Remove global randomness parameter for validator

DAS/simulator.py

@@ -50,7 +50,7 @@ class Simulator:
                     end   = offset+((j+1)*self.shape.chi)
                 r =    rows[start:end]
                 c = columns[start:end]
-                val = Validator(i, int(not i!=0), self.logger, self.shape, r, c, self.config.evenLineDistribution)
+                val = Validator(i, int(not i!=0), self.logger, self.shape, r, c)
             else:
                 val = Validator(i, int(not i!=0), self.logger, self.shape)
             if i == self.proposerID:

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, rows = None, columns = None, globalRandomness = True):
+    def __init__(self, ID, amIproposer, logger, shape, 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)
@@ -66,13 +66,9 @@ class Validator:
             else:
                 #if shape.deterministic:
                 #    random.seed(self.ID)
-                if globalRandomness:
-                    self.rowIDs = rows
-                    self.columnIDs = columns
-                else:
-                    vpn = self.shape.vpn1 if (self.ID <= shape.numberNodes * shape.class1ratio) else self.shape.vpn2
-                    self.rowIDs = rows if rows else unionOfSamples(range(self.shape.blockSize), self.shape.chi, vpn)
-                    self.columnIDs = columns if columns else unionOfSamples(range(self.shape.blockSize), self.shape.chi, vpn)
+                vpn = self.shape.vpn1 if (self.ID <= shape.numberNodes * shape.class1ratio) else self.shape.vpn2
+                self.rowIDs = rows if rows else unionOfSamples(range(self.shape.blockSize), self.shape.chi, vpn)
+                self.columnIDs = columns if columns else unionOfSamples(range(self.shape.blockSize), self.shape.chi, vpn)
         self.rowNeighbors = collections.defaultdict(dict)
         self.columnNeighbors = collections.defaultdict(dict)
 

config_example.py

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