LinkPrediction.py 文件源码

def Prediction_LinkScores_Ratio(G, Predictor, Proportion, Toleration, Predict_Gap):
    print "Prediction_LinkScores_Ratio!"
    Rank_List_Set = {}
    OK_Value = float(G.number_of_edges())/Proportion

    if nx.is_connected(G) == True:
        Edge_Set = G.edges(data='True')

        Total = 0
        Error = 0
        Rank_List_Set[0] = [Link_Predictors.Wighted_Link_Prediction(Predictor, G), nx.average_clustering(G), nx.average_shortest_path_length(G) ]  ##Running time !!!!!
        '''
        while 1:
            #print i,len(Edge_Set),
            Tep_Edge = []
            Del = random.randint(0, len(Edge_Set)-1)
            Tep_Edge.append(Edge_Set[Del])

            #print "random range:", len(Edge_Set)-1
            #print Del,

            #Prediction with different training set
            G.remove_edge(Edge_Set[Del][0], Edge_Set[Del][1])
            if nx.is_connected(G) != True:
                G.add_edges_from(Tep_Edge)
                Error = Error + 1
                #print "Error:", Error
            else:
                #print Edge_Set[Del],
                Error = 0
                Total = Total + 1
                #print "Total:", Total

                if Total%Predict_Gap == 0:
                    V1 = Link_Predictors.Wighted_Link_Prediction(Predictor, G)
                    V2 = nx.average_clustering(G)
                    V3 = nx.average_shortest_path_length(G)
                    #V4 = Performance_Evaluation_AUC(Predictor, G, Probe_Set, Non_existing_links)
                    Rank_List_Set[Total] = [V1,V2,V3]
                Edge_Set = G.edges(data='True')
            #end if
            if Total > OK_Value or Error == Toleration:
                #print "complete with Total, Error:", Total, Error
                return Rank_List_Set
        #end while
        '''
        return Rank_List_Set
    #end if
    #return Rank_List_Set

##==========================================================================================
#Native_Prediction_Experiment(G, 'WSD', Probe_Set, Top_L, 3) #Top_K, Deleted_Ratio