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https://github.com/codex-storage/das-research.git
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Add logic for multi-simulation studies
This commit is contained in:
Leonardo Bautista-Gomez
parent
2df3ef45f7
commit
8221490196
105
simulator/DAS.py
105
simulator/DAS.py
@ -1,6 +1,6 @@
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#! /bin/python3
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import random, logging
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import random, logging, time
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from datetime import datetime
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class Block:
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@ -94,20 +94,20 @@ class Validator:
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if self.proposer == 1:
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self.logger.warning("I am a block proposer."% self.ID)
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else:
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self.logger.info("Selected rows: "+str(self.rowIDs), extra=self.format)
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self.logger.info("Selected columns: "+str(self.columnIDs), extra=self.format)
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self.logger.debug("Selected rows: "+str(self.rowIDs), extra=self.format)
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self.logger.debug("Selected columns: "+str(self.columnIDs), extra=self.format)
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def initBlock(self):
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self.logger.info("I am a block proposer.", extra=self.format)
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self.logger.debug("I am a block proposer.", extra=self.format)
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self.block = Block(self.blockSize)
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self.block.fill()
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self.block.print()
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#self.block.print()
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def broadcastBlock(self, broadcasted):
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if self.proposer == 0:
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self.logger.error("I am NOT a block proposer", extra=self.format)
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else:
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self.logger.info("Broadcasting my block...", extra=self.format)
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self.logger.debug("Broadcasting my block...", extra=self.format)
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tempBlock = self.block
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order = [i for i in range(self.blockSize * self.blockSize)]
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random.shuffle(order)
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@ -115,7 +115,7 @@ class Validator:
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i = order.pop()
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if (random.randint(0,99) > self.failureRate):
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broadcasted.data[i] = self.block.data[i]
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broadcasted.print()
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#broadcasted.print()
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def getColumn(self, columnID, broadcasted):
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column = [0] * self.blockSize
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@ -191,9 +191,9 @@ class Validator:
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if success >= len(row)/2:
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for i in range(len(row)):
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self.rows[rid][i] = goldenData[(self.rowIDs[rid]*self.blockSize)+i]
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self.logger.info("%d samples restored in row %d" % (failures, self.rowIDs[rid]), extra=self.format )
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self.logger.debug("%d samples restored in row %d" % (failures, self.rowIDs[rid]), extra=self.format )
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else:
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self.logger.warning("Row %d cannot be restored" % (self.rowIDs[rid]), extra=self.format)
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self.logger.debug("Row %d cannot be restored" % (self.rowIDs[rid]), extra=self.format)
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def checkRestoreColumns(self, goldenData):
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for cid in range(len(self.columns)):
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@ -212,9 +212,9 @@ class Validator:
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if success >= len(column)/2:
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for i in range(len(column)):
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self.columns[cid][i] = goldenData[(i*self.blockSize)+self.columnIDs[cid]]
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self.logger.info("%d samples restored in column %d" % (failures, self.columnIDs[cid]), extra=self.format)
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self.logger.debug("%d samples restored in column %d" % (failures, self.columnIDs[cid]), extra=self.format)
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else:
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self.logger.info("Column %d cannot be restored" % (self.columnIDs[cid]), extra=self.format)
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self.logger.debug("Column %d cannot be restored" % (self.columnIDs[cid]), extra=self.format)
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class Observer:
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@ -230,11 +230,13 @@ class Observer:
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def __init__(self, blockSize, logger):
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self.format = {"entity": "Observer"}
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self.blockSize = blockSize
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self.logger = logger
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def reset(self):
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self.block = [0] * self.blockSize * self.blockSize
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self.goldenData = [0] * self.blockSize * self.blockSize
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self.rows = [0] * self.blockSize
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self.columns = [0] * self.blockSize
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self.logger = logger
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self.broadcasted = Block(self.blockSize)
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def checkRowsColumns(self, validators):
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@ -246,9 +248,9 @@ class Observer:
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self.columns[c] += 1
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for i in range(self.blockSize):
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self.logger.info("Row/Column %d have %d and %d validators assigned." % (i, self.rows[i], self.columns[i]), extra=self.format)
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self.logger.debug("Row/Column %d have %d and %d validators assigned." % (i, self.rows[i], self.columns[i]), extra=self.format)
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if self.rows[i] == 0 or self.columns[i] == 0:
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logging.warning("There is a row/column that has not been assigned", extra=self.format)
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self.logger.warning("There is a row/column that has not been assigned", extra=self.format)
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def setGoldenData(self, block):
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for i in range(self.blockSize*self.blockSize):
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@ -260,16 +262,16 @@ class Observer:
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if self.broadcasted.data[i] == 0:
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zeros += 1
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if zeros > 0:
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self.logger.warning("There are %d missing samples in the network" % zeros, extra=self.format)
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self.logger.debug("There are %d missing samples in the network" % zeros, extra=self.format)
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return zeros
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class Simulator:
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chi = 4
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blockSize = 16
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numberValidators = 32
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failureRate = 66
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chi = 8
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blockSize = 256
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numberValidators = 8192
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failureRate = 0
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proposerID = 0
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logLevel = logging.INFO
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deterministic = 0
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@ -279,20 +281,17 @@ class Simulator:
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format = {}
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steps = 0
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def __init__(self):
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logger = logging.getLogger("DAS")
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logger.setLevel(self.logLevel)
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ch = logging.StreamHandler()
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ch.setLevel(self.logLevel)
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def __init__(self, failureRate):
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self.failureRate = failureRate
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self.format = {"entity": "Simulator"}
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ch.setFormatter(CustomFormatter())
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logger.addHandler(ch)
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self.logger = logger
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self.steps = 0
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def initValidators(self):
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if not self.deterministic:
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random.seed(datetime.now())
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self.glob = Observer(self.blockSize, self.logger)
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self.glob.reset()
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self.validators = []
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for i in range(self.numberValidators):
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val = Validator(i, self.chi, self.blockSize, int(not i!=0), self.failureRate, self.deterministic, self.logger)
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if i == self.proposerID:
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@ -302,14 +301,26 @@ class Simulator:
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val.logIDs()
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self.validators.append(val)
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def initLogger(self):
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logger = logging.getLogger("DAS")
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logger.setLevel(self.logLevel)
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ch = logging.StreamHandler()
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ch.setLevel(self.logLevel)
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ch.setFormatter(CustomFormatter())
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logger.addHandler(ch)
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self.logger = logger
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def resetFailureRate(self, failureRate):
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self.failureRate = failureRate
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def run(self):
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self.glob.checkRowsColumns(self.validators)
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self.validators[self.proposerID].broadcastBlock(self.glob.broadcasted)
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missingSamples = self.glob.checkBroadcasted()
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self.steps = 0
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while(missingSamples > 0):
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oldMissingSamples = missingSamples
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self.logger.info("Step %d:" % self.steps, extra=self.format)
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self.logger.debug("Step %d:" % self.steps, extra=self.format)
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for i in range(1,self.numberValidators):
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self.validators[i].receiveRowsColumns(self.glob.broadcasted)
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#Rows
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@ -332,14 +343,38 @@ class Simulator:
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self.steps += 1
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if missingSamples == 0:
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self.logger.info("The entire block is available at step %d!" % self.steps, extra=self.format)
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self.logger.debug("The entire block is available at step %d, with failure rate %d !" % (self.steps, self.failureRate), extra=self.format)
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return 0
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else:
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self.logger.warning("The block is CANNOT be recovered!", extra=self.format)
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self.logger.info("End of simulation", extra=self.format)
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sim = Simulator()
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sim.run()
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self.logger.debug("The block cannot be recovered, failure rate %d!" % self.failureRate, extra=self.format)
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return 1
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def study():
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sim = Simulator(0)
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sim.initLogger()
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maxTries = 5
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step = 25
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frRange = []
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resultRange = []
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simCnt = 0
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sim.logger.info("Starting %d simulations:" % (maxTries*100), extra=sim.format)
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start = time.time()
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for fr in range(0, 100, step):
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if fr % 10 == 0:
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sim.logger.info("Failure rate %d %% ..." % fr, extra=sim.format)
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sim.resetFailureRate(fr)
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result = 0
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for i in range(maxTries):
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sim.initValidators()
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result += sim.run()
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simCnt += 1
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frRange.append(fr)
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resultRange.append(100-result)
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end = time.time()
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sim.logger.info("A total of %d simulations ran in %d seconds" % (simCnt, end-start), extra=sim.format)
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for i in range(len(frRange)):
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sim.logger.info("For failure rate of %d we got %d %% success rate in DAS!" % (frRange[i], resultRange[i]), extra=sim.format)
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study()
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