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Pull Request — master (#202)
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unknown
01:18
created

run_amsde   A

↳ Parent: Project

Complexity

Total Complexity 0

Size/Duplication

Total Lines 20
Duplicated Lines 0 %

Importance

Changes 0
Metric Value
eloc 13
dl 0
loc 20
rs 10
c 0
b 0
f 0
wmc 0
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# encoding=utf8
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# This is temporary fix to import module from parent folder
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# It will be removed when package is published on PyPI
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import sys
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sys.path.append('../')
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# End of fix
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import random

            


            
                                                        
            
                                    
            
            

                
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from NiaPy.algorithms.basic import AgingNpMultiMutationDifferentialEvolution

            


            
                                                        
            
                                    
            
            

                
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from NiaPy.algorithms.basic.de import CrossCurr2Best1, CrossBest2

            


            
                                                        
            
                                    
            
            

                
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from NiaPy.util import StoppingTask, OptimizationType

            


            
                                                        
            
                                    
            
            

                
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from NiaPy.benchmarks import Sphere

            


            
                                                        
            
                                    
            
            

                
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#we will run Differential Evolution for 5 independent runs

            


            
                                                        
            
                                    
            
            

                
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for i in range(5):

            


            
                                                        
            
                                    
            
            

                
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    task = StoppingTask(D=10, nFES=5000, optType=OptimizationType.MINIMIZATION, benchmark=Sphere())

            


            
                                                        
            
                                    
            
            

                
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    algo = AgingNpMultiMutationDifferentialEvolution(NP=10, F=0.2, CR=0.65, strategies=(CrossCurr2Best1, CrossBest2), delta_np=0.05, omega=0.9)

            


            
                                                        
            
                                    
            
            

                
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    best = algo.run(task=task)

            


            
                                                        
            
                                    
            
            

                
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    print('%s -> %s' % (best[0].x, best[1]))

            


            
                                                        
            
                                    
            
            

                
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