tests.test_catch - Code Metrics - Inspection of "remove test-case that shows in linter" - SimonBlanke/Hyperactive - Measure and Improve Code Quality continuously with Scrutinizer

Passed

Push — master ( 6d9b4e...95402e )

by Simon

created 2024-05-31 16:56 UTC

tests.test_catch A

↳ Parent: Project

Complexity

Total Complexity

Size/Duplication

Total Lines	121
Duplicated Lines	0 %

Importance

Changes

Metric	Value
wmc	5
eloc	86
dl	0
loc	121
rs	10
c	0
b	0
f	0

5 Functions

Rating	Name	Size	Complexity
A	test_catch_2()	14	1
A	test_catch_3()	14	1
A	test_catch_1()	14	1
A	test_catch_all_1()	30	1
A	test_catch_all_0()	26	1

import copy
import pytest
import math
import numpy as np
import pandas as pd

from hyperactive import Hyperactive


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


def test_catch_1():
    def objective_function(access):
        a = 1 + "str"

        return 0

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=100,
        catch={TypeError: np.nan},
    )
    hyper.run()


def test_catch_2():
    def objective_function(access):
        math.sqrt(-10)

        return 0

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=100,
        catch={ValueError: np.nan},
    )
    hyper.run()


def test_catch_3():
    def objective_function(access):
        x = 1 / 0

        return 0

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=100,
        catch={ZeroDivisionError: np.nan},
    )
    hyper.run()


def test_catch_all_0():
    def objective_function(access):
        x = y

        a = 1 + "str"
        math.sqrt(-10)
        x = 1 / 0

        return 0

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=100,
        catch={
            NameError: np.nan,
            TypeError: np.nan,
            ValueError: np.nan,
            ZeroDivisionError: np.nan,
        },
    )
    hyper.run()

    nan_ = hyper.search_data(objective_function)["score"].values[0]

    assert math.isnan(nan_)


def test_catch_all_1():
    def objective_function(access):
        x = y

        a = 1 + "str"
        math.sqrt(-10)
        x = 1 / 0

        return 0, {"error": False}

    catch_return = (np.nan, {"error": True})

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=100,
        catch={
            NameError: catch_return,
            TypeError: catch_return,
            ValueError: catch_return,
            ZeroDivisionError: catch_return,
        },
    )
    hyper.run()

    nan_ = hyper.search_data(objective_function)["score"].values[0]
    error_ = hyper.search_data(objective_function)["error"].values[0]

    assert math.isnan(nan_)
    assert error_ == True


1			import copy
2			import pytest
3			import math
4			import numpy as np
5			import pandas as pd
6
7			from hyperactive import Hyperactive
8
9
10			search_space = {
11			"x1": list(np.arange(-100, 100, 1)),
12			}
13
14
15			def test_catch_1():
16			def objective_function(access):
17			a = 1 + "str"
18
19			return 0
20
21			hyper = Hyperactive()
22			hyper.add_search(
23			objective_function,
24			search_space,
25			n_iter=100,
26			catch={TypeError: np.nan},
27			)
28			hyper.run()
29
30
31			def test_catch_2():
32			def objective_function(access):
33			math.sqrt(-10)
34
35			return 0
36
37			hyper = Hyperactive()
38			hyper.add_search(
39			objective_function,
40			search_space,
41			n_iter=100,
42			catch={ValueError: np.nan},
43			)
44			hyper.run()
45
46
47			def test_catch_3():
48			def objective_function(access):
49			x = 1 / 0
50
51			return 0
52
53			hyper = Hyperactive()
54			hyper.add_search(
55			objective_function,
56			search_space,
57			n_iter=100,
58			catch={ZeroDivisionError: np.nan},
59			)
60			hyper.run()
61
62
63			def test_catch_all_0():
64			def objective_function(access):
65			x = y
			0 ignored issues – show Comprehensibility Best Practice introduced 2022-05-03 11:02 UTC by Report Bug Copy Issue Report The variable `y` does not seem to be defined. Loading history...
66			a = 1 + "str"
67			math.sqrt(-10)
68			x = 1 / 0
69
70			return 0
71
72			hyper = Hyperactive()
73			hyper.add_search(
74			objective_function,
75			search_space,
76			n_iter=100,
77			catch={
78			NameError: np.nan,
79			TypeError: np.nan,
80			ValueError: np.nan,
81			ZeroDivisionError: np.nan,
82			},
83			)
84			hyper.run()
85
86			nan_ = hyper.search_data(objective_function)["score"].values[0]
87
88			assert math.isnan(nan_)
89
90
91			def test_catch_all_1():
92			def objective_function(access):
93			x = y
			0 ignored issues – show Comprehensibility Best Practice introduced 2022-05-03 11:02 UTC by Report Bug Copy Issue Report The variable `y` does not seem to be defined. Loading history...
94			a = 1 + "str"
95			math.sqrt(-10)
96			x = 1 / 0
97
98			return 0, {"error": False}
99
100			catch_return = (np.nan, {"error": True})
101
102			hyper = Hyperactive()
103			hyper.add_search(
104			objective_function,
105			search_space,
106			n_iter=100,
107			catch={
108			NameError: catch_return,
109			TypeError: catch_return,
110			ValueError: catch_return,
111			ZeroDivisionError: catch_return,
112			},
113			)
114			hyper.run()
115
116			nan_ = hyper.search_data(objective_function)["score"].values[0]
117			error_ = hyper.search_data(objective_function)["error"].values[0]
118
119			assert math.isnan(nan_)
120			assert error_ == True
121

SimonBlanke / Hyperactive

Push — master ( 6d9b4e...95402e )

tests.test_catch A

Complexity

Size/Duplication

Importance

5 Functions

Duplication Side-by-Side

Filter issues like