diff --git a/DAS/block.py b/DAS/block.py index 76379d8..426bdfd 100644 --- a/DAS/block.py +++ b/DAS/block.py @@ -51,3 +51,58 @@ class Block: print(line+"|") print(dash) +class SparseBlock: + + def __init__(self, size, rows, columns): + self.blockSize = size + self.rows = {r: zeros(self.blockSize) for r in rows} + self.columns = {r: zeros(self.blockSize) for r in columns} + + def fill(self): + for line in self.rows: + line.setall(1) + for line in self.columns: + line.setall(1) + + def merge(self, merged): + for id in self.rows: + self.mergeRow(id, merged.getRow(id)) + for id in self.columns: + self.mergeColumn(id, merged.getColumn(id)) + + def getColumn(self, id): + return self.columns[id] + + def mergeColumn(self, id, column): + self.columns[id] |= column + for xid, line in self.rows.items(): + line[id] |= self.columns[id][xid] + + def repairColumn(self, id): + success = self.columns[id].count(1) + if success >= self.blockSize/2: + self.columns[id].setall(1) + + def getRow(self, id): + return self.rows[id] + + def mergeRow(self, id, row): + self.rows[id] |= row + for xid, line in self.columns.items(): + line[id] |= self.rows[id][xid] + + def repairRow(self, id): + success = self.rows[id].count(1) + if success >= self.blockSize/2: + self.rows[id].setall(1) + + # def print(self): + # dash = "-" * (self.blockSize+2) + # print(dash) + # for i in range(self.blockSize): + # line = "|" + # for j in range(self.blockSize): + # line += "%i" % self.data[(i*self.blockSize)+j] + # print(line+"|") + # print(dash) + diff --git a/DAS/validator.py b/DAS/validator.py index df64afe..4a581f1 100644 --- a/DAS/validator.py +++ b/DAS/validator.py @@ -22,8 +22,6 @@ class Validator: self.ID = ID self.format = {"entity": "Val "+str(self.ID)} self.blockSize = blockSize - self.block = Block(blockSize) - self.receivedBlock = Block(blockSize) self.proposer = proposer self.failureRate = failureRate self.logger = logger @@ -43,6 +41,8 @@ class Validator: random.seed(self.ID) self.rowIDs = random.sample(range(self.blockSize), self.chi) self.columnIDs = random.sample(range(self.blockSize), self.chi) + self.block = SparseBlock(blockSize, self.rowIDs, self.columnIDs) + self.receivedBlock = SparseBlock(blockSize, self.rowIDs, self.columnIDs) self.rowNeighbors = collections.defaultdict(list) self.columnNeighbors = collections.defaultdict(list)