def __init__(self, *args, **kwargs):
super(SimpleContourAlgorithm, self).__init__(*args, **kwargs)
self.narmour_features_cnt= defaultdict(dict)
for feature_name, all_vals in all_features_values().iteritems():
for val in all_vals:
self.narmour_features_cnt[feature_name][val]=0.5
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)
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)
