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Merge pull request #26 from status-im/fix-uniformDistribution

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Fixing the global random uniform distribution
This commit is contained in:
Csaba Kiraly 2023-03-24 16:46:42 +01:00 committed by GitHub
commit c7a3fb1c52
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2 changed files with 28 additions and 7 deletions
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33
DAS/simulator.py
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@ -30,15 +30,27 @@ class Simulator:
self.glob.reset()
self.validators = []
if self.config.evenLineDistribution:
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)
lightVal = int(self.shape.numberNodes * self.shape.class1ratio * self.shape.vpn1)
heavyVal = int(self.shape.numberNodes * (1-self.shape.class1ratio) * self.shape.vpn2)
totalValidators = lightVal + heavyVal
rows = list(range(self.shape.blockSize)) * (int(totalValidators/self.shape.blockSize)+1)
columns = list(range(self.shape.blockSize)) * (int(totalValidators/self.shape.blockSize)+1)
offset = heavyVal*self.shape.chi
random.shuffle(rows)
random.shuffle(columns)
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)],
columns[(i*self.shape.chi):((i+1)*self.shape.chi)])
if i < int(heavyVal/self.shape.vpn2): # First start with the heavy nodes
start = i *self.shape.chi*self.shape.vpn2
end = (i+1)*self.shape.chi*self.shape.vpn2
else: # Then the solo stakers
j = i - int(heavyVal/self.shape.vpn2)
start = offset+( j *self.shape.chi)
end = offset+((j+1)*self.shape.chi)
r = rows[start:end]
c = columns[start:end]
val = Validator(i, int(not i!=0), self.logger, self.shape, r, c)
else:
val = Validator(i, int(not i!=0), self.logger, self.shape)
if i == self.proposerID:
@ -47,6 +59,7 @@ class Simulator:
else:
val.logIDs()
self.validators.append(val)
self.logger.debug("Validators initialized.", extra=self.format)
def initNetwork(self):
"""It initializes the simulated network."""
@ -59,6 +72,14 @@ class Simulator:
for id in v.columnIDs:
columnChannels[id].append(v)
# Check rows/columns distribution
#totalR = 0
#totalC = 0
#for r in rowChannels:
# totalR += len(r)
#for c in columnChannels:
# totalC += len(c)
for id in range(self.shape.blockSize):
# If the number of nodes in a channel is smaller or equal to the
@ -178,7 +199,7 @@ class Simulator:
# log TX and RX statistics
statsTxInSlot = [v.statsTxInSlot for v in self.validators]
statsRxInSlot = [v.statsRxInSlot for v in self.validators]
self.logger.debug("step %d: TX_prod=%.1f, RX_prod=%.1f, TX_avg=%.1f, TX_max=%.1f, Rx_avg=%.1f, Rx_max=%.1f" %
self.logger.debug("step %d: TX_prod=%.1f, RX_prod=%.1f, TX_avg=%.1f, TX_max=%.1f, Rx_avg=%.1f, Rx_max=%.1f" %
(steps, statsTxInSlot[0], statsRxInSlot[0],
mean(statsTxInSlot[1:]), max(statsTxInSlot[1:]),
mean(statsRxInSlot[1:]), max(statsRxInSlot[1:])), extra=self.format)

2
config_example.py
View File

@ -28,7 +28,7 @@ numJobs = 3
# distribute rows/columns evenly between validators (True)
# or generate it using local randomness (False)
evenLineDistribution = False
evenLineDistribution = True
# Number of simulation runs with the same parameters for statistical relevance
runs = range(10)