Geometric distribution fixed

dream/simulation/Globals.py

@@ -40,7 +40,8 @@ import simpy
 class G:   
     seed=1450                       #the seed of the random number generator
     Rnd = Random(seed)              #random number generator
-    
+    import numpy
+    numpyRnd=numpy    
 
     ObjList=[]                      #a list that holds all the CoreObjects 
     EntityList=[]                   #a list that holds all the Entities 

dream/simulation/LineGenerationJSON.py

@@ -530,8 +530,10 @@ def main(argv=[], input_data=None):
         
         if G.seed:
             G.Rnd=Random('%s%s' % (G.seed, i))
+            G.numpyRnd.random.seed(G.seed)
         else:
             G.Rnd=Random()
+            G.numpyRnd.random.seed()
         createWIP()
         initializeObjects()
         Globals.setWIP(G.EntityList)        

dream/simulation/RandomNumberGenerator.py

@@ -25,6 +25,7 @@ Created on 14 Feb 2013
 '''
 holds methods for generations of numbers from different distributions
 '''
+
 class RandomNumberGenerator(object):
     def __init__(self, obj, distributionType, mean=0, stdev=0, min=0, max=0, alpha=0, beta=0,
                  logmean=0,logsd=0, probability=0, shape=0, scale=0, location=0):
@@ -43,8 +44,6 @@ class RandomNumberGenerator(object):
         self.location=float(location or 0)
         self.obj = obj
 
-        
-
     def generateNumber(self):
         from Globals import G
         if(self.distributionType=="Fixed"):     #if the distribution is Fixed 
@@ -76,7 +75,7 @@ class RandomNumberGenerator(object):
                 else:
                     continue
         elif(self.distributionType=="Geometric"):     #if the distribution is Geometric
-            return 1
+            return G.numpyRnd.random.geometric(self.probability)
         elif(self.distributionType=="Lognormal"):     #if the distribution is Lognormal
             # XXX from the files lognormvariate(mu, sigma)
             # it would be better to use same mean,stdev