gradient_free_optimizers.optimizers.exp_opt.random_annealing.RandomAnnealingOptimizer.iterate() - Code Metrics - SimonBlanke/Gradient-Free-Optimizers - Measure and Improve Code Quality continuously with Scrutinizer

RandomAnnealingOptimizer.iterate() A
last analyzed 2025-08-06 16:49 UTC

↳ Parent: gradient_free_optimizers.optimizers.exp_opt.random_annealing

Complexity

Conditions

Size

Total Lines	12
Code Lines	10

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	10
dl	0
loc	12
rs	9.9
c	0
b	0
f	0
cc	1
nop	1

# Author: Simon Blanke
# Email: [email protected]
# License: MIT License


from ..local_opt import HillClimbingOptimizer


class RandomAnnealingOptimizer(HillClimbingOptimizer):
    name = "Random Annealing"
    _name_ = "random_annealing"
    __name__ = "RandomAnnealingOptimizer"

    def __init__(

        self,
        search_space,
        initialize={"grid": 4, "random": 2, "vertices": 4},
        constraints=[],
        random_state=None,
        rand_rest_p=0,
        nth_process=None,
        epsilon=0.03,
        distribution="normal",
        n_neighbours=3,
        annealing_rate=0.98,
        start_temp=10,
    ):
        super().__init__(
            search_space=search_space,
            initialize=initialize,
            constraints=constraints,
            random_state=random_state,
            rand_rest_p=rand_rest_p,
            nth_process=nth_process,
            epsilon=epsilon,
            distribution=distribution,
            n_neighbours=n_neighbours,
        )
        self.epsilon = epsilon
        self.distribution = distribution
        self.n_neighbours = n_neighbours
        self.annealing_rate = annealing_rate
        self.start_temp = start_temp
        self.temp = start_temp

    @HillClimbingOptimizer.track_new_pos
    @HillClimbingOptimizer.random_iteration
    def iterate(self):
        pos = self.move_climb(
            self.pos_current,
            epsilon=self.epsilon,
            distribution=self.distribution,
            epsilon_mod=self.temp,
        )
        self.temp = self.temp * self.annealing_rate

        return pos


1		# Author: Simon Blanke
2		# Email: [email protected]
3		# License: MIT License
4
5
6		from ..local_opt import HillClimbingOptimizer
7
8
9		class RandomAnnealingOptimizer(HillClimbingOptimizer):
10		name = "Random Annealing"
11		_name_ = "random_annealing"
12		__name__ = "RandomAnnealingOptimizer"
13
14	View Code Duplication	def __init__(
		0 ignored issues – show Duplication introduced 2024-12-07 10:49 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
15		self,
16		search_space,
17		initialize={"grid": 4, "random": 2, "vertices": 4},
18		constraints=[],
19		random_state=None,
20		rand_rest_p=0,
21		nth_process=None,
22		epsilon=0.03,
23		distribution="normal",
24		n_neighbours=3,
25		annealing_rate=0.98,
26		start_temp=10,
27		):
28		super().__init__(
29		search_space=search_space,
30		initialize=initialize,
31		constraints=constraints,
32		random_state=random_state,
33		rand_rest_p=rand_rest_p,
34		nth_process=nth_process,
35		epsilon=epsilon,
36		distribution=distribution,
37		n_neighbours=n_neighbours,
38		)
39		self.epsilon = epsilon
40		self.distribution = distribution
41		self.n_neighbours = n_neighbours
42		self.annealing_rate = annealing_rate
43		self.start_temp = start_temp
44		self.temp = start_temp
45
46		@HillClimbingOptimizer.track_new_pos
47		@HillClimbingOptimizer.random_iteration
48		def iterate(self):
49		pos = self.move_climb(
50		self.pos_current,
51		epsilon=self.epsilon,
52		distribution=self.distribution,
53		epsilon_mod=self.temp,
54		)
55		self.temp = self.temp * self.annealing_rate
56
57		return pos
58

SimonBlanke / Gradient-Free-Optimizers

RandomAnnealingOptimizer.iterate() A last analyzed 2025-08-06 16:49 UTC

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RandomAnnealingOptimizer.iterate() A
last analyzed 2025-08-06 16:49 UTC