def save_info(self, folder, score): feature_names= all_features_values().keys() feature_names.append(None) # XXX prob_model= ProbModel(self.ec.narmour_features_prob, self.notes_distr, use_harmony=False) from plot import plot_narmour_feature for feature_name in feature_names: plot_narmour_feature(prob_model, 50, 50+12+6, feature_name, folder) #reference_pitch= max(self.notes_distr.iteritems(), key=lambda x:x[1])[0].pitch for reference_pitch in xrange(12): plot_narmour_feature(prob_model, 50, 50+12+6, None, folder, reference_note=Note(reference_pitch)) #plot_narmour_feature(prob_model, 50, 50+12+6, None, folder, reference_note=Note((reference_pitch+7)%12)) from pprint import pprint with open(os.path.join(folder, 'narmour.txt'), 'w') as f: pprint(self.ec.narmour_features_prob, f)
def save_info(self, folder, score, params): from plot import plot_narmour_feature, plot_first_note, paper_plot_narmour_feature, plot_arrival_contexts ### XXX para el paper #prob_model= ProbModel(self.ec.narmour_features_prob, self.notes_distr, use_harmony=True) #n1= n2= 83 #plot_narmour_feature(prob_model, params['min_pitch'], params['max_pitch'], folder, n1, n2) #plot_first_note(prob_model, params['min_pitch'], params['max_pitch'], folder, n1, n2) #plot_arrival_contexts(prob_model, params['min_pitch'], params['max_pitch'], 78, folder) #import ipdb;ipdb.set_trace() # XXX feature_names= all_features_values().keys() feature_names.append(None) # XXX pitches_distr= {} for n, p in self.notes_distr.iteritems(): pitches_distr[n.get_canonical_note()]= pitches_distr.get(n.get_canonical_note(), 0) + p prob_model= ProbModel(self.ec.narmour_features_prob, pitches_distr, use_harmony=False) for feature_name in feature_names: plot_narmour_feature(prob_model, 50, 50+12+6, feature_name, folder) reference_pitch= 11 #reference_pitch= max(self.notes_distr.iteritems(), key=lambda x:x[1])[0].pitch plot_narmour_feature(prob_model, params['min_pitch'], params['max_pitch'], None, folder, reference_note=Note(reference_pitch)) reference_pitch= 6 plot_narmour_feature(prob_model, params['min_pitch'], params['max_pitch'], None, folder, reference_note=Note(reference_pitch)) #plot_narmour_feature(prob_model, 50, 50+12+6, None, folder, reference_note=Note((reference_pitch+7)%12)) from pprint import pprint with open(os.path.join(folder, 'narmour.txt'), 'w') as f: pprint(self.ec.narmour_features_prob, f)