def test_coin_sample_post(self):
"""Test sampling from posterior distribution"""
outdir = 'test/tmp/test_hmm/test_coin_sample_post/'
make_clean_dir(outdir)
model = make_coin_model()
# sample states and data
ndata = 100
states = list(islice(hmm.sample_hmm_states(model), ndata))
data = list(hmm.sample_hmm_data(model, states))
model.prob_emission = (
lambda pos, state: model.prob_emission_data(state, data[pos]))
p = Gnuplot()
p.enableOutput(False)
p.plot(states, style="lines")
probs = hmm.get_posterior_probs(model, len(data))
states2 = [exp(probs[i][1]) for i in xrange(len(data))]
p.plot(util.vadds(states2, 1.5), style="lines", miny=-1, maxy=12)
for i in range(2, 10):
states2 = hmm.sample_posterior(model, ndata)
self.assertTrue(stats.corr(states, states2) > .5)
p.plot(util.vadds(states2, 1.5 * i),
style="lines",
miny=-1,
maxy=12)
p.enableOutput(True)
p.save(outdir + 'plot.png')
def test_coin_sample_post(self):
"""Test sampling from posterior distribution"""
outdir = 'test/tmp/test_hmm/test_coin_sample_post/'
make_clean_dir(outdir)
model = make_coin_model()
# sample states and data
ndata = 100
states = list(islice(hmm.sample_hmm_states(model), ndata))
data = list(hmm.sample_hmm_data(model, states))
model.prob_emission = (lambda pos, state:
model.prob_emission_data(state, data[pos]))
p = Gnuplot()
p.enableOutput(False)
p.plot(states, style="lines")
probs = hmm.get_posterior_probs(model, len(data))
states2 = [exp(probs[i][1]) for i in xrange(len(data))]
p.plot(util.vadds(states2, 1.5), style="lines", miny=-1, maxy=12)
for i in range(2, 10):
states2 = hmm.sample_posterior(model, ndata)
self.assertTrue(stats.corr(states, states2) > .5)
p.plot(util.vadds(states2, 1.5*i), style="lines", miny=-1, maxy=12)
p.enableOutput(True)
p.save(outdir + 'plot.png')
def test_coin(self):
"""Test that viterbi and posterior coding work well."""
outdir = 'test/tmp/test_hmm/test_coin/'
make_clean_dir(outdir)
model = make_coin_model()
# sample states
ndata = 100
states = list(islice(hmm.sample_hmm_states(model), ndata))
p = Gnuplot()
p.enableOutput(False)
p.plot(states, style="lines")
# sample data
data = list(hmm.sample_hmm_data(model, states))
# viterbi
model.prob_emission = (
lambda pos, state: model.prob_emission_data(state, data[pos]))
states2 = hmm.viterbi(model, len(data))
# posterior
probs = hmm.get_posterior_probs(model, len(data))
states3 = [exp(probs[i][1]) for i in xrange(len(data))]
# assert that inferences correlates with true state
self.assertTrue(stats.corr(states, states2) > .5)
self.assertTrue(stats.corr(states, states3) > .5)
# plot inference
p.plot(util.vadds(states2, 1.5), style="lines", miny=-1, maxy=4)
p.plot(util.vadds(states3, 2.5), style="lines", miny=-1, maxy=4)
p.enableOutput(True)
p.save(outdir + 'plot.png')
def test_coin(self):
"""Test that viterbi and posterior coding work well."""
outdir = 'test/tmp/test_hmm/test_coin/'
make_clean_dir(outdir)
model = make_coin_model()
# sample states
ndata = 100
states = list(islice(hmm.sample_hmm_states(model), ndata))
p = Gnuplot()
p.enableOutput(False)
p.plot(states, style="lines")
# sample data
data = list(hmm.sample_hmm_data(model, states))
# viterbi
model.prob_emission = (lambda pos, state:
model.prob_emission_data(state, data[pos]))
states2 = hmm.viterbi(model, len(data))
# posterior
probs = hmm.get_posterior_probs(model, len(data))
states3 = [exp(probs[i][1]) for i in xrange(len(data))]
# assert that inferences correlates with true state
self.assertTrue(stats.corr(states, states2) > .5)
self.assertTrue(stats.corr(states, states3) > .5)
# plot inference
p.plot(util.vadds(states2, 1.5), style="lines", miny=-1, maxy=4)
p.plot(util.vadds(states3, 2.5), style="lines", miny=-1, maxy=4)
p.enableOutput(True)
p.save(outdir + 'plot.png')
