Adding multidimensional simulator and results module to gather data for visualization.
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@ -2,29 +2,49 @@
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class Configuration:
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blockSize = 0
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failureRateStep = 0
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maxTries = 0
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numberValidators = 0
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chi = 0
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failureRate = 0
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deterministic = 0
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blockSize = 0
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numberValidators = 0
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failureRate = 0
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failureRateStart = 0
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failureRateStop = 0
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failureRateStep = 0
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chio = 0
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chiStart = 0
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chiStop = 0
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chiStep = 0
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run =0
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runStart = 0
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runStop = 0
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runStep = 0
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def __init__(self, deterministic, blockSize, numberValidators,\
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failureRateStart, failureRateStop, failureRateStep,\
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chiStart, chiStop, chiStep,\
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runStart, runStop, runStep):
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def __init__(self, blockSize, failureRateStep, maxTries, numberValidators, chi, failureRate, deterministic):
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if numberValidators < (blockSize*4):
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print("ERROR: The number of validators cannot be lower than the block size * 4")
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exit(1)
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if chi < 1:
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if chiStart < 1:
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print("Chi has to be greater than 0")
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exit(1)
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if chi > blockSize:
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if chiStop > blockSize:
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print("Chi has to be smaller than %d" % blockSize)
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exit(1)
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self.blockSize = blockSize
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self.failureRateStep = failureRateStep
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self.maxTries = maxTries
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self.numberValidators = numberValidators
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self.chi = chi
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self.failureRate = failureRate
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self.deterministic = deterministic
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self.blockSize = blockSize
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self.numberValidators = numberValidators
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self.failureRateStart = failureRateStart
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self.failureRateStop = failureRateStop
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self.failureRateStep = failureRateStep
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self.failureRate = failureRateStart
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self.chiStart = chiStart
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self.chiStop = chiStop
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self.chiStep = chiStep
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self.chi = chiStart
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self.runStart = runStart
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self.runStop = runStop
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self.runStep = runStep
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self.run = runStart
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@ -0,0 +1,17 @@
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#!/bin/python3
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class Result:
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config = []
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missingVector = []
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blockAvailable = -1
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def __init__(self, config):
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self.config = config
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self.blockAvailable = -1
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self.missingVector = []
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def addMissing(self, missingVector):
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self.missingVector = missingVector
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@ -4,6 +4,7 @@ import networkx as nx
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import logging
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from datetime import datetime
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from DAS.tools import *
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from DAS.results import *
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from DAS.observer import *
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from DAS.validator import *
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@ -13,6 +14,7 @@ class Simulator:
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logLevel = logging.INFO
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validators = []
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glob = []
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result = []
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config = []
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logger = []
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format = {}
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@ -20,6 +22,7 @@ class Simulator:
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def __init__(self, config):
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self.config = config
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self.format = {"entity": "Simulator"}
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self.result = Result(self.config)
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def initValidators(self):
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if not self.config.deterministic:
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@ -48,7 +51,7 @@ class Simulator:
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for id in range(self.config.blockSize):
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G = nx.random_regular_graph(d, len(rowChannels[id]))
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if not nx.is_connected(G):
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self.logger.error("graph not connected for row %d !" % id, extra=self.format)
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self.logger.error("Graph not connected for row %d !" % id, extra=self.format)
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for u, v in G.edges:
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val1=rowChannels[id][u]
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val2=rowChannels[id][v]
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@ -56,7 +59,7 @@ class Simulator:
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val2.rowNeighbors[id].append(val1)
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G = nx.random_regular_graph(d, len(columnChannels[id]))
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if not nx.is_connected(G):
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self.logger.error("graph not connected for column %d !" % id, extra=self.format)
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self.logger.error("Graph not connected for column %d !" % id, extra=self.format)
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for u, v in G.edges:
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val1=columnChannels[id][u]
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val2=columnChannels[id][v]
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@ -73,15 +76,25 @@ class Simulator:
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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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self.config.failureRate = failureRate
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for val in self.validators:
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val.config.failureRate = failureRate
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def resetChi(self, chi):
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self.config.chi = chi
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for val in self.validators:
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val.config.chi = chi
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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()
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arrived, expected = self.glob.checkStatus(self.validators)
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missingSamples = expected - arrived
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missingVector = []
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steps = 0
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while(missingSamples > 0):
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missingVector.append(missingSamples)
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oldMissingSamples = missingSamples
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for i in range(1,self.config.numberValidators):
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self.validators[i].receiveRowsColumns()
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@ -96,7 +109,7 @@ class Simulator:
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arrived, expected = self.glob.checkStatus(self.validators)
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missingSamples = expected - arrived
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missingRate = missingSamples*100/expected
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self.logger.info("step %d, missing %d of %d (%0.02f %%)" % (steps, missingSamples, expected, missingRate), extra=self.format)
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self.logger.debug("step %d, missing %d of %d (%0.02f %%)" % (steps, missingSamples, expected, missingRate), extra=self.format)
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if missingSamples == oldMissingSamples:
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break
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elif missingSamples == 0:
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@ -104,10 +117,13 @@ class Simulator:
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else:
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steps += 1
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self.result.addMissing(missingVector)
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if missingSamples == 0:
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self.logger.debug("The entire block is available at step %d, with failure rate %d !" % (steps, self.failureRate), extra=self.format)
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return 0
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self.result.blockAvailable = 1
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self.logger.debug("The entire block is available at step %d, with failure rate %d !" % (steps, self.config.failureRate), extra=self.format)
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return self.result
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else:
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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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self.result.blockAvailable = 0
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self.logger.debug("The block cannot be recovered, failure rate %d!" % self.config.failureRate, extra=self.format)
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return self.result
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@ -70,7 +70,7 @@ class Validator:
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self.block.data[i] = 0
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nbFailures = self.block.data.count(0)
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measuredFailureRate = nbFailures * 100 / (self.config.blockSize * self.config.blockSize)
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self.logger.info("Number of failures: %d (%0.02f %%)", nbFailures, measuredFailureRate, extra=self.format)
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self.logger.debug("Number of failures: %d (%0.02f %%)", nbFailures, measuredFailureRate, extra=self.format)
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#broadcasted.print()
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for id in range(self.config.blockSize):
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self.sendColumn(id)
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30
study.py
30
study.py
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@ -5,30 +5,34 @@ from DAS import *
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def study():
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config = Configuration(64, 20, 10, 256, 8, 0, 0)
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config = Configuration(0, 64, 256, 0, 100, 20, 8, 16, 4, 0, 10, 1)
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sim = Simulator(config)
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sim.initLogger()
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frRange = []
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results = []
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resultRange = []
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simCnt = 0
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sim.logger.info("Starting simulations:", extra=sim.format)
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start = time.time()
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for fr in range(0, 100, config.failureRateStep):
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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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for fr in range(config.failureRateStart, config.failureRateStop+1, config.failureRateStep):
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sim.resetFailureRate(fr)
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result = 0
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for i in range(config.maxTries):
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sim.initValidators()
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sim.initNetwork()
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result += sim.run()
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simCnt += 1
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for chi in range(config.chiStart, config.chiStop+1, config.chiStep):
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sim.resetChi(chi)
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blockAvailable = 0
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for run in range(config.runStart, config.runStop, config.runStep):
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sim.logger.info("FR: %d %%, Chi: %d %%, Run: %d ..." % (fr, chi, run), extra=sim.format)
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sim.initValidators()
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sim.initNetwork()
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result = sim.run()
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blockAvailable += result.blockAvailable
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results.append(result)
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simCnt += 1
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frRange.append(fr)
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resultRange.append((config.maxTries-result)*100/config.maxTries)
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resultRange.append((blockAvailable)*100/config.runStop)
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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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#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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