLIP:
- for (i = 0; i < n; i++) {
- for (j = 0; j < m; j++) {
- tmp = ((npy_intp *)(PyArray_DATA(indices)))[j];
- if (tmp < 0) {
- tmp = 0;
- }
- else if (tmp >= max_item) {
- tmp = max_item - 1;
- }
- tmp_src = src + tmp * chunk;
- if (needs_refcounting) {
- for (k=0; k < nelem; k++) {
- PyArray_Item_INCREF(tmp_src, PyArray_DESCR(self));
- PyArray_Item_XDECREF(dest, PyArray_DESCR(self));
- memmove(dest, tmp_src, itemsize);
- dest += itemsize;
- tmp_src += itemsize;
- }
- }
- else {
- memmove(dest, tmp_src, chunk);
- dest += chunk;
- }
- }
- src += chunk*max_item;
- }
- break;
- }
- NPY_END_THREADS;
- }
- else {
- /* no gil release, need it for error reporting */
- err = func(dest, src, (npy_intp *)(PyArray_DATA(indices)),
- max_item, n, m, nelem, clipmode);
- if (err) {
- goto fail;
- }
+ if (npy_fasttake(
+ dest, src, indices_data, n, m, max_item, nelem, chunk,
+ clipmode, itemsize, needs_refcounting, dtype, axis) < 0) {
+ goto fail;
}
Py_XDECREF(indices);
diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py
index bf1fcc76e..5a1135914 100644
--- a/numpy/core/tests/test_multiarray.py
+++ b/numpy/core/tests/test_multiarray.py
@@ -4484,11 +4484,10 @@ class TestCompress:
class TestPutmask:
def tst_basic(self, x, T, mask, val):
np.putmask(x, mask, val)
- assert_equal(x[mask], T(val))
- assert_equal(x.dtype, T)
+ assert_equal(x[mask], np.array(val, T))
def test_ip_types(self):
- unchecked_types = [bytes, unicode, np.void, object]
+ unchecked_types = [bytes, unicode, np.void]
x = np.random.random(1000)*100
mask = x < 40
@@ -4499,6 +4498,10 @@ class TestPutmask:
if T not in unchecked_types:
self.tst_basic(x.copy().astype(T), T, mask, val)
+ # Also test string of a length which uses an untypical length
+ dt = np.dtype("S3")
+ self.tst_basic(x.astype(dt), dt.type, mask, dt.type(val)[:3])
+
def test_mask_size(self):
assert_raises(ValueError, np.putmask, np.array([1, 2, 3]), [True], 5)
@@ -4538,7 +4541,7 @@ class TestTake:
assert_array_equal(x.take(ind, axis=0), x)
def test_ip_types(self):
- unchecked_types = [bytes, unicode, np.void, object]
+ unchecked_types = [bytes, unicode, np.void]
x = np.random.random(24)*100
x.shape = 2, 3, 4
@@ -4547,6 +4550,9 @@ class TestTake:
if T not in unchecked_types:
self.tst_basic(x.copy().astype(T))
+ # Also test string of a length which uses an untypical length
+ self.tst_basic(x.astype("S3"))
+
def test_raise(self):
x = np.random.random(24)*100
x.shape = 2, 3, 4
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