Patch for __init__.py for clifford

clifford__init__.py

def _get_mult_function(mt: sparse.COO):
    """
    Get a function similar to `` lambda a, b: np.einsum('i,ijk,k->j', a, mt, b)``

    Returns
    -------
    func : function (array_like (n_dims,), array_like (n_dims,)) -> array_like (n_dims,)
        A function that computes the appropriate multiplication
    """
    # unpack for numba
    dims = mt.shape[1]
    k_list, l_list, m_list = mt.coords
    mult_table_vals = mt.data

    @_numba_utils.njit
    def mv_mult(value, other_value):
        # 컴파일 타임에 타입 추론이 일어나므로,
        # ret_dtype은 (value, other_value, mult_table_vals)의 dtype 조합으로 결정됨
        ret_dtype = _get_mult_function_result_type(value, other_value, mult_table_vals.dtype)
        mult_table_vals_t = mult_table_vals.astype(ret_dtype)

        output = np.zeros(dims, dtype=ret_dtype)
        for k, l, m, val in zip(k_list, l_list, m_list, mult_table_vals_t):
            output[l] += value[k] * val * other_value[m]
        return output

    return mv_mult


def _get_mult_function_runtime_sparse(mt: sparse.COO):
    """
    A variant of `_get_mult_function` that attempts to exploit runtime zeros

    The returned function avoids performing multiplications if vectors contain
    zeros.

    TODO: determine if this actually helps.
    """
    # unpack for numba
    dims = mt.shape[1]
    k_list, l_list, m_list = mt.coords
    mult_table_vals = mt.data

    @_numba_utils.njit
    def mv_mult(value, other_value):
        ret_dtype = _get_mult_function_result_type(value, other_value, mult_table_vals.dtype)
        mult_table_vals_t = mult_table_vals.astype(ret_dtype)

        output = np.zeros(dims, dtype=ret_dtype)
        for ind, k in enumerate(k_list):
            v_val = value[k]
            if v_val != 0.0:
                m = m_list[ind]
                ov_val = other_value[m]
                if ov_val != 0.0:
                    l = l_list[ind]
                    output[l] += v_val * mult_table_vals_t[ind] * ov_val
        return output

    return mv_mult