def probability(self, S, log=False, performance=False, name=None):
if not S.hasLength():
if not S.tree() in self.allowed:
return 0.0, 1
return 1.0, 1
# If time is greater than previous, all is fine, if time is smaller that previous, it becomes increasingly less probable
# If time is smaller than next, all is fine, if time is greater than next, it becomes increasingly less probable
start = S.downbeat()
(pos, (previous, on, next)) = S.features
length = len(S.children) * (S.beats[1] - S.beats[0])
if previous - start > 0.1 * length or\
(start + length) - next > 0.1 * length:
return 0.0, 1
obs = expression.observations(S, performance=performance)
if log:
p = 0.0
for o in obs:
if self.observation_likelihood(o, S.depth) == 0:
print o, name, S.depth-o[0], self.expressionModel[(S.depth-o[0], )]
p += math.log(1.0)
else:
p += math.log(self.observation_likelihood(o, S.depth))
else:
p = 1.0
for o in obs:
#if not (S.depth-o[0], ) in self.expressionModel:
# print S.beats
# S.view()
# exit(0)
p *= self.observation_likelihood(o, S.depth)
return p, len(obs)
def probability(self, S, log=False, performance=False, name=None):
if not S.hasLength():
if self.allowed == None:
if S.depth > self.maxDepth:
return 0.0, 1
elif not S.tree() in self.allowed:
return 0.0, 1
return 1.0, 1
# If time is greater than previous, all is fine, if time is smaller that previous, it becomes increasingly less probable
# If time is smaller than next, all is fine, if time is greater than next, it becomes increasingly less probable
start = S.downbeat()
(pos, (previous, on, next)) = S.features
length = len(S.children) * (S.beats[1] - S.beats[0])
if previous - start > self.tieThreshold * length or\
(start + length) - next > self.tieThreshold * length:
return 0.0, 1
obs = expression.observations(S, performance=performance)
if len(obs) == 0:
if S.beats[0] == 0 and S.beats[1] == 0:
print S.beats
print expression.observations(S.children[1])
expression.observations(S.children[1], verbose=2)
S.view(showOnsets=True, showFeatures=True)
exit(0)
return 1.0, 1
if log:
p = 0.0
for f, exp in obs:
if self.observation_likelihood(f, exp) == 0:
# print o, name, S.depth-o[0], self.expressionModel[(S.depth-o[0], )]
p += math.log(1.0)
else:
p += math.log(self.observation_likelihood(f, exp))
else:
p = 1.0
for f, exp in obs:
#if not (S.depth-o[0], ) in self.expressionModel:
# print S.beats
# S.view()
# exit(0)
p *= self.observation_likelihood(f, exp)
return p, len(obs)
def probability(self, S):
if not S.hasLength():
if not S.tree() in self.allowed:
return 0.0, 1
return 1.0, 1
# If time is greater than previous, all is fine, if time is smaller that previous, it becomes increasingly less probable
# If time is smaller than next, all is fine, if time is greater than next, it becomes increasingly less probable
start = S.downbeat()
(pos, (previous, on, next)) = S.features
length = len(S.children) * (S.beats[1] - S.beats[0])
if previous - start > 0.1 * length or\
(start + length) - next > 0.1 * length:
return 0.0, 1
obs = expression.observations(S)
p = 1.0
for o in obs:
p *= self.observation_likelihood(o)
return p, len(obs)
