def buildSampleTransitions(self):
self.transitionsSampler = dict()
for (key, value) in self.transitions.iteritems():
self.transitionsSampler[key] = rand_generator(value)
for stateID in range(len(self.states)):
self.states[stateID].buildSampleEmission()
self.initStateSampler = rand_generator(
[(float(self.states[i].getStartProbability()), i)
for i in range(len(self.states))]
)
def buildSampleEmission(self):
duration_dict = defaultdict(float)
for (k, v) in self.durations:
duration_dict[k] += v
em = dict(self.emissions)
for (key, _) in em.iteritems():
em[key] *= duration_dict[len(key)]
self._sampleEmission = rand_generator(em)
def buildSampleEmission(self):
duration_dict = defaultdict(float)
for (k, v) in self.durations:
duration_dict[k] += v
em = dict(self.emissions)
for (key, _) in em.iteritems():
em[key] *= duration_dict[len(key)]
self._sampleEmission = rand_generator(em)
def setParams(self, p, start, fractions):
self.p = self.mathType(p)
self.samplingConst = math.log(1.0 - p)
fractions = [self.mathType(x) for x in fractions]
self.fractionSampler = rand_generator(zip(
fractions,
range(len(fractions)),
),
normalize=True)
self.start = start
self.fractions = fractions
def setParams(self, p, start, fractions):
self.p = self.mathType(p)
self.samplingConst = math.log(1.0 - p)
fractions = [self.mathType(x) for x in fractions]
self.fractionSampler = rand_generator(
zip(
fractions,
range(len(fractions)),
),
normalize=True
)
self.start = start
self.fractions = fractions
def buildSampleEmission(self):
dur = defaultdict(int)
cons = defaultdict(int)
total = 0;
for rg in [self.repeatGeneratorX, self.repeatGeneratorY]:
if rg != None:
for rep in rg.repeats:
dur[rep.end - rep.start] += 1
cons[rep.consensus] += 1
total += 1
total = float(total)
for (key, val) in dur.iteritems():
dur[key] = float(val) / total
for (key, val) in cons.iteritems():
cons[key] = float(val) / total
if self.repeatLengthDistribution != None and self.version != 'v2':
dur = self.repeatLengthDistribution
if self.consensusDistribution != None:
cons = self.consensusDistribution
self.durationSampler = rand_generator(dur)
self.consensusSampler = rand_generator(cons)
self.trackEmissionsSampler = rand_generator(self.trackEmissions)
def buildSampleEmission(self):
self._sampleEmission = rand_generator(self.emissions)
