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Remote test and other stuff

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This commit is contained in:
kianenigma
2020-08-06 16:35:59 +02:00
parent 2c908f3493
commit 115074225a
4 changed files with 148 additions and 67 deletions
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NPoS/.gitignore
+2
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@@ -0,0 +1,2 @@
.vscode
__pycache__
NPoS/ComplicatedPhragmén.py
+40 -40
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@@ -7,7 +7,7 @@ class edge:
#self.index
#self.voterindex
#self.canindex
class voter:
def __init__(self,votetuple):
@@ -83,7 +83,7 @@ class assignment:
def unelect(self,candidate):
self.canelected[candidate.index]=False
self.electedcandidates.remove(candidate)
def setuplists(votelist):
#Instead of Python's dict here, you can use anything with O(log n) addition and lookup.
#We can also use a hashmap, by generating a random constant r and useing H(canid+r)
@@ -94,7 +94,7 @@ def setuplists(votelist):
numcandidates=0
numvoters=0
numedges=0
#Get an array of candidates that we can reference these by index
for nom in voterlist:
nom.index=numvoters
@@ -115,13 +115,13 @@ def setuplists(votelist):
edge.canindex=numcandidates
numcandidates += 1
return(voterlist,candidatearray)
def seqPhragmén(votelist,numtoelect):
nomlist,candidates=setuplists(votelist)
#creating an assignment now also computes the total possible stake for each candidate
a=assignment(nomlist,candidates)
for round in range(numtoelect):
for canindex in range(len(candidates)):
if not a.canelected[canindex]:
@@ -172,8 +172,8 @@ def calculateScores(a,cutoff):
#if not a.canelected[canindex]:
#print(a.candidates[canindex].canid," has score ", a.canscore[canindex]," with cutoff ",cutoff)
#print("Approval stake: ", a.canapproval[canindex]," support: ",a.cansupport[canindex]," denominator: ",a.canscoredenominator[canindex], " numerator: ",a.canscorenumerator[canindex])
def calculateMaxScore(a):
supportList=[a.cansupport[can.index] for can in a.electedcandidates]
supportList.append(0.0)
@@ -249,7 +249,7 @@ def equalise(a, nom, tolerance):
# Attempts to redistribute the nominators budget between elected validators
# Assumes that all elected validators have backedstake set correctly
# returns the max difference in stakes between sup
electededges=[edge for edge in nom.edges if a.canelected[edge.canindex]]
if len(electededges)==0:
return 0.0
@@ -310,7 +310,7 @@ def seqPhragménwithpostprocessing(votelist,numtoelect, ratio=1):
def factor3point15(votelist, numtoelect,tolerance=0.1):
nomlist,candidates=setuplists(votelist)
a=assignment(nomlist,candidates)
for round in range(numtoelect):
bestcandidate,score=calculateMaxScore(a)
insertWithScore(a,bestcandidate, score)
@@ -325,7 +325,7 @@ def maybecandidate(a,newcandidate,shouldremoveworst, tolerance):
if shouldremoveworst:
worstcanidate =min(electedcandidates, key = lambda x: b.cansupport[x.index])
b.unelect(worstcandidate)
b.elect(newcandidate)
b.elect(newcandidate)
equaliseall(b,100000000,tolerance)
newvalue=min([b.cansupport[candidate.index] for candidate in b.electedcandidates])
return b, newvalue
@@ -395,7 +395,7 @@ def binarysearchfeasible(votelist,numtoelect,tolerance=0.1):
else:
targetvalue=currentvalue
#print(targetvalue,lastgoodindex, maxvalue,bestknownvalue,currentvalue)
for round in range(lastgoodindex+1,numtoelect):
# First try maxscore candidate, which will help with PJR
@@ -460,22 +460,22 @@ def doall(votelist, numtoelect, listvoters=True, listcans=True):
if listvoters:
print("Votes ",votelist)
alglist=[(approvalvoting,"Approval voting"), (seqPhragmén, "Sequential Phragmén"),
(seqPhragménwithpostprocessing, "Sequential Phragmén with post processing"),
(seqPhragménwithpostprocessing, "Sequential Phragmén with post processing"),
(factor3point15, "The factor 3.15 thing"), (binarysearchfeasible,"Factor 2 by binary search"), (SFFB18, "SFFB18")]
for alg,name in alglist:
st=time.perf_counter()
st=time.perf_counter()
a = alg(votelist,numtoelect)
et=time.perf_counter()
et=time.perf_counter()
print(name, " gives")
printresult(a,listvoters,listcans)
print(" in ",et-st," seconds.")
print()
def example1():
votelist=[("A",10.0,["X","Y"]),("B",20.0,["X","Z"]),("C",30.0,["Y","Z"])]
doall(votelist,2)
def example2():
# Approval voting does not do so well for this kind of thing.
@@ -491,7 +491,7 @@ def example3():
bluevoters = [("BlueV"+str(i),20.0,blueparty) for i in range(20)]
votelist= redvoters+bluevoters
doall(votelist, 20, False)
def example4():
#Now we want an example where seq Phragmén is not so good.
@@ -518,7 +518,7 @@ def example6():
("M",50.0, ["M"])]
print("Votes ",votelist)
doall(votelist,5)
def exampleLine():
votelist = [
("a", 2000, ["A"]),
@@ -530,7 +530,7 @@ def exampleLine():
("g", 1000, ["F","G"])
]
doall(votelist,7)
def ri(vals=20,noms=2000, votesize=10):
#Let's try a random instance
candidates=["Val"+str(i) for i in range(vals)]
@@ -560,28 +560,28 @@ def riparty(vals=200,noms=2000, votesize=10,seed=1):
NPoS/simplePhragmén.py → NPoS/npos.py
+14 -27
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@@ -1,5 +1,4 @@
import unittest
import sys
def print_list(ll):
@@ -16,7 +15,7 @@ class edge:
self.candidate = None
def __str__(self):
return "Edge({}, weight = {})".format(
return "Edge({}, weight = {:,})".format(
self.validator_id,
self.weight,
)
@@ -30,7 +29,7 @@ class nominator:
self.load = 0
def __str__(self):
return "Nominator({}, budget = {}, load = {}, edges = {})".format(
return "Nominator({}, budget = {:,}, load = {}, edges = {})".format(
self.nominator_id,
self.budget,
self.load,
@@ -49,12 +48,10 @@ class candidate:
self.scoredenom = 0
def __str__(self):
return "Candidate({}, approval = {}, backed = {}, score = {}, scoredenom = {})".format(
return "Candidate({}, approval = {:,}, backed_stake = {:,})".format(
self.validator_id,
self.approval_stake,
self.backed_stake,
self.score,
self.scoredenom,
int(self.backed_stake),
)
@@ -194,7 +191,6 @@ def calculateMaxScoreNoCutoff(nomlist, candidates):
for candidate in candidates:
if candidate.approval_stake > 0.0:
candidate.score = candidate.approval_stake / candidate.scoredenom
print("score of {} in this round is {}".format(candidate.validator_id, candidate.score))
if not candidate.elected and candidate.score > best_score:
best_score = candidate.score
best_candidate = candidate
@@ -209,19 +205,23 @@ def electWithScore(nomlist, elected_candidate, cutoff):
for new_edge in nom.edges:
if new_edge.validator_id == elected_candidate.validator_id:
used_budget = sum([edge.weight for edge in nom.edges])
new_edge.weight = nom.budget - used_budget
elected_candidate.backed_stake += nom.budget - used_budget
for edge in nom.edges:
if edge.validator_id != elected_candidate.validator_id and edge.weight > 0.0:
if edge.candidate.backed_stake > cutoff:
stake_to_take = edge.weight * cutoff / edge.candidate.backed_stake
new_edge.weight += stake_to_take
edge.weight -= stake_to_take
edge.candidate.backed_stake -= stake_to_take
elected_candidate.backed_stake += stake_to_take
edge.weight -= stake_to_take
edge.candidate.backed_stake -= stake_to_take
def balanced_heuristic(votelist, num_to_elect, tolerance=0.1):
def phragmms(votelist, num_to_elect, tolerance=0.1):
nomlist, candidates = setuplists(votelist)
calculate_approval(nomlist)
@@ -229,16 +229,12 @@ def balanced_heuristic(votelist, num_to_elect, tolerance=0.1):
for round in range(num_to_elect):
(elected_candidate, score) = calculateMaxScoreNoCutoff(nomlist, candidates)
electWithScore(nomlist, elected_candidate, score)
print("####\nRound {} max candidate {} with score {}".format(round, elected_candidate.validator_id, score))
print_list(nomlist)
elected_candidate.elected = True
elected_candidates.append(elected_candidate)
elected_candidate.electedpos = round
equalise_all(nomlist, 10, tolerance)
print("After balancing")
print_list(nomlist)
return nomlist, elected_candidates
@@ -309,7 +305,7 @@ def run_and_print_all(votelist, to_elect):
printresult(nomlist, elected_candidates)
print("\nBalanced Heuristic (3.15 factor) gives")
nomlist, elected_candidates = balanced_heuristic(votelist, to_elect)
nomlist, elected_candidates = phragmms(votelist, to_elect)
printresult(nomlist, elected_candidates)
@@ -367,7 +363,7 @@ class MaxScoreTest(unittest.TestCase):
(20, 20.0, [1, 3]),
(30, 30.0, [2, 3]),
]
nomlist, winners = balanced_heuristic(votelist, 2, 0)
nomlist, winners = phragmms(votelist, 2, 0)
self.assertEqual(winners[0].validator_id, 3)
self.assertEqual(winners[1].validator_id, 2)
@@ -385,7 +381,7 @@ class MaxScoreTest(unittest.TestCase):
(130, 1000, [61, 71]),
]
nomlist, winners = balanced_heuristic(votelist, 4, 0)
nomlist, winners = phragmms(votelist, 4, 0)
self.assertEqual(winners[0].validator_id, 11)
self.assertEqual(winners[0].backed_stake, 3000)
@@ -430,12 +426,3 @@ def main():
# example1()
example2()
# example3()
if len(sys.argv) >= 2:
if sys.argv[1] == "run":
main()
else:
unittest.main()
else:
unittest.main()
NPoS/remote_test.py
+92
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@@ -0,0 +1,92 @@
import npos
import pprint
from substrateinterface import SubstrateInterface
from substrateinterface.utils.ss58 import ss58_decode, ss58_encode
pp = pprint.PrettyPrinter(indent=4)
substrate = SubstrateInterface(
url="ws://localhost:9944",
address_type=0,
type_registry={'types': {
"StakingLedger<AccountId, BalanceOf>": {
"type": "struct",
"type_mapping": [
["stash", "AccountId"],
["total", "Compact<Balance>"],
["active", "Compact<Balance>"],
["unlocking", "Vec<UnlockChunk<Balance>>"],
["claimedReward", "Vec<EraIndex>"]
]
},
}
},
type_registry_preset='polkadot',
)
head = substrate.get_chain_finalised_head()
def get_candidates():
prefix = substrate.generate_storage_hash("Staking", "Validators")
pairs = substrate.rpc_request(method="state_getPairs", params=[prefix, head])['result']
last_32_bytes = list(map(lambda p: "0x" + p[0][-64:], pairs))
return list(map(lambda k: ss58_encode(k), last_32_bytes))
def get_nominators():
prefix = substrate.generate_storage_hash("Staking", "Nominators")
pairs = substrate.rpc_request(method="state_getPairs", params=[prefix, head])['result']
nominators = list(
map(lambda p: ("0x" + p[0][-64:], substrate.decode_scale("Nominations<AccountId>", p[1])['targets']), pairs)
)
nominators = list(map(lambda x: (
ss58_encode(x[0], substrate.address_type),
x[1],
), nominators))
return list(map(lambda x: (
x[0],
get_backing_stake_of(x[0]),
[ss58_encode(acc, substrate.address_type) for acc in x[1]],
), nominators))
def get_backing_stake_of(who):
ctrl = substrate.get_runtime_state(
module="Staking",
storage_function="Bonded",
params=[who],
block_hash=head,
)['result']
ctrl = ss58_encode(ctrl, substrate.address_type)
ledger = substrate.get_runtime_state(
module="Staking",
storage_function="Ledger",
params=[ctrl],
block_hash=head,
)['result']
return ledger['active']
def validator_count():
return substrate.get_runtime_state("Staking", "ValidatorCount", [], head)['result']
candidates = get_candidates()
nominators = get_nominators()
to_elect = validator_count()
print("{} validators, {} nominators, electing {}".format(len(candidates), len(nominators), to_elect))
distribution, winners = npos.phragmms(nominators, to_elect)
npos.print_list(winners)
print(sum([c.backed_stake for c in winners]))
print(min([c.backed_stake for c in winners]))
score = [min([c.backed_stake for c in winners]), sum([c.backed_stake for c in winners])]
print("score = [{:,}, {:,}]".format(int(score[0]), int(score[1])))