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'