SimonBlanke /
Gradient-Free-Optimizers
| Total Complexity | 5 |
| Total Lines | 44 |
| Duplicated Lines | 0 % |
| Changes | 0 | ||
| 1 | # Author: Simon Blanke |
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| 2 | # Email: [email protected] |
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| 3 | # License: MIT License |
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| 4 | |||
| 5 | import pandas as pd |
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| 6 | |||
| 7 | |||
| 8 | class ResultsManager: |
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| 9 | def __init__(self): |
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| 10 | super().__init__() |
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| 11 | self.conv = None |
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| 12 | |||
| 13 | self.results_list = [] |
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| 14 | |||
| 15 | def _obj_func_results(self, objective_function, para): |
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| 16 | results = objective_function(para) |
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| 17 | |||
| 18 | if isinstance(results, tuple): |
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| 19 | score = results[0] |
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| 20 | results_dict = results[1] |
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| 21 | else: |
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| 22 | score = results |
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| 23 | results_dict = {} |
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| 24 | |||
| 25 | results_dict["score"] = score |
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| 26 | |||
| 27 | return results_dict |
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| 28 | |||
| 29 | def score(self, objective_function): |
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| 30 | def _wrapper(pos): |
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| 31 | value = self.conv.position2value(pos) |
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| 32 | para = self.conv.value2para(value) |
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| 33 | results_dict = self._obj_func_results(objective_function, para) |
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| 34 | |||
| 35 | self.results_list.append({**results_dict, **para}) |
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| 36 | |||
| 37 | return results_dict["score"] |
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| 38 | |||
| 39 | return _wrapper |
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| 40 | |||
| 41 | @property |
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| 42 | def search_data(self): |
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| 43 | return pd.DataFrame(self.results_list) |
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| 44 |
