mirror of
https://github.com/pezkuwichain/consensus.git
synced 2026-04-22 09:07:58 +00:00
AlistairStewart
330 lines
12 KiB
Python
330 lines
12 KiB
Python
#from itertools import count
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class edge:
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def __init__(self,nomid,valiid):
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self.nomid=nomid
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self.valiid=valiid
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#self.validator
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self.load=0
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self.weight=0
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class nominator:
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def __init__(self,votetuple):
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self.nomid=votetuple[0]
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self.budget=votetuple[1]
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self.edges=[edge(self.nomid,valiid) for valiid in votetuple[2]]
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self.load=0
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class candidate:
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def __init__(self,valiid,valindex):
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self.valiid = valiid
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self.valindex=valindex
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self.approvalstake=0
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self.elected=False
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self.backedstake=0
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self.score=0
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self.scoredenom=0
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def setuplists(votelist):
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#Instead of Python's dict here, you can use anything with O(log n) addition and lookup.
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#We can also use a hashmap like dict, by generating a random constant r and useing H(canid+r)
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#since the naive thing is obviously attackable.
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nomlist = [nominator(votetuple) for votetuple in votelist]
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candidatedict=dict()
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candidatearray=list()
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numcandidates=0
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#Get an array of candidates. ]#We could reference these by index
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#rather than pointer
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for nom in nomlist:
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for edge in nom.edges:
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valiid = edge.valiid
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if valiid in candidatedict:
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edge.candidate=candidatearray[candidatedict[valiid]]
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else:
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candidatedict[valiid]=numcandidates
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newcandidate=candidate(valiid,numcandidates)
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candidatearray.append(newcandidate)
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edge.candidate=newcandidate
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numcandidates += 1
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return(nomlist,candidatearray)
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def seqPhragmén(votelist,numtoelect):
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nomlist,candidates=setuplists(votelist)
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#Compute the total possible stake for each candidate
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for nom in nomlist:
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for edge in nom.edges:
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edge.candidate.approvalstake += nom.budget
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electedcandidates=list()
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for round in range(numtoelect):
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for candidate in candidates:
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if not candidate.elected:
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candidate.score=1/candidate.approvalstake
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for nom in nomlist:
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for edge in nom.edges:
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if not edge.candidate.elected:
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edge.candidate.score +=nom.budget * nom.load / edge.candidate.approvalstake
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bestcandidate=0
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bestscore = 1000 #should be infinite but I'm lazy
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for candidate in candidates:
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if not candidate.elected and candidate.score < bestscore:
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bestscore=candidate.score
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bestcandidate=candidate.valindex
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electedcandidate=candidates[bestcandidate]
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electedcandidate.elected=True
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electedcandidate.electedpos=round
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electedcandidates.append(electedcandidate)
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for nom in nomlist:
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for edge in nom.edges:
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if edge.candidate.valindex == bestcandidate:
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edge.load=electedcandidate.score - nom.load
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nom.load=electedcandidate.score
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for candidate in electedcandidates:
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candidate.backedstake=0
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for nom in nomlist:
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for edge in nom.edges:
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if nom.load > 0.0:
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edge.weight = nom.budget * edge.load/nom.load
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edge.candidate.backedstake += edge.weight
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else:
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edge.weight = 0
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return (nomlist,electedcandidates)
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def calculateMaxScoreNoCutoff(nomlist,candidates):
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# First we compute the denominator of the score
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for candidate in candidates:
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if not candidate.elected:
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candidate.scoredenom=1.0
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for nom in nomlist:
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denominatorcontrib = 0
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for edge in nom.edges:
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if edge.candidate.elected:
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denominatorcontrib += edge.weight/edge.candidate.backedstake
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# print(nom.nomid, denominatorcontrib)
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for edge in nom.edges:
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if not edge.candidate.elected:
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edge.candidate.scoredenom += denominatorcontrib
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# print(edge.candidate.valiid, nom.nomid, denominatorcontrib, edge.candidate.scoredenom)
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# Then we divide. Not that score here is comparable to the recipricol of the score in seqPhragmen.
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# In particular there low scores are good whereas here high scores are good.
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bestcandidate=0
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bestscore = 0.0
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for candidate in candidates:
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# print(candidate.valiid, candidate.approvalstake, candidate.scoredenom)
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if candidate.approvalstake > 0.0:
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candidate.score = candidate.approvalstake/candidate.scoredenom
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if not candidate.elected and candidate.score > bestscore:
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bestscore=candidate.score
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bestcandidate=candidate
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else:
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candidate.score=0.0
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# print(len(candidates), bestcandidate, bestscore)
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return (bestcandidate,bestscore)
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def electWithScore(nomlist, electedcandidate, cutoff):
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for nom in nomlist:
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for newedge in nom.edges:
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if newedge.valiid == electedcandidate.valiid:
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usedbudget = sum([edge.weight for edge in nom.edges])
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newedge.weight = nom.budget-usedbudget
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electedcandidate.backedstake += nom.budget-usedbudget
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for edge in nom.edges:
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if edge.valiid != electedcandidate.valiid and edge.weight > 0.0:
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if edge.candidate.backedstake > cutoff:
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staketotake = edge.weight * cutoff / edge.candidate.backedstake
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newedge.weight += staketotake
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edge.weight -= staketotake
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edge.candidate.backedstake -= staketotake
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electedcandidate.backedstake += staketotake
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def approvalvoting(votelist,numtoelect):
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nomlist,candidates=setuplists(votelist)
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#Compute the total possible stake for each candidate
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for nom in nomlist:
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for edge in nom.edges:
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edge.candidate.approvalstake += nom.budget
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edge.weight = nom.budget/min(len(nom.edges),numtoelect)
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edge.candidate.backedstake += edge.weight
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candidates.sort( key = lambda x : x.approvalstake, reverse=True)
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electedcandidates=candidates[0:numtoelect]
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return nomlist,electedcandidates
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def printresult(nomlist,electedcandidates):
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for candidate in electedcandidates:
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print(candidate.valiid," is elected with stake ",candidate.backedstake, "and score ",candidate.score)
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print()
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for nom in nomlist:
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print(nom.nomid," has load ",nom.load, "and supported ")
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for edge in nom.edges:
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print(edge.valiid," with stake ",edge.weight, end=" ")
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print()
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def equalise(nom, tolerance):
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# Attempts to redistribute the nominators budget between elected validators
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# Assumes that all elected validators have backedstake set correctly
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# returns the max difference in stakes between sup
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electededges=[edge for edge in nom.edges if edge.candidate.elected]
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if len(electededges)==0:
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return 0.0
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stakeused = sum([edge.weight for edge in electededges])
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backedstakes=[edge.candidate.backedstake for edge in electededges]
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backingbackedstakes=[edge.candidate.backedstake for edge in electededges if edge.weight > 0.0]
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if len(backingbackedstakes) > 0:
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difference = max(backingbackedstakes)-min(backedstakes)
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difference += nom.budget-stakeused
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if difference < tolerance:
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return difference
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else:
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difference = nom.budget
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#remove all backing
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for edge in nom.edges:
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edge.candidate.backedstake -= edge.weight
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edge.weight=0
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electededges.sort(key=lambda x: x.candidate.backedstake)
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cumulativebackedstake=0
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lastcandidateindex=len(electededges)-1
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for i in range(len(electededges)):
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backedstake=electededges[i].candidate.backedstake
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#print(nom.nomid,electededges[i].valiid,backedstake,cumulativebackedstake,i)
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if backedstake * i - cumulativebackedstake > nom.budget:
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lastcandidateindex=i-1
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break
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cumulativebackedstake +=backedstake
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laststake=electededges[lastcandidateindex].candidate.backedstake
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waystosplit=lastcandidateindex+1
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excess = nom.budget + cumulativebackedstake - laststake*waystosplit
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for edge in electededges[0:waystosplit]:
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edge.weight = excess / waystosplit + laststake - edge.candidate.backedstake
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edge.candidate.backedstake += edge.weight
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return difference
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import random
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def equaliseall(nomlist,maxiterations,tolerance):
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for i in range(maxiterations):
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for j in range(len(nomlist)):
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nom=random.choice(nomlist)
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equalise(nom,tolerance/10)
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maxdifference=0
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for nom in nomlist:
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difference=equalise(nom,tolerance/10)
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maxdifference=max(difference,maxdifference)
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if maxdifference < tolerance:
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return
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def seqPhragménwithpostprocessing(votelist,numtoelect):
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nomlist,electedcandidates = seqPhragmén(votelist,numtoelect)
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equaliseall(nomlist,2,0.1)
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return nomlist,electedcandidates
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def factor3point15(votelist, numtoelect,tolerance=0.1):
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nomlist,candidates=setuplists(votelist)
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# Compute the total possible stake for each candidate
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for nom in nomlist:
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for edge in nom.edges:
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edge.candidate.approvalstake += nom.budget
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electedcandidates=list()
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for round in range(numtoelect):
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electedcandidate,score=calculateMaxScoreNoCutoff(nomlist,candidates)
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electWithScore(nomlist, electedcandidate, score)
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electedcandidate.elected=True
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electedcandidates.append(electedcandidate)
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electedcandidate.electedpos=round
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equaliseall(nomlist,100,tolerance)
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return nomlist,electedcandidates
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def example1():
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votelist=[("A",10.0,["X","Y"]),("B",20.0,["X","Z"]),("C",30.0,["Y","Z"])]
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print("Votes ",votelist)
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nomlist, electedcandidates = seqPhragmén(votelist,2)
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print("Sequential Phragmén gives")
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printresult(nomlist, electedcandidates)
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nomlist, electedcandidates = approvalvoting(votelist,2)
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print()
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print("Approval voting gives")
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printresult(nomlist, electedcandidates)
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nomlist, electedcandidates = seqPhragménwithpostprocessing(votelist,2)
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print("Sequential Phragmén with post processing gives")
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printresult(nomlist, electedcandidates)
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nomlist, electedcandidates = factor3point15(votelist,2)
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print("Factor 3.15 thing gives")
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printresult(nomlist, electedcandidates)
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def example2():
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votelist = [
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("10", 1000, ["10"]),
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("20", 1000, ["20"]),
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("30", 1000, ["30"]),
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("40", 1000, ["40"]),
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('2', 500, ['10', '20', '30']),
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('4', 500, ['10', '20', '40'])
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]
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print("Votes ",votelist)
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nomlist, electedcandidates = seqPhragmén(votelist,2)
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print("Sequential Phragmén gives")
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printresult(nomlist, electedcandidates)
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nomlist, electedcandidates = approvalvoting(votelist,2)
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print()
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print("Approval voting gives")
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printresult(nomlist, electedcandidates)
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nomlist, electedcandidates = seqPhragménwithpostprocessing(votelist,2)
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print("Sequential Phragmén with post processing gives")
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printresult(nomlist, electedcandidates)
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nomlist, electedcandidates = factor3point15(votelist,2)
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print("Factor 3.15 thing gives")
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printresult(nomlist, electedcandidates)
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import unittest
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class electiontests(unittest.TestCase):
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def testexample1Phragmén(self):
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votelist=[("A",10.0,["X","Y"]),("B",20.0,["X","Z"]),("C",30.0,["Y","Z"])]
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nomlist, electedcandidates = seqPhragmén(votelist,2)
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self.assertEqual(electedcandidates[0].valiid,"Z")
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self.assertAlmostEqual(electedcandidates[0].score,0.02)
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self.assertEqual(electedcandidates[1].valiid,"Y")
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self.assertAlmostEqual(electedcandidates[1].score,0.04)
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def testexample1approval(self):
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votelist=[("A",10.0,["X","Y"]),("B",20.0,["X","Z"]),("C",30.0,["Y","Z"])]
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nomlist, electedcandidates = approvalvoting(votelist,2)
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self.assertEqual(electedcandidates[0].valiid,"Z")
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self.assertAlmostEqual(electedcandidates[0].approvalstake,50.0)
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self.assertEqual(electedcandidates[1].valiid,"Y")
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self.assertAlmostEqual(electedcandidates[1].approvalstake,40.0)
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def dotests():
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unittest.main()
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