SimonBlanke /
Gradient-Free-Optimizers
| Total Complexity | 5 |
| Total Lines | 31 |
| Duplicated Lines | 41.94 % |
| Changes | 0 | ||
Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.
Common duplication problems, and corresponding solutions are:
| 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 random |
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| 6 | import numpy as np |
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| 7 | |||
| 8 | |||
| 9 | View Code Duplication | def set_random_seed(nth_process, random_state): |
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Duplication
introduced
by
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| 10 | """ |
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| 11 | Sets the random seed separately for each thread |
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| 12 | (to avoid getting the same results in each thread) |
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| 13 | """ |
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| 14 | if nth_process is None: |
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| 15 | nth_process = 0 |
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| 16 | |||
| 17 | if random_state is None: |
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| 18 | random_state = np.random.randint(0, high=2 ** 31 - 2, dtype=np.int64) |
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| 19 | |||
| 20 | random.seed(random_state + nth_process) |
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| 21 | np.random.seed(random_state + nth_process) |
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| 22 | |||
| 23 | |||
| 24 | def move_random(ss_positions): |
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| 25 | position = [] |
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| 26 | for search_space_pos in ss_positions: |
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| 27 | pos_ = random.choice(search_space_pos) |
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| 28 | position.append(pos_) |
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| 29 | |||
| 30 | return np.array(position) |
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| 31 |
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