full_like

Return a full array with the same shape and type as a given array.

Parameters:

Name	Type	Description	Default
a	array_like	The shape and data-type of the result will match those of a.	required
dtype	data - type	Overrides the data type of the result.	None
format	str	A format string.	None
compressed_axes	iterable	The axes to compress if returning a GCXS array.	required

Returns:

Name	Type	Description
out	SparseArray	Array of fill_value with the same shape and type as a.

Examples:

>>> x = np.ones((2, 3), dtype="i8")
>>> full_like(x, 9.0).todense()
array([[9, 9, 9],
       [9, 9, 9]])

Source code in sparse/numba_backend/_common.py

@_check_device
def full_like(a, fill_value, dtype=None, shape=None, format=None, *, device=None, **kwargs):
    """Return a full array with the same shape and type as a given array.

    Parameters
    ----------
    a : array_like
        The shape and data-type of the result will match those of `a`.
    dtype : data-type, optional
        Overrides the data type of the result.
    format : str, optional
        A format string.
    compressed_axes : iterable, optional
        The axes to compress if returning a GCXS array.

    Returns
    -------
    out : SparseArray
        Array of `fill_value` with the same shape and type as `a`.

    Examples
    --------
    >>> x = np.ones((2, 3), dtype="i8")
    >>> full_like(x, 9.0).todense()  # doctest: +NORMALIZE_WHITESPACE
    array([[9, 9, 9],
           [9, 9, 9]])
    """
    if format is None and not isinstance(a, np.ndarray):
        format = type(a).__name__.lower()
    elif format is None:
        format = "coo"

    compressed_axes = kwargs.pop("compressed_axes", None)
    if hasattr(a, "compressed_axes") and compressed_axes is None:
        compressed_axes = a.compressed_axes
    return full(
        a.shape if shape is None else shape,
        fill_value,
        dtype=(a.dtype if dtype is None else dtype),
        format=format,
        **kwargs,
    )