diff --git a/DAS/block.py b/DAS/block.py index d002345..6d5c1d3 100644 --- a/DAS/block.py +++ b/DAS/block.py @@ -9,7 +9,6 @@ class Block: def __init__(self, blockSizeR, blockSizeRK=0, blockSizeC=0, blockSizeCK=0): """Initialize the block with a data array of blocksize^2 zeros. - BlockSizeR: row size BlockSizeRK: original row size, before erasure coding to BlocksSizeR BlockSizeC: column size (i.e. number of rows) @@ -51,12 +50,14 @@ class Block: """ line = self.data[id::self.blockSizeR] success = line.count(1) + repairedSamples = 0 if success >= self.blockSizeCK: ret = ~line self.data[id::self.blockSizeR] = 1 + repairedSamples = len(line) - success else: ret = zeros(self.blockSizeC) - return ret + return ret, repairedSamples def getRow(self, rowID): """It returns the block row corresponding to rowID.""" @@ -72,12 +73,14 @@ class Block: """ line = self.data[id*self.blockSizeR:(id+1)*self.blockSizeR] success = line.count(1) + repairedSamples = 0 if success >= self.blockSizeRK: ret = ~line self.data[id*self.blockSizeR:(id+1)*self.blockSizeR] = 1 + repairedSamples = len(line) - success else: ret = zeros(self.blockSizeR) - return ret + return ret, repairedSamples def print(self): """It prints the block in the terminal (outside of the logger rules)).""" @@ -89,4 +92,3 @@ class Block: line += "%i" % self.data[(i*self.blockSizeR)+j] print(line+"|") print(dash) - diff --git a/DAS/observer.py b/DAS/observer.py index f848837..328a11d 100644 --- a/DAS/observer.py +++ b/DAS/observer.py @@ -100,4 +100,4 @@ class Observer: "RxDup": {"mean": meanOrNan(RxDup), "max": maxOrNan(RxDup)}, } - return trafficStats + return trafficStats \ No newline at end of file diff --git a/DAS/results.py b/DAS/results.py index 76d96d1..f679702 100644 --- a/DAS/results.py +++ b/DAS/results.py @@ -16,6 +16,26 @@ class Result: self.tta = -1 self.missingVector = [] self.metrics = {} + self.amImalicious = [0] * shape.numberNodes + self.msgSentCount = [0] * shape.numberNodes + self.msgRecvCount = [0] * shape.numberNodes + self.sampleRecvCount = [0] * shape.numberNodes + self.restoreRowCount = [0] * shape.numberNodes + self.restoreColumnCount = [0] * shape.numberNodes + self.repairedSampleCount = [0] * shape.numberNodes + self.numberNodes = shape.numberNodes + self.class1ratio = shape.class1ratio + + def copyValidators(self, validators): + """Copy information from simulator.validators to result.""" + for i in range(0,self.shape.numberNodes): + self.amImalicious[i] = validators[i].amImalicious + self.msgSentCount[i] = validators[i].msgSentCount + self.msgRecvCount[i] = validators[i].msgRecvCount + self.sampleRecvCount[i] = validators[i].sampleRecvCount + self.restoreRowCount[i] = validators[i].restoreRowCount + self.restoreColumnCount[i] = validators[i].restoreColumnCount + self.repairedSampleCount[i] = validators[i].repairedSampleCount def populate(self, shape, config, missingVector): """It populates part of the result data inside a vector.""" diff --git a/DAS/shape.py b/DAS/shape.py index c8ace30..1047988 100644 --- a/DAS/shape.py +++ b/DAS/shape.py @@ -2,9 +2,8 @@ class Shape: """This class represents a set of parameters for a specific simulation.""" - - def __init__(self, blockSizeR, blockSizeRK, blockSizeC, blockSizeCK, - numberNodes, failureModel, failureRate, class1ratio, chiR, chiC, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run): + def __init__(self, blockSizeR, blockSizeRK, blockSizeC, blockSizeCK, + numberNodes, failureModel, failureRate, maliciousNodes, class1ratio, chiR, chiC, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run): """Initializes the shape with the parameters passed in argument.""" self.run = run self.numberNodes = numberNodes @@ -14,6 +13,7 @@ class Shape: self.blockSizeCK = blockSizeCK self.failureModel = failureModel self.failureRate = failureRate + self.maliciousNodes = maliciousNodes self.netDegree = netDegree self.class1ratio = class1ratio self.chiR = chiR @@ -28,7 +28,7 @@ class Shape: def __repr__(self): """Returns a printable representation of the shape""" shastr = "" - shastr += "bsrn-"+str(self.blockSizeR) + shastr += "-bsrn-"+str(self.blockSizeR) shastr += "-bsrk-"+str(self.blockSizeRK) shastr += "-bscn-"+str(self.blockSizeC) shastr += "-bsck-"+str(self.blockSizeCK) @@ -45,9 +45,9 @@ class Shape: shastr += "-bwup2-"+str(self.bwUplink2) shastr += "-nd-"+str(self.netDegree) shastr += "-r-"+str(self.run) + shastr += "-mn-"+str(self.maliciousNodes) return shastr def setSeed(self, seed): """Adds the random seed to the shape""" self.randomSeed = seed - diff --git a/DAS/simulator.py b/DAS/simulator.py index a51a291..7bc91bf 100644 --- a/DAS/simulator.py +++ b/DAS/simulator.py @@ -47,7 +47,8 @@ class Simulator: """It initializes all the validators in the network.""" self.glob = Observer(self.logger, self.shape) self.validators = [] - if self.config.evenLineDistribution: + evenLineDistribution = False + if evenLineDistribution: lightNodes = int(self.shape.numberNodes * self.shape.class1ratio) heavyNodes = self.shape.numberNodes - lightNodes @@ -59,7 +60,7 @@ class Simulator: rows = list(range(self.shape.blockSizeC)) * (int(totalRows/self.shape.blockSizeC)+1) columns = list(range(self.shape.blockSizeR)) * (int(totalColumns/self.shape.blockSizeR)+1) rows = rows[0:totalRows] - columns = columns[0:totalRows] + columns = columns[0:totalColumns] random.shuffle(rows) random.shuffle(columns) offsetR = lightVal*self.shape.chiR @@ -73,8 +74,28 @@ class Simulator: assignedRows = [] assignedCols = [] + maliciousNodesCount = int((self.shape.maliciousNodes / 100) * self.shape.numberNodes) + remainingMaliciousNodes = maliciousNodesCount + for i in range(self.shape.numberNodes): - if self.config.evenLineDistribution: + if i == 0: + amImalicious_value = 0 + else: + if not self.config.randomizeMaliciousNodes: + # Assign based on predefined pattern when randomization is turned off + if i < maliciousNodesCount + 1: + amImalicious_value = 1 + else: + amImalicious_value = 0 + else: + # Randomly assign amImalicious_value when randomization is turned on + if remainingMaliciousNodes > 0 and random.random() < (self.shape.maliciousNodes / 100): + amImalicious_value = 1 + remainingMaliciousNodes -= 1 + else: + amImalicious_value = 0 + + if evenLineDistribution: if i < int(lightVal/self.shape.vpn1): # First start with the light nodes startR = i *self.shape.chiR*self.shape.vpn1 endR = (i+1)*self.shape.chiR*self.shape.vpn1 @@ -88,7 +109,7 @@ class Simulator: endC = offsetC+((j+1)*self.shape.chiC*self.shape.vpn2) r = rows[startR:endR] c = columns[startC:endC] - val = Validator(i, int(not i!=0), self.logger, self.shape, self.config, r, c) + val = Validator(i, int(not i!=0), amImalicious_value, self.logger, self.shape, self.config, r, c) self.logger.debug("Node %d has row IDs: %s" % (val.ID, val.rowIDs), extra=self.format) self.logger.debug("Node %d has column IDs: %s" % (val.ID, val.columnIDs), extra=self.format) assignedRows = assignedRows + list(r) @@ -97,7 +118,7 @@ class Simulator: self.nodeColumns.append(val.columnIDs) else: - val = Validator(i, int(not i!=0), self.logger, self.shape, self.config) + val = Validator(i, int(not i!=0), amImalicious_value, self.logger, self.shape, self.config) if i == self.proposerID: val.initBlock() else: @@ -151,7 +172,7 @@ class Simulator: val2.rowNeighbors[id].update({val1.ID : Neighbor(val1, 0, self.shape.blockSizeR)}) for id in range(self.shape.blockSizeR): - + if not columnChannels[id]: self.logger.error("No nodes for column %d !" % id, extra=self.format) continue @@ -230,7 +251,8 @@ class Simulator: self.glob.checkRowsColumns(self.validators) for i in range(0,self.shape.numberNodes): if i == self.proposerID: - self.validators[i].initBlock() + # self.validators[i].initBlock() + self.logger.warning("I am a block proposer.", extra=self.format) else: self.validators[i].logIDs() arrived, expected, ready, validatedall, validated = self.glob.checkStatus(self.validators) @@ -238,13 +260,17 @@ class Simulator: missingVector = [] progressVector = [] trafficStatsVector = [] + malicious_nodes_not_added_count = 0 steps = 0 while(True): missingVector.append(missingSamples) + self.logger.debug("Expected Samples: %d" % expected, extra=self.format) + self.logger.debug("Missing Samples: %d" % missingSamples, extra=self.format) oldMissingSamples = missingSamples self.logger.debug("PHASE SEND %d" % steps, extra=self.format) for i in range(0,self.shape.numberNodes): - self.validators[i].send() + if not self.validators[i].amImalicious: + self.validators[i].send() self.logger.debug("PHASE RECEIVE %d" % steps, extra=self.format) for i in range(1,self.shape.numberNodes): self.validators[i].receiveRowsColumns() @@ -307,6 +333,25 @@ class Simulator: break steps += 1 + for i in range(0,self.shape.numberNodes): + if not self.validators[i].amIaddedToQueue : + malicious_nodes_not_added_count += 1 + + for i in range(0,self.shape.numberNodes): + column_ids = [] + row_ids = [] + for rID in self.validators[i].rowIDs: + row_ids.append(rID) + for cID in self.validators[i].columnIDs: + column_ids.append(cID) + + self.logger.debug("List of columnIDs for %d node: %s", i, column_ids, extra=self.format) + self.logger.debug("List of rowIDs for %d node: %s", i, row_ids, extra=self.format) + + self.logger.debug("Number of malicious nodes not added to the send queue: %d" % malicious_nodes_not_added_count, extra=self.format) + malicious_nodes_not_added_percentage = (malicious_nodes_not_added_count * 100)/(self.shape.numberNodes) + self.logger.debug("Percentage of malicious nodes not added to the send queue: %d" % malicious_nodes_not_added_percentage, extra=self.format) + progress = pd.DataFrame(progressVector) if self.config.saveRCdist: self.result.addMetric("rowDist", self.distR) @@ -314,5 +359,5 @@ class Simulator: if self.config.saveProgress: self.result.addMetric("progress", progress.to_dict(orient='list')) self.result.populate(self.shape, self.config, missingVector) + self.result.copyValidators(self.validators) return self.result - diff --git a/DAS/validator.py b/DAS/validator.py index 2b489b8..d7ca2f5 100644 --- a/DAS/validator.py +++ b/DAS/validator.py @@ -38,7 +38,7 @@ class Validator: """It returns the validator ID.""" return str(self.ID) - def __init__(self, ID, amIproposer, logger, shape, config, rows = None, columns = None): + def __init__(self, ID, amIproposer, amImalicious, logger, shape, config, rows = None, columns = None): """It initializes the validator with the logger shape and rows/columns. If rows/columns are specified these are observed, otherwise (default) @@ -54,6 +54,15 @@ class Validator: self.receivedQueue = deque() self.sendQueue = deque() self.amIproposer = amIproposer + self.amImalicious = amImalicious + self.amIaddedToQueue = 0 + self.msgSentCount = 0 + self.msgRecvCount = 0 + self.sampleSentCount = 0 + self.sampleRecvCount = 0 + self.restoreRowCount = 0 + self.restoreColumnCount = 0 + self.repairedSampleCount = 0 self.logger = logger if self.shape.chiR < 1 and self.shape.chiC < 1: self.logger.error("Chi has to be greater than 0", extra=self.format) @@ -196,8 +205,10 @@ class Validator: if not self.receivedBlock.getSegment(rID, cID): self.logger.trace("Recv new: %d->%d: %d,%d", src, self.ID, rID, cID, extra=self.format) self.receivedBlock.setSegment(rID, cID) + self.sampleRecvCount += 1 if self.perNodeQueue or self.perNeighborQueue: self.receivedQueue.append((rID, cID)) + self.msgRecvCount += 1 else: self.logger.trace("Recv DUP: %d->%d: %d,%d", src, self.ID, rID, cID, extra=self.format) self.statsRxDupInSlot += 1 @@ -205,17 +216,23 @@ class Validator: def addToSendQueue(self, rID, cID): """Queue a segment for forwarding.""" - if self.perNodeQueue: + if self.perNodeQueue and not self.amImalicious: self.sendQueue.append((rID, cID)) + self.amIaddedToQueue = 1 + self.msgSentCount += 1 - if self.perNeighborQueue: + if self.perNeighborQueue and not self.amImalicious: if rID in self.rowIDs: for neigh in self.rowNeighbors[rID].values(): neigh.sendQueue.append(cID) + self.amIaddedToQueue = 1 + self.msgSentCount += 1 if cID in self.columnIDs: for neigh in self.columnNeighbors[cID].values(): neigh.sendQueue.append(rID) + self.amIaddedToQueue = 1 + self.msgSentCount += 1 def receiveRowsColumns(self): """Finalize time step by merging newly received segments in state.""" @@ -232,11 +249,14 @@ class Validator: neigh.received |= neigh.receiving neigh.receiving.setall(0) + for rID, cID in self.receivedQueue: + self.msgRecvCount += 1 # add newly received segments to the send queue if self.perNodeQueue or self.perNeighborQueue: while self.receivedQueue: (rID, cID) = self.receivedQueue.popleft() - self.addToSendQueue(rID, cID) + if not self.amImalicious: + self.addToSendQueue(rID, cID) def updateStats(self): """It updates the stats related to sent and received data.""" @@ -250,25 +270,27 @@ class Validator: def checkSegmentToNeigh(self, rID, cID, neigh): """Check if a segment should be sent to a neighbor.""" - if (neigh.sent | neigh.received).count(1) >= (self.sendLineUntilC if neigh.dim else self.sendLineUntilR): - return False # sent enough, other side can restore - i = rID if neigh.dim else cID - if not neigh.sent[i] and not neigh.received[i] : - return True + if not self.amImalicious: + if (neigh.sent | neigh.received).count(1) >= (self.sendLineUntilC if neigh.dim else self.sendLineUntilR): + return False # sent enough, other side can restore + i = rID if neigh.dim else cID + if not neigh.sent[i] and not neigh.received[i] : + return True else: - return False # received or already sent + return False # received or already sent or malicious def sendSegmentToNeigh(self, rID, cID, neigh): """Send segment to a neighbor (without checks).""" - self.logger.trace("sending %d/%d to %d", rID, cID, neigh.node.ID, extra=self.format) - i = rID if neigh.dim else cID - neigh.sent[i] = 1 - neigh.node.receiveSegment(rID, cID, self.ID) - self.statsTxInSlot += 1 + if not self.amImalicious: + self.logger.trace("sending %d/%d to %d", rID, cID, neigh.node.ID, extra=self.format) + i = rID if neigh.dim else cID + neigh.sent[i] = 1 + neigh.node.receiveSegment(rID, cID, self.ID) + self.statsTxInSlot += 1 def checkSendSegmentToNeigh(self, rID, cID, neigh): """Check and send a segment to a neighbor if needed.""" - if self.checkSegmentToNeigh(rID, cID, neigh): + if self.checkSegmentToNeigh(rID, cID, neigh) and not self.amImalicious: self.sendSegmentToNeigh(rID, cID, neigh) return True else: @@ -283,16 +305,18 @@ class Validator: while self.sendQueue: (rID, cID) = self.sendQueue[0] - if rID in self.rowIDs: + if rID in self.rowIDs and not self.amImalicious: for _, neigh in shuffledDict(self.rowNeighbors[rID], self.shuffleNeighbors): - self.checkSendSegmentToNeigh(rID, cID, neigh) + if not self.amImalicious: + self.checkSendSegmentToNeigh(rID, cID, neigh) if self.statsTxInSlot >= self.bwUplink: return - if cID in self.columnIDs: + if cID in self.columnIDs and not self.amImalicious: for _, neigh in shuffledDict(self.columnNeighbors[cID], self.shuffleNeighbors): - self.checkSendSegmentToNeigh(rID, cID, neigh) + if not self.amImalicious: + self.checkSendSegmentToNeigh(rID, cID, neigh) if self.statsTxInSlot >= self.bwUplink: return @@ -317,19 +341,20 @@ class Validator: # collect and shuffle for rID, neighs in self.rowNeighbors.items(): for neigh in neighs.values(): - if (neigh.sendQueue): + if (neigh.sendQueue) and not self.amImalicious: queues.append((0, rID, neigh)) for cID, neighs in self.columnNeighbors.items(): for neigh in neighs.values(): - if (neigh.sendQueue): + if (neigh.sendQueue) and not self.amImalicious: queues.append((1, cID, neigh)) for dim, lineID, neigh in shuffled(queues, self.shuffleQueues): - if dim == 0: - self.checkSendSegmentToNeigh(lineID, neigh.sendQueue.popleft(), neigh) - else: - self.checkSendSegmentToNeigh(neigh.sendQueue.popleft(), lineID, neigh) + if not self.amImalicious: + if dim == 0: + self.checkSendSegmentToNeigh(lineID, neigh.sendQueue.popleft(), neigh) + else: + self.checkSendSegmentToNeigh(neigh.sendQueue.popleft(), lineID, neigh) progress = True if self.statsTxInSlot >= self.bwUplink: return @@ -345,32 +370,32 @@ class Validator: def collectSegmentsToSend(): # yields list of segments to send as (dim, lineID, id) segmentsToSend = [] - for rID, neighs in self.rowNeighbors.items(): - line = self.getRow(rID) - needed = zeros(self.shape.blockSizeR) - for neigh in neighs.values(): - sentOrReceived = neigh.received | neigh.sent - if sentOrReceived.count(1) < self.sendLineUntilR: - needed |= ~sentOrReceived - needed &= line - if (needed).any(): - for i in range(len(needed)): - if needed[i]: - segmentsToSend.append((0, rID, i)) - - for cID, neighs in self.columnNeighbors.items(): - line = self.getColumn(cID) - needed = zeros(self.shape.blockSizeC) - for neigh in neighs.values(): - sentOrReceived = neigh.received | neigh.sent - if sentOrReceived.count(1) < self.sendLineUntilC: - needed |= ~sentOrReceived - needed &= line - if (needed).any(): - for i in range(len(needed)): - if needed[i]: - segmentsToSend.append((1, cID, i)) + if not self.amImalicious: + for rID, neighs in self.rowNeighbors.items(): + line = self.getRow(rID) + needed = zeros(self.shape.blockSizeR) + for neigh in neighs.values(): + sentOrReceived = neigh.received | neigh.sent + if sentOrReceived.count(1) < self.sendLineUntilR: + needed |= ~sentOrReceived + needed &= line + if (needed).any(): + for i in range(len(needed)): + if needed[i]: + segmentsToSend.append((0, rID, i)) + for cID, neighs in self.columnNeighbors.items(): + line = self.getColumn(cID) + needed = zeros(self.shape.blockSizeC) + for neigh in neighs.values(): + sentOrReceived = neigh.received | neigh.sent + if sentOrReceived.count(1) < self.sendLineUntilC: + needed |= ~sentOrReceived + needed &= line + if (needed).any(): + for i in range(len(needed)): + if needed[i]: + segmentsToSend.append((1, cID, i)) return segmentsToSend def nextSegment(): @@ -380,12 +405,12 @@ class Validator: for dim, lineID, id in self.segmentShuffleGen: if dim == 0: for _, neigh in shuffledDict(self.rowNeighbors[lineID], self.shuffleNeighbors): - if self.checkSegmentToNeigh(lineID, id, neigh): + if self.checkSegmentToNeigh(lineID, id, neigh) and not self.amImalicious: yield((lineID, id, neigh)) break else: for _, neigh in shuffledDict(self.columnNeighbors[lineID], self.shuffleNeighbors): - if self.checkSegmentToNeigh(id, lineID, neigh): + if self.checkSegmentToNeigh(id, lineID, neigh) and not self.amImalicious: yield((id, lineID, neigh)) break @@ -400,7 +425,8 @@ class Validator: for rid, cid, neigh in nextSegment(): # segments are checked just before yield, so we can send directly - self.sendSegmentToNeigh(rid, cid, neigh) + if not self.amImalicious: + self.sendSegmentToNeigh(rid, cid, neigh) if self.statsTxInSlot >= self.bwUplink: if not self.segmentShuffleSchedulerPersist: @@ -425,7 +451,7 @@ class Validator: cID = random.randrange(0, self.shape.blockSizeR) if self.block.getSegment(rID, cID) : neigh = random.choice(list(self.rowNeighbors[rID].values())) - if self.checkSegmentToNeigh(rID, cID, neigh): + if self.checkSegmentToNeigh(rID, cID, neigh) and not self.amImalicious: yield(rID, cID, neigh) t = tries if self.columnIDs: @@ -433,14 +459,15 @@ class Validator: rID = random.randrange(0, self.shape.blockSizeC) if self.block.getSegment(rID, cID) : neigh = random.choice(list(self.columnNeighbors[cID].values())) - if self.checkSegmentToNeigh(rID, cID, neigh): + if self.checkSegmentToNeigh(rID, cID, neigh) and not self.amImalicious: yield(rID, cID, neigh) t = tries t -= 1 for rid, cid, neigh in nextSegment(): # segments are checked just before yield, so we can send directly - self.sendSegmentToNeigh(rid, cid, neigh) + if not self.amImalicious: + self.sendSegmentToNeigh(rid, cid, neigh) if self.statsTxInSlot >= self.bwUplink: return @@ -449,22 +476,24 @@ class Validator: """ Send as much as we can in the timestep, limited by bwUplink.""" # process node level send queue - self.processSendQueue() + if not self.amImalicious: + self.processSendQueue() if self.statsTxInSlot >= self.bwUplink: return # process neighbor level send queues in shuffled breadth-first order - self.processPerNeighborSendQueue() + if not self.amImalicious: + self.processPerNeighborSendQueue() if self.statsTxInSlot >= self.bwUplink: return # process possible segments to send in shuffled breadth-first order - if self.segmentShuffleScheduler: + if self.segmentShuffleScheduler and not self.amImalicious: self.runSegmentShuffleScheduler() if self.statsTxInSlot >= self.bwUplink: return - if self.dumbRandomScheduler: + if self.dumbRandomScheduler and not self.amImalicious: self.runDumbRandomScheduler() if self.statsTxInSlot >= self.bwUplink: return @@ -489,14 +518,17 @@ class Validator: def restoreRow(self, id): """Restore a given row if repairable.""" - rep = self.block.repairRow(id) + rep, repairedSamples = self.block.repairRow(id) + self.repairedSampleCount += repairedSamples if (rep.any()): # If operation is based on send queues, segments should # be queued after successful repair. + self.restoreRowCount += 1 for i in range(len(rep)): if rep[i]: self.logger.trace("Rep: %d,%d", id, i, extra=self.format) - self.addToSendQueue(id, i) + if not self.amImalicious: + self.addToSendQueue(id, i) # self.statsRepairInSlot += rep.count(1) def restoreColumns(self): @@ -507,14 +539,17 @@ class Validator: def restoreColumn(self, id): """Restore a given column if repairable.""" - rep = self.block.repairColumn(id) + rep, repairedSamples = self.block.repairColumn(id) + self.repairedSampleCount += repairedSamples if (rep.any()): # If operation is based on send queues, segments should # be queued after successful repair. + self.restoreColumnCount += 1 for i in range(len(rep)): if rep[i]: self.logger.trace("Rep: %d,%d", i, id, extra=self.format) - self.addToSendQueue(i, id) + if not self.amImalicious: + self.addToSendQueue(i, id) # self.statsRepairInSlot += rep.count(1) def checkStatus(self): @@ -542,4 +577,4 @@ class Validator: if a == e: validated+=1 - return arrived, expected, validated + return arrived, expected, validated \ No newline at end of file diff --git a/DAS/visualizer.py b/DAS/visualizer.py index 2f12547..db2b021 100644 --- a/DAS/visualizer.py +++ b/DAS/visualizer.py @@ -241,21 +241,6 @@ class Visualizer: plt.savefig(filename) plt.clf() - def plotHist(self, bandwidth): - """Plot Bandwidth Frequency Histogram""" - plt.hist(bandwidth, bins=5) - plt.xlabel('Bandwidth') - plt.ylabel('Frequency') - plt.title('Bandwidth Histogram') - - """Create the directory if it doesn't exist already""" - histogramFolder = self.folderPath + '/histogram' - if not os.path.exists(histogramFolder): - os.makedirs(histogramFolder) - filename = os.path.join(histogramFolder, 'histogram.png') - plt.savefig(filename) - plt.clf() - def plotCandleStick(self, TX_prod, TX_avg, TX_max): #x-axis corresponding to steps steps = range(len(TX_prod)) @@ -274,4 +259,4 @@ class Visualizer: plt.ylabel('Price') #Test - plt.show() + plt.show() \ No newline at end of file diff --git a/DAS/visualizor.py b/DAS/visualizor.py index 5eab2f7..b57cfd7 100644 --- a/DAS/visualizor.py +++ b/DAS/visualizor.py @@ -1,23 +1,33 @@ #!/bin/python3 import matplotlib.pyplot as plt +import seaborn as sns import numpy as np import os def plotData(conf): plt.clf() fig = plt.figure("9, 3") + plt.grid(True) if conf["desLoc"] == 1: xDes = 0 else: xDes = conf["xdots"][-1] * 0.6 props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) - plt.text(xDes, conf["yaxismax"]/4, conf["textBox"], fontsize=10, verticalalignment='top', bbox=props) - for i in range(len(conf["data"])): - if conf["type"] == "plot": + plt.text(xDes, conf["yaxismax"]/3, conf["textBox"], fontsize=10, verticalalignment='top', bbox=props) + if conf["type"] == "plot" or conf["type"] == "plot_with_1line": + for i in range(len(conf["data"])): plt.plot(conf["xdots"], conf["data"][i], conf["colors"][i], label=conf["labels"][i]) - if conf["type"] == "bar": + elif conf["type"] == "individual_bar" or conf["type"] == "individual_bar_with_2line": + plt.bar(conf["xdots"], conf["data"]) + elif conf["type"] == "grouped_bar": + for i in range(len(conf["data"])): plt.bar(conf["xdots"], conf["data"][i], label=conf["labels"][i]) + if conf["type"] == "individual_bar_with_2line": + plt.axhline(y = conf["expected_value1"], color='r', linestyle='--', label=conf["line_label1"]) + plt.axhline(y = conf["expected_value2"], color='g', linestyle='--', label=conf["line_label2"]) + if conf["type"] == "plot_with_1line": + plt.axhline(y = conf["expected_value"], color='g', linestyle='--', label=conf["line_label"]) plt.title(conf["title"]) plt.ylabel(conf["ylabel"]) plt.xlabel(conf["xlabel"]) @@ -25,6 +35,20 @@ def plotData(conf): plt.legend(loc=conf["legLoc"]) plt.savefig(conf["path"], bbox_inches="tight") +def plotBoxData(conf): + plt.clf() + plt.grid(True) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + num_boxes = len(conf["data"]) + positions = np.arange(num_boxes) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.boxplot(conf["data"], patch_artist=True, showmeans=True, meanline=True, positions=positions) + plt.title(conf["title"], fontsize=14) + plt.ylabel(conf["ylabel"], fontsize=12) + plt.xlabel(conf["xlabel"], fontsize=12) + plt.xticks(fontsize=10) + plt.yticks(fontsize=10) + plt.savefig(conf["path"], bbox_inches="tight") class Visualizor: """This class helps the visualization of the results""" @@ -39,7 +63,7 @@ class Visualizor: def __get_attrbs__(self, result): text = str(result.shape).split("-") d = dict() - for i in range(0, len(text), 2): + for i in range(1, len(text), 2): d[text[i]] = text[i + 1] return d @@ -69,6 +93,32 @@ class Visualizor: + def plotHeatmaps(self, x, y): + """Plot the heatmap using the parameters given as x axis and y axis""" + print("Plotting heatmap "+x+" vs "+y) + #Find the location of x in shape + #Find the location of y in shape + #Find the location od r in shape + + #Loop over all results + #Add unique values foir every parameter + + #Find number of runs from r + #If number of values for x and y > 3 then plot heatmap, otherwise finish + + #Create a 2D grid with the dimensions of the number of values for x and y + #For all values of x + #For all values of y + # For all values in r + #Fixing all other values to 1 (in the mean time) + #Add/sum TTA into 2D grid + #if last r divide by number of runs + + #Plot 2D grid + + + + def plotAll(self): """Plot all the important elements of each result""" for result in self.results: @@ -79,17 +129,573 @@ class Visualizor: self.plotSentData(result, plotPath) self.plotRecvData(result, plotPath) self.plotDupData(result, plotPath) - if self.config.saveRCdist: - self.plotRowCol(result, plotPath) + # self.plotSamplesRepaired(result, plotPath) + # self.plotMessagesSent(result, plotPath) + # self.plotMessagesRecv(result, plotPath) + # self.plotSampleRecv(result, plotPath) + # self.plotRestoreRowCount(result, plotPath) + # self.plotRestoreColumnCount(result, plotPath) + # if self.config.saveRCdist: + # self.plotRowCol(result, plotPath) + + # self.plotBoxSamplesRepaired(result, plotPath) + # self.plotBoxMessagesSent(result, plotPath) + # self.plotBoxMessagesRecv(result, plotPath) + # self.plotBoxSampleRecv(result, plotPath) + # self.plotBoxRestoreColumnCount(result, plotPath) + # self.plotBoxRestoreRowCount(result, plotPath) + # if self.config.saveRCdist: + # self.plotBoxRowCol(result, plotPath) + + self.plotBoxenSamplesRepaired(result, plotPath) + self.plotBoxenMessagesSent(result, plotPath) + self.plotBoxenMessagesRecv(result, plotPath) + self.plotBoxenSamplesRecv(result, plotPath) + self.plotBoxenRestoreRowCount(result, plotPath) + self.plotBoxenRestoreColumnCount(result, plotPath) + if self.config.saveRCdist: + self.plotBoxenRowColDist(result, plotPath) + + self.plotECDFSamplesRepaired(result, plotPath) + self.plotECDFMessagesSent(result, plotPath) + self.plotECDFMessagesRecv(result, plotPath) + self.plotECDFSamplesReceived(result, plotPath) + self.plotECDFRestoreRowCount(result, plotPath) + self.plotECDFRestoreColumnCount(result, plotPath) + if self.config.saveRCdist: + self.plotECDFRowColDist(result, plotPath) + + + def plotBoxRestoreRowCount(self, result, plotPath): + """Box Plot of restoreRowCount for all nodes""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Box Plot of Restore Row Count by Nodes" + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Restore Row Count" + n1 = int(result.numberNodes * result.class1ratio) + class1_data = result.restoreRowCount[1: n1] + class2_data = result.restoreRowCount[n1+1: ] + data = [class1_data, class2_data] + plt.boxplot(data) + plt.xticks([1, 2], ['Class 1 Nodes', 'Class 2 Nodes']) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/box_restoreRowCount.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/box_restoreRowCount.png")) + + def plotBoxRestoreColumnCount(self, result, plotPath): + """Box Plot of restoreColumnCount for all nodes""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Box Plot of Restore Column Count by Nodes" + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Restore Column Count" + n1 = int(result.numberNodes * result.class1ratio) + class1_data = result.restoreColumnCount[1: n1] + class2_data = result.restoreColumnCount[n1+1: ] + data = [class1_data, class2_data] + plt.boxplot(data) + plt.xticks([1, 2], ['Class 1 Nodes', 'Class 2 Nodes']) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/box_restoreColumnCount.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/box_restoreColumnCount.png")) + + def plotBoxenRestoreRowCount(self, result, plotPath): + """Plots the Boxen plot of restoreRowCount for all nodes""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Boxen Plot of Restore Row Count by Nodes" + conf["xlabel"] = "Restore Row Count" + conf["ylabel"] = "Nodes" + n1 = int(result.numberNodes * result.class1ratio) + data = [result.restoreRowCount[1: n1], result.restoreRowCount[n1+1: ]] + plt.figure(figsize=(8, 6)) + sns.boxenplot(data=data, width=0.8) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/boxen_restoreRowCount.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/boxen_restoreRowCount.png")) + + def plotBoxenRestoreColumnCount(self, result, plotPath): + """Plots the Boxen plot of restoreColumnCount for all nodes""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Boxen Plot of Restore Column Count by Nodes" + conf["xlabel"] = "Restore Column Count" + conf["ylabel"] = "Nodes" + n1 = int(result.numberNodes * result.class1ratio) + data = [result.restoreColumnCount[1: n1], result.restoreColumnCount[n1+1: ]] + plt.figure(figsize=(8, 6)) + sns.boxenplot(data=data, width=0.8) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/boxen_restoreColumnCount.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/boxen_restoreColumnCount.png")) + + def plotECDFRestoreRowCount(self, result, plotPath): + """Plots the ECDF of restoreRowCount for all nodes using seaborn's ecdfplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "ECDF of Restore Row Count by Nodes" + conf["xlabel"] = "Restore Row Count" + conf["ylabel"] = "ECDF" + n1 = int(result.numberNodes * result.class1ratio) + class1_data = result.restoreRowCount[1: n1] + class2_data = result.restoreRowCount[n1+1: ] + sns.ecdfplot(data=class1_data, label='Class 1 Nodes') + sns.ecdfplot(data=class2_data, label='Class 2 Nodes') + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + plt.xlim(left=0, right=max(result.restoreRowCount) * 1.1) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.legend(title='Node Class', labels=['Class 1 Nodes', 'Class 2 Nodes'], loc=1) + plt.savefig(plotPath + "/ecdf_restoreRowCount.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/ecdf_restoreRowCount.png")) + + def plotECDFRestoreColumnCount(self, result, plotPath): + """Plots the ECDF of restoreColumnCount for all nodes using seaborn's ecdfplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "ECDF of Restore Column Count by Nodes" + conf["xlabel"] = "Restore Column Count" + conf["ylabel"] = "ECDF" + n1 = int(result.numberNodes * result.class1ratio) + class1_data = result.restoreColumnCount[1: n1] + class2_data = result.restoreColumnCount[n1+1: ] + sns.ecdfplot(data=class1_data, label='Class 1 Nodes') + sns.ecdfplot(data=class2_data, label='Class 2 Nodes') + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + plt.xlim(left=0, right=max(result.restoreColumnCount) * 1.1) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.legend(title='Node Class', labels=['Class 1 Nodes', 'Class 2 Nodes'], loc=1) + plt.savefig(plotPath + "/ecdf_restoreColumnCount.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/ecdf_restoreColumnCount.png")) + + def plotECDFMessagesSent(self, result, plotPath): + """Plots the ECDF of messages sent by all nodes using seaborn's ecdfplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "ECDF of Messages Sent by Nodes" + conf["xlabel"] = "Number of Messages Sent" + conf["ylabel"] = "ECDF" + n1 = int(result.numberNodes * result.class1ratio) + class1_data = result.msgSentCount[1: n1] + class2_data = result.msgSentCount[n1+1: ] + sns.ecdfplot(data=class1_data, label='Class 1 Nodes') + sns.ecdfplot(data=class2_data, label='Class 2 Nodes') + plt.legend(title='Node Class', labels=['Class 1 Nodes', 'Class 2 Nodes'], loc=1) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + plt.xlim(left=0, right=max(result.msgSentCount) * 1.1) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/ecdf_messagesSent.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/ecdf_messagesSent.png")) + + def plotECDFMessagesRecv(self, result, plotPath): + """Plots the ECDF of messages received by all nodes using seaborn's ecdfplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "ECDF of Messages Received by Nodes" + conf["xlabel"] = "Number of Messages Received" + conf["ylabel"] = "ECDF" + n1 = int(result.numberNodes * result.class1ratio) + class1_data = result.msgRecvCount[1: n1] + class2_data = result.msgRecvCount[n1+1: ] + sns.ecdfplot(data=class1_data, label='Class 1 Nodes') + sns.ecdfplot(data=class2_data, label='Class 2 Nodes') + plt.legend(title='Node Class', labels=['Class 1 Nodes', 'Class 2 Nodes'], loc=1) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + plt.xlim(left=0, right=max(result.msgRecvCount) * 1.1) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/ecdf_messagesRecv.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/ecdf_messagesRecv.png")) + + def plotECDFSamplesReceived(self, result, plotPath): + """Plots the ECDF of samples received by all nodes using seaborn's ecdfplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "ECDF of Samples Received by Nodes" + conf["xlabel"] = "Number of Samples Received" + conf["ylabel"] = "ECDF" + n1 = int(result.numberNodes * result.class1ratio) + class1_data = result.sampleRecvCount[1: n1] + class2_data = result.sampleRecvCount[n1+1: ] + sns.ecdfplot(data=class1_data, label='Class 1 Nodes') + sns.ecdfplot(data=class2_data, label='Class 2 Nodes') + plt.legend(title='Node Class', labels=['Class 1 Nodes', 'Class 2 Nodes'], loc=1) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + plt.xlim(left=0, right=max(result.sampleRecvCount) * 1.1) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/ecdf_samplesReceived.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/ecdf_samplesReceived.png")) + + def plotECDFRowColDist(self, result, plotPath): + """Plots the ECDF of row col distance by all nodes using seaborn's ecdfplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "ECDF of Row-Col Distance by Nodes" + conf["xlabel"] = "Row-Col Distance" + conf["ylabel"] = "ECDF" + vector1 = result.metrics["rowDist"] + vector2 = result.metrics["columnDist"] + n1 = int(result.numberNodes * result.class1ratio) + sns.ecdfplot(data=vector1, label='Rows') + sns.ecdfplot(data=vector2, label='Columns') + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + plt.xlim(left=0, right=max(max(vector1), max(vector2)) * 1.1) + plt.legend(labels=['Row Dist', 'Column Dist'], loc=1) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/ecdf_rowColDist.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/ecdf_rowColDist.png")) + + def plotECDFSamplesRepaired(self, result, plotPath): + """Plots the ECDF of samples repaired by all nodes using seaborn's ecdfplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "ECDF of Samples Repaired by Nodes" + conf["xlabel"] = "Number of Samples Repaired" + conf["ylabel"] = "ECDF" + n1 = int(result.numberNodes * result.class1ratio) + class1_data = result.repairedSampleCount[1: n1] + class2_data = result.repairedSampleCount[n1+1: ] + sns.ecdfplot(data=class1_data, label='Class 1 Nodes') + sns.ecdfplot(data=class2_data, label='Class 2 Nodes') + plt.legend(title='Node Class', labels=['Class 1 Nodes', 'Class 2 Nodes']) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + plt.xlim(left=0, right=max(result.repairedSampleCount) * 1.1) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/ecdf_samplesRepaired.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/ecdf_samplesRepaired.png")) + + def plotBoxenSamplesRecv(self, result, plotPath): + """Boxen Plot of the number of samples received by all nodes""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Samples Received by Nodes" + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Number of Samples Received" + n1 = int(result.numberNodes * result.class1ratio) + data = [result.sampleRecvCount[1: n1], result.sampleRecvCount[n1+1: ]] + plt.figure(figsize=(8, 6)) + sns.boxenplot(data=data, width=0.8) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.tight_layout() + plt.savefig(plotPath + "/boxen_samplesRecv.png") + plt.close() + print("Plot %s created." % (plotPath + "/boxen_samplesRecv.png")) + + def plotBoxenSamplesRepaired(self, result, plotPath): + """Boxen Plot of the number of samples repaired by all nodes""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Samples Repaired by Nodes" + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Number of Samples Repaired" + n1 = int(result.numberNodes * result.class1ratio) + data = [result.repairedSampleCount[1: n1], result.repairedSampleCount[n1+1: ]] + plt.figure(figsize=(8, 6)) + sns.boxenplot(data=data, width=0.8) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.tight_layout() + plt.savefig(plotPath + "/boxen_samplesRepaired.png") + plt.close() + print("Plot %s created." % (plotPath + "/boxen_samplesRepaired.png")) + + def plotBoxenRowColDist(self, result, plotPath): + """Boxen Plot of the Row/Column distribution""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Row/Column Distribution" + conf["xlabel"] = "Row/Column Type" + conf["ylabel"] = "Validators Subscribed" + vector1 = result.metrics["rowDist"] + vector2 = result.metrics["columnDist"] + if len(vector1) > len(vector2): + vector2 += [np.nan] * (len(vector1) - len(vector2)) + elif len(vector1) < len(vector2): + vector1 += [np.nan] * (len(vector2) - len(vector1)) + data = [vector1, vector2] + plt.figure(figsize=(8, 6)) + sns.boxenplot(data=data, width=0.8) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.tight_layout() + plt.savefig(plotPath + "/boxen_rowColDist.png") + plt.close() + print("Plot %s created." % (plotPath + "/boxen_rowColDist.png")) + + def plotBoxenMessagesSent(self, result, plotPath): + """Plots the number of messages sent by all nodes using seaborn's boxenplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Messages Sent by Nodes" + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Number of Messages Sent" + n1 = int(result.numberNodes * result.class1ratio) + data = [result.msgSentCount[1: n1], result.msgSentCount[n1+1: ]] + labels = ["Class 1", "Class 2"] + sns.boxenplot(data=data, palette="Set2", ax=plt.gca()) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/boxen_messagesSent.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/boxen_messagesSent.png")) + + def plotBoxenMessagesRecv(self, result, plotPath): + """Plots the number of messages received by all nodes using seaborn's boxenplot""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Messages Received by Nodes" + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Number of Messages Received" + n1 = int(result.numberNodes * result.class1ratio) + data = [result.msgRecvCount[1: n1], result.msgRecvCount[n1+1: ]] + labels = ["Class 1", "Class 2"] + sns.boxenplot(data=data, palette="Set2", ax=plt.gca()) + plt.xlabel(conf["xlabel"]) + plt.ylabel(conf["ylabel"]) + plt.title(conf["title"]) + props = dict(boxstyle='round', facecolor='wheat', alpha=0.5) + plt.text(0.05, 0.05, conf["textBox"], fontsize=10, verticalalignment='bottom', transform=plt.gca().transAxes, bbox=props) + plt.savefig(plotPath + "/boxen_messagesRecv.png", bbox_inches="tight") + print("Plot %s created." % (plotPath + "/boxen_messagesRecv.png")) + + def plotBoxSamplesRepaired(self, result, plotPath): + """Box Plot of the number of samples repaired by all nodes""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Samples Repaired by Nodes" + conf["type"] = "individual_bar" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Number of Samples Repaired" + n1 = int(result.numberNodes * result.class1ratio) + conf["data"] = [result.repairedSampleCount[1: n1], result.repairedSampleCount[n1+1: ]] + conf["path"] = plotPath + "/box_samplesRepaired.png" + plotBoxData(conf) + print("Plot %s created." % conf["path"]) + + def plotBoxRowCol(self, result, plotPath): + """Box Plot of the Row/Column distribution""" + plt.clf() + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Row/Column Distribution" + conf["xlabel"] = "" + conf["ylabel"] = "Validators Subscribed" + vector1 = result.metrics["rowDist"] + vector2 = result.metrics["columnDist"] + if len(vector1) > len(vector2): + vector2 += [np.nan] * (len(vector1) - len(vector2)) + elif len(vector1) < len(vector2): + vector1 += [np.nan] * (len(vector2) - len(vector1)) + n1 = int(result.numberNodes * result.class1ratio) + conf["data"] = [vector1, vector2] + conf["path"] = plotPath + "/box_rowColDist.png" + plotBoxData(conf) + print("Plot %s created." % conf["path"]) + + def plotRestoreRowCount(self, result, plotPath): + """Plots the restoreRowCount for each node""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Restore Row Count for Each Node" + conf["type"] = "individual_bar" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Nodes" + conf["ylabel"] = "Restore Row Count" + conf["data"] = result.restoreRowCount + conf["xdots"] = range(result.shape.numberNodes) + conf["path"] = plotPath + "/restoreRowCount.png" + maxi = max(conf["data"]) + conf["yaxismax"] = maxi + plotData(conf) + print("Plot %s created." % conf["path"]) + + def plotRestoreColumnCount(self, result, plotPath): + """Plots the restoreColumnCount for each node""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Restore Column Count for Each Node" + conf["type"] = "individual_bar" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Nodes" + conf["ylabel"] = "Restore Column Count" + conf["data"] = result.restoreColumnCount + conf["xdots"] = range(result.shape.numberNodes) + conf["path"] = plotPath + "/restoreColumnCount.png" + maxi = max(conf["data"]) + conf["yaxismax"] = maxi + plotData(conf) + print("Plot %s created." % conf["path"]) + + def plotSampleRecv(self, result, plotPath): + """Plots the percentage sampleRecv for each node""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Percentage of Samples Received by Nodes" + conf["type"] = "individual_bar_with_2line" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Nodes" + conf["ylabel"] = "Percentage of samples received (%)" + total_samples = result.shape.blockSizeR * result.shape.blockSizeC + percentage_data = [(count / total_samples) * 100 for count in result.sampleRecvCount] + conf["data"] = percentage_data + conf["xdots"] = range(result.shape.numberNodes) + conf["path"] = plotPath + "/sampleRecv.png" + maxi = max(conf["data"]) + # conf["yaxismax"] = maxi * 1.1 + expected_percentage1 = (result.shape.vpn1 * (result.shape.blockSizeR * result.shape.chiR + result.shape.blockSizeC * result.shape.chiC) * 100)/total_samples + expected_percentage2 = (result.shape.vpn2 * (result.shape.blockSizeR * result.shape.chiR + result.shape.blockSizeC * result.shape.chiC) * 100)/total_samples + if expected_percentage1 > 100: + expected_percentage1 = 100 + if expected_percentage2 > 100: + expected_percentage2 = 100 + conf["expected_value1"] = expected_percentage1 + conf["expected_value2"] = expected_percentage2 + conf["line_label1"] = "Expected Value for class 1 nodes" + conf["line_label2"] = "Expected Value for class 2 nodes" + conf["yaxismax"] = max(expected_percentage1, expected_percentage2) * 1.05 + plotData(conf) + print("Plot %s created." % conf["path"]) + + def plotBoxSampleRecv(self, result, plotPath): + """Box Plot of the sampleRecv for each node""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Samples Received by Nodes" + conf["type"] = "individual_bar_with_2line" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Number of samples received (%)" + n1 = int(result.numberNodes * result.class1ratio) + conf["data"] = [result.sampleRecvCount[1: n1], result.sampleRecvCount[n1+1: ]] + conf["xdots"] = range(result.shape.numberNodes) + conf["path"] = plotPath + "/box_sampleRecv.png" + plotBoxData(conf) + print("Plot %s created." % conf["path"]) + def plotMissingSamples(self, result, plotPath): """Plots the missing samples in the network""" conf = {} attrbs = self.__get_attrbs__(result) conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ - +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+" \nNetwork degree: "+attrbs['nd'] + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] conf["title"] = "Missing Samples" - conf["type"] = "plot" + conf["type"] = "plot_with_1line" conf["legLoc"] = 1 conf["desLoc"] = 1 conf["colors"] = ["m-"] @@ -104,18 +710,21 @@ class Visualizor: if max(v) > maxi: maxi = max(v) conf["yaxismax"] = maxi + x = result.shape.blockSizeR * result.shape.chiR + result.shape.blockSizeC * result.shape.chiC + conf["expected_value"] = (result.shape.numberNodes - 1) * (result.shape.class1ratio * result.shape.vpn1 * x + (1 - result.shape.class1ratio) * result.shape.vpn2 * x) + conf["line_label"] = "Total samples to deliver" plotData(conf) print("Plot %s created." % conf["path"]) def plotProgress(self, result, plotPath): """Plots the percentage of nodes ready in the network""" - vector1 = result.metrics["progress"]["nodes ready"] - vector2 = result.metrics["progress"]["validators ready"] - vector3 = result.metrics["progress"]["samples received"] + vector1 = [x * 100 for x in result.metrics["progress"]["nodes ready"]] + vector2 = [x * 100 for x in result.metrics["progress"]["validators ready"]] + vector3 = [x * 100 for x in result.metrics["progress"]["samples received"]] conf = {} attrbs = self.__get_attrbs__(result) conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ - +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+" \nNetwork degree: "+attrbs['nd'] + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] conf["title"] = "Nodes/validators ready" conf["type"] = "plot" conf["legLoc"] = 2 @@ -147,7 +756,7 @@ class Visualizor: conf = {} attrbs = self.__get_attrbs__(result) conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ - +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+" \nNetwork degree: "+attrbs['nd'] + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] conf["title"] = "Sent data" conf["type"] = "plot" conf["legLoc"] = 2 @@ -177,7 +786,7 @@ class Visualizor: conf = {} attrbs = self.__get_attrbs__(result) conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ - +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+" \nNetwork degree: "+attrbs['nd'] + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] conf["title"] = "Received data" conf["type"] = "plot" conf["legLoc"] = 2 @@ -207,7 +816,7 @@ class Visualizor: conf = {} attrbs = self.__get_attrbs__(result) conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ - +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+" \nNetwork degree: "+attrbs['nd'] + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] conf["title"] = "Duplicated data" conf["type"] = "plot" conf["legLoc"] = 2 @@ -238,9 +847,9 @@ class Visualizor: conf = {} attrbs = self.__get_attrbs__(result) conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ - +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+" \nNetwork degree: "+attrbs['nd'] + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] conf["title"] = "Row/Column distribution" - conf["type"] = "bar" + conf["type"] = "grouped_bar" conf["legLoc"] = 2 conf["desLoc"] = 2 conf["colors"] = ["r+", "b+"] @@ -258,3 +867,98 @@ class Visualizor: plotData(conf) print("Plot %s created." % conf["path"]) + def plotMessagesSent(self, result, plotPath): + """Plots the number of messages sent by all nodes""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Messages Sent by Nodes" + conf["type"] = "individual_bar" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Nodes" + conf["ylabel"] = "Number of Messages Sent" + conf["data"] = result.msgSentCount + conf["xdots"] = range(result.shape.numberNodes) + conf["path"] = plotPath + "/messagesSent.png" + maxi = max(conf["data"]) + conf["yaxismax"] = maxi + plotData(conf) + print("Plot %s created." % conf["path"]) + + def plotBoxMessagesSent(self, result, plotPath): + """Box Plot of the number of messages sent by all nodes""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Messages Sent by Nodes" + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Number of Messages Sent" + n1 = int(result.numberNodes * result.class1ratio) + conf["data"] = [result.msgSentCount[1: n1], result.msgSentCount[n1+1: ]] + conf["path"] = plotPath + "/box_messagesSent.png" + plotBoxData(conf) + print("Plot %s created." % conf["path"]) + + def plotMessagesRecv(self, result, plotPath): + """Plots the number of messages received by all nodes""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Messages Received by Nodes" + conf["type"] = "individual_bar" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Nodes" + conf["ylabel"] = "Number of Messages Received" + conf["data"] = result.msgRecvCount + conf["xdots"] = range(result.shape.numberNodes) + conf["path"] = plotPath + "/messagesRecv.png" + maxi = max(conf["data"]) + conf["yaxismax"] = maxi + plotData(conf) + print("Plot %s created." % conf["path"]) + + def plotBoxMessagesRecv(self, result, plotPath): + """Plots the number of messages received by all nodes""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Messages Received by Nodes" + conf["type"] = "individual_bar" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Node Type" + conf["ylabel"] = "Number of Messages Received" + n1 = int(result.numberNodes * result.class1ratio) + conf["data"] = [result.msgRecvCount[1: n1], result.msgRecvCount[n1+1: ]] + conf["xdots"] = range(result.shape.numberNodes) + conf["path"] = plotPath + "/box_messagesRecv.png" + maxi = max(conf["data"]) + conf["yaxismax"] = maxi + plotBoxData(conf) + print("Plot %s created." % conf["path"]) + + def plotSamplesRepaired(self, result, plotPath): + """Plots the number of samples repaired by all nodes""" + conf = {} + attrbs = self.__get_attrbs__(result) + conf["textBox"] = "Block Size R: "+attrbs['bsrn']+"\nBlock Size C: "+attrbs['bscn']\ + +"\nNumber of nodes: "+attrbs['nn']+"\nFailure rate: "+attrbs['fr']+"\nMalicious Node: "+attrbs['mn']+"\nNetwork degree: "+attrbs['nd'] + conf["title"] = "Number of Samples Repaired by Nodes" + conf["type"] = "individual_bar" + conf["legLoc"] = 1 + conf["desLoc"] = 1 + conf["xlabel"] = "Nodes" + conf["ylabel"] = "Number of Samples Repaired" + conf["data"] = result.repairedSampleCount + conf["xdots"] = range(result.shape.numberNodes) + conf["path"] = plotPath + "/repairedSampleCount.png" + maxi = max(conf["data"]) + conf["yaxismax"] = maxi + plotData(conf) + print("Plot %s created." % conf["path"]) diff --git a/smallConf.py b/smallConf.py index a166cec..7a76030 100644 --- a/smallConf.py +++ b/smallConf.py @@ -40,10 +40,6 @@ logLevel = logging.INFO # for more details, see joblib.Parallel numJobs = -1 -# distribute rows/columns evenly between validators (True) -# or generate it using local randomness (False) -evenLineDistribution = True - # Number of simulation runs with the same parameters for statistical relevance runs = range(3) @@ -56,21 +52,22 @@ failureModels = ["random"] # Percentage of block not released by producer failureRates = range(40, 81, 20) -# Block size in one dimension in segments. Block is blockSizes * blockSizes segments. -blockSizes = range(64, 113, 128) +# Percentage of nodes that are considered malicious +maliciousNodes = range(40,41,20) + +# Parameter to determine whether to randomly assign malicious nodes or not +# If True, the malicious nodes will be assigned randomly; if False, a predefined pattern may be used +randomizeMaliciousNodes = True # Per-topic mesh neighborhood size netDegrees = range(8, 9, 2) -# number of rows and columns a validator is interested in -chis = range(2, 3, 2) - # ratio of class1 nodes (see below for parameters per class) class1ratios = [0.8] # Number of validators per beacon node -validatorsPerNode1 = [1] -validatorsPerNode2 = [500] +validatorsPerNode1 = [10] +validatorsPerNode2 = [50] # Set uplink bandwidth in megabits/second bwUplinksProd = [200] @@ -101,13 +98,17 @@ diagnostics = False # True to save git diff and git commit saveGit = False +blockSizeR = range(64, 113, 128) +blockSizeC = range(32, 113, 128) +blockSizeRK = range(32, 65, 128) +blockSizeCK = range(32, 65, 128) +chiR = range(2, 3, 2) +chiC = range(2, 3, 2) + def nextShape(): - for run, fm, fr, class1ratio, chi, vpn1, vpn2, blockSize, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product( - runs, failureModels, failureRates, class1ratios, chis, validatorsPerNode1, validatorsPerNode2, blockSizes, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2): + for blckSizeR, blckSizeRK, blckSizeC, blckSizeCK, run, fm, fr, mn, class1ratio, chR, chC, vpn1, vpn2, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product( + blockSizeR, blockSizeRK, blockSizeC, blockSizeCK, runs, failureModels, failureRates, maliciousNodes, class1ratios, chiR, chiC, validatorsPerNode1, validatorsPerNode2, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2): # Network Degree has to be an even number if netDegree % 2 == 0: - blockSizeR = blockSizeC = blockSize - blockSizeRK = blockSizeCK = blockSize // 2 - chiR = chiC = chi - shape = Shape(blockSizeR, blockSizeRK, blockSizeC, blockSizeCK, nn, fm, fr, class1ratio, chiR, chiC, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run) + shape = Shape(blckSizeR, blckSizeRK, blckSizeC, blckSizeCK, nn, fm, fr, mn, class1ratio, chR, chC, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run) yield shape