Merge remote-tracking branch 'upstream/master' into docs-skeleton

bhmm · May 17, 2015 · ba0b2f0 · ba0b2f0
2 parents 01bcfdf + 8c5713b
commit ba0b2f0
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Showing 5 changed files with 8 additions and 8 deletions.
diff --git a/bhmm/__init__.py b/bhmm/__init__.py
@@ -14,12 +14,12 @@
 
 # hmms
 from bhmm.hmm.generic_hmm import HMM
-#from bhmm.hmm.gaussian_hmm import GaussianHMM
-#from bhmm.hmm.discrete_hmm import DiscreteHMM
+from bhmm.hmm.gaussian_hmm import GaussianHMM
+from bhmm.hmm.discrete_hmm import DiscreteHMM
 
 from bhmm.hmm.generic_sampled_hmm import SampledHMM
-#from bhmm.hmm.gaussian_hmm import SampledGaussianHMM
-#from bhmm.hmm.discrete_hmm import SampledDiscreteHMM
+from bhmm.hmm.gaussian_hmm import SampledGaussianHMM
+from bhmm.hmm.discrete_hmm import SampledDiscreteHMM
 
 # estimators
 from bhmm.estimators.bayesian_sampling import BayesianHMMSampler as BHMM

diff --git a/examples/discrete_1d_2min/run.py b/examples/discrete_1d_2min/run.py
@@ -26,7 +26,7 @@
         observations.append(o[shift:][::lag])
 
     # initial HMM
-    hmm = bhmm.estimate_hmm(observations, nstates, output_model_type='discrete')
+    hmm = bhmm.estimate_hmm(observations, nstates, type='discrete')
     its[i] = lag*hmm.timescales
     likelihoods[i] = hmm.likelihood
 

diff --git a/examples/p5ab-hairpin/generate-figure.py b/examples/p5ab-hairpin/generate-figure.py
@@ -50,7 +50,7 @@ def run(nstates, nsamples):
 
     # Initialize BHMM, using MLHMM model as initial model.
     print "Initializing BHMM and running with "+str(nsamples)+" samples."
-    sampler = bhmm.BayesianHMMSampler(O, nstates, initial_model=mle)
+    sampler = bhmm.BHMM(O, nstates, initial_model=mle)
 
     # Sample models.
     bhmm_models = sampler.sample(nsamples=nsamples, save_hidden_state_trajectory=False)

diff --git a/examples/rnase-h-d10a/generate-figure.py b/examples/rnase-h-d10a/generate-figure.py
@@ -46,7 +46,7 @@ def run(nstates, nsamples):
 
     # Initialize BHMM, using MLHMM model as initial model.
     print "Initializing BHMM and running with "+str(nsamples)+" samples."
-    sampler = bhmm.BayesianHMMSampler(O, nstates, initial_model=mle)
+    sampler = bhmm.BHMM(O, nstates, initial_model=mle)
 
     # Sample models.
     bhmm_models = sampler.sample(nsamples=nsamples, save_hidden_state_trajectory=False)

diff --git a/examples/synthetic-three-state-model/generate-figure.py b/examples/synthetic-three-state-model/generate-figure.py
@@ -61,7 +61,7 @@ def run(nstates, nsamples):
 
     # Initialize BHMM with MLHMM model.
     print "Sampling models from BHMM..."
-    sampler = bhmm.BayesianHMMSampler(O, nstates, initial_model=mle)
+    sampler = bhmm.BHMM(O, nstates, initial_model=mle)
     bhmm_models = sampler.sample(nsamples=nsamples, save_hidden_state_trajectory=False)
 
     # Generate a sample saving a hidden state trajectory.