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Module « numpy »

Fonction unstack - module numpy

Signature de la fonction unstack

def unstack(x, /, *, axis=0) 

Description

help(numpy.unstack)

Split an array into a sequence of arrays along the given axis.

The ``axis`` parameter specifies the dimension along which the array will
be split. For example, if ``axis=0`` (the default) it will be the first
dimension and if ``axis=-1`` it will be the last dimension.

The result is a tuple of arrays split along ``axis``.

.. versionadded:: 2.1.0

Parameters
----------
x : ndarray
    The array to be unstacked.
axis : int, optional
    Axis along which the array will be split. Default: ``0``.

Returns
-------
unstacked : tuple of ndarrays
    The unstacked arrays.

See Also
--------
stack : Join a sequence of arrays along a new axis.
concatenate : Join a sequence of arrays along an existing axis.
block : Assemble an nd-array from nested lists of blocks.
split : Split array into a list of multiple sub-arrays of equal size.

Notes
-----
``unstack`` serves as the reverse operation of :py:func:`stack`, i.e.,
``stack(unstack(x, axis=axis), axis=axis) == x``.

This function is equivalent to ``tuple(np.moveaxis(x, axis, 0))``, since
iterating on an array iterates along the first axis.

Examples
--------
>>> arr = np.arange(24).reshape((2, 3, 4))
>>> np.unstack(arr)
(array([[ 0,  1,  2,  3],
        [ 4,  5,  6,  7],
        [ 8,  9, 10, 11]]),
 array([[12, 13, 14, 15],
        [16, 17, 18, 19],
        [20, 21, 22, 23]]))
>>> np.unstack(arr, axis=1)
(array([[ 0,  1,  2,  3],
        [12, 13, 14, 15]]),
 array([[ 4,  5,  6,  7],
        [16, 17, 18, 19]]),
 array([[ 8,  9, 10, 11],
        [20, 21, 22, 23]]))
>>> arr2 = np.stack(np.unstack(arr, axis=1), axis=1)
>>> arr2.shape
(2, 3, 4)
>>> np.all(arr == arr2)
np.True_

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