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Commitc6e1fd0

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API: Add .mT attribute for arrays (#23762)
This adds the `.mT` attribute to arrays and specific implementation for masked arrays.
1 parent9cba469 commitc6e1fd0

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Matrix transpose support for ndarrays
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-------------------------------------
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NumPy now offers support for calculating the matrix transpose of an array. The
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matrix transpose is equivalent to swapping the last two axes of an array.
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`np.ndarray` and `np.ma.MaskedArray` now exposes a `.mT` attribute.

‎numpy/__init__.pyi‎

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@@ -992,6 +992,8 @@ class _ArrayOrScalarCommon:
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@property
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defT(self:_ArraySelf)->_ArraySelf: ...
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@property
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defmT(self:_ArraySelf)->_ArraySelf: ...
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@property
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defdata(self)->memoryview: ...
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@property
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defflags(self)->flagsobj: ...

‎numpy/core/_add_newdocs.py‎

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@@ -2877,6 +2877,45 @@
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"""))
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add_newdoc('numpy.core.multiarray','ndarray', ('mT',
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"""
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View of the matrix transposed array.
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The matrix transpose is the transpose of the last two dimensions, even
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if the array is of higher dimension.
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.. versionadded:: 2.0
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Raises
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------
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ValueError
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If the array is of dimension less than 2.
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Examples
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--------
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>>> a = np.array([[1, 2], [3, 4]])
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>>> a
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array([[1, 2],
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[3, 4]])
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>>> a.mT
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array([[1, 3],
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[2, 4]])
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>>> a = np.arange(8).reshape((2, 2, 2))
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>>> a
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array([[[0, 1],
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[2, 3]],
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[[4, 5],
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[6, 7]]])
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>>> a.mT
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array([[[0, 2],
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[1, 3]],
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[[4, 6],
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[5, 7]]])
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"""))
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##############################################################################
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#
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# ndarray methods

‎numpy/core/src/multiarray/getset.c‎

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@@ -22,6 +22,7 @@
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#include"mem_overlap.h"
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#include"alloc.h"
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#include"npy_buffer.h"
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#include"shape.h"
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/******************* array attribute get and set routines ******************/
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@@ -931,6 +932,12 @@ array_transpose_get(PyArrayObject *self, void *NPY_UNUSED(ignored))
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returnPyArray_Transpose(self,NULL);
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}
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staticPyObject*
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array_matrix_transpose_get(PyArrayObject*self,void*NPY_UNUSED(ignored))
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{
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returnPyArray_MatrixTranspose(self);
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}
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NPY_NO_EXPORTPyGetSetDefarray_getsetlist[]= {
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{"ndim",
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(getter)array_ndim_get,
@@ -992,6 +999,10 @@ NPY_NO_EXPORT PyGetSetDef array_getsetlist[] = {
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(getter)array_transpose_get,
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NULL,
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NULL,NULL},
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{"mT",
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(getter)array_matrix_transpose_get,
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NULL,
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NULL,NULL},
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{"__array_interface__",
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(getter)array_interface_get,
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NULL,

‎numpy/core/src/multiarray/shape.c‎

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@@ -731,6 +731,22 @@ PyArray_Transpose(PyArrayObject *ap, PyArray_Dims *permute)
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return (PyObject*)ret;
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}
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/*
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* Return matrix transpose (swap last two dimensions).
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*/
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NPY_NO_EXPORTPyObject*
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PyArray_MatrixTranspose(PyArrayObject*ap)
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{
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intndim=PyArray_NDIM(ap);
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if (ndim<2) {
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PyErr_SetString(PyExc_ValueError,
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"matrix transpose with ndim < 2 is undefined");
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returnNULL;
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}
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returnPyArray_SwapAxes(ap,ndim-2,ndim-1);
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}
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/*
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* Sorts items so stride is descending, because C-order
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* is the default in the face of ambiguity.

‎numpy/core/src/multiarray/shape.h‎

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@@ -21,4 +21,10 @@ PyArray_CreateMultiSortedStridePerm(int narrays, PyArrayObject **arrays,
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NPY_NO_EXPORTPyObject*
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PyArray_SqueezeSelected(PyArrayObject*self,npy_bool*axis_flags);
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/*
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* Return matrix transpose (swap last two dimensions).
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*/
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NPY_NO_EXPORTPyObject*
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PyArray_MatrixTranspose(PyArrayObject*ap);
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#endif/* NUMPY_CORE_SRC_MULTIARRAY_SHAPE_H_ */
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importpytest
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importnumpyasnp
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fromnumpy.testingimportassert_array_equal
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deftest_matrix_transpose_raises_error_for_1d():
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msg="matrix transpose with ndim < 2 is undefined"
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arr=np.arange(48)
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withpytest.raises(ValueError,match=msg):
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arr.mT
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deftest_matrix_transpose_equals_transpose_2d():
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arr=np.arange(48).reshape((6,8))
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assert_array_equal(arr.T,arr.mT)
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ARRAY_SHAPES_TO_TEST= (
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(5,2),
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(5,2,3),
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(5,2,3,4),
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)
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@pytest.mark.parametrize("shape",ARRAY_SHAPES_TO_TEST)
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deftest_matrix_transpose_equals_swapaxes(shape):
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num_of_axes=len(shape)
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vec=np.arange(shape[-1])
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arr=np.broadcast_to(vec,shape)
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tgt=np.swapaxes(arr,num_of_axes-2,num_of_axes-1)
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mT=arr.mT
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assert_array_equal(tgt,mT)

‎numpy/ma/core.py‎

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Original file line numberDiff line numberDiff line change
@@ -6092,6 +6092,41 @@ def take(self, indices, axis=None, out=None, mode='raise'):
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T=property(fget=lambdaself:self.transpose())
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transpose=_arraymethod('transpose')
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@property
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defmT(self):
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"""
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Return the matrix-transpose of the masked array.
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The matrix transpose is the transpose of the last two dimensions, even
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if the array is of higher dimension.
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.. versionadded:: 2.0
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Returns
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-------
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result: MaskedArray
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The masked array with the last two dimensions transposed
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Raises
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------
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ValueError
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If the array is of dimension less than 2.
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See Also
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--------
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ndarray.mT:
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Equivalent method for arrays
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"""
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ifself.ndim<2:
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raiseValueError("matrix transpose with ndim < 2 is undefined")
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ifself._maskisnomask:
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returnmasked_array(data=self._data.mT)
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else:
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returnmasked_array(data=self.data.mT,mask=self.mask.mT)
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deftolist(self,fill_value=None):
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"""
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Return the data portion of the masked array as a hierarchical Python list.

‎numpy/ma/core.pyi‎

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@@ -293,6 +293,8 @@ class MaskedArray(ndarray[_ShapeType, _DType_co]):
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swapaxes:Any
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T:Any
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transpose:Any
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@property# type: ignore[misc]
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defmT(self): ...
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deftolist(self,fill_value=...): ...
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deftobytes(self,fill_value=...,order=...): ...
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deftofile(self,fid,sep=...,format=...): ...

‎numpy/ma/tests/test_arrayobject.py‎

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importpytest
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importnumpyasnp
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fromnumpy.maimportmasked_array
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fromnumpy.testingimportassert_array_equal
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deftest_matrix_transpose_raises_error_for_1d():
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msg="matrix transpose with ndim < 2 is undefined"
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ma_arr=masked_array(data=[1,2,3,4,5,6],
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mask=[1,0,1,1,1,0])
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withpytest.raises(ValueError,match=msg):
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ma_arr.mT
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deftest_matrix_transpose_equals_transpose_2d():
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ma_arr=masked_array(data=[[1,2,3], [4,5,6]],
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mask=[[1,0,1], [1,1,0]])
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assert_array_equal(ma_arr.T,ma_arr.mT)
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ARRAY_SHAPES_TO_TEST= (
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(5,2),
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(5,2,3),
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(5,2,3,4),
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)
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@pytest.mark.parametrize("shape",ARRAY_SHAPES_TO_TEST)
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deftest_matrix_transpose_equals_swapaxes(shape):
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num_of_axes=len(shape)
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vec=np.arange(shape[-1])
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arr=np.broadcast_to(vec,shape)
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rng=np.random.default_rng(42)
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mask=rng.choice([0,1],size=shape)
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ma_arr=masked_array(data=arr,mask=mask)
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tgt=np.swapaxes(arr,num_of_axes-2,num_of_axes-1)
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assert_array_equal(tgt,ma_arr.mT)

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