Method __init__

libpgm/tablecpdfactorization.py:41–59

This class is constructed with a :doc:`DiscreteBayesianNetwork ` instance as argument. First, it takes the input itself and stores it in the *bn* attribute. Then, it transforms the information of each of these nodes from standard discrete CPD form into a :doc:`Table

(self, bn)

    '''

    def __init__(self, bn):
        '''
        This class is constructed with a :doc:`DiscreteBayesianNetwork <discretebayesiannetwork>` instance as argument. First, it takes the input itself and stores it in the *bn* attribute. Then, it transforms the information of each of these nodes from standard discrete CPD form into a :doc:`TableCPDFactor <tablecpdfactor>` isntance and stores the instances in an array in the attribute *originalfactorlist*. Finally, it makes a copy of this list to work with and stores it in *factorlist*.
        
        ''&#x27;
        assert hasattr(bn, "V") and hasattr(bn, "E") and hasattr(bn, "Vdata"), \
            "Input must be a DiscreteBayesianNetwork instance."
        
        self.bn = bn
        '''The Bayesian network used as argument at instantiation.'''
        self.originalfactorlist = []
        '''A list of :doc:`TableCPDFactor <tablecpdfactor>` instances, one per node.'''
        for vertex in bn.V:
            factor = TableCPDFactor(vertex, bn)
            self.originalfactorlist.append(factor)
        self.factorlist = copy.deepcopy(self.originalfactorlist)  
        '''A working copy of *originalfactorlist*.'''

        assert self.factorlist, "Factor list not properly loaded, check for an incomplete class instance as input."
    
    def refresh(self):
        ''&#x27;