SimonBlanke /
Gradient-Free-Optimizers
| Total Complexity | 5 |
| Total Lines | 37 |
| 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 numpy as np |
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| 6 | from .search_tracker import SearchTracker |
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| 7 | |||
| 8 | |||
| 9 | class BaseOptimizer(SearchTracker): |
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| 10 | def __init__(self, search_space): |
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| 11 | super().__init__() |
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| 12 | self.search_space = search_space |
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| 13 | self.space_dim = np.array([array.size - 1 for array in search_space]) |
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| 14 | |||
| 15 | self.optimizers = [self] |
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| 16 | |||
| 17 | def move_random(self): |
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| 18 | self.pos_new = np.random.randint(self.space_dim, size=self.space_dim.shape) |
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| 19 | return self.pos_new |
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| 20 | |||
| 21 | def iter_dec(func): |
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| 22 | def wrapper(self, *args, **kwargs): |
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| 23 | self.nth_iter = len(self.score_new_list) |
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| 24 | return func(self, *args, **kwargs) |
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| 25 | |||
| 26 | return wrapper |
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| 27 | |||
| 28 | @iter_dec |
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| 29 | def init_pos(self, pos): |
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| 30 | self.pos_new = pos |
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| 31 | |||
| 32 | def evaluate(self, score_new): |
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| 33 | self.score_new = score_new |
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| 34 | |||
| 35 | self._evaluate_new2current(score_new) |
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| 36 | self._evaluate_current2best() |
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| 37 |
