ldaseqmodel.py 文件源码

def df_obs(x, *args):

    """
    Derivative of function which optimises obs.
    """
    sslm, word_counts, totals, mean_deriv_mtx, word, deriv = args

    sslm.obs[word] = x
    sslm.mean[word], sslm.fwd_mean[word] = sslm.compute_post_mean(word, sslm.chain_variance)

    model = "DTM"
    if model == "DTM":
        deriv = sslm.compute_obs_deriv(word, word_counts, totals, mean_deriv_mtx, deriv)
    elif model == "DIM":
        deriv = sslm.compute_obs_deriv_fixed(p.word, p.word_counts, p.totals, p.sslm, p.mean_deriv_mtx, deriv)

    return np.negative(deriv)