tests_old.test_results_methods - Code Metrics - Inspection of "V5 api design" - SimonBlanke/Hyperactive - Measure and Improve Code Quality continuously with Scrutinizer

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Pull Request — master (#101)

by Simon

created 2025-04-12 10:21 UTC

tests_old.test_results_methods A

↳ Parent: Project

Complexity

Total Complexity

Size/Duplication

Total Lines	238
Duplicated Lines	0 %

Importance

Changes

Metric	Value
eloc	92
dl	0
loc	238
rs	10
c	0
b	0
f	0
wmc	14

11 Functions

Rating	Name	Size	Complexity
A	test_attributes_results_objective_function_0()	10	1
A	test_attributes_result_errors_1()	7	2
A	test_attributes_results_objective_function_1()	15	1
A	objective_function1()	3	1
A	test_attributes_best_para_objective_function_0()	10	1
A	test_attributes_best_score_objective_function_1()	15	1
A	test_attributes_best_para_objective_function_1()	15	1
A	test_attributes_result_errors_0()	7	2
A	objective_function()	3	1
A	test_attributes_result_errors_2()	7	2
A	test_attributes_best_score_objective_function_0()	10	1

import pytest
import numbers
import numpy as np
import pandas as pd

from hyperactive import Hyperactive


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


def objective_function1(opt):
    score = -opt["x1"] * opt["x1"]
    return score


search_space = {
    "x1": list(np.arange(0, 100, 1)),
}


def test_attributes_best_score_objective_function_0():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.best_score(objective_function), numbers.Number)


def test_attributes_best_score_objective_function_1():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=15,
    )
    hyper.add_search(
        objective_function1,
        search_space,
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.best_score(objective_function), numbers.Number)


"""
def test_attributes_best_score_search_id_0():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        search_id="1",
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.best_score(objective_function), numbers.Number)


def test_attributes_best_score_search_id_1():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        search_id="1",
        n_iter=15,
    )
    hyper.add_search(
        objective_function1,
        search_space,
        search_id="2",
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.best_score(objective_function), numbers.Number)
"""


def test_attributes_best_para_objective_function_0():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.best_para(objective_function), dict)


def test_attributes_best_para_objective_function_1():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=15,
    )
    hyper.add_search(
        objective_function1,
        search_space,
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.best_para(objective_function), dict)


"""
def test_attributes_best_para_search_id_0():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        search_id="1",
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.best_para("1"), dict)


def test_attributes_best_para_search_id_1():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        search_id="1",
        n_iter=15,
    )
    hyper.add_search(
        objective_function1,
        search_space,
        search_id="2",
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.best_para("1"), dict)
"""


def test_attributes_results_objective_function_0():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)


def test_attributes_results_objective_function_1():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=15,
    )
    hyper.add_search(
        objective_function1,
        search_space,
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)


"""
def test_attributes_results_search_id_0():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        search_id="1",
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.search_data("1"), pd.DataFrame)


def test_attributes_results_search_id_1():
    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        search_id="1",
        n_iter=15,
    )
    hyper.add_search(
        objective_function1,
        search_space,
        search_id="2",
        n_iter=15,
    )
    hyper.run()

    assert isinstance(hyper.search_data("1"), pd.DataFrame)
"""


def test_attributes_result_errors_0():
    with pytest.raises(ValueError):
        hyper = Hyperactive()
        hyper.add_search(objective_function, search_space, n_iter=15)
        hyper.run()

        hyper.best_para(objective_function1)


def test_attributes_result_errors_1():
    with pytest.raises(ValueError):
        hyper = Hyperactive()
        hyper.add_search(objective_function, search_space, n_iter=15)
        hyper.run()

        hyper.best_score(objective_function1)


def test_attributes_result_errors_2():
    with pytest.raises(ValueError):
        hyper = Hyperactive()
        hyper.add_search(objective_function, search_space, n_iter=15)
        hyper.run()

        hyper.search_data(objective_function1)


1			import pytest
2			import numbers
3			import numpy as np
4			import pandas as pd
5
6			from hyperactive import Hyperactive
7
8
9			def objective_function(opt):
10			score = -opt["x1"] * opt["x1"]
11			return score
12
13
14			def objective_function1(opt):
15			score = -opt["x1"] * opt["x1"]
16			return score
17
18
19			search_space = {
20			"x1": list(np.arange(0, 100, 1)),
21			}
22
23
24			def test_attributes_best_score_objective_function_0():
25			hyper = Hyperactive()
26			hyper.add_search(
27			objective_function,
28			search_space,
29			n_iter=15,
30			)
31			hyper.run()
32
33			assert isinstance(hyper.best_score(objective_function), numbers.Number)
34
35
36			def test_attributes_best_score_objective_function_1():
37			hyper = Hyperactive()
38			hyper.add_search(
39			objective_function,
40			search_space,
41			n_iter=15,
42			)
43			hyper.add_search(
44			objective_function1,
45			search_space,
46			n_iter=15,
47			)
48			hyper.run()
49
50			assert isinstance(hyper.best_score(objective_function), numbers.Number)
51
52
53			"""
54			def test_attributes_best_score_search_id_0():
55			hyper = Hyperactive()
56			hyper.add_search(
57			objective_function,
58			search_space,
59			search_id="1",
60			n_iter=15,
61			)
62			hyper.run()
63
64			assert isinstance(hyper.best_score(objective_function), numbers.Number)
65
66
67			def test_attributes_best_score_search_id_1():
68			hyper = Hyperactive()
69			hyper.add_search(
70			objective_function,
71			search_space,
72			search_id="1",
73			n_iter=15,
74			)
75			hyper.add_search(
76			objective_function1,
77			search_space,
78			search_id="2",
79			n_iter=15,
80			)
81			hyper.run()
82
83			assert isinstance(hyper.best_score(objective_function), numbers.Number)
84			"""
85
86
87			def test_attributes_best_para_objective_function_0():
88			hyper = Hyperactive()
89			hyper.add_search(
90			objective_function,
91			search_space,
92			n_iter=15,
93			)
94			hyper.run()
95
96			assert isinstance(hyper.best_para(objective_function), dict)
97
98
99			def test_attributes_best_para_objective_function_1():
100			hyper = Hyperactive()
101			hyper.add_search(
102			objective_function,
103			search_space,
104			n_iter=15,
105			)
106			hyper.add_search(
107			objective_function1,
108			search_space,
109			n_iter=15,
110			)
111			hyper.run()
112
113			assert isinstance(hyper.best_para(objective_function), dict)
114
115
116			"""
117			def test_attributes_best_para_search_id_0():
118			hyper = Hyperactive()
119			hyper.add_search(
120			objective_function,
121			search_space,
122			search_id="1",
123			n_iter=15,
124			)
125			hyper.run()
126
127			assert isinstance(hyper.best_para("1"), dict)
128
129
130			def test_attributes_best_para_search_id_1():
131			hyper = Hyperactive()
132			hyper.add_search(
133			objective_function,
134			search_space,
135			search_id="1",
136			n_iter=15,
137			)
138			hyper.add_search(
139			objective_function1,
140			search_space,
141			search_id="2",
142			n_iter=15,
143			)
144			hyper.run()
145
146			assert isinstance(hyper.best_para("1"), dict)
147			"""
148
149
150			def test_attributes_results_objective_function_0():
151			hyper = Hyperactive()
152			hyper.add_search(
153			objective_function,
154			search_space,
155			n_iter=15,
156			)
157			hyper.run()
158
159			assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
160
161
162			def test_attributes_results_objective_function_1():
163			hyper = Hyperactive()
164			hyper.add_search(
165			objective_function,
166			search_space,
167			n_iter=15,
168			)
169			hyper.add_search(
170			objective_function1,
171			search_space,
172			n_iter=15,
173			)
174			hyper.run()
175
176			assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
177
178
179			"""
180			def test_attributes_results_search_id_0():
181			hyper = Hyperactive()
182			hyper.add_search(
183			objective_function,
184			search_space,
185			search_id="1",
186			n_iter=15,
187			)
188			hyper.run()
189
190			assert isinstance(hyper.search_data("1"), pd.DataFrame)
191
192
193			def test_attributes_results_search_id_1():
194			hyper = Hyperactive()
195			hyper.add_search(
196			objective_function,
197			search_space,
198			search_id="1",
199			n_iter=15,
200			)
201			hyper.add_search(
202			objective_function1,
203			search_space,
204			search_id="2",
205			n_iter=15,
206			)
207			hyper.run()
208
209			assert isinstance(hyper.search_data("1"), pd.DataFrame)
210			"""
211
212
213			def test_attributes_result_errors_0():
214			with pytest.raises(ValueError):
215			hyper = Hyperactive()
216			hyper.add_search(objective_function, search_space, n_iter=15)
217			hyper.run()
218
219			hyper.best_para(objective_function1)
220
221
222			def test_attributes_result_errors_1():
223			with pytest.raises(ValueError):
224			hyper = Hyperactive()
225			hyper.add_search(objective_function, search_space, n_iter=15)
226			hyper.run()
227
228			hyper.best_score(objective_function1)
229
230
231			def test_attributes_result_errors_2():
232			with pytest.raises(ValueError):
233			hyper = Hyperactive()
234			hyper.add_search(objective_function, search_space, n_iter=15)
235			hyper.run()
236
237			hyper.search_data(objective_function1)
238

SimonBlanke / Hyperactive

Pull Request — master (#101)

tests_old.test_results_methods A

Complexity

Size/Duplication

Importance

11 Functions

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