squeeze(a, axis=None)

Parameters

a : array_like

Input data.

axis : None or int or tuple of ints, optional

versionadded

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.

Raises

ValueError

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

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

Remove axes of length one from a.

See Also

expand_dims

The inverse operation, adding entries of length one

reshape

Insert, remove, and combine dimensions, and resize existing ones

Examples

This example is valid syntax, but we were not able to check execution

>>> x = np.array([[[0], [1], [2]]])
... x.shape
(1, 3, 1)

This example is valid syntax, but we were not able to check execution

>>> np.squeeze(x).shape
(3,)

This example is valid syntax, but we were not able to check execution

>>> np.squeeze(x, axis=0).shape
(3, 1)

This example is valid syntax, but we were not able to check execution

>>> 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

This example is valid syntax, but we were not able to check execution

>>> np.squeeze(x, axis=2).shape
(1, 3)

This example is valid syntax, but we were not able to check execution

>>> x = np.array([[1234]])
... x.shape
(1, 1)

This example is valid syntax, but we were not able to check execution

>>> np.squeeze(x)
array(1234)  # 0d array

This example is valid syntax, but we were not able to check execution

>>> np.squeeze(x).shape
()

This example is valid syntax, but we were not able to check execution

>>> np.squeeze(x)[()]
1234

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.signal._ltisys.dstep numpy.matrixlib.defmatrix.matrix.squeeze dask.array.core.Array.squeeze dask.array.routines.squeeze scipy.signal._ltisys.dimpulse scipy.signal._lti_conversion.cont2discrete numpy.expand_dims

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GitHub : /numpy/core/fromnumeric.py#1478
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