# melody_dict_LOADED = {} # melody_dict_LOADED = pickle.load(open("MelodyDict_1606493916.28312.pkl", "rb")) melody_dict_LOADED = {} melody_dict_LOADED = pickle.load(open("melodies.pkl", "rb")) # print(melody_dict_LOADED) # print("++++++++++") # print("**********") # phrase_dict_LOADED = {} # phrase_dict_LOADED = pickle.load(open("PhraseDict_1606493916.2988284.pkl", "rb")) phrase_dict_LOADED = {} phrase_dict_LOADED = pickle.load(open("phrases.pkl", "rb")) # print(phrase_dict_LOADED) # ev_results = prepare_evaluation(full_results, phrase_dict) # print(pattern_precision_recall(ev_results, melody_dict, phrase_dict, "ed", 'ann1')) # full_results = distance_measures(melody_dict_LOADED, phrase_dict_LOADED, music_representation='pitch', return_positions=True, scaling=None) full_results = matches_in_corpus(melody_dict_LOADED, phrase_dict_LOADED, measure=SIAM) ts = time.time() pickle.dump( full_results, open('./O2_SIAM_DistanceMeasures_LOADED_{0}.pkl'.format(str(ts)), "wb"))
# melody_dict_LOADED = {} # melody_dict_LOADED = pickle.load(open("MelodyDict_1606493916.28312.pkl", "rb")) melody_dict_LOADED = {} melody_dict_LOADED = pickle.load(open("melodies.pkl", "rb")) # print(melody_dict_LOADED) # print("++++++++++") # print("**********") # phrase_dict_LOADED = {} # phrase_dict_LOADED = pickle.load(open("PhraseDict_1606493916.2988284.pkl", "rb")) phrase_dict_LOADED = {} phrase_dict_LOADED = pickle.load(open("phrases.pkl", "rb")) # print(phrase_dict_LOADED) # ev_results = prepare_evaluation(full_results, phrase_dict) # print(pattern_precision_recall(ev_results, melody_dict, phrase_dict, "ed", 'ann1')) # full_results = distance_measures(melody_dict_LOADED, phrase_dict_LOADED, music_representation='pitch', return_positions=True, scaling=None) full_results = matches_in_corpus(melody_dict_LOADED, phrase_dict_LOADED, measure=local_aligner_mod_tempo) ts = time.time() pickle.dump( full_results, open('./O2_LAMODTEMPO_DistanceMeasures_LOADED_{0}.pkl'.format(str(ts)), "wb"))
meta_dict_LOADED = {} with open('./MetaDict_1606493901.686324.json') as json_file: meta_dict_LOADED = json.load(json_file) # melody_dict_LOADED = {} # melody_dict_LOADED = pickle.load(open("MelodyDict_1606493916.28312.pkl", "rb")) melody_dict_LOADED = {} melody_dict_LOADED = pickle.load(open("melodies.pkl", "rb")) # print(melody_dict_LOADED) # print("++++++++++") # print("**********") # phrase_dict_LOADED = {} # phrase_dict_LOADED = pickle.load(open("PhraseDict_1606493916.2988284.pkl", "rb")) phrase_dict_LOADED = {} phrase_dict_LOADED = pickle.load(open("phrases.pkl", "rb")) # print(phrase_dict_LOADED) # ev_results = prepare_evaluation(full_results, phrase_dict) # print(pattern_precision_recall(ev_results, melody_dict, phrase_dict, "ed", 'ann1')) # full_results = distance_measures(melody_dict_LOADED, phrase_dict_LOADED, music_representation='pitch', return_positions=True, scaling=None) full_results = matches_in_corpus(melody_dict_LOADED, phrase_dict_LOADED, measure=distance_measures) ts = time.time() pickle.dump(full_results, open('./O2_DMS_DistanceMeasures_LOADED_{0}.pkl'.format(str(ts)), "wb"))