def next(self):
#if self.nsteps == self.length: raise StopIteration()
nexts= {}
intersections= {}
nexts_distr= self._get_state_distr(self.actual_state)
for state, prob in nexts_distr.iteritems():
# si las notas que vengo tocando interseccion con las que debo tocar no es vacio
intersections[state]= self.now_pitches.intersection(self.must_dict[self.length-self.nsteps][state])
if len(intersections[state]) > 0:
nexts[state]= prob
if len(nexts) == 0:
import ipdb;ipdb.set_trace()
raise Exception('Impossible phrase: actual_state= %(actual_state)s, start_pitch: %(n0)s, %(n1)s end_pitch: %(nfs)s, length:%(length)s' % self.__dict__)
s= sum(nexts.itervalues())
for state, prob in nexts.iteritems():
nexts[state]= prob/s
next= RandomPicker(values=nexts).get_value()
self.actual_state= next
now_pitches= set()
for p in intersections[next]:
now_pitches.update(next.related_notes(p[0], p[1], self.available_notes, reverse=False))
self.now_pitches= now_pitches
self.history.append((self.now_pitches, self.actual_state))
self.nsteps+=1
return next
def next(self):
#if self.nsteps == self.length: raise StopIteration()
nexts= {}
intersections= {}
nexts_distr= self._get_state_distr(self.actual_state)
#for state, prob in self.hmm.nexts(self.actual_state).iteritems():
for state, prob in nexts_distr.iteritems():
# si las notas que vengo tocando interseccion con las que debo tocar hay
intersections[state]= self.now_pitches.intersection(self.must_dict[self.length-self.nsteps][state])
if len(intersections[state]) > 0:
nexts[state]= prob
if len(nexts) == 0:
raise ImpossiblePhraseException('Impossible phrase: start_pitch: %(n0)s, end_pitch: %(nf)s, length:%(length)s' % self.__dict__)
s= sum(nexts.itervalues())
for state, prob in nexts.iteritems():
nexts[state]= prob/s
next= RandomPicker(values=nexts, random=self.random).get_value()
self.actual_state= next
now_pitches= set()
for p in intersections[next]:
now_pitches.update(next.related_notes(p, reverse=False))
self.now_pitches= now_pitches
self.history.append((self.now_pitches, self.actual_state))
self.nsteps+=1
return next
def next(self, available_states):
distr= {}
state_counters= self.states_counters[self.actual_state]
n= sum(state_counters.itervalues())
alpha= self.alpha
# solo esta parte cambia, donde uso available_states
nexts= self.hmm.nexts(self.actual_state)
nexts= dict(((k, v) for (k,v) in nexts.iteritems() if k in available_states))
s= sum(nexts.itervalues())
for k, v in nexts.iteritems():
nexts[k]= v/s
for state, prob in nexts.iteritems():
distr[state]= alpha/(alpha+n)*prob + n/(alpha+n)*state_counters[state]
rnd_picker= RandomPicker("",distr)
self.actual_state= rnd_picker.get_value()
state_counters[self.actual_state]+=1
res= {}
for random_variable in self.hmm.observators(self.actual_state):
res[random_variable]= random_variable.get_value()
return res
def next(self, input, result, prev_notes):
available_notes= self.next_candidates(input.notes_distr, input.min_pitch, input.max_pitch)
if len(available_notes) == 0:
result.pitch= -1
return
actual_note= RandomPicker(values=available_notes, random=self.random).get_value()
self.ec.last_note= actual_note
self.ec.last_pitch= actual_note.get_canonical_note()
result.pitch= actual_note.pitch
