rename numberValidators to numberNodes

Signed-off-by: Csaba Kiraly <csaba.kiraly@gmail.com>
This commit is contained in:
Csaba Kiraly 2023-03-13 15:03:55 +01:00
parent 065086f88c
commit 9d9612fd34
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GPG Key ID: 0FE274EE8C95166E
5 changed files with 21 additions and 21 deletions

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@ -3,10 +3,10 @@
class Shape:
"""This class represents a set of parameters for a specific simulation."""
def __init__(self, blockSize, numberValidators, failureRate, class1ratio, chi, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run):
def __init__(self, blockSize, numberNodes, failureRate, class1ratio, chi, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run):
"""Initializes the shape with the parameters passed in argument."""
self.run = run
self.numberValidators = numberValidators
self.numberNodes = numberNodes
self.blockSize = blockSize
self.failureRate = failureRate
self.netDegree = netDegree
@ -23,7 +23,7 @@ class Shape:
"""Returns a printable representation of the shape"""
shastr = ""
shastr += "bs-"+str(self.blockSize)
shastr += "-nbv-"+str(self.numberValidators)
shastr += "-nn-"+str(self.numberNodes)
shastr += "-fr-"+str(self.failureRate)
shastr += "-c1r-"+str(self.class1ratio)
shastr += "-chi-"+str(self.chi)

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@ -30,11 +30,11 @@ class Simulator:
self.glob.reset()
self.validators = []
if self.config.evenLineDistribution:
rows = list(range(self.shape.blockSize)) * int(self.shape.chi*self.shape.numberValidators/self.shape.blockSize)
columns = list(range(self.shape.blockSize)) * int(self.shape.chi*self.shape.numberValidators/self.shape.blockSize)
rows = list(range(self.shape.blockSize)) * int(self.shape.chi*self.shape.numberNodes/self.shape.blockSize)
columns = list(range(self.shape.blockSize)) * int(self.shape.chi*self.shape.numberNodes/self.shape.blockSize)
random.shuffle(rows)
random.shuffle(columns)
for i in range(self.shape.numberValidators):
for i in range(self.shape.numberNodes):
if self.config.evenLineDistribution:
val = Validator(i, int(not i!=0), self.logger, self.shape,
rows[(i*self.shape.chi):((i+1)*self.shape.chi)],
@ -104,7 +104,7 @@ class Simulator:
v.columnNeighbors[id].update({vi.ID : Neighbor(vi, 1, self.shape.blockSize)})
if self.logger.isEnabledFor(logging.DEBUG):
for i in range(0, self.shape.numberValidators):
for i in range(0, self.shape.numberNodes):
self.logger.debug("Val %d : rowN %s", i, self.validators[i].rowNeighbors, extra=self.format)
self.logger.debug("Val %d : colN %s", i, self.validators[i].columnNeighbors, extra=self.format)
@ -155,17 +155,17 @@ class Simulator:
missingVector.append(missingSamples)
oldMissingSamples = missingSamples
self.logger.debug("PHASE SEND %d" % steps, extra=self.format)
for i in range(0,self.shape.numberValidators):
for i in range(0,self.shape.numberNodes):
self.validators[i].send()
self.logger.debug("PHASE RECEIVE %d" % steps, extra=self.format)
for i in range(1,self.shape.numberValidators):
for i in range(1,self.shape.numberNodes):
self.validators[i].receiveRowsColumns()
self.logger.debug("PHASE RESTORE %d" % steps, extra=self.format)
for i in range(1,self.shape.numberValidators):
for i in range(1,self.shape.numberNodes):
self.validators[i].restoreRows()
self.validators[i].restoreColumns()
self.logger.debug("PHASE LOG %d" % steps, extra=self.format)
for i in range(0,self.shape.numberValidators):
for i in range(0,self.shape.numberNodes):
self.validators[i].logRows()
self.validators[i].logColumns()
@ -176,7 +176,7 @@ class Simulator:
(steps, statsTxInSlot[0], statsRxInSlot[0],
mean(statsTxInSlot[1:]), max(statsTxInSlot[1:]),
mean(statsRxInSlot[1:]), max(statsRxInSlot[1:])), extra=self.format)
for i in range(0,self.shape.numberValidators):
for i in range(0,self.shape.numberNodes):
self.validators[i].updateStats()
arrived, expected = self.glob.checkStatus(self.validators)

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@ -62,7 +62,7 @@ class Validator:
else:
if self.amIproposer:
self.chi = 1 # not used
elif self.ID <= shape.numberValidators * shape.class1ratio:
elif self.ID <= shape.numberNodes * shape.class1ratio:
self.chi = shape.chi * shape.vpn1
else:
self.chi = shape.chi * shape.vpn2 # TODO: union of random subsets vpn2 times
@ -94,7 +94,7 @@ class Validator:
# TODO: this should be a parameter
if self.amIproposer:
self.bwUplink = shape.bwUplinkProd
elif self.ID <= shape.numberValidators * shape.class1ratio:
elif self.ID <= shape.numberNodes * shape.class1ratio:
self.bwUplink = shape.bwUplink1
else:
self.bwUplink = shape.bwUplink2

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@ -12,7 +12,7 @@ class Visualizer:
def __init__(self, execID):
self.execID = execID
self.folderPath = "results/"+self.execID
self.parameters = ['run', 'blockSize', 'failureRate', 'numberValidators', 'netDegree',
self.parameters = ['run', 'blockSize', 'failureRate', 'numberNodes', 'netDegree',
'chi', 'vpn1', 'vpn2', 'bwUplinkProd', 'bwUplink1', 'bwUplink2']
self.minimumDataPoints = 2
@ -28,7 +28,7 @@ class Visualizer:
run = int(root.find('run').text)
blockSize = int(root.find('blockSize').text)
failureRate = int(root.find('failureRate').text)
numberValidators = int(root.find('numberValidators').text)
numberNodes = int(root.find('numberNodes').text)
netDegree = int(root.find('netDegree').text)
chi = int(root.find('chi').text)
vpn1 = int(root.find('vpn1').text)
@ -42,7 +42,7 @@ class Visualizer:
for combination in combinations(self.parameters, 4):
# Get the indices and values of the parameters in the combination
indices = [self.parameters.index(element) for element in combination]
selectedValues = [run, blockSize, failureRate, numberValidators, netDegree, chi, vpn1, vpn2, bwUplinkProd, bwUplink1, bwUplink2]
selectedValues = [run, blockSize, failureRate, numberNodes, netDegree, chi, vpn1, vpn2, bwUplinkProd, bwUplink1, bwUplink2]
values = [selectedValues[index] for index in indices]
names = [self.parameters[i] for i in indices]
keyComponents = [f"{name}_{value}" for name, value in zip(names, values)]

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@ -34,7 +34,7 @@ evenLineDistribution = False
runs = range(10)
# Number of validators
numberValidators = range(256, 513, 128)
numberNodes = range(256, 513, 128)
# Percentage of block not released by producer
failureRates = range(10, 91, 40)
@ -68,9 +68,9 @@ deterministic = False
randomSeed = "DAS"
def nextShape():
for run, fr, class1ratio, chi, vpn1, vpn2, blockSize, nv, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product(
runs, failureRates, class1ratios, chis, validatorsPerNode1, validatorsPerNode2, blockSizes, numberValidators, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2):
for run, fr, class1ratio, chi, vpn1, vpn2, blockSize, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product(
runs, failureRates, class1ratios, chis, validatorsPerNode1, validatorsPerNode2, blockSizes, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2):
# Network Degree has to be an even number
if netDegree % 2 == 0:
shape = Shape(blockSize, nv, fr, class1ratio, chi, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run)
shape = Shape(blockSize, nn, fr, class1ratio, chi, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run)
yield shape