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-rw-r--r--numpy/__init__.pyi14
-rw-r--r--numpy/compat/py3k.py4
-rw-r--r--numpy/core/fromnumeric.py42
-rw-r--r--numpy/core/fromnumeric.pyi8
-rw-r--r--numpy/core/multiarray.py2
-rw-r--r--numpy/core/src/multiarray/calculation.c103
-rw-r--r--numpy/core/src/multiarray/calculation.h6
-rw-r--r--numpy/core/src/multiarray/methods.c9
-rw-r--r--numpy/core/tests/test_multiarray.py82
-rw-r--r--numpy/lib/format.py2
-rw-r--r--numpy/lib/index_tricks.py1
-rw-r--r--numpy/ma/core.py12
-rw-r--r--numpy/ma/core.pyi4
-rw-r--r--numpy/ma/extras.py1
-rw-r--r--numpy/ma/mrecords.py1
-rw-r--r--numpy/typing/_array_like.py3
16 files changed, 248 insertions, 46 deletions
diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi
index 0eda5d2ac..dd12c9063 100644
--- a/numpy/__init__.pyi
+++ b/numpy/__init__.pyi
@@ -1289,18 +1289,24 @@ class _ArrayOrScalarCommon:
self,
axis: None = ...,
out: None = ...,
+ *,
+ keepdims: L[False] = ...,
) -> intp: ...
@overload
def argmax(
self,
axis: _ShapeLike = ...,
out: None = ...,
+ *,
+ keepdims: bool = ...,
) -> Any: ...
@overload
def argmax(
self,
axis: Optional[_ShapeLike] = ...,
out: _NdArraySubClass = ...,
+ *,
+ keepdims: bool = ...,
) -> _NdArraySubClass: ...
@overload
@@ -1308,18 +1314,24 @@ class _ArrayOrScalarCommon:
self,
axis: None = ...,
out: None = ...,
+ *,
+ keepdims: L[False] = ...,
) -> intp: ...
@overload
def argmin(
self,
axis: _ShapeLike = ...,
- out: None = ...,
+ out: None = ...,
+ *,
+ keepdims: bool = ...,
) -> Any: ...
@overload
def argmin(
self,
axis: Optional[_ShapeLike] = ...,
out: _NdArraySubClass = ...,
+ *,
+ keepdims: bool = ...,
) -> _NdArraySubClass: ...
def argsort(
diff --git a/numpy/compat/py3k.py b/numpy/compat/py3k.py
index e1e236d92..1fa17621a 100644
--- a/numpy/compat/py3k.py
+++ b/numpy/compat/py3k.py
@@ -20,10 +20,6 @@ import sys
import os
from pathlib import Path
import io
-
-import abc
-from abc import ABC as abc_ABC
-
try:
import pickle5 as pickle
except ImportError:
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index ee93da901..7164a2c28 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -1114,12 +1114,12 @@ def argsort(a, axis=-1, kind=None, order=None):
return _wrapfunc(a, 'argsort', axis=axis, kind=kind, order=order)
-def _argmax_dispatcher(a, axis=None, out=None):
+def _argmax_dispatcher(a, axis=None, out=None, *, keepdims=np._NoValue):
return (a, out)
@array_function_dispatch(_argmax_dispatcher)
-def argmax(a, axis=None, out=None):
+def argmax(a, axis=None, out=None, *, keepdims=np._NoValue):
"""
Returns the indices of the maximum values along an axis.
@@ -1133,12 +1133,18 @@ def argmax(a, axis=None, out=None):
out : array, optional
If provided, the result will be inserted into this array. It should
be of the appropriate shape and dtype.
+ keepdims : bool, optional
+ If this is set to True, the axes which are reduced are left
+ in the result as dimensions with size one. With this option,
+ the result will broadcast correctly against the array.
Returns
-------
index_array : ndarray of ints
Array of indices into the array. It has the same shape as `a.shape`
- with the dimension along `axis` removed.
+ with the dimension along `axis` removed. If `keepdims` is set to True,
+ then the size of `axis` will be 1 with the resulting array having same
+ shape as `a.shape`.
See Also
--------
@@ -1191,16 +1197,23 @@ def argmax(a, axis=None, out=None):
>>> np.take_along_axis(x, np.expand_dims(index_array, axis=-1), axis=-1).squeeze(axis=-1)
array([4, 3])
+ Setting `keepdims` to `True`,
+
+ >>> x = np.arange(24).reshape((2, 3, 4))
+ >>> res = np.argmax(x, axis=1, keepdims=True)
+ >>> res.shape
+ (2, 1, 4)
"""
- return _wrapfunc(a, 'argmax', axis=axis, out=out)
+ kwds = {'keepdims': keepdims} if keepdims is not np._NoValue else {}
+ return _wrapfunc(a, 'argmax', axis=axis, out=out, **kwds)
-def _argmin_dispatcher(a, axis=None, out=None):
+def _argmin_dispatcher(a, axis=None, out=None, *, keepdims=np._NoValue):
return (a, out)
@array_function_dispatch(_argmin_dispatcher)
-def argmin(a, axis=None, out=None):
+def argmin(a, axis=None, out=None, *, keepdims=np._NoValue):
"""
Returns the indices of the minimum values along an axis.
@@ -1214,12 +1227,18 @@ def argmin(a, axis=None, out=None):
out : array, optional
If provided, the result will be inserted into this array. It should
be of the appropriate shape and dtype.
+ keepdims : bool, optional
+ If this is set to True, the axes which are reduced are left
+ in the result as dimensions with size one. With this option,
+ the result will broadcast correctly against the array.
Returns
-------
index_array : ndarray of ints
Array of indices into the array. It has the same shape as `a.shape`
- with the dimension along `axis` removed.
+ with the dimension along `axis` removed. If `keepdims` is set to True,
+ then the size of `axis` will be 1 with the resulting array having same
+ shape as `a.shape`.
See Also
--------
@@ -1272,8 +1291,15 @@ def argmin(a, axis=None, out=None):
>>> np.take_along_axis(x, np.expand_dims(index_array, axis=-1), axis=-1).squeeze(axis=-1)
array([2, 0])
+ Setting `keepdims` to `True`,
+
+ >>> x = np.arange(24).reshape((2, 3, 4))
+ >>> res = np.argmin(x, axis=1, keepdims=True)
+ >>> res.shape
+ (2, 1, 4)
"""
- return _wrapfunc(a, 'argmin', axis=axis, out=out)
+ kwds = {'keepdims': keepdims} if keepdims is not np._NoValue else {}
+ return _wrapfunc(a, 'argmin', axis=axis, out=out, **kwds)
def _searchsorted_dispatcher(a, v, side=None, sorter=None):
diff --git a/numpy/core/fromnumeric.pyi b/numpy/core/fromnumeric.pyi
index 3342ec3ac..45057e4b1 100644
--- a/numpy/core/fromnumeric.pyi
+++ b/numpy/core/fromnumeric.pyi
@@ -130,12 +130,16 @@ def argmax(
a: ArrayLike,
axis: None = ...,
out: Optional[ndarray] = ...,
+ *,
+ keepdims: Literal[False] = ...,
) -> intp: ...
@overload
def argmax(
a: ArrayLike,
axis: Optional[int] = ...,
out: Optional[ndarray] = ...,
+ *,
+ keepdims: bool = ...,
) -> Any: ...
@overload
@@ -143,12 +147,16 @@ def argmin(
a: ArrayLike,
axis: None = ...,
out: Optional[ndarray] = ...,
+ *,
+ keepdims: Literal[False] = ...,
) -> intp: ...
@overload
def argmin(
a: ArrayLike,
axis: Optional[int] = ...,
out: Optional[ndarray] = ...,
+ *,
+ keepdims: bool = ...,
) -> Any: ...
@overload
diff --git a/numpy/core/multiarray.py b/numpy/core/multiarray.py
index 3205f4ecd..154df6f4d 100644
--- a/numpy/core/multiarray.py
+++ b/numpy/core/multiarray.py
@@ -7,8 +7,6 @@ by importing from the extension module.
"""
import functools
-import warnings
-
from . import overrides
from . import _multiarray_umath
from ._multiarray_umath import * # noqa: F403
diff --git a/numpy/core/src/multiarray/calculation.c b/numpy/core/src/multiarray/calculation.c
index de67b35b5..e89018889 100644
--- a/numpy/core/src/multiarray/calculation.c
+++ b/numpy/core/src/multiarray/calculation.c
@@ -34,11 +34,9 @@ power_of_ten(int n)
return ret;
}
-/*NUMPY_API
- * ArgMax
- */
NPY_NO_EXPORT PyObject *
-PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out)
+_PyArray_ArgMaxWithKeepdims(PyArrayObject *op,
+ int axis, PyArrayObject *out, int keepdims)
{
PyArrayObject *ap = NULL, *rp = NULL;
PyArray_ArgFunc* arg_func;
@@ -46,6 +44,14 @@ PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out)
npy_intp *rptr;
npy_intp i, n, m;
int elsize;
+ // Keep a copy because axis changes via call to PyArray_CheckAxis
+ int axis_copy = axis;
+ npy_intp _shape_buf[NPY_MAXDIMS];
+ npy_intp *out_shape;
+ // Keep the number of dimensions and shape of
+ // original array. Helps when `keepdims` is True.
+ npy_intp* original_op_shape = PyArray_DIMS(op);
+ int out_ndim = PyArray_NDIM(op);
NPY_BEGIN_THREADS_DEF;
if ((ap = (PyArrayObject *)PyArray_CheckAxis(op, &axis, 0)) == NULL) {
@@ -86,6 +92,29 @@ PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out)
if (ap == NULL) {
return NULL;
}
+
+ // Decides the shape of the output array.
+ if (!keepdims) {
+ out_ndim = PyArray_NDIM(ap) - 1;
+ out_shape = PyArray_DIMS(ap);
+ }
+ else {
+ out_shape = _shape_buf;
+ if (axis_copy == NPY_MAXDIMS) {
+ for (int i = 0; i < out_ndim; i++) {
+ out_shape[i] = 1;
+ }
+ }
+ else {
+ /*
+ * While `ap` may be transposed, we can ignore this for `out` because the
+ * transpose only reorders the size 1 `axis` (not changing memory layout).
+ */
+ memcpy(out_shape, original_op_shape, out_ndim * sizeof(npy_intp));
+ out_shape[axis] = 1;
+ }
+ }
+
arg_func = PyArray_DESCR(ap)->f->argmax;
if (arg_func == NULL) {
PyErr_SetString(PyExc_TypeError,
@@ -103,16 +132,16 @@ PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out)
if (!out) {
rp = (PyArrayObject *)PyArray_NewFromDescr(
Py_TYPE(ap), PyArray_DescrFromType(NPY_INTP),
- PyArray_NDIM(ap) - 1, PyArray_DIMS(ap), NULL, NULL,
+ out_ndim, out_shape, NULL, NULL,
0, (PyObject *)ap);
if (rp == NULL) {
goto fail;
}
}
else {
- if ((PyArray_NDIM(out) != PyArray_NDIM(ap) - 1) ||
- !PyArray_CompareLists(PyArray_DIMS(out), PyArray_DIMS(ap),
- PyArray_NDIM(out))) {
+ if ((PyArray_NDIM(out) != out_ndim) ||
+ !PyArray_CompareLists(PyArray_DIMS(out), out_shape,
+ out_ndim)) {
PyErr_SetString(PyExc_ValueError,
"output array does not match result of np.argmax.");
goto fail;
@@ -135,7 +164,7 @@ PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out)
NPY_END_THREADS_DESCR(PyArray_DESCR(ap));
Py_DECREF(ap);
- /* Trigger the UPDATEIFCOPY/WRTIEBACKIFCOPY if necessary */
+ /* Trigger the UPDATEIFCOPY/WRITEBACKIFCOPY if necessary */
if (out != NULL && out != rp) {
PyArray_ResolveWritebackIfCopy(rp);
Py_DECREF(rp);
@@ -151,10 +180,17 @@ PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out)
}
/*NUMPY_API
- * ArgMin
+ * ArgMax
*/
NPY_NO_EXPORT PyObject *
-PyArray_ArgMin(PyArrayObject *op, int axis, PyArrayObject *out)
+PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out)
+{
+ return _PyArray_ArgMaxWithKeepdims(op, axis, out, 0);
+}
+
+NPY_NO_EXPORT PyObject *
+_PyArray_ArgMinWithKeepdims(PyArrayObject *op,
+ int axis, PyArrayObject *out, int keepdims)
{
PyArrayObject *ap = NULL, *rp = NULL;
PyArray_ArgFunc* arg_func;
@@ -162,6 +198,14 @@ PyArray_ArgMin(PyArrayObject *op, int axis, PyArrayObject *out)
npy_intp *rptr;
npy_intp i, n, m;
int elsize;
+ // Keep a copy because axis changes via call to PyArray_CheckAxis
+ int axis_copy = axis;
+ npy_intp _shape_buf[NPY_MAXDIMS];
+ npy_intp *out_shape;
+ // Keep the number of dimensions and shape of
+ // original array. Helps when `keepdims` is True.
+ npy_intp* original_op_shape = PyArray_DIMS(op);
+ int out_ndim = PyArray_NDIM(op);
NPY_BEGIN_THREADS_DEF;
if ((ap = (PyArrayObject *)PyArray_CheckAxis(op, &axis, 0)) == NULL) {
@@ -202,6 +246,27 @@ PyArray_ArgMin(PyArrayObject *op, int axis, PyArrayObject *out)
if (ap == NULL) {
return NULL;
}
+
+ // Decides the shape of the output array.
+ if (!keepdims) {
+ out_ndim = PyArray_NDIM(ap) - 1;
+ out_shape = PyArray_DIMS(ap);
+ } else {
+ out_shape = _shape_buf;
+ if (axis_copy == NPY_MAXDIMS) {
+ for (int i = 0; i < out_ndim; i++) {
+ out_shape[i] = 1;
+ }
+ } else {
+ /*
+ * While `ap` may be transposed, we can ignore this for `out` because the
+ * transpose only reorders the size 1 `axis` (not changing memory layout).
+ */
+ memcpy(out_shape, original_op_shape, out_ndim * sizeof(npy_intp));
+ out_shape[axis] = 1;
+ }
+ }
+
arg_func = PyArray_DESCR(ap)->f->argmin;
if (arg_func == NULL) {
PyErr_SetString(PyExc_TypeError,
@@ -219,16 +284,15 @@ PyArray_ArgMin(PyArrayObject *op, int axis, PyArrayObject *out)
if (!out) {
rp = (PyArrayObject *)PyArray_NewFromDescr(
Py_TYPE(ap), PyArray_DescrFromType(NPY_INTP),
- PyArray_NDIM(ap) - 1, PyArray_DIMS(ap), NULL, NULL,
+ out_ndim, out_shape, NULL, NULL,
0, (PyObject *)ap);
if (rp == NULL) {
goto fail;
}
}
else {
- if ((PyArray_NDIM(out) != PyArray_NDIM(ap) - 1) ||
- !PyArray_CompareLists(PyArray_DIMS(out), PyArray_DIMS(ap),
- PyArray_NDIM(out))) {
+ if ((PyArray_NDIM(out) != out_ndim) ||
+ !PyArray_CompareLists(PyArray_DIMS(out), out_shape, out_ndim)) {
PyErr_SetString(PyExc_ValueError,
"output array does not match result of np.argmin.");
goto fail;
@@ -267,6 +331,15 @@ PyArray_ArgMin(PyArrayObject *op, int axis, PyArrayObject *out)
}
/*NUMPY_API
+ * ArgMin
+ */
+NPY_NO_EXPORT PyObject *
+PyArray_ArgMin(PyArrayObject *op, int axis, PyArrayObject *out)
+{
+ return _PyArray_ArgMinWithKeepdims(op, axis, out, 0);
+}
+
+/*NUMPY_API
* Max
*/
NPY_NO_EXPORT PyObject *
diff --git a/numpy/core/src/multiarray/calculation.h b/numpy/core/src/multiarray/calculation.h
index 34bc31f69..49105a138 100644
--- a/numpy/core/src/multiarray/calculation.h
+++ b/numpy/core/src/multiarray/calculation.h
@@ -5,9 +5,15 @@ NPY_NO_EXPORT PyObject*
PyArray_ArgMax(PyArrayObject* self, int axis, PyArrayObject *out);
NPY_NO_EXPORT PyObject*
+_PyArray_ArgMaxWithKeepdims(PyArrayObject* self, int axis, PyArrayObject *out, int keepdims);
+
+NPY_NO_EXPORT PyObject*
PyArray_ArgMin(PyArrayObject* self, int axis, PyArrayObject *out);
NPY_NO_EXPORT PyObject*
+_PyArray_ArgMinWithKeepdims(PyArrayObject* self, int axis, PyArrayObject *out, int keepdims);
+
+NPY_NO_EXPORT PyObject*
PyArray_Max(PyArrayObject* self, int axis, PyArrayObject* out);
NPY_NO_EXPORT PyObject*
diff --git a/numpy/core/src/multiarray/methods.c b/numpy/core/src/multiarray/methods.c
index 251e527a6..dc23b3471 100644
--- a/numpy/core/src/multiarray/methods.c
+++ b/numpy/core/src/multiarray/methods.c
@@ -284,16 +284,18 @@ array_argmax(PyArrayObject *self,
{
int axis = NPY_MAXDIMS;
PyArrayObject *out = NULL;
+ npy_bool keepdims = NPY_FALSE;
NPY_PREPARE_ARGPARSER;
if (npy_parse_arguments("argmax", args, len_args, kwnames,
"|axis", &PyArray_AxisConverter, &axis,
"|out", &PyArray_OutputConverter, &out,
+ "$keepdims", &PyArray_BoolConverter, &keepdims,
NULL, NULL, NULL) < 0) {
return NULL;
}
- PyObject *ret = PyArray_ArgMax(self, axis, out);
+ PyObject *ret = _PyArray_ArgMaxWithKeepdims(self, axis, out, keepdims);
/* this matches the unpacking behavior of ufuncs */
if (out == NULL) {
@@ -310,16 +312,17 @@ array_argmin(PyArrayObject *self,
{
int axis = NPY_MAXDIMS;
PyArrayObject *out = NULL;
+ npy_bool keepdims = NPY_FALSE;
NPY_PREPARE_ARGPARSER;
-
if (npy_parse_arguments("argmin", args, len_args, kwnames,
"|axis", &PyArray_AxisConverter, &axis,
"|out", &PyArray_OutputConverter, &out,
+ "$keepdims", &PyArray_BoolConverter, &keepdims,
NULL, NULL, NULL) < 0) {
return NULL;
}
- PyObject *ret = PyArray_ArgMin(self, axis, out);
+ PyObject *ret = _PyArray_ArgMinWithKeepdims(self, axis, out, keepdims);
/* this matches the unpacking behavior of ufuncs */
if (out == NULL) {
diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py
index b36b35938..de6662b1d 100644
--- a/numpy/core/tests/test_multiarray.py
+++ b/numpy/core/tests/test_multiarray.py
@@ -4192,6 +4192,88 @@ class TestStringCompare:
assert_array_equal(g1 < g2, [g1[i] < g2[i] for i in [0, 1, 2]])
assert_array_equal(g1 > g2, [g1[i] > g2[i] for i in [0, 1, 2]])
+class TestArgmaxArgminCommon:
+
+ sizes = [(), (3,), (3, 2), (2, 3),
+ (3, 3), (2, 3, 4), (4, 3, 2),
+ (1, 2, 3, 4), (2, 3, 4, 1),
+ (3, 4, 1, 2), (4, 1, 2, 3)]
+
+ @pytest.mark.parametrize("size, axis", itertools.chain(*[[(size, axis)
+ for axis in list(range(-len(size), len(size))) + [None]]
+ for size in sizes]))
+ @pytest.mark.parametrize('method', [np.argmax, np.argmin])
+ def test_np_argmin_argmax_keepdims(self, size, axis, method):
+
+ arr = np.random.normal(size=size)
+
+ # contiguous arrays
+ if axis is None:
+ new_shape = [1 for _ in range(len(size))]
+ else:
+ new_shape = list(size)
+ new_shape[axis] = 1
+ new_shape = tuple(new_shape)
+
+ _res_orig = method(arr, axis=axis)
+ res_orig = _res_orig.reshape(new_shape)
+ res = method(arr, axis=axis, keepdims=True)
+ assert_equal(res, res_orig)
+ assert_(res.shape == new_shape)
+ outarray = np.empty(res.shape, dtype=res.dtype)
+ res1 = method(arr, axis=axis, out=outarray,
+ keepdims=True)
+ assert_(res1 is outarray)
+ assert_equal(res, outarray)
+
+ if len(size) > 0:
+ wrong_shape = list(new_shape)
+ if axis is not None:
+ wrong_shape[axis] = 2
+ else:
+ wrong_shape[0] = 2
+ wrong_outarray = np.empty(wrong_shape, dtype=res.dtype)
+ with pytest.raises(ValueError):
+ method(arr.T, axis=axis,
+ out=wrong_outarray, keepdims=True)
+
+ # non-contiguous arrays
+ if axis is None:
+ new_shape = [1 for _ in range(len(size))]
+ else:
+ new_shape = list(size)[::-1]
+ new_shape[axis] = 1
+ new_shape = tuple(new_shape)
+
+ _res_orig = method(arr.T, axis=axis)
+ res_orig = _res_orig.reshape(new_shape)
+ res = method(arr.T, axis=axis, keepdims=True)
+ assert_equal(res, res_orig)
+ assert_(res.shape == new_shape)
+ outarray = np.empty(new_shape[::-1], dtype=res.dtype)
+ outarray = outarray.T
+ res1 = method(arr.T, axis=axis, out=outarray,
+ keepdims=True)
+ assert_(res1 is outarray)
+ assert_equal(res, outarray)
+
+ if len(size) > 0:
+ # one dimension lesser for non-zero sized
+ # array should raise an error
+ with pytest.raises(ValueError):
+ method(arr[0], axis=axis,
+ out=outarray, keepdims=True)
+
+ if len(size) > 0:
+ wrong_shape = list(new_shape)
+ if axis is not None:
+ wrong_shape[axis] = 2
+ else:
+ wrong_shape[0] = 2
+ wrong_outarray = np.empty(wrong_shape, dtype=res.dtype)
+ with pytest.raises(ValueError):
+ method(arr.T, axis=axis,
+ out=wrong_outarray, keepdims=True)
class TestArgmax:
diff --git a/numpy/lib/format.py b/numpy/lib/format.py
index 9b8f90dbd..6ac66c22a 100644
--- a/numpy/lib/format.py
+++ b/numpy/lib/format.py
@@ -606,7 +606,7 @@ def _read_array_header(fp, version):
if EXPECTED_KEYS != d.keys():
keys = sorted(d.keys())
msg = "Header does not contain the correct keys: {!r}"
- raise ValueError(msg.format(d.keys()))
+ raise ValueError(msg.format(keys))
# Sanity-check the values.
if (not isinstance(d['shape'], tuple) or
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index 5140ffa61..8d1b6e5be 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -201,7 +201,6 @@ class nd_grid:
length = int(step)
if step != 1:
step = (key.stop-start)/float(step-1)
- stop = key.stop + step
return _nx.arange(0, length, 1, float)*step + start
else:
return _nx.arange(start, stop, step)
diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index e3c6bc611..152d17965 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -5488,7 +5488,8 @@ class MaskedArray(ndarray):
filled = self.filled(fill_value)
return filled.argsort(axis=axis, kind=kind, order=order)
- def argmin(self, axis=None, fill_value=None, out=None):
+ def argmin(self, axis=None, fill_value=None, out=None, *,
+ keepdims=np._NoValue):
"""
Return array of indices to the minimum values along the given axis.
@@ -5531,9 +5532,11 @@ class MaskedArray(ndarray):
if fill_value is None:
fill_value = minimum_fill_value(self)
d = self.filled(fill_value).view(ndarray)
- return d.argmin(axis, out=out)
+ keepdims = False if keepdims is np._NoValue else bool(keepdims)
+ return d.argmin(axis, out=out, keepdims=keepdims)
- def argmax(self, axis=None, fill_value=None, out=None):
+ def argmax(self, axis=None, fill_value=None, out=None, *,
+ keepdims=np._NoValue):
"""
Returns array of indices of the maximum values along the given axis.
Masked values are treated as if they had the value fill_value.
@@ -5568,7 +5571,8 @@ class MaskedArray(ndarray):
if fill_value is None:
fill_value = maximum_fill_value(self._data)
d = self.filled(fill_value).view(ndarray)
- return d.argmax(axis, out=out)
+ keepdims = False if keepdims is np._NoValue else bool(keepdims)
+ return d.argmax(axis, out=out, keepdims=keepdims)
def sort(self, axis=-1, kind=None, order=None,
endwith=True, fill_value=None):
diff --git a/numpy/ma/core.pyi b/numpy/ma/core.pyi
index e7e3f1f36..bc1f45a8d 100644
--- a/numpy/ma/core.pyi
+++ b/numpy/ma/core.pyi
@@ -270,8 +270,8 @@ class MaskedArray(ndarray[_ShapeType, _DType_co]):
def std(self, axis=..., dtype=..., out=..., ddof=..., keepdims=...): ...
def round(self, decimals=..., out=...): ...
def argsort(self, axis=..., kind=..., order=..., endwith=..., fill_value=...): ...
- def argmin(self, axis=..., fill_value=..., out=...): ...
- def argmax(self, axis=..., fill_value=..., out=...): ...
+ def argmin(self, axis=..., fill_value=..., out=..., *, keepdims=...): ...
+ def argmax(self, axis=..., fill_value=..., out=..., *, keepdims=...): ...
def sort(self, axis=..., kind=..., order=..., endwith=..., fill_value=...): ...
def min(self, axis=..., out=..., fill_value=..., keepdims=...): ...
# NOTE: deprecated
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py
index c139f4640..73abfc296 100644
--- a/numpy/ma/extras.py
+++ b/numpy/ma/extras.py
@@ -743,7 +743,6 @@ def _median(a, axis=None, out=None, overwrite_input=False):
return np.ma.mean(asorted[indexer], axis=axis, out=out)
if asorted.ndim == 1:
- counts = count(asorted)
idx, odd = divmod(count(asorted), 2)
mid = asorted[idx + odd - 1:idx + 1]
if np.issubdtype(asorted.dtype, np.inexact) and asorted.size > 0:
diff --git a/numpy/ma/mrecords.py b/numpy/ma/mrecords.py
index 9ea4e4e36..d8434b0d3 100644
--- a/numpy/ma/mrecords.py
+++ b/numpy/ma/mrecords.py
@@ -129,7 +129,6 @@ class MaskedRecords(MaskedArray):
msg = "Mask and data not compatible: data size is %i, " + \
"mask size is %i."
raise MAError(msg % (nd, nm))
- copy = True
if not keep_mask:
self.__setmask__(mask)
self._sharedmask = True
diff --git a/numpy/typing/_array_like.py b/numpy/typing/_array_like.py
index b41accc21..c562f3c1f 100644
--- a/numpy/typing/_array_like.py
+++ b/numpy/typing/_array_like.py
@@ -2,7 +2,6 @@ from __future__ import annotations
import sys
from typing import Any, Sequence, TYPE_CHECKING, Union, TypeVar, Generic
-
from numpy import (
ndarray,
dtype,
@@ -20,9 +19,7 @@ from numpy import (
str_,
bytes_,
)
-
from . import _HAS_TYPING_EXTENSIONS
-from ._dtype_like import DTypeLike
if sys.version_info >= (3, 8):
from typing import Protocol
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