numpy.squeeze#

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

Remove axes of length one from a.

Parameters:

aarray_like: Input data.
axisNone or int or tuple of ints, optional: Selects a subset of the entries of length one in the shape. If an axis is selected with shape entry greater than one, an error is raised.

Returns:

squeezedndarray: 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. Note that if all axes are squeezed, the result is a 0d array and not a scalar.

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 entries of length one
reshape: Insert, remove, and combine dimensions, and resize existing ones

Examples

>>> import numpy as np
>>> 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)
>>> x = np.array([[1234]])
>>> x.shape
(1, 1)
>>> np.squeeze(x)
array(1234)  # 0d array
>>> np.squeeze(x).shape
()
>>> np.squeeze(x)[()]
1234