solver.SetGenerationMonitor(stepmon)
solver.Solve(CF, termination = ChangeOverGeneration(generations=100), \
CrossProbability=0.5, ScalingFactor=0.5)
solution = solver.Solution()
return solution, stepmon
if __name__ == '__main__':
F = CostFactory()
F.addModel(ForwardMogiFactory, 4, 'mogi1', outputFilter=component(2))
myCostFunction = F.getCostFunction(evalpts=stations, observations=data_z)
print(F)
rp = F.getRandomParams()
print("new Cost Function : %s " % myCostFunction(rp))
print("orig Cost Function: %s " % cost_function(rp))
f1 = ForwardMogiFactory(rp)
f2 = ForwardMogiFactory(rp)
print('start cf')
for i in range(3000):
xx = cost_function(rp)
print('end cf')
print('start cf2')
for i in range(3000):
xx = myCostFunction(rp)
print('end cf2')
solver.SetEvaluationLimits(generations=MAX_GENERATIONS)
solver.SetGenerationMonitor(stepmon)
solver.Solve(CF, termination = ChangeOverGeneration(generations=100), \
CrossProbability=0.5, ScalingFactor=0.5)
solution = solver.Solution()
return solution, stepmon
if __name__ == '__main__':
F = CostFactory()
F.addModel(ForwardMogiFactory, 'mogi1', 4, outputFilter = PickComponent(2))
myCostFunction = F.getCostFunction(evalpts = stations, observations = data_z)
print F
rp = F.getRandomParams()
print "new Cost Function : %s " % myCostFunction(rp)
print "orig Cost Function: %s " % cost_function(rp)
f1 = ForwardMogiFactory(rp)
f2 = ForwardMogiFactory(rp)
print 'start cf'
for i in range(3000):
xx = cost_function(rp)
print 'end cf'
print 'start cf2'
for i in range(3000):
xx = myCostFunction(rp)
print 'end cf2'
