tests_old.test_catch.test_catch_all_1() - 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 2025-03-16 17:31 UTC

tests_old.test_catch.test_catch_all_1() A

↳ Parent: tests_old.test_catch

Complexity

Conditions

Size

Total Lines	28
Code Lines	21

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	1
eloc	21
nop	0
dl	0
loc	28
rs	9.376
c	0
b	0
f	0

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

        return 0

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=100,
        catch={
            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):
        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={
            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			a = 1 + "str"
66			math.sqrt(-10)
67			x = 1 / 0
68
69			return 0
70
71			hyper = Hyperactive()
72			hyper.add_search(
73			objective_function,
74			search_space,
75			n_iter=100,
76			catch={
77			TypeError: np.nan,
78			ValueError: np.nan,
79			ZeroDivisionError: np.nan,
80			},
81			)
82			hyper.run()
83
84			nan_ = hyper.search_data(objective_function)["score"].values[0]
85
86			assert math.isnan(nan_)
87
88
89			def test_catch_all_1():
90			def objective_function(access):
91			a = 1 + "str"
92			math.sqrt(-10)
93			x = 1 / 0
94
95			return 0, {"error": False}
96
97			catch_return = (np.nan, {"error": True})
98
99			hyper = Hyperactive()
100			hyper.add_search(
101			objective_function,
102			search_space,
103			n_iter=100,
104			catch={
105			TypeError: catch_return,
106			ValueError: catch_return,
107			ZeroDivisionError: catch_return,
108			},
109			)
110			hyper.run()
111
112			nan_ = hyper.search_data(objective_function)["score"].values[0]
113			error_ = hyper.search_data(objective_function)["error"].values[0]
114
115			assert math.isnan(nan_)
116			assert error_ == True
117

SimonBlanke / Hyperactive

Pull Request — master (#101)

tests_old.test_catch.test_catch_all_1() A

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