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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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from .base_positioner import BasePositioner |
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class BaseOptimizer: |
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def __init__(self, _opt_args_): |
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self._opt_args_ = _opt_args_ |
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self.p_list = [] |
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def iterate(self, i, _cand_): |
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self.i = i |
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if i < self.n_positioners: |
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p = self._init_iteration(_cand_) |
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self.p_list.append(p) |
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else: |
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self._iterate(i, _cand_) |
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return _cand_ |
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def _finish_search(self): |
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self._pbar_.close_p_bar() |
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def _update_pos(self, _cand_, _p_): |
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if _p_.score_new > _p_.score_best: |
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_p_.pos_best = _p_.pos_new |
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_p_.score_best = _p_.score_new |
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if _p_.score_new > _cand_.score_best: |
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_p_.pos_current = _p_.pos_new |
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_p_.score_current = _p_.score_new |
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_cand_.pos_best = _p_.pos_new |
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_cand_.score_best = _p_.score_new |
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self._pbar_.best_since_iter = _cand_.i |
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def _optimizer_eval(self, _cand_, _p_): |
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_p_.score_new = _cand_.eval_pos(_p_.pos_new) |
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self._pbar_.update_p_bar(1, _cand_) |
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def _init_base_positioner(self, _cand_, positioner=None): |
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if positioner: |
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_p_ = positioner(**self._opt_args_.kwargs_opt) |
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else: |
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_p_ = BasePositioner(**self._opt_args_.kwargs_opt) |
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_p_.pos_new = _cand_.pos_best |
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_p_.score_new = _cand_.score_best |
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return _p_ |
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SimonBlanke /
Hyperactive
