def get_path(self):
truth_path = []
curstate = 0
costs = np.zeros((self.frame_count, self.score.state_count()))
for t in range(0, self.frame_count):
notes = self.get_notes(t*self.frame_duration)
for i in range(0, self.score.state_count()):
state_notes = self.score.states[i].notes
if notes == state_notes:
costs[t,i] = 10
else:
costs[t, i] = 1-float(len(notes.intersection(state_notes))) / len(notes.union(state_notes))
truth_path = path.factory("dtw").calculate(costs, self.score)
return truth_path
def __init__(self, lik_method, path_method):
self.likproc = likelihood.factory(lik_method)
self.pathproc = path.factory(path_method)
self.lik_method = lik_method
self.path_method = path_method
def __init__(self, lik_method, path_method):
self.likproc = likelihood.factory(lik_method)
self.pathproc = path.factory(path_method)
self.lik_method = lik_method
self.path_method = path_method
