nanreduce

Performs an NaN skipping reduction on this array. See the documentation on sparse.COO.reduce for examples.

Parameters:

Name	Type	Description	Default
x	COO	The array to reduce.	required
method	ufunc	The method to use for performing the reduction.	required
identity	number	The identity value for this reduction. Inferred from method if not given. Note that some ufunc objects don't have this, so it may be necessary to give it.	None
axis	Union[int, Iterable[int]]	The axes along which to perform the reduction. Uses all axes by default.	None
keepdims	bool_	Whether or not to keep the dimensions of the original array.	False
**kwargs	dict	Any extra arguments to pass to the reduction operation.	{}

Returns:

Type	Description
COO	The result of the reduction operation.

Raises:

Type	Description
ValueError	If reducing an all-zero axis would produce a nonzero result.

See Also

sparse.COO.reduce : Similar method without NaN skipping functionality.

Source code in sparse/numba_backend/_coo/common.py

def nanreduce(x, method, identity=None, axis=None, keepdims=False, **kwargs):
    """
    Performs an `NaN` skipping reduction on this array. See the documentation
    on [`sparse.COO.reduce`][] for examples.

    Parameters
    ----------
    x : COO
        The array to reduce.
    method : numpy.ufunc
        The method to use for performing the reduction.
    identity : numpy.number
        The identity value for this reduction. Inferred from ``method`` if not given.
        Note that some ``ufunc`` objects don't have this, so it may be necessary to give it.
    axis : Union[int, Iterable[int]], optional
        The axes along which to perform the reduction. Uses all axes by default.
    keepdims : bool, optional
        Whether or not to keep the dimensions of the original array.
    **kwargs : dict
        Any extra arguments to pass to the reduction operation.

    Returns
    -------
    COO
        The result of the reduction operation.

    Raises
    ------
    ValueError
        If reducing an all-zero axis would produce a nonzero result.

    See Also
    --------
    [`sparse.COO.reduce`][] : Similar method without `NaN` skipping functionality.
    """
    arr = _replace_nan(x, method.identity if identity is None else identity)
    return arr.reduce(method, axis, keepdims, **kwargs)