Feb 29, 2024 · Nov 17, 2023 · Dec 8, 2023 · Dec 15, 2023 · Feb 19, 2024 · Feb 21, 2024
diff --git a/numpy/_core/_add_newdocs.py b/numpy/_core/_add_newdocs.py
        a default ``dtype`` that can represent the values (by applying promotion
        rules when necessary.)
    copy : bool, optional
        Iftrue (default), then the array data is copied.Otherwise, a copy
        will only be made if ``__array__`` returns a copy, if obj is a nested
        sequence, or if a copy is needed to satisfy any of the other
        If``True`` (default), then the array data is copied.If ``None``,
 a copywill only be made if ``__array__`` returns a copy, if obj is
 a nestedsequence, or if a copy is needed to satisfy any of the other
        requirements (``dtype``, ``order``, etc.). Note that any copy of
        the data is shallow, i.e., for arrays with object dtype, the new
        array will point to the same objects. See Examples for `ndarray.copy`.
        For ``False`` it raises a ``ValueError`` if a copy cannot be avoided.
        Default: ``True``.
    order : {'K', 'A', 'C', 'F'}, optional
        Specify the memory layout of the array. If object is not an array, the
        newly created array will be in C order (row major) unless 'F' is
        'F'   F order   F order
        ===== ========= ===================================================

        When ``copy=False`` and a copy is made for other reasons, the result is
        When ``copy=None`` and a copy is made for other reasons, the result is
        the same as if ``copy=True``, with some exceptions for 'A', see the
        Notes section. The default order is 'K'.
    subok : bool, optional

 add_newdoc('numpy._core.multiarray', 'asarray',
    """
    asarray(a, dtype=None, order=None, *, device=None, like=None)
    asarray(a, dtype=None, order=None, *, device=None,copy=None,like=None)

    Convert the input to an array.


        .. versionadded:: 2.0.0
    copy : bool, optional
        Iftrue, then the object is copied. Iffalse then the object is
        If``True``, then the object is copied. If``None`` then the object is
        copied only if needed, i.e. if ``__array__`` returns a copy, if obj
        is a nested sequence, or if a copy is needed to satisfy any of
        the other requirements (``dtype``, ``order``, etc.).
        For ``np._CopyMode.NEVER`` it raises a ``ValueError`` if a copy
 cannot be avoided.Default:false.
        For ``False`` it raises a ``ValueError`` if a copy cannot be avoided.
        Default:``None``.
    ${ARRAY_FUNCTION_LIKE}

        .. versionadded:: 1.20.0
diff --git a/numpy/_core/_asarray.py b/numpy/_core/_asarray.py
        order = 'C'
        requirements.remove('C')

    arr = array(a, dtype=dtype, order=order, copy=False, subok=subok)
    arr = array(a, dtype=dtype, order=order, copy=None, subok=subok)

    for prop in requirements:
        if not arr.flags[prop]:
diff --git a/numpy/_core/function_base.py b/numpy/_core/function_base.py
    """
    ndmax = np.broadcast(start, stop, base).ndim
    start, stop, base = (
        np.array(a, copy=False, subok=True, ndmin=ndmax)
        np.array(a, copy=None, subok=True, ndmin=ndmax)
        for a in (start, stop, base)
    )
    y = linspace(start, stop, num=num, endpoint=endpoint, axis=axis)
    base = np.expand_dims(base, axis=axis)
    if dtype is None:
        return _nx.power(base, y)
    return _nx.power(base, y).astype(dtype, copy=False)
    return _nx.power(base, y).astype(dtype, copy=None)


 def _geomspace_dispatcher(start, stop, num=None, endpoint=None, dtype=None,
    if axis != 0:
        result = _nx.moveaxis(result, 0, axis)

    return result.astype(dtype, copy=False)
    return result.astype(dtype, copy=None)


 def _needs_add_docstring(obj):
diff --git a/numpy/_core/multiarray.pyi b/numpy/_core/multiarray.pyi
    object: _ArrayType,
    dtype: None = ...,
    *,
    copy: bool | _CopyMode = ...,
    copy:None |bool | _CopyMode = ...,
    order: _OrderKACF = ...,
    subok: L[True],
    ndmin: int = ...,
    object: _ArrayLike[_SCT],
    dtype: None = ...,
    *,
    copy: bool | _CopyMode = ...,
    copy:None |bool | _CopyMode = ...,
    order: _OrderKACF = ...,
    subok: bool = ...,
    ndmin: int = ...,
    object: object,
    dtype: None = ...,
    *,
    copy: bool | _CopyMode = ...,
    copy:None |bool | _CopyMode = ...,
    order: _OrderKACF = ...,
    subok: bool = ...,
    ndmin: int = ...,
    object: Any,
    dtype: _DTypeLike[_SCT],
    *,
    copy: bool | _CopyMode = ...,
    copy:None |bool | _CopyMode = ...,
    order: _OrderKACF = ...,
    subok: bool = ...,
    ndmin: int = ...,
    object: Any,
    dtype: DTypeLike,
    *,
    copy: bool | _CopyMode = ...,
    copy:None |bool | _CopyMode = ...,
    order: _OrderKACF = ...,
    subok: bool = ...,
    ndmin: int = ...,
    order: _OrderKACF = ...,
    *,
    device: None | L["cpu"] = ...,
    copy: None | bool = ...,
    like: None | _SupportsArrayFunc = ...,
 ) -> NDArray[_SCT]: ...
 @overload
    order: _OrderKACF = ...,
    *,
    device: None | L["cpu"] = ...,
    copy: None | bool = ...,
    like: None | _SupportsArrayFunc = ...,
 ) -> NDArray[Any]: ...
 @overload
    order: _OrderKACF = ...,
    *,
    device: None | L["cpu"] = ...,
    copy: None | bool = ...,
    like: None | _SupportsArrayFunc = ...,
 ) -> NDArray[_SCT]: ...
 @overload
    order: _OrderKACF = ...,
    *,
    device: None | L["cpu"] = ...,
    copy: None | bool = ...,
    like: None | _SupportsArrayFunc = ...,
 ) -> NDArray[Any]: ...

diff --git a/numpy/_core/numeric.py b/numpy/_core/numeric.py
    if np.issubdtype(a.dtype, np.character):
        a_bool = a != a.dtype.type()
    else:
        a_bool = a.astype(np.bool, copy=False)
        a_bool = a.astype(np.bool, copy=None)

    return a_bool.sum(axis=axis, dtype=np.intp, keepdims=keepdims)

    array([2.5])

    """
    a, v = array(a, copy=False, ndmin=1), array(v, copy=False, ndmin=1)
    a, v = array(a, copy=None, ndmin=1), array(v, copy=None, ndmin=1)
    if (len(v) > len(a)):
        a, v = v, a
    if len(a) == 0:
diff --git a/numpy/_core/shape_base.py b/numpy/_core/shape_base.py
 def _atleast_nd(a, ndim):
    # Ensures `a` has at least `ndim` dimensions by prepending
    # ones to `a.shape` as necessary
    return array(a, ndmin=ndim, copy=False, subok=True)
    return array(a, ndmin=ndim, copy=None, subok=True)


 def _accumulate(values):
diff --git a/numpy/_core/src/multiarray/conversion_utils.c b/numpy/_core/src/multiarray/conversion_utils.c
 NPY_NO_EXPORT int
 PyArray_CopyConverter(PyObject *obj, NPY_COPYMODE *copymode) {
    if (obj == Py_None) {
        PyErr_SetString(PyExc_ValueError,
                        "NoneType copy mode not allowed.");
        return NPY_FAIL;
        *copymode = NPY_COPY_IF_NEEDED;
        return NPY_SUCCEED;
    }

    int int_copymode;
diff --git a/numpy/_core/src/multiarray/conversion_utils.h b/numpy/_core/src/multiarray/conversion_utils.h
 PyArray_OptionalIntpConverter(PyObject *obj, PyArray_Dims *seq);

 typedef enum {
 NPY_COPY_IF_NEEDED = 0,
 NPY_COPY_NEVER = 0,
    NPY_COPY_ALWAYS = 1,
 NPY_COPY_NEVER = 2,
 NPY_COPY_IF_NEEDED = 2,
 } NPY_COPYMODE;

 NPY_NO_EXPORT int
diff --git a/numpy/_core/src/multiarray/methods.c b/numpy/_core/src/multiarray/methods.c

    if (forcecopy == NPY_COPY_NEVER) {
        PyErr_SetString(PyExc_ValueError,
                "Unable to avoid copy while casting in never copy mode.");
                "Unable to avoid copy while casting in never copy mode. "
                "Use copy=None to copy only if necessary.");
        Py_DECREF(dtype);
        return NULL;
    }
diff --git a/numpy/_core/src/multiarray/multiarraymodule.c b/numpy/_core/src/multiarray/multiarraymodule.c
    }

    PyObject *res = _array_fromobject_generic(
            op, dt_info.descr, dt_info.dtype,NPY_FALSE, order, NPY_TRUE, 0);
            op, dt_info.descr, dt_info.dtype,NPY_COPY_IF_NEEDED, order, NPY_TRUE, 0);
    Py_XDECREF(dt_info.descr);
    Py_XDECREF(dt_info.dtype);
    return res;
    }

    PyObject *res = _array_fromobject_generic(
            op, dt_info.descr, dt_info.dtype,NPY_FALSE, NPY_CORDER, NPY_FALSE,
            op, dt_info.descr, dt_info.dtype,NPY_COPY_IF_NEEDED, NPY_CORDER, NPY_FALSE,
            1);
    Py_XDECREF(dt_info.descr);
    Py_XDECREF(dt_info.dtype);
    }

    PyObject *res = _array_fromobject_generic(
            op, dt_info.descr, dt_info.dtype,NPY_FALSE, NPY_FORTRANORDER,
            op, dt_info.descr, dt_info.dtype,NPY_COPY_IF_NEEDED, NPY_FORTRANORDER,
            NPY_FALSE, 1);
    Py_XDECREF(dt_info.descr);
    Py_XDECREF(dt_info.dtype);
diff --git a/numpy/_core/tests/test_api.py b/numpy/_core/tests/test_api.py
    assert_equal(a, b)
    assert_(not (a is b))

    # copy=False parametercan sometimes skip a copy
    # copy=False parameterskips a copy
    b = a.astype('f4', copy=False)
    assert_(a is b)

    # order parameter allows overriding of the memory layout,
    # forcing a copy if the layout is wrong
    b = a.astype('f4', order='F', copy=False)
    b = a.astype('f4', order='F', copy=None)
    assert_equal(a, b)
    assert_(not (a is b))
    assert_(b.flags.f_contiguous)

    b = a.astype('f4', order='C', copy=False)
    b = a.astype('f4', order='C', copy=None)
    assert_equal(a, b)
    assert_(a is b)
    assert_(b.flags.c_contiguous)
    assert_(a is b)

    # subok=True is default, and creates a subtype on a cast
    b = a.astype('i4', copy=False)
    b = a.astype('i4', copy=None)
    assert_equal(a, b)
    assert_equal(type(b), MyNDArray)

    # subok=False never returns a subclass
    b = a.astype('f4', subok=False, copy=False)
    b = a.astype('f4', subok=False, copy=None)
    assert_equal(a, b)
    assert_(not (a is b))
    assert_(type(b) is not MyNDArray)
    check_contig(np.empty((2, 2), order='F'), False, True)

    # Check that np.array creates correct contiguous flags:
    check_contig(np.array(a, copy=False), False, False)
    check_contig(np.array(a, copy=False, order='C'), True, False)
    check_contig(np.array(a, ndmin=4, copy=False, order='F'), False, True)
    check_contig(np.array(a, copy=None), False, False)
    check_contig(np.array(a, copy=None, order='C'), True, False)
    check_contig(np.array(a, ndmin=4, copy=None, order='F'), False, True)

    # Check slicing update of flags and :
    check_contig(a[0], True, True)
    res_false = arr.astype(np.intp, copy=False)
    # `res_false is arr` currently, but check `may_share_memory`.
    assert np.may_share_memory(arr, res_false)
    res_if_needed = arr.astype(np.intp, copy=np._CopyMode.IF_NEEDED)
    res_if_needed = arr.astype(np.intp, copy=None)
    # `res_if_needed is arr` currently, but check `may_share_memory`.
    assert np.may_share_memory(arr, res_if_needed)

    res_never = arr.astype(np.intp, copy=np._CopyMode.NEVER)
    assert np.may_share_memory(arr, res_never)

    # Simple tests for when a copy is necessary:
    res_false = arr.astype(np.float64, copy=False)
    assert_array_equal(res_false, arr)
    res_if_needed = arr.astype(np.float64,
                               copy=np._CopyMode.IF_NEEDED)
    res_if_needed = arr.astype(np.float64, copy=None)
    assert_array_equal(res_if_needed, arr)
    assert_raises(ValueError, arr.astype, np.float64,
                  copy=np._CopyMode.NEVER)
                  copy=False)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -807,12 +807,14 @@
		a default ``dtype`` that can represent the values (by applying promotion
		rules when necessary.)
		copy : bool, optional
		Iftrue (default), then the array data is copied.Otherwise, a copy
		will only be made if ``__array__`` returns a copy, if obj is a nested
		sequence, or if a copy is needed to satisfy any of the other
		If``True`` (default), then the array data is copied.If ``None``,
		a copywill only be made if ``__array__`` returns a copy, if obj is
		a nestedsequence, or if a copy is needed to satisfy any of the other
		requirements (``dtype``, ``order``, etc.). Note that any copy of
		the data is shallow, i.e., for arrays with object dtype, the new
		array will point to the same objects. See Examples for `ndarray.copy`.
		For ``False`` it raises a ``ValueError`` if a copy cannot be avoided.
		Default: ``True``.
		order : {'K', 'A', 'C', 'F'}, optional
		Specify the memory layout of the array. If object is not an array, the
		newly created array will be in C order (row major) unless 'F' is
Expand All		@@ -828,7 +830,7 @@
		'F' F order F order
		===== ========= ===================================================

		When ``copy=False`` and a copy is made for other reasons, the result is
		When ``copy=None`` and a copy is made for other reasons, the result is
		the same as if ``copy=True``, with some exceptions for 'A', see the
		Notes section. The default order is 'K'.
		subok : bool, optional
Expand DownExpand Up		@@ -915,7 +917,7 @@

		add_newdoc('numpy._core.multiarray', 'asarray',
		"""
		asarray(a, dtype=None, order=None, *, device=None, like=None)
		asarray(a, dtype=None, order=None, *, device=None,copy=None,like=None)

		Convert the input to an array.

Expand All		@@ -940,12 +942,12 @@

		.. versionadded:: 2.0.0
		copy : bool, optional
		Iftrue, then the object is copied. Iffalse then the object is
		If``True``, then the object is copied. If``None`` then the object is
		copied only if needed, i.e. if ``__array__`` returns a copy, if obj
		is a nested sequence, or if a copy is needed to satisfy any of
		the other requirements (``dtype``, ``order``, etc.).
		For ``np._CopyMode.NEVER`` it raises a ``ValueError`` if a copy
		cannot be avoided.Default:false.
		For ``False`` it raises a ``ValueError`` if a copy cannot be avoided.
		Default:``None``.
		${ARRAY_FUNCTION_LIKE}

		.. versionadded:: 1.20.0
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -123,7 +123,7 @@ def require(a, dtype=None, requirements=None, *, like=None):
		order = 'C'
		requirements.remove('C')

		arr = array(a, dtype=dtype, order=order, copy=False, subok=subok)
		arr = array(a, dtype=dtype, order=order, copy=None, subok=subok)

		for prop in requirements:
		if not arr.flags[prop]:
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -300,14 +300,14 @@ def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None,
		"""
		ndmax = np.broadcast(start, stop, base).ndim
		start, stop, base = (
		np.array(a, copy=False, subok=True, ndmin=ndmax)
		np.array(a, copy=None, subok=True, ndmin=ndmax)
		for a in (start, stop, base)
		)
		y = linspace(start, stop, num=num, endpoint=endpoint, axis=axis)
		base = np.expand_dims(base, axis=axis)
		if dtype is None:
		return _nx.power(base, y)
		return _nx.power(base, y).astype(dtype, copy=False)
		return _nx.power(base, y).astype(dtype, copy=None)


		def _geomspace_dispatcher(start, stop, num=None, endpoint=None, dtype=None,
Expand DownExpand Up		@@ -461,7 +461,7 @@ def geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0):
		if axis != 0:
		result = _nx.moveaxis(result, 0, axis)

		return result.astype(dtype, copy=False)
		return result.astype(dtype, copy=None)


		def _needs_add_docstring(obj):
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -181,7 +181,7 @@ def array(
		object: _ArrayType,
		dtype: None = ...,
		*,
		copy: bool \| _CopyMode = ...,
		copy:None \|bool \| _CopyMode = ...,
		order: _OrderKACF = ...,
		subok: L[True],
		ndmin: int = ...,
Expand All		@@ -192,7 +192,7 @@ def array(
		object: _ArrayLike[_SCT],
		dtype: None = ...,
		*,
		copy: bool \| _CopyMode = ...,
		copy:None \|bool \| _CopyMode = ...,
		order: _OrderKACF = ...,
		subok: bool = ...,
		ndmin: int = ...,
Expand All		@@ -203,7 +203,7 @@ def array(
		object: object,
		dtype: None = ...,
		*,
		copy: bool \| _CopyMode = ...,
		copy:None \|bool \| _CopyMode = ...,
		order: _OrderKACF = ...,
		subok: bool = ...,
		ndmin: int = ...,
Expand All		@@ -214,7 +214,7 @@ def array(
		object: Any,
		dtype: _DTypeLike[_SCT],
		*,
		copy: bool \| _CopyMode = ...,
		copy:None \|bool \| _CopyMode = ...,
		order: _OrderKACF = ...,
		subok: bool = ...,
		ndmin: int = ...,
Expand All		@@ -225,7 +225,7 @@ def array(
		object: Any,
		dtype: DTypeLike,
		*,
		copy: bool \| _CopyMode = ...,
		copy:None \|bool \| _CopyMode = ...,
		order: _OrderKACF = ...,
		subok: bool = ...,
		ndmin: int = ...,
Expand DownExpand Up		@@ -485,6 +485,7 @@ def asarray(
		order: _OrderKACF = ...,
		*,
		device: None \| L["cpu"] = ...,
		copy: None \| bool = ...,
		like: None \| _SupportsArrayFunc = ...,
		) -> NDArray[_SCT]: ...
		@overload
Expand All		@@ -494,6 +495,7 @@ def asarray(
		order: _OrderKACF = ...,
		*,
		device: None \| L["cpu"] = ...,
		copy: None \| bool = ...,
		like: None \| _SupportsArrayFunc = ...,
		) -> NDArray[Any]: ...
		@overload
Expand All		@@ -503,6 +505,7 @@ def asarray(
		order: _OrderKACF = ...,
		*,
		device: None \| L["cpu"] = ...,
		copy: None \| bool = ...,
		like: None \| _SupportsArrayFunc = ...,
		) -> NDArray[_SCT]: ...
		@overload
Expand All		@@ -512,6 +515,7 @@ def asarray(
		order: _OrderKACF = ...,
		*,
		device: None \| L["cpu"] = ...,
		copy: None \| bool = ...,
		like: None \| _SupportsArrayFunc = ...,
		) -> NDArray[Any]: ...

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -526,7 +526,7 @@ def count_nonzero(a, axis=None, *, keepdims=False):
		if np.issubdtype(a.dtype, np.character):
		a_bool = a != a.dtype.type()
		else:
		a_bool = a.astype(np.bool, copy=False)
		a_bool = a.astype(np.bool, copy=None)

		return a_bool.sum(axis=axis, dtype=np.intp, keepdims=keepdims)

Expand DownExpand Up		@@ -868,7 +868,7 @@ def convolve(a, v, mode='full'):
		array([2.5])

		"""
		a, v = array(a, copy=False, ndmin=1), array(v, copy=False, ndmin=1)
		a, v = array(a, copy=None, ndmin=1), array(v, copy=None, ndmin=1)
		if (len(v) > len(a)):
		a, v = v, a
		if len(a) == 0:
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -552,7 +552,7 @@ def _block_check_depths_match(arrays, parent_index=[]):
		def _atleast_nd(a, ndim):
		# Ensures `a` has at least `ndim` dimensions by prepending
		# ones to `a.shape` as necessary
		return array(a, ndmin=ndim, copy=False, subok=True)
		return array(a, ndmin=ndim, copy=None, subok=True)


		def _accumulate(values):
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -229,9 +229,8 @@ PyArray_OptionalIntpConverter(PyObject obj, PyArray_Dims seq)
		NPY_NO_EXPORT int
		PyArray_CopyConverter(PyObject obj, NPY_COPYMODE copymode) {
		if (obj == Py_None) {
		PyErr_SetString(PyExc_ValueError,
		"NoneType copy mode not allowed.");
		return NPY_FAIL;
		*copymode = NPY_COPY_IF_NEEDED;
		return NPY_SUCCEED;
		}

		int int_copymode;
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -13,9 +13,9 @@ NPY_NO_EXPORT int
		PyArray_OptionalIntpConverter(PyObject obj, PyArray_Dims seq);

		typedef enum {
		NPY_COPY_IF_NEEDED = 0,
		NPY_COPY_NEVER = 0,
		NPY_COPY_ALWAYS = 1,
		NPY_COPY_NEVER = 2,
		NPY_COPY_IF_NEEDED = 2,
		} NPY_COPYMODE;

		NPY_NO_EXPORT int
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -831,7 +831,8 @@ array_astype(PyArrayObject *self,

		if (forcecopy == NPY_COPY_NEVER) {
		PyErr_SetString(PyExc_ValueError,
		"Unable to avoid copy while casting in never copy mode.");
		"Unable to avoid copy while casting in never copy mode. "
		"Use copy=None to copy only if necessary.");
		Py_DECREF(dtype);
		return NULL;
		}
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -1828,7 +1828,7 @@ array_asanyarray(PyObject *NPY_UNUSED(ignored),
		}

		PyObject *res = _array_fromobject_generic(
		op, dt_info.descr, dt_info.dtype,NPY_FALSE, order, NPY_TRUE, 0);
		op, dt_info.descr, dt_info.dtype,NPY_COPY_IF_NEEDED, order, NPY_TRUE, 0);
		Py_XDECREF(dt_info.descr);
		Py_XDECREF(dt_info.dtype);
		return res;
Expand DownExpand Up		@@ -1869,7 +1869,7 @@ array_ascontiguousarray(PyObject *NPY_UNUSED(ignored),
		}

		PyObject *res = _array_fromobject_generic(
		op, dt_info.descr, dt_info.dtype,NPY_FALSE, NPY_CORDER, NPY_FALSE,
		op, dt_info.descr, dt_info.dtype,NPY_COPY_IF_NEEDED, NPY_CORDER, NPY_FALSE,
		1);
		Py_XDECREF(dt_info.descr);
		Py_XDECREF(dt_info.dtype);
Expand DownExpand Up		@@ -1911,7 +1911,7 @@ array_asfortranarray(PyObject *NPY_UNUSED(ignored),
		}

		PyObject *res = _array_fromobject_generic(
		op, dt_info.descr, dt_info.dtype,NPY_FALSE, NPY_FORTRANORDER,
		op, dt_info.descr, dt_info.dtype,NPY_COPY_IF_NEEDED, NPY_FORTRANORDER,
		NPY_FALSE, 1);
		Py_XDECREF(dt_info.descr);
		Py_XDECREF(dt_info.dtype);
Expand Down