def fit(trace_fpath, num_topics, alpha_zh, beta_zs, kernel, \
        residency_priors, num_iter, burn_in, from_=0, to=np.inf):
    Dts, Trace, previous_stamps, Count_zh, Count_sz, \
            count_h, count_z, prob_topics_aux, Theta_zh, Psi_sz, \
            hyper2id, source2id = \
            dataio.initialize_trace(trace_fpath, num_topics, num_iter, \
            from_, to)
    
    em(Dts, Trace, previous_stamps, Count_zh, \
            Count_sz, count_h, count_z, alpha_zh, beta_zs, \
            prob_topics_aux, Theta_zh, Psi_sz, num_iter, \
            burn_in, kernel)
    
    rv = prepare_results(trace_fpath, num_topics, alpha_zh, beta_zs, \
            kernel, residency_priors, num_iter, burn_in, Dts, Trace, \
            Count_zh, Count_sz, count_h, \
            count_z, prob_topics_aux, Theta_zh, Psi_sz, hyper2id, \
            source2id, from_, to)
    rv['algorithm'] = np.asarray(['serial gibbs + em'])
    return rv
Opens user information dialog.
dataset/ETHPy150Open flaviovdf/tribeflow/tribeflow/learn.py/fit--crossover with--dataset/ETHPy150Open Skype4Py/Skype4Py/Skype4Py/client.py/Client.OpenUserInfoDialog