005cd59c9327b7376cd5140ea5f0435620964669,pgmpy/inference/Sampling.py,BayesianModelSampling,__init__,#BayesianModelSampling#,32

Before Change

            raise TypeError("model must an instance of BayesianModel")
        super(BayesianModelSampling, self).__init__(model)
        self.topological_order = nx.topological_sort(model)
        self.cpds = {node: model.get_cpds(node) for node in model.nodes()}

    def forward_sample(self, size=1):
        
        Generates sample(s) from joint distribution of the bayesian network.

After Change

    
    def __init__(self, model):
        if not isinstance(model, BayesianModel):
            raise TypeError("Model expected type: BayesianModel, got type: ", type(model))

        self.topological_order = nx.topological_sort(model)
        super(BayesianModelSampling, self).__init__(model)
        // self.cpds = {node: model.get_cpds(node) for node in model.nodes()}

Instances