SimonBlanke /
Gradient-Free-Optimizers
| Total Complexity | 10 |
| Total Lines | 48 |
| 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.eval_times = [] |
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| 16 | self.iter_times = [] |
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| 17 | |||
| 18 | def _evaluate_new2current(self, score_new): |
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| 19 | if score_new >= self.score_current: |
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| 20 | self.score_current = score_new |
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| 21 | self.pos_current = self.pos_new |
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| 22 | |||
| 23 | def _evaluate_current2best(self): |
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| 24 | if self.score_current >= self.score_best: |
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| 25 | self.score_best = self.score_current |
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| 26 | self.pos_best = self.pos_current |
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| 27 | |||
| 28 | def _current2best(self): |
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| 29 | self.score_best = self.score_current |
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| 30 | self.pos_best = self.pos_current |
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| 31 | |||
| 32 | def _new2current(self): |
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| 33 | self.score_current = self.score_new |
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| 34 | self.pos_current = self.pos_new |
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| 35 | |||
| 36 | def move_random(self): |
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| 37 | self.pos_new = np.random.randint(self.space_dim, size=self.space_dim.shape) |
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| 38 | return self.pos_new |
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| 39 | |||
| 40 | def init_pos(self, pos): |
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| 41 | self.pos_new = pos |
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| 42 | |||
| 43 | def evaluate(self, score_new): |
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| 44 | self.score_new = score_new |
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| 45 | |||
| 46 | self._evaluate_new2current(score_new) |
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| 47 | self._evaluate_current2best() |
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| 48 |
