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()