MaskedArray.transpose()

MaskedArray.transpose(*axes) [source]

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]), then a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0]).

Parameters:

Parameters:	axes : None, tuple of ints, or `n` ints None or no argument: reverses the order of the axes. tuple of ints: `i` in the `j`-th place in the tuple means `a`?s `i`-th axis becomes `a.transpose()`?s `j`-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.

axes : None, tuple of ints, or n ints

None or no argument: reverses the order of the axes.
tuple of ints: i in the j-th place in the tuple means a?s i-th axis becomes a.transpose()?s j-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.

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]])

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.ma.MaskedArray.transpose.html

doc_NumPy

2025-01-10 15:47:30

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