Function expand_dims

numpy/lib/_shape_base_impl.py:514–600

Expand the shape of an array. Insert a new axis that will appear at the `axis` position in the expanded array shape. Parameters ---------- a : array_like Input array. axis : int or tuple of ints Position in the expanded axes where the new axis (or axes)

(a, axis)

@array_function_dispatch(_expand_dims_dispatcher)
def expand_dims(a, axis):
    """
    Expand the shape of an array.

    Insert a new axis that will appear at the `axis` position in the expanded
    array shape.

    Parameters
    ----------
    a : array_like
        Input array.
    axis : int or tuple of ints
        Position in the expanded axes where the new axis (or axes) is placed.

        .. deprecated:: 1.13.0
            Passing an axis where ``axis > a.ndim`` will be treated as
            ``axis == a.ndim``, and passing ``axis < -a.ndim - 1`` will
            be treated as ``axis == 0``. This behavior is deprecated.

    Returns
    -------
    result : ndarray
        View of `a` with the number of dimensions increased.

    See Also
    --------
    squeeze : The inverse operation, removing singleton dimensions
    reshape : Insert, remove, and combine dimensions, and resize existing ones
    atleast_1d, atleast_2d, atleast_3d

    Examples
    --------
    >>> import numpy as np
    >>> x = np.array([1, 2])
    >>> x.shape
    (2,)

    The following is equivalent to ``x[np.newaxis, :]`` or ``x[np.newaxis]``:

    >>> y = np.expand_dims(x, axis=0)
    >>> y
    array([[1, 2]])
    >>> y.shape
    (1, 2)

    The following is equivalent to ``x[:, np.newaxis]``:

    >>> y = np.expand_dims(x, axis=1)
    >>> y
    array([[1],
           [2]])
    >>> y.shape
    (2, 1)

    ``axis`` may also be a tuple:

    >>> y = np.expand_dims(x, axis=(0, 1))
    >>> y