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This is documentation for an old release of NumPy (version 1.13). Read this page in the documentation of the latest stable release (version 2.2).

numpy.squeeze

numpy.squeeze(a, axis=None)[source]

Remove single-dimensional entries from the shape of an array.

Parameters:

a : array_like

Input data.

axis : None or int or tuple of ints, optional

New in version 1.7.0.

Selects a subset of the single-dimensional entries in the shape. If an axis is selected with shape entry greater than one, an error is raised.

Returns:

squeezed : ndarray

The input array, but with all or a subset of the dimensions of length 1 removed. This is always a itself or a view into a.

Raises:

ValueError

If axis is not None, and an axis being squeezed is not of length 1

See also

expand_dims
The inverse operation, adding singleton dimensions
reshape
Insert, remove, and combine dimensions, and resize existing ones

Examples

>>> x = np.array([[[0], [1], [2]]])
>>> x.shape
(1, 3, 1)
>>> np.squeeze(x).shape
(3,)
>>> np.squeeze(x, axis=0).shape
(3, 1)
>>> np.squeeze(x, axis=1).shape
Traceback (most recent call last):
...
ValueError: cannot select an axis to squeeze out which has size not equal to one
>>> np.squeeze(x, axis=2).shape
(1, 3)