dot

Perform the equivalent of numpy.dot on two arrays.

Parameters:

Name	Type	Description	Default
a	Union[SparseArray, ndarray, spmatrix]	The arrays to perform the dot operation on.	required
b	Union[SparseArray, ndarray, spmatrix]	The arrays to perform the dot operation on.	required

Returns:

Type	Description
Union[SparseArray, ndarray]	The result of the operation.

Raises:

Type	Description
ValueError	If all arguments don't have zero fill-values.

See Also

• numpy.dot : NumPy equivalent function.
• sparse.COO.dot : Equivalent function for COO objects.

Source code in sparse/numba_backend/_common.py

def dot(a, b):
    """
    Perform the equivalent of [`numpy.dot`][] on two arrays.

    Parameters
    ----------
    a, b : Union[SparseArray, np.ndarray, scipy.sparse.spmatrix]
        The arrays to perform the `dot` operation on.

    Returns
    -------
    Union[SparseArray, numpy.ndarray]
        The result of the operation.

    Raises
    ------
    ValueError
        If all arguments don't have zero fill-values.

    See Also
    --------
    - [`numpy.dot`][] : NumPy equivalent function.
    - [`sparse.COO.dot`][] : Equivalent function for COO objects.
    """
    check_zero_fill_value(a, b)
    if not hasattr(a, "ndim") or not hasattr(b, "ndim"):
        raise TypeError(f"Cannot perform dot product on types {type(a)}, {type(b)}")

    if a.ndim == 1 and b.ndim == 1:
        if isinstance(a, SparseArray):
            a = as_coo(a)
        if isinstance(b, SparseArray):
            b = as_coo(b)
        return (a * b).sum()

    a_axis = -1
    b_axis = -2

    if b.ndim == 1:
        b_axis = -1
    return tensordot(a, b, axes=(a_axis, b_axis))