tests.test_early_stop - Code Metrics - SimonBlanke/Hyperactive - Measure and Improve Code Quality continuously with Scrutinizer

tests.test_early_stop A
last analyzed 2025-06-23 18:24 UTC

↳ Parent: Project

Complexity

Total Complexity

Size/Duplication

Total Lines	338
Duplicated Lines	65.09 %

Importance

Changes

Metric	Value
eloc	249
dl	220
loc	338
rs	10
c	0
b	0
f	0
wmc	9

9 Functions

Rating	Name	Duplication	Size	Complexity
A	test_early_stop_3()	0	31	1
A	test_early_stop_1()	0	16	1
A	test_early_stop_2()	0	16	1
A	test_early_stop_0()	0	16	1
B	test_early_stop_4()	59	59	1
B	test_early_stop_6()	59	59	1
B	test_early_stop_5()	51	51	1
A	objective_function()	0	3	1
B	test_early_stop_7()	51	51	1

How to fix Duplicated Code

import time
import pytest
import numpy as np
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import cross_val_score
from sklearn.tree import DecisionTreeClassifier

from hyperactive import Hyperactive
from hyperactive.optimizers import (
    RandomSearchOptimizer,
    HillClimbingOptimizer,
)


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


search_space = {
    "x1": list(np.arange(0, 100000, 0.1)),
}


def test_early_stop_0():
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": 0.1,
        "tol_rel": 0.1,
    }

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=1000,
        initialize={"warm_start": [{"x1": 0}]},
        early_stopping=early_stopping,
    )
    hyper.run()


def test_early_stop_1():
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": None,
        "tol_rel": 5,
    }

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=1000,
        initialize={"warm_start": [{"x1": 0}]},
        early_stopping=early_stopping,
    )
    hyper.run()


def test_early_stop_2():
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": 0.1,
        "tol_rel": None,
    }

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=1000,
        initialize={"warm_start": [{"x1": 0}]},
        early_stopping=early_stopping,
    )
    hyper.run()


def test_early_stop_3():
    def objective_function(para):
        score = -para["x1"] * para["x1"]
        return score

    search_space = {
        "x1": list(np.arange(0, 100, 0.1)),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": n_iter_no_change,
    }

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=100000,
        initialize={"warm_start": [{"x1": 0}]},
        early_stopping=early_stopping,
    )
    hyper.run()

    search_data = hyper.search_data(objective_function)
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == (n_iter_no_change + 1)


def test_early_stop_4():

    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": list(np.arange(0, 100, 0.1)),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": 0.1,
        "tol_rel": None,
    }

    start1 = {"x1": 0}
    start2 = {"x1": 0.1}
    start3 = {"x1": 0.2}
    start4 = {"x1": 0.3}
    start5 = {"x1": 0.4}

    warm_start_l = [
        start1,
        start1,
        start1,
        start1,
        start1,
        start2,
        start2,
        start2,
        start3,
        start3,
        start3,
        start4,
        start4,
        start4,
        start5,
        start5,
        start5,
    ]
    n_iter = len(warm_start_l)

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=n_iter,
        initialize={"warm_start": warm_start_l},
        early_stopping=early_stopping,
    )
    hyper.run()

    search_data = hyper.search_data(objective_function)
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == n_iter


def test_early_stop_5():

    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": list(np.arange(0, 100, 0.01)),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": n_iter_no_change,
        "tol_abs": 0.1,
        "tol_rel": None,
    }

    start1 = {"x1": 0}
    start2 = {"x1": 0.09}
    start3 = {"x1": 0.20}

    warm_start_l = [
        start1,
        start1,
        start1,
        start1,
        start1,
        start2,
        start2,
        start2,
        start3,
        start3,
        start3,
    ]
    n_iter = len(warm_start_l)

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=n_iter,
        initialize={"warm_start": warm_start_l},
        early_stopping=early_stopping,
    )
    hyper.run()

    search_data = hyper.search_data(objective_function)
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == (n_iter_no_change + 1)


def test_early_stop_6():

    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": list(np.arange(0, 100, 0.01)),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": None,
        "tol_rel": 10,
    }

    start1 = {"x1": 1}
    start2 = {"x1": 1.1}
    start3 = {"x1": 1.22}
    start4 = {"x1": 1.35}
    start5 = {"x1": 1.48}

    warm_start_l = [
        start1,
        start1,
        start1,
        start1,
        start1,
        start2,
        start2,
        start2,
        start3,
        start3,
        start3,
        start4,
        start4,
        start4,
        start5,
        start5,
        start5,
    ]
    n_iter = len(warm_start_l)

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=n_iter,
        initialize={"warm_start": warm_start_l},
        early_stopping=early_stopping,
    )
    hyper.run()

    search_data = hyper.search_data(objective_function)
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == n_iter


def test_early_stop_7():

    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": list(np.arange(0, 100, 0.01)),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": n_iter_no_change,
        "tol_abs": None,
        "tol_rel": 10,
    }

    start1 = {"x1": 1}
    start2 = {"x1": 1.09}
    start3 = {"x1": 1.20}

    warm_start_l = [
        start1,
        start1,
        start1,
        start1,
        start1,
        start2,
        start2,
        start2,
        start3,
        start3,
        start3,
    ]
    n_iter = len(warm_start_l)

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        n_iter=n_iter,
        initialize={"warm_start": warm_start_l},
        early_stopping=early_stopping,
    )
    hyper.run()

    search_data = hyper.search_data(objective_function)
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == (n_iter_no_change + 1)


1		import time
2		import pytest
3		import numpy as np
4		from sklearn.datasets import load_breast_cancer
5		from sklearn.model_selection import cross_val_score
6		from sklearn.tree import DecisionTreeClassifier
7
8		from hyperactive import Hyperactive
9		from hyperactive.optimizers import (
10		RandomSearchOptimizer,
11		HillClimbingOptimizer,
12		)
13
14
15		def objective_function(para):
16		score = -para["x1"] * para["x1"]
17		return score
18
19
20		search_space = {
21		"x1": list(np.arange(0, 100000, 0.1)),
22		}
23
24
25		def test_early_stop_0():
26		early_stopping = {
27		"n_iter_no_change": 5,
28		"tol_abs": 0.1,
29		"tol_rel": 0.1,
30		}
31
32		hyper = Hyperactive()
33		hyper.add_search(
34		objective_function,
35		search_space,
36		n_iter=1000,
37		initialize={"warm_start": [{"x1": 0}]},
38		early_stopping=early_stopping,
39		)
40		hyper.run()
41
42
43		def test_early_stop_1():
44		early_stopping = {
45		"n_iter_no_change": 5,
46		"tol_abs": None,
47		"tol_rel": 5,
48		}
49
50		hyper = Hyperactive()
51		hyper.add_search(
52		objective_function,
53		search_space,
54		n_iter=1000,
55		initialize={"warm_start": [{"x1": 0}]},
56		early_stopping=early_stopping,
57		)
58		hyper.run()
59
60
61		def test_early_stop_2():
62		early_stopping = {
63		"n_iter_no_change": 5,
64		"tol_abs": 0.1,
65		"tol_rel": None,
66		}
67
68		hyper = Hyperactive()
69		hyper.add_search(
70		objective_function,
71		search_space,
72		n_iter=1000,
73		initialize={"warm_start": [{"x1": 0}]},
74		early_stopping=early_stopping,
75		)
76		hyper.run()
77
78
79		def test_early_stop_3():
80		def objective_function(para):
81		score = -para["x1"] * para["x1"]
82		return score
83
84		search_space = {
85		"x1": list(np.arange(0, 100, 0.1)),
86		}
87
88		n_iter_no_change = 5
89		early_stopping = {
90		"n_iter_no_change": n_iter_no_change,
91		}
92
93		hyper = Hyperactive()
94		hyper.add_search(
95		objective_function,
96		search_space,
97		n_iter=100000,
98		initialize={"warm_start": [{"x1": 0}]},
99		early_stopping=early_stopping,
100		)
101		hyper.run()
102
103		search_data = hyper.search_data(objective_function)
104		n_performed_iter = len(search_data)
105
106		print("\n n_performed_iter \n", n_performed_iter)
107		print("\n n_iter_no_change \n", n_iter_no_change)
108
109		assert n_performed_iter == (n_iter_no_change + 1)
110
111
112	View Code Duplication	def test_early_stop_4():
		0 ignored issues – show Duplication introduced 2022-03-16 12:55 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
113		def objective_function(para):
114		return para["x1"]
115
116		search_space = {
117		"x1": list(np.arange(0, 100, 0.1)),
118		}
119
120		n_iter_no_change = 5
121		early_stopping = {
122		"n_iter_no_change": 5,
123		"tol_abs": 0.1,
124		"tol_rel": None,
125		}
126
127		start1 = {"x1": 0}
128		start2 = {"x1": 0.1}
129		start3 = {"x1": 0.2}
130		start4 = {"x1": 0.3}
131		start5 = {"x1": 0.4}
132
133		warm_start_l = [
134		start1,
135		start1,
136		start1,
137		start1,
138		start1,
139		start2,
140		start2,
141		start2,
142		start3,
143		start3,
144		start3,
145		start4,
146		start4,
147		start4,
148		start5,
149		start5,
150		start5,
151		]
152		n_iter = len(warm_start_l)
153
154		hyper = Hyperactive()
155		hyper.add_search(
156		objective_function,
157		search_space,
158		n_iter=n_iter,
159		initialize={"warm_start": warm_start_l},
160		early_stopping=early_stopping,
161		)
162		hyper.run()
163
164		search_data = hyper.search_data(objective_function)
165		n_performed_iter = len(search_data)
166
167		print("\n n_performed_iter \n", n_performed_iter)
168		print("\n n_iter_no_change \n", n_iter_no_change)
169
170		assert n_performed_iter == n_iter
171
172
173	View Code Duplication	def test_early_stop_5():
		0 ignored issues – show Duplication introduced 2022-03-16 12:55 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
174		def objective_function(para):
175		return para["x1"]
176
177		search_space = {
178		"x1": list(np.arange(0, 100, 0.01)),
179		}
180
181		n_iter_no_change = 5
182		early_stopping = {
183		"n_iter_no_change": n_iter_no_change,
184		"tol_abs": 0.1,
185		"tol_rel": None,
186		}
187
188		start1 = {"x1": 0}
189		start2 = {"x1": 0.09}
190		start3 = {"x1": 0.20}
191
192		warm_start_l = [
193		start1,
194		start1,
195		start1,
196		start1,
197		start1,
198		start2,
199		start2,
200		start2,
201		start3,
202		start3,
203		start3,
204		]
205		n_iter = len(warm_start_l)
206
207		hyper = Hyperactive()
208		hyper.add_search(
209		objective_function,
210		search_space,
211		n_iter=n_iter,
212		initialize={"warm_start": warm_start_l},
213		early_stopping=early_stopping,
214		)
215		hyper.run()
216
217		search_data = hyper.search_data(objective_function)
218		n_performed_iter = len(search_data)
219
220		print("\n n_performed_iter \n", n_performed_iter)
221		print("\n n_iter_no_change \n", n_iter_no_change)
222
223		assert n_performed_iter == (n_iter_no_change + 1)
224
225
226	View Code Duplication	def test_early_stop_6():
		0 ignored issues – show Duplication introduced 2022-03-16 12:55 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
227		def objective_function(para):
228		return para["x1"]
229
230		search_space = {
231		"x1": list(np.arange(0, 100, 0.01)),
232		}
233
234		n_iter_no_change = 5
235		early_stopping = {
236		"n_iter_no_change": 5,
237		"tol_abs": None,
238		"tol_rel": 10,
239		}
240
241		start1 = {"x1": 1}
242		start2 = {"x1": 1.1}
243		start3 = {"x1": 1.22}
244		start4 = {"x1": 1.35}
245		start5 = {"x1": 1.48}
246
247		warm_start_l = [
248		start1,
249		start1,
250		start1,
251		start1,
252		start1,
253		start2,
254		start2,
255		start2,
256		start3,
257		start3,
258		start3,
259		start4,
260		start4,
261		start4,
262		start5,
263		start5,
264		start5,
265		]
266		n_iter = len(warm_start_l)
267
268		hyper = Hyperactive()
269		hyper.add_search(
270		objective_function,
271		search_space,
272		n_iter=n_iter,
273		initialize={"warm_start": warm_start_l},
274		early_stopping=early_stopping,
275		)
276		hyper.run()
277
278		search_data = hyper.search_data(objective_function)
279		n_performed_iter = len(search_data)
280
281		print("\n n_performed_iter \n", n_performed_iter)
282		print("\n n_iter_no_change \n", n_iter_no_change)
283
284		assert n_performed_iter == n_iter
285
286
287	View Code Duplication	def test_early_stop_7():
		0 ignored issues – show Duplication introduced 2022-03-16 12:55 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
288		def objective_function(para):
289		return para["x1"]
290
291		search_space = {
292		"x1": list(np.arange(0, 100, 0.01)),
293		}
294
295		n_iter_no_change = 5
296		early_stopping = {
297		"n_iter_no_change": n_iter_no_change,
298		"tol_abs": None,
299		"tol_rel": 10,
300		}
301
302		start1 = {"x1": 1}
303		start2 = {"x1": 1.09}
304		start3 = {"x1": 1.20}
305
306		warm_start_l = [
307		start1,
308		start1,
309		start1,
310		start1,
311		start1,
312		start2,
313		start2,
314		start2,
315		start3,
316		start3,
317		start3,
318		]
319		n_iter = len(warm_start_l)
320
321		hyper = Hyperactive()
322		hyper.add_search(
323		objective_function,
324		search_space,
325		n_iter=n_iter,
326		initialize={"warm_start": warm_start_l},
327		early_stopping=early_stopping,
328		)
329		hyper.run()
330
331		search_data = hyper.search_data(objective_function)
332		n_performed_iter = len(search_data)
333
334		print("\n n_performed_iter \n", n_performed_iter)
335		print("\n n_iter_no_change \n", n_iter_no_change)
336
337		assert n_performed_iter == (n_iter_no_change + 1)
338

SimonBlanke / Hyperactive

tests.test_early_stop A last analyzed 2025-06-23 18:24 UTC

Complexity

Size/Duplication

Importance

9 Functions

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tests.test_early_stop A
last analyzed 2025-06-23 18:24 UTC