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test_replacement_0()   A

↳ Parent: tests.test_parameters.test_bayesian_optimization

Complexity

Conditions 2

Size

Total Lines 7
Code Lines 6

Duplication

Lines 0
Ratio 0 %

Importance

Changes 0
Metric Value
cc 2
eloc 6
nop 0
dl 0
loc 7
rs 10
c 0
b 0
f 0
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# Author: Simon Blanke
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# Email: [email protected]
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# License: MIT License
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import pytest

            


            
                                                                                                            
                            
            
                                    
            
            

                
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import numpy as np

            


            
                                                                                                            
                            
            
                                    
            
            

                
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from gradient_free_optimizers import BayesianOptimizer

            


            
                                                                                                            
                            
            
                                    
            
            

                
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def parabola_function(para):

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    loss = para["x"] * para["x"] + para["y"] * para["y"]

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    return -loss

            


            
                                                                                                            
                            
            
                                    
            
            

                
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search_space = {

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    "x": np.arange(-1, 1, 1),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    "y": np.arange(-1, 1, 1),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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}

            


            
                                                                                                            
                            
            
                                    
            
            

                
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def test_replacement_0():

            


            
                                                        
            
                                    
            
            

                
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    opt = BayesianOptimizer(search_space, replacement=True)

            


            
                                                        
            
                                    
            
            

                
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    opt.search(parabola_function, n_iter=15)

            


            
                                                        
            
                                    
            
            

                
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    with pytest.raises(ValueError):

            


            
                                                        
            
                                    
            
            

                
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        opt = BayesianOptimizer(search_space, replacement=False)

            


            
                                                        
            
                                    
            
            

                
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        opt.search(parabola_function, n_iter=15)

            


            
                                                        
            
                                    
            
            

                
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