stack

Stack the input arrays along the given dimension.

Parameters:

Name	Type	Description	Default
arrays	Iterable[SparseArray]	The input arrays to stack.	required
axis	int	The axis along which to stack the input arrays.	0
compressed_axes	iterable	The axes to compress if returning a GCXS array.	None

Returns:

Type	Description
SparseArray	The output stacked array.

Raises:

Type	Description
ValueError	If all elements of arrays don't have the same fill-value.

See Also

numpy.stack: NumPy equivalent function

Source code in sparse/numba_backend/_common.py

def stack(arrays, axis=0, compressed_axes=None):
    """
    Stack the input arrays along the given dimension.

    Parameters
    ----------
    arrays : Iterable[SparseArray]
        The input arrays to stack.
    axis : int, optional
        The axis along which to stack the input arrays.
    compressed_axes : iterable, optional
        The axes to compress if returning a GCXS array.

    Returns
    -------
    SparseArray
        The output stacked array.

    Raises
    ------
    ValueError
        If all elements of `arrays` don't have the same fill-value.

    See Also
    --------
    [`numpy.stack`][]: NumPy equivalent function
    """
    from ._compressed import GCXS

    if not builtins.all(isinstance(arr, GCXS) for arr in arrays):
        from ._coo import stack as coo_stack

        return coo_stack(arrays, axis)

    from ._compressed import stack as gcxs_stack

    return gcxs_stack(arrays, axis, compressed_axes)