unique_values

Returns the unique elements of an input array x.

Parameters:

Name	Type	Description	Default
x	COO	Input COO array. It will be flattened if it is not already 1-D.	required

Returns:

Name	Type	Description
out	ndarray	The unique elements of an input array.

Raises:

Type	Description
ValueError	If the input array is in a different format than COO.

Examples:

>>> import sparse
>>> x = sparse.COO.from_numpy([1, 0, 2, 1, 2, -3])
>>> sparse.unique_values(x)
array([-3,  0,  1,  2])

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

def unique_values(x, /):
    """
    Returns the unique elements of an input array `x`.

    Parameters
    ----------
    x : COO
        Input COO array. It will be flattened if it is not already 1-D.

    Returns
    -------
    out : ndarray
        The unique elements of an input array.

    Raises
    ------
    ValueError
        If the input array is in a different format than COO.

    Examples
    --------
    >>> import sparse
    >>> x = sparse.COO.from_numpy([1, 0, 2, 1, 2, -3])
    >>> sparse.unique_values(x)
    array([-3,  0,  1,  2])
    """

    x = _validate_coo_input(x)

    x = x.flatten()
    values = np.unique(x.data, equal_nan=False)
    fill_count = x.size - x.nnz
    if fill_count > 0:
        if np.isnan(x.fill_value):
            # Per the Array API spec, NaNs compare as False, so each NaN is distinct.
            values = np.concatenate([values, np.full(fill_count, x.fill_value)])
        else:
            values = np.sort(np.concatenate([[x.fill_value], values]))
    return values