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"""optimizer_attributes module for Hyperactive optimization.""" |
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# Email: [email protected] |
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# License: MIT License |
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import pandas as pd |
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class OptimizerAttributes: |
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"""OptimizerAttributes class.""" |
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def __init__(self): |
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self.best_para = None |
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self.best_score = None |
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self.best_since_iter = None |
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self.eval_times = None |
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self.iter_times = None |
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self.search_data = None |
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self.random_seed = None |
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def _add_result_attributes( |
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self, |
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best_para, |
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best_score, |
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best_since_iter, |
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eval_times, |
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iter_times, |
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search_data, |
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random_seed, |
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): |
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if self.best_para is None: |
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self.best_para = best_para |
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else: |
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if best_score > self.best_score: |
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self.best_para = best_para |
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if self.best_score is None: |
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self.best_score = best_score |
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else: |
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if best_score > self.best_score: |
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self.best_score = best_score |
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if self.best_since_iter is None: |
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self.best_since_iter = best_since_iter |
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else: |
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if best_score > self.best_score: |
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self.best_since_iter = best_since_iter |
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if self.eval_times is None: |
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self.eval_times = eval_times |
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else: |
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self.eval_times = self.eval_times + eval_times |
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if self.iter_times is None: |
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self.iter_times = iter_times |
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else: |
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self.iter_times = self.iter_times + eval_times |
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if self.search_data is None: |
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self.search_data = search_data |
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else: |
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self.search_data = pd.concat( |
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[self.search_data, search_data], ignore_index=True |
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) |
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if self.random_seed is None: |
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self.random_seed = random_seed |
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SimonBlanke /
Hyperactive
