def __init__(self, data, data_opts, model_opts, dimensionalities, seed):
buildModel.__init__(self, data, data_opts, model_opts, dimensionalities, seed)
# create an instance of initModel
self.init_model = initModel(self.dim, self.data, self.model_opts["likelihoods"], seed=self.seed)
# Build all nodes
self.build_nodes()
# Define markov blankets
self.createMarkovBlankets()
def main(self):
# create an instance of initModel
self.init_model = initModel(dim=self.dim,
data=self.data,
lik=self.model_opts["likelihoods"],
groups=self.data_opts['samples_groups'],
seed=self.train_opts['seed'])
# Build all nodes
self.build_nodes()
# Define markov blankets
self.createMarkovBlankets()