def run_one_simulation(mahal_timeseries, c_timeseries, global_pace_timeseries):
    initial_state, trans_matrix, emission_matrix = randomly_draw_parameters()
    
    events, predictions = detect_events_hmm(mahal_timeseries, c_timeseries,
                        global_pace_timeseries, threshold_quant=.95,
                        trans_matrix = trans_matrix,
                      emission_matrix=emission_matrix)
    
    return match_events(events)
def run_random_sims(outlier_score_file, feature_dir):
    
    mahal_timeseries, c_timeseries = readOutlierScores(outlier_score_file)
    global_pace_timeseries = readGlobalPace(feature_dir)
    
    for p in range(50):
        print ("Sim %d" % p)
        initial_state, trans_matrix, emission_matrix = randomly_draw_parameters()
    
        events, predictions = detect_events_hmm(mahal_timeseries, c_timeseries,
                        global_pace_timeseries, threshold_quant=.95,
                        trans_matrix = trans_matrix,
                      emission_matrix=emission_matrix)
        new_scores_file = 'tmp_results/coarse_events_k%d_scores.csv'%p
    
        augment_outlier_scores(outlier_score_file, new_scores_file, predictions)