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)