python中的普通PageRank编码的问题

如何解决python中的普通PageRank编码的问题

问题是我了解背后的数学或机制，但我不明白为什么我的老师 找到该页面的等级后使用蒸发 很难用字母解释，所以我只给你完整的代码 我将零件与---------分开，所以您可以轻易注意到吗？ 我为什么要使用EVAP，TODIFF的问题，简而言之，就是所选网站的说明

从这里开始

\导入sqlite3

            conn = sqlite3.connect('spider.sqlite')
            cur = conn.cursor()

            # Find the ids that send out page rank - we only are interested
            # in pages in the SCC that have in and out links
            cur.execute('''SELECT DISTINCT from_id FROM Links''')
            from_ids = list()
            for row in cur:
                from_ids.append(row[0])

            # Find the ids that receive page rank
            to_ids = list()
            links = list()
            cur.execute('''SELECT DISTINCT from_id,to_id FROM Links''')
            for row in cur:
                from_id = row[0]
                to_id = row[1]
                if from_id == to_id : continue
                if from_id not in from_ids : continue
                if to_id not in from_ids : continue
                links.append(row)

                if to_id not in to_ids : to_ids.append(to_id)

            #for i in links:
            #    print(i)
            # Get latest page ranks for strongly connected component
            prev_ranks = dict()
            for node in from_ids:
                cur.execute('''SELECT new_rank FROM Pages WHERE id = ?''',(node,))
                row = cur.fetchone()
                prev_ranks[node] = row[0]
                print('--')
                print(node)

            sval = input('How many iterations:')
            many = 1
            if ( len(sval) > 0 ) : many = int(sval)

            # Sanity check
            if len(prev_ranks) < 1 :
                print("Nothing to page rank.  Check data.")
                quit()

            # Lets do Page Rank in memory so it is really fast
            for i in range(many):
                # print prev_ranks.items()[:5]
                next_ranks = dict()
                total = 0.0
                for (node,old_rank) in list(prev_ranks.items()):
                    total = total + old_rank
                    #print(total)
                    next_ranks[node] = 0.0
                    #print('--',next_ranks[node],'--')
                # print total
                #print(next_ranks)
                # Find the number of outbound links and sent the page rank down each
                for (node,old_rank) in list(prev_ranks.items()):
                    # print node,old_rank
                    give_ids = list()
                    for (from_id,to_id) in links:
                        if from_id != node : continue
                       #  print '   ',from_id,to_id

                        if to_id not in to_ids: continue
                        give_ids.append(to_id)
                    if ( len(give_ids) < 1 ) : continue
                    print(old_rank)
                    amount = old_rank / len(give_ids)
                    print (node,old_rank,amount,give_ids)

                    for id in give_ids:
                        next_ranks[id] = next_ranks[id] + amount
                print(next_ranks)
                -----------------------------------------------------------------------



                newtot = 0
                for (node,next_rank) in list(next_ranks.items()):
                    print(node,'---',next_rank)
                    newtot = newtot + next_rank
                evap = (total - newtot) / len(next_ranks)

                # print newtot,evap
                for node in next_ranks:
                    next_ranks[node] = next_ranks[node] + evap

                newtot = 0
                for (node,next_rank) in list(next_ranks.items()):
                    newtot = newtot + next_rank

                # Compute the per-page average change from old rank to new rank
                # As indication of convergence of the algorithm
                totdiff = 0
                for (node,old_rank) in list(prev_ranks.items()):
                    new_rank = next_ranks[node]
                    diff = abs(old_rank-new_rank)
                    print('====',diff)
                    totdiff = totdiff + diff

                avediff = totdiff / len(prev_ranks)
                print(i+1,avediff)
               ---------------------------------------------------------------------------------



                # rotate
                prev_ranks = next_ranks

            # Put the final ranks back into the database
            print(list(next_ranks.items())[:5])
            cur.execute('''UPDATE Pages SET old_rank=new_rank''')
            for (id,new_rank) in list(next_ranks.items()) :
                cur.execute('''UPDATE Pages SET new_rank=? WHERE id=?''',(new_rank,id))
            conn.commit()
            cur.close()

\