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tests.test_empty_output.verbose.ackley_function()   A

↳ Parent: tests.test_empty_output.verbose

Complexity

Conditions 1

Size

Total Lines 11
Code Lines 8

Duplication

Lines 11
Ratio 100 %

Importance

Changes 0
Metric Value
cc 1
eloc 8
nop 1
dl 11
loc 11
rs 10
c 0
b 0
f 0
1 
import numpy as np
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from gradient_free_optimizers import RandomSearchOptimizer
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def ackley_function(para):

            


                            

                    
                        
                    
                    
                    
                    
                                                                                                    
                        

                            
                            
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    x, y = para["x"], para["y"]

            


            
                                                                        
                            
            
                                    
            
            

                
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    loss = (

            


            
                                                                        
                            
            
                                    
            
            

                
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        -20 * np.exp(-0.2 * np.sqrt(0.5 * (x * x + y * y)))

            


            
                                                                        
                            
            
                                    
            
            

                
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        - np.exp(0.5 * (np.cos(2 * np.pi * x) + np.cos(2 * np.pi * y)))

            


            
                                                                        
                            
            
                                    
            
            

                
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        + np.exp(1)

            


            
                                                                        
                            
            
                                    
            
            

                
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        + 20

            


            
                                                                        
                            
            
                                    
            
            

                
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    )

            


            
                                                                        
                            
            
                                    
            
            

                
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    return -loss

            


            
                                                                                                            
                            
            
                                    
            
            

                
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search_space = {

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    "x": np.arange(-10, 10, 0.01),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    "y": np.arange(-10, 10, 0.01),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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}

            


            
                                                                                                            
                            
            
                                    
            
            

                
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opt = RandomSearchOptimizer(search_space)

            


            
                                                                                                            
                                                                
            
                                    
            
            

                
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opt.search(ackley_function, n_iter=30)

            


            
                                                        
            
                                    
            
            

                
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