-
matrix.transpose(*axes)
-
Returns a view of the array with axes transposed.
For a 1-D array, this has no effect. (To change between column and row vectors, first cast the 1-D array into a matrix object.) For a 2-D array, this is the usual matrix transpose. For an n-D array, if axes are given, their order indicates how the axes are permuted (see Examples). If axes are not provided and
a.shape = (i[0], i[1], ... i[n-2], i[n-1])
, thena.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])
.Parameters: axes : None, tuple of ints, or
n
ints- None or no argument: reverses the order of the axes.
- tuple of ints:
i
in thej
-th place in the tuple meansa
?si
-th axis becomesa.transpose()
?sj
-th axis. -
n
ints: same as an n-tuple of the same ints (this form is intended simply as a ?convenience? alternative to the tuple form)
Returns: out : ndarray
View of
a
, with axes suitably permuted.See also
-
ndarray.T
- Array property returning the array transposed.
Examples
>>> a = np.array([[1, 2], [3, 4]]) >>> a array([[1, 2], [3, 4]]) >>> a.transpose() array([[1, 3], [2, 4]]) >>> a.transpose((1, 0)) array([[1, 3], [2, 4]]) >>> a.transpose(1, 0) array([[1, 3], [2, 4]])
matrix.transpose()
2017-01-10 18:11:29
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