tests.test_optimizers.test_multiple_searches.objective_function() - Code Metrics - SimonBlanke/Gradient-Free-Optimizers - Measure and Improve Code Quality continuously with Scrutinizer

objective_function() A
last analyzed 2025-08-06 16:49 UTC

↳ Parent: tests.test_optimizers.test_multiple_searches

Complexity

Conditions

Size

Total Lines	3
Code Lines	3

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	1
eloc	3
nop	1
dl	0
loc	3
rs	10
c	0
b	0
f	0

import pytest
import numpy as np

from ._parametrize import optimizers_singleOpt, optimizers_PopBased, optimizers_SBOM


def objective_function(para):
    score = -para["x1"] * para["x1"]
    return score


search_space = {"x1": np.arange(-100, 1, 1)}


@pytest.mark.parametrize(*optimizers_singleOpt)
def test_searches_0(Optimizer):

    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=1)
    opt.search(objective_function, n_iter=1)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 2

    assert opt.n_init_total == 1
    assert opt.n_iter_total == 1
    assert opt.n_init_search == 0
    assert opt.n_iter_search == 1


@pytest.mark.parametrize(*optimizers_PopBased)

def test_searches_pop_0(Optimizer):

    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=1)
    opt.search(objective_function, n_iter=1)

    print("\n opt.search_data \n", opt.search_data)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 2

    assert opt.n_init_total == 2
    assert opt.n_iter_total == 0
    assert opt.n_init_search == 1
    assert opt.n_iter_search == 0


@pytest.mark.parametrize(*optimizers_singleOpt)

def test_searches_1(Optimizer):
    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=1)

    print("\n opt.search_data \n", opt.search_data)

    opt.search(objective_function, n_iter=10)

    print("\n opt.search_data \n", opt.search_data)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 11

    assert opt.n_init_total == 1
    assert opt.n_iter_total == 10
    assert opt.n_init_search == 0
    assert opt.n_iter_search == 10


@pytest.mark.parametrize(*optimizers_PopBased)
def test_searches_pop_1(Optimizer):
    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=1)
    opt.search(objective_function, n_iter=10)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 11

    assert opt.n_init_total != 1
    assert opt.n_iter_total != 10
    assert opt.n_init_search != 0
    assert opt.n_iter_search != 10


@pytest.mark.parametrize(*optimizers_singleOpt)
def test_searches_2(Optimizer):
    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=1)
    opt.search(objective_function, n_iter=20)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 21

    assert opt.n_init_total == 1
    assert opt.n_iter_total == 20
    assert opt.n_init_search == 0
    assert opt.n_iter_search == 20


@pytest.mark.parametrize(*optimizers_PopBased)
def test_searches_pop_2(Optimizer):
    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=1)
    opt.search(objective_function, n_iter=20)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 21

    assert opt.n_init_total != 1
    assert opt.n_iter_total != 20
    assert opt.n_init_search != 0
    assert opt.n_iter_search != 20


@pytest.mark.parametrize(*optimizers_singleOpt)
def test_searches_3(Optimizer):
    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=10)
    opt.search(objective_function, n_iter=20)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 30

    assert opt.n_init_total == 1
    assert opt.n_iter_total == 29
    assert opt.n_init_search == 0
    assert opt.n_iter_search == 20


@pytest.mark.parametrize(*optimizers_PopBased)
def test_searches_pop_3(Optimizer):
    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=20)
    opt.search(objective_function, n_iter=20)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 40

    assert 1 < opt.n_init_total < 20
    assert opt.n_iter_total > 20
    assert opt.n_init_search == 0
    assert opt.n_iter_search == 20


@pytest.mark.parametrize(*optimizers_singleOpt)
def test_searches_4(Optimizer):
    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=10)
    opt.search(objective_function, n_iter=10)
    opt.search(objective_function, n_iter=10)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 30

    assert opt.n_init_total == 1
    assert opt.n_iter_total == 29
    assert opt.n_init_search == 0
    assert opt.n_iter_search == 10


@pytest.mark.parametrize(*optimizers_PopBased)
def test_searches_pop_4(Optimizer):
    initialize = {"warm_start": [{"x1": -100}]}

    opt = Optimizer(search_space, initialize=initialize)
    opt.search(objective_function, n_iter=10)
    opt.search(objective_function, n_iter=10)
    opt.search(objective_function, n_iter=10)

    assert -100 in opt.search_data["x1"].values
    assert len(opt.search_data["x1"]) == 30

    assert opt.n_init_total != 1
    assert opt.n_iter_total != 29
    assert opt.n_init_search == 0
    assert opt.n_iter_search == 10


1		import pytest
2		import numpy as np
3
4		from ._parametrize import optimizers_singleOpt, optimizers_PopBased, optimizers_SBOM
5
6
7		def objective_function(para):
8		score = -para["x1"] * para["x1"]
9		return score
10
11
12		search_space = {"x1": np.arange(-100, 1, 1)}
13
14
15		@pytest.mark.parametrize(*optimizers_singleOpt)
16		def test_searches_0(Optimizer):
17
18		initialize = {"warm_start": [{"x1": -100}]}
19
20		opt = Optimizer(search_space, initialize=initialize)
21		opt.search(objective_function, n_iter=1)
22		opt.search(objective_function, n_iter=1)
23
24		assert -100 in opt.search_data["x1"].values
25		assert len(opt.search_data["x1"]) == 2
26
27		assert opt.n_init_total == 1
28		assert opt.n_iter_total == 1
29		assert opt.n_init_search == 0
30		assert opt.n_iter_search == 1
31
32
33	View Code Duplication	@pytest.mark.parametrize(*optimizers_PopBased)
		0 ignored issues – show Duplication introduced 2021-01-06 10:56 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
34		def test_searches_pop_0(Optimizer):
35
36		initialize = {"warm_start": [{"x1": -100}]}
37
38		opt = Optimizer(search_space, initialize=initialize)
39		opt.search(objective_function, n_iter=1)
40		opt.search(objective_function, n_iter=1)
41
42		print("\n opt.search_data \n", opt.search_data)
43
44		assert -100 in opt.search_data["x1"].values
45		assert len(opt.search_data["x1"]) == 2
46
47		assert opt.n_init_total == 2
48		assert opt.n_iter_total == 0
49		assert opt.n_init_search == 1
50		assert opt.n_iter_search == 0
51
52
53	View Code Duplication	@pytest.mark.parametrize(*optimizers_singleOpt)
		0 ignored issues – show Duplication introduced 2021-01-06 10:56 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
54		def test_searches_1(Optimizer):
55		initialize = {"warm_start": [{"x1": -100}]}
56
57		opt = Optimizer(search_space, initialize=initialize)
58		opt.search(objective_function, n_iter=1)
59
60		print("\n opt.search_data \n", opt.search_data)
61
62		opt.search(objective_function, n_iter=10)
63
64		print("\n opt.search_data \n", opt.search_data)
65
66		assert -100 in opt.search_data["x1"].values
67		assert len(opt.search_data["x1"]) == 11
68
69		assert opt.n_init_total == 1
70		assert opt.n_iter_total == 10
71		assert opt.n_init_search == 0
72		assert opt.n_iter_search == 10
73
74
75		@pytest.mark.parametrize(*optimizers_PopBased)
76		def test_searches_pop_1(Optimizer):
77		initialize = {"warm_start": [{"x1": -100}]}
78
79		opt = Optimizer(search_space, initialize=initialize)
80		opt.search(objective_function, n_iter=1)
81		opt.search(objective_function, n_iter=10)
82
83		assert -100 in opt.search_data["x1"].values
84		assert len(opt.search_data["x1"]) == 11
85
86		assert opt.n_init_total != 1
87		assert opt.n_iter_total != 10
88		assert opt.n_init_search != 0
89		assert opt.n_iter_search != 10
90
91
92		@pytest.mark.parametrize(*optimizers_singleOpt)
93		def test_searches_2(Optimizer):
94		initialize = {"warm_start": [{"x1": -100}]}
95
96		opt = Optimizer(search_space, initialize=initialize)
97		opt.search(objective_function, n_iter=1)
98		opt.search(objective_function, n_iter=20)
99
100		assert -100 in opt.search_data["x1"].values
101		assert len(opt.search_data["x1"]) == 21
102
103		assert opt.n_init_total == 1
104		assert opt.n_iter_total == 20
105		assert opt.n_init_search == 0
106		assert opt.n_iter_search == 20
107
108
109		@pytest.mark.parametrize(*optimizers_PopBased)
110		def test_searches_pop_2(Optimizer):
111		initialize = {"warm_start": [{"x1": -100}]}
112
113		opt = Optimizer(search_space, initialize=initialize)
114		opt.search(objective_function, n_iter=1)
115		opt.search(objective_function, n_iter=20)
116
117		assert -100 in opt.search_data["x1"].values
118		assert len(opt.search_data["x1"]) == 21
119
120		assert opt.n_init_total != 1
121		assert opt.n_iter_total != 20
122		assert opt.n_init_search != 0
123		assert opt.n_iter_search != 20
124
125
126		@pytest.mark.parametrize(*optimizers_singleOpt)
127		def test_searches_3(Optimizer):
128		initialize = {"warm_start": [{"x1": -100}]}
129
130		opt = Optimizer(search_space, initialize=initialize)
131		opt.search(objective_function, n_iter=10)
132		opt.search(objective_function, n_iter=20)
133
134		assert -100 in opt.search_data["x1"].values
135		assert len(opt.search_data["x1"]) == 30
136
137		assert opt.n_init_total == 1
138		assert opt.n_iter_total == 29
139		assert opt.n_init_search == 0
140		assert opt.n_iter_search == 20
141
142
143		@pytest.mark.parametrize(*optimizers_PopBased)
144		def test_searches_pop_3(Optimizer):
145		initialize = {"warm_start": [{"x1": -100}]}
146
147		opt = Optimizer(search_space, initialize=initialize)
148		opt.search(objective_function, n_iter=20)
149		opt.search(objective_function, n_iter=20)
150
151		assert -100 in opt.search_data["x1"].values
152		assert len(opt.search_data["x1"]) == 40
153
154		assert 1 < opt.n_init_total < 20
155		assert opt.n_iter_total > 20
156		assert opt.n_init_search == 0
157		assert opt.n_iter_search == 20
158
159
160		@pytest.mark.parametrize(*optimizers_singleOpt)
161		def test_searches_4(Optimizer):
162		initialize = {"warm_start": [{"x1": -100}]}
163
164		opt = Optimizer(search_space, initialize=initialize)
165		opt.search(objective_function, n_iter=10)
166		opt.search(objective_function, n_iter=10)
167		opt.search(objective_function, n_iter=10)
168
169		assert -100 in opt.search_data["x1"].values
170		assert len(opt.search_data["x1"]) == 30
171
172		assert opt.n_init_total == 1
173		assert opt.n_iter_total == 29
174		assert opt.n_init_search == 0
175		assert opt.n_iter_search == 10
176
177
178		@pytest.mark.parametrize(*optimizers_PopBased)
179		def test_searches_pop_4(Optimizer):
180		initialize = {"warm_start": [{"x1": -100}]}
181
182		opt = Optimizer(search_space, initialize=initialize)
183		opt.search(objective_function, n_iter=10)
184		opt.search(objective_function, n_iter=10)
185		opt.search(objective_function, n_iter=10)
186
187		assert -100 in opt.search_data["x1"].values
188		assert len(opt.search_data["x1"]) == 30
189
190		assert opt.n_init_total != 1
191		assert opt.n_iter_total != 29
192		assert opt.n_init_search == 0
193		assert opt.n_iter_search == 10
194

SimonBlanke / Gradient-Free-Optimizers

objective_function() A last analyzed 2025-08-06 16:49 UTC

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objective_function() A
last analyzed 2025-08-06 16:49 UTC