Function squeeze

numpy/_core/fromnumeric.py:1635–1701

Remove axes of length one from `a`. Parameters ---------- a : array_like Input data. axis : None 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 on

(a, axis=None)

@array_function_dispatch(_squeeze_dispatcher)
def squeeze(a, axis=None):
    """
    Remove axes of length one from `a`.

    Parameters
    ----------
    a : array_like
        Input data.
    axis : None 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
    -------
    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.

    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