xorbits.numpy.transpose

xorbits.numpy.transpose(a, axes=None)

Returns an array with axes transposed.

For a 1-D array, this returns an unchanged view of the original array, as a transposed vector is simply the same vector. To convert a 1-D array into a 2-D column vector, an additional dimension must be added, e.g., np.atleast2d(a).T achieves this, as does a[:, np.newaxis]. For a 2-D array, this is the standard 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, then transpose(a).shape == a.shape[::-1].

参数

• a (array_like) – Input array.

• axes (tuple or list of ints, optional) – If specified, it must be a tuple or list which contains a permutation of [0,1,…,N-1] where N is the number of axes of a. The i’th axis of the returned array will correspond to the axis numbered axes[i] of the input. If not specified, defaults to range(a.ndim)[::-1], which reverses the order of the axes.

返回

p – a with its axes permuted. A view is returned whenever possible.

返回类型

ndarray

参见

ndarray.transpose

Equivalent method.

moveaxis

Move axes of an array to new positions.

argsort

Return the indices that would sort an array.

提示

Use transpose(a, argsort(axes)) to invert the transposition of tensors when using the axes keyword argument.

实际案例

>>> a = np.array([[1, 2], [3, 4]])  
>>> a  
array([[1, 2],
       [3, 4]])
>>> np.transpose(a)  
array([[1, 3],
       [2, 4]])

>>> a = np.array([1, 2, 3, 4])  
>>> a  
array([1, 2, 3, 4])
>>> np.transpose(a)  
array([1, 2, 3, 4])

>>> a = np.ones((1, 2, 3))  
>>> np.transpose(a, (1, 0, 2)).shape  
(2, 1, 3)

>>> a = np.ones((2, 3, 4, 5))  
>>> np.transpose(a).shape  
(5, 4, 3, 2)

This docstring was copied from numpy.