trustsvd.py 文件源码

def _compute_extra_terms(Y, W, items_u, trustees_u):
    # Implicit information
    norm_Iu = math.sqrt(len(items_u))

    # TODO: Clean this. Hint: np.nans
    y_term = 0
    if norm_Iu > 0:
        y_sum = np.sum(Y[items_u, :], axis=0)
        y_term = y_sum / norm_Iu

    # Trust information
    w_term = 0
    norm_Tu = math.sqrt(len(trustees_u))
    if norm_Tu > 0:
        w_sum = np.sum(W[trustees_u, :], axis=0)
        w_term = w_sum / norm_Tu

    return y_term, w_term, norm_Iu, norm_Tu