tests.test_HillClimbing._base_test() - Code Metrics - Inspection of "rename tests" - SimonBlanke/Gradient-Free-Optimizers - Measure and Improve Code Quality continuously with Scrutinizer

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by Simon

created 2020-04-30 08:04 UTC

tests.test_HillClimbing._base_test() A

↳ Parent: tests.test_HillClimbing

Complexity

Conditions

Size

Total Lines	10
Code Lines	9

Duplication

Lines	10
Ratio	100 %

Importance

Changes

Metric	Value
eloc	9
dl	10
loc	10
rs	9.95
c	0
b	0
f	0
cc	3
nop	2

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

import numpy as np

from gradient_free_optimizers import HillClimbingOptimizer

n_iter = 100


def get_score(pos_new):
    return -(pos_new[0] * pos_new[0])


space_dim = np.array([10])
init_positions = [np.array([0]), np.array([1]), np.array([2]), np.array([3])]


def _base_test(opt, init_positions):

    for nth_init in range(len(init_positions)):
        pos_new = opt.init_pos(nth_init)
        score_new = get_score(pos_new)
        opt.evaluate(score_new)

    for nth_iter in range(len(init_positions), n_iter):
        pos_new = opt.iterate(nth_iter)
        score_new = get_score(pos_new)
        opt.evaluate(score_new)


def _test_HillClimbingOptimizer(
    init_positions=init_positions, space_dim=space_dim, opt_para={}
):
    opt = HillClimbingOptimizer(init_positions, space_dim, opt_para)
    _base_test(opt, init_positions)


def test_epsilon():
    for epsilon in [0.00001, 100]:
        opt_para = {"epsilon": epsilon}
        _test_HillClimbingOptimizer(opt_para=opt_para)


def test_n_neighbours():
    for n_neighbours in [1, 100]:
        opt_para = {"n_neighbours": n_neighbours}
        _test_HillClimbingOptimizer(opt_para=opt_para)


1		# Author: Simon Blanke
2		# Email: [email protected]
3		# License: MIT License
4
5		import numpy as np
6
7		from gradient_free_optimizers import HillClimbingOptimizer
8
9		n_iter = 100
10
11
12		def get_score(pos_new):
13		return -(pos_new[0] * pos_new[0])
14
15
16		space_dim = np.array([10])
17		init_positions = [np.array([0]), np.array([1]), np.array([2]), np.array([3])]
18
19
20	View Code Duplication	def _base_test(opt, init_positions):
		0 ignored issues – show Duplication introduced 2020-04-30 08:02 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
21		for nth_init in range(len(init_positions)):
22		pos_new = opt.init_pos(nth_init)
23		score_new = get_score(pos_new)
24		opt.evaluate(score_new)
25
26		for nth_iter in range(len(init_positions), n_iter):
27		pos_new = opt.iterate(nth_iter)
28		score_new = get_score(pos_new)
29		opt.evaluate(score_new)
30
31
32		def _test_HillClimbingOptimizer(
33		init_positions=init_positions, space_dim=space_dim, opt_para={}
34		):
35		opt = HillClimbingOptimizer(init_positions, space_dim, opt_para)
36		_base_test(opt, init_positions)
37
38
39		def test_epsilon():
40		for epsilon in [0.00001, 100]:
41		opt_para = {"epsilon": epsilon}
42		_test_HillClimbingOptimizer(opt_para=opt_para)
43
44
45		def test_n_neighbours():
46		for n_neighbours in [1, 100]:
47		opt_para = {"n_neighbours": n_neighbours}
48		_test_HillClimbingOptimizer(opt_para=opt_para)
49

SimonBlanke / Gradient-Free-Optimizers

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