def pickStartCountry():
## Move refs from all countries:
if graph.vs[0]['NumRefs']<10000:
coIDs = range( 38 )
numRefsCos = []
for coid in coIDs:
# graph.vs[coid]['NumRefs']
numRefsCos.append( graph.vs[coid]['NumRefs'] )
originCoWeight = [ i/float(sum(numRefsCos)) for i in numRefsCos ]
# print originCoWeight
return np.random.choice(coIDs, p=originCoWeight)
## Move Refs only from Origin and Transition countries
else:
coList = COS.originCoList() + COS.transitionCoList()
coIDs = []#[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 18, 19, 30, 31, 32, 33, 34, 35, 36, 37, 38]
numRefsCos = []
for vertex in graph.vs:
if vertex['label'] in coList:
numRefsCos.append( vertex['NumRefs'] )
coIDs.append( vertex.index )
# for coid in coIDs:
# graph.vs[coid]['NumRefs']
# numRefsCos.append( graph.vs[coid]['NumRefs'] )
originCoWeight = [ i/float(sum(numRefsCos)) for i in numRefsCos ]
# print originCoWeight
return np.random.choice(coIDs, p=originCoWeight)
def selfCostMSIMcalculate(vertex, update=True):
# if vertex['NumRefs'] <.0001:
# vertex['NumRefs'] = 1
if vertex['label'] in COS.originCoList():
cost = .3
else:
n1 = 2 * vertex['SafetyCo'] * \
vertex['Resources'] * \
vertex['NumRefs']**2
adjacents = graph.adjacent( target ) #returns edge labels
adjTargets = graph.vs[ graph.es[adjacents]['Target'] ]
## Do the weird pi cumulitive product thing:
distSum = 1#1.15
# for distance in graph.es[adjacents]['Distance']:
# distSum = distSum + distance
# print 'dist is: ', distance, distSum
#lnPi = math.log(distProd)
numeratorMoneySigma = sum( graph.es[adjacents]['MoneyCost'] )
denomSafetySigma = sum( graph.es[adjacents]['Safety'] ) + \
sum( adjTargets['SafetyCo'] )
denomResourceSigma = sum( adjTargets['Resources'] )
cost = n1 * distSum * numeratorMoneySigma / \
vertex['RefCap'] / denomSafetySigma / denomResourceSigma
# vertex['Jessie'] = (n1, vertex['SafetyCo'], vertex['Resources'],vertex['NumRefs']**2)
if update==True:
vertex['CostSelf'] = cost
return cost