Das deutsche Python-Forum

Code: Alles auswählen

liste_numpy_arrays = 
[array([[ 1, 2, 3], [4, 5, 6], [7, 8, 9]]),
 array([[ 1, 2, 3], [4, 5, 6], [7, 8, 9]]),
 array([[ 1, 2, 3], [4, 5, 6], [7, 8, 9]])]

Code: Alles auswählen

liste_numpy_arrays = 
[array([[ 1, 2, 3], [ 1, 2, 3], [ 1, 2, 3]]),
 array([[4, 5, 6], [4, 5, 6], [4, 5, 6]]),
 array([[7, 8, 9], [7, 8, 9], [7, 8, 9]])]

Code: Alles auswählen

quelle = np.array([np.array([[ 1, 2, 3], [4, 5, 6], [7, 8, 9]]),  np.array([[ 1, 2, 3], [4, 5, 6], [7, 8, 9]]),  np.array([[ 1, 2, 3], [4, 5, 6], [7, 8, 9]])])
ziel = np.array([quelle[:,0,:], quelle[:,1,:], quelle[:,2,:]])
ziel

Code: Alles auswählen

array([[[1, 2, 3],
        [1, 2, 3],
        [1, 2, 3]],

       [[4, 5, 6],
        [4, 5, 6],
        [4, 5, 6]],

       [[7, 8, 9],
        [7, 8, 9],
        [7, 8, 9]]])

Code: Alles auswählen

In [25]: list_of_points
Out[25]:
[array([[1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]]), array([[1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]]), array([[1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]])]

In [26]: ps = np.array(list_of_points)

In [27]: ps
Out[27]:
array([[[1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]],

       [[1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]],

       [[1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]]])

In [28]: ps.transpose(1, 0, 2)
Out[28]:
array([[[1, 2, 3],
        [1, 2, 3],
        [1, 2, 3]],

       [[4, 5, 6],
        [4, 5, 6],
        [4, 5, 6]],

       [[7, 8, 9],
        [7, 8, 9],
        [7, 8, 9]]])

In [32]: ps.transpose?
Docstring:
a.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])``, then
``a.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 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.

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]])
Type:      builtin_function_or_method

In [33]: