tests.test_optimizers.test_early_stop.test_early_stop_1() - Code Metrics - SimonBlanke/Gradient-Free-Optimizers - Measure and Improve Code Quality continuously with Scrutinizer

test_early_stop_1() A
last analyzed 2025-08-06 16:49 UTC

↳ Parent: tests.test_optimizers.test_early_stop

Complexity

Conditions

Size

Total Lines	13
Code Lines	11

Duplication

Lines	13
Ratio	100 %

Importance

Changes

Metric	Value
cc	1
eloc	11
nop	1
dl	13
loc	13
rs	9.85
c	0
b	0
f	0

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

from ._parametrize import optimizers


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


search_space = {
    "x1": np.arange(0, 10, 0.1),
}


@pytest.mark.parametrize(*optimizers)

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

    opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}], "random": 1})
    opt.search(
        objective_function,
        n_iter=1000,
        early_stopping=early_stopping,
    )


@pytest.mark.parametrize(*optimizers)

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

    opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}], "random": 1})
    opt.search(
        objective_function,
        n_iter=1000,
        early_stopping=early_stopping,
    )


@pytest.mark.parametrize(*optimizers)

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

    opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}], "random": 1})
    opt.search(
        objective_function,
        n_iter=1000,
        early_stopping=early_stopping,
    )


@pytest.mark.parametrize(*optimizers)

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

    search_space = {
        "x1": np.arange(0, 1000, 0.01),
    }

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

    opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}], "random": 1})
    opt.search(
        objective_function,
        n_iter=100000,
        early_stopping=early_stopping,
    )
    search_data = opt.search_data
    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 + 2)


@pytest.mark.parametrize(*optimizers)

def test_early_stop_4(Optimizer):
    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": 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)

    opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
    opt.search(
        objective_function,
        n_iter=n_iter,
        early_stopping=early_stopping,
    )
    search_data = opt.search_data
    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


@pytest.mark.parametrize(*optimizers)

def test_early_stop_5(Optimizer):
    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": 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)

    opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
    opt.search(
        objective_function,
        n_iter=n_iter,
        early_stopping=early_stopping,
    )
    search_data = opt.search_data
    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)


@pytest.mark.parametrize(*optimizers)

def test_early_stop_6(Optimizer):
    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": 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)

    opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
    opt.search(
        objective_function,
        n_iter=n_iter,
        early_stopping=early_stopping,
    )
    search_data = opt.search_data
    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


@pytest.mark.parametrize(*optimizers)

def test_early_stop_7(Optimizer):
    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": 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)

    opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
    opt.search(
        objective_function,
        n_iter=n_iter,
        early_stopping=early_stopping,
    )
    search_data = opt.search_data
    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
7		from ._parametrize import optimizers
8
9
10		def objective_function(para):
11		score = -para["x1"] * para["x1"]
12		return score
13
14
15		search_space = {
16		"x1": np.arange(0, 10, 0.1),
17		}
18
19
20	View Code Duplication	@pytest.mark.parametrize(*optimizers)
		0 ignored issues – show Duplication introduced 2021-09-03 05:42 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
21		def test_early_stop_0(Optimizer):
22		early_stopping = {
23		"n_iter_no_change": 5,
24		"tol_abs": 0.1,
25		"tol_rel": 0.1,
26		}
27
28		opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}], "random": 1})
29		opt.search(
30		objective_function,
31		n_iter=1000,
32		early_stopping=early_stopping,
33		)
34
35
36	View Code Duplication	@pytest.mark.parametrize(*optimizers)
		0 ignored issues – show Duplication introduced 2021-09-03 05:42 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
37		def test_early_stop_1(Optimizer):
38		early_stopping = {
39		"n_iter_no_change": 5,
40		"tol_abs": None,
41		"tol_rel": 5,
42		}
43
44		opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}], "random": 1})
45		opt.search(
46		objective_function,
47		n_iter=1000,
48		early_stopping=early_stopping,
49		)
50
51
52	View Code Duplication	@pytest.mark.parametrize(*optimizers)
		0 ignored issues – show Duplication introduced 2021-09-03 05:42 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
53		def test_early_stop_2(Optimizer):
54		early_stopping = {
55		"n_iter_no_change": 5,
56		"tol_abs": 0.1,
57		"tol_rel": None,
58		}
59
60		opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}], "random": 1})
61		opt.search(
62		objective_function,
63		n_iter=1000,
64		early_stopping=early_stopping,
65		)
66
67
68	View Code Duplication	@pytest.mark.parametrize(*optimizers)
		0 ignored issues – show Duplication introduced 2021-09-03 05:42 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
69		def test_early_stop_3(Optimizer):
70		def objective_function(para):
71		score = -para["x1"] * para["x1"]
72		return score
73
74		search_space = {
75		"x1": np.arange(0, 1000, 0.01),
76		}
77
78		n_iter_no_change = 5
79		early_stopping = {
80		"n_iter_no_change": n_iter_no_change,
81		}
82
83		opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}], "random": 1})
84		opt.search(
85		objective_function,
86		n_iter=100000,
87		early_stopping=early_stopping,
88		)
89		search_data = opt.search_data
90		n_performed_iter = len(search_data)
91
92		print("\n n_performed_iter \n", n_performed_iter)
93		print("\n n_iter_no_change \n", n_iter_no_change)
94
95		assert n_performed_iter == (n_iter_no_change + 2)
96
97
98	View Code Duplication	@pytest.mark.parametrize(*optimizers)
		0 ignored issues – show Duplication introduced 2021-09-03 05:42 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
99		def test_early_stop_4(Optimizer):
100		def objective_function(para):
101		return para["x1"]
102
103		search_space = {
104		"x1": np.arange(0, 100, 0.1),
105		}
106
107		n_iter_no_change = 5
108		early_stopping = {
109		"n_iter_no_change": 5,
110		"tol_abs": 0.1,
111		"tol_rel": None,
112		}
113
114		start1 = {"x1": 0}
115		start2 = {"x1": 0.1}
116		start3 = {"x1": 0.2}
117		start4 = {"x1": 0.3}
118		start5 = {"x1": 0.4}
119
120		warm_start_l = [
121		start1,
122		start1,
123		start1,
124		start1,
125		start1,
126		start2,
127		start2,
128		start2,
129		start3,
130		start3,
131		start3,
132		start4,
133		start4,
134		start4,
135		start5,
136		start5,
137		start5,
138		]
139		n_iter = len(warm_start_l)
140
141		opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
142		opt.search(
143		objective_function,
144		n_iter=n_iter,
145		early_stopping=early_stopping,
146		)
147		search_data = opt.search_data
148		n_performed_iter = len(search_data)
149
150		print("\n n_performed_iter \n", n_performed_iter)
151		print("\n n_iter_no_change \n", n_iter_no_change)
152
153		assert n_performed_iter == n_iter
154
155
156	View Code Duplication	@pytest.mark.parametrize(*optimizers)
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157		def test_early_stop_5(Optimizer):
158		def objective_function(para):
159		return para["x1"]
160
161		search_space = {
162		"x1": np.arange(0, 100, 0.01),
163		}
164
165		n_iter_no_change = 5
166		early_stopping = {
167		"n_iter_no_change": n_iter_no_change,
168		"tol_abs": 0.1,
169		"tol_rel": None,
170		}
171
172		start1 = {"x1": 0}
173		start2 = {"x1": 0.09}
174		start3 = {"x1": 0.20}
175
176		warm_start_l = [
177		start1,
178		start1,
179		start1,
180		start1,
181		start1,
182		start2,
183		start2,
184		start2,
185		start3,
186		start3,
187		start3,
188		]
189		n_iter = len(warm_start_l)
190
191		opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
192		opt.search(
193		objective_function,
194		n_iter=n_iter,
195		early_stopping=early_stopping,
196		)
197		search_data = opt.search_data
198		n_performed_iter = len(search_data)
199
200		print("\n n_performed_iter \n", n_performed_iter)
201		print("\n n_iter_no_change \n", n_iter_no_change)
202
203		assert n_performed_iter == (n_iter_no_change + 1)
204
205
206	View Code Duplication	@pytest.mark.parametrize(*optimizers)
		0 ignored issues – show Duplication introduced 2021-12-01 10:59 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
207		def test_early_stop_6(Optimizer):
208		def objective_function(para):
209		return para["x1"]
210
211		search_space = {
212		"x1": np.arange(0, 100, 0.01),
213		}
214
215		n_iter_no_change = 5
216		early_stopping = {
217		"n_iter_no_change": 5,
218		"tol_abs": None,
219		"tol_rel": 10,
220		}
221
222		start1 = {"x1": 1}
223		start2 = {"x1": 1.1}
224		start3 = {"x1": 1.22}
225		start4 = {"x1": 1.35}
226		start5 = {"x1": 1.48}
227
228		warm_start_l = [
229		start1,
230		start1,
231		start1,
232		start1,
233		start1,
234		start2,
235		start2,
236		start2,
237		start3,
238		start3,
239		start3,
240		start4,
241		start4,
242		start4,
243		start5,
244		start5,
245		start5,
246		]
247		n_iter = len(warm_start_l)
248
249		opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
250		opt.search(
251		objective_function,
252		n_iter=n_iter,
253		early_stopping=early_stopping,
254		)
255		search_data = opt.search_data
256		n_performed_iter = len(search_data)
257
258		print("\n n_performed_iter \n", n_performed_iter)
259		print("\n n_iter_no_change \n", n_iter_no_change)
260
261		assert n_performed_iter == n_iter
262
263
264	View Code Duplication	@pytest.mark.parametrize(*optimizers)
		0 ignored issues – show Duplication introduced 2021-12-01 10:59 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
265		def test_early_stop_7(Optimizer):
266		def objective_function(para):
267		return para["x1"]
268
269		search_space = {
270		"x1": np.arange(0, 100, 0.01),
271		}
272
273		n_iter_no_change = 5
274		early_stopping = {
275		"n_iter_no_change": n_iter_no_change,
276		"tol_abs": None,
277		"tol_rel": 10,
278		}
279
280		start1 = {"x1": 1}
281		start2 = {"x1": 1.09}
282		start3 = {"x1": 1.20}
283
284		warm_start_l = [
285		start1,
286		start1,
287		start1,
288		start1,
289		start1,
290		start2,
291		start2,
292		start2,
293		start3,
294		start3,
295		start3,
296		]
297		n_iter = len(warm_start_l)
298
299		opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
300		opt.search(
301		objective_function,
302		n_iter=n_iter,
303		early_stopping=early_stopping,
304		)
305		search_data = opt.search_data
306		n_performed_iter = len(search_data)
307
308		print("\n n_performed_iter \n", n_performed_iter)
309		print("\n n_iter_no_change \n", n_iter_no_change)
310
311		assert n_performed_iter == (n_iter_no_change + 1)
312

SimonBlanke / Gradient-Free-Optimizers

test_early_stop_1() A last analyzed 2025-08-06 16:49 UTC

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test_early_stop_1() A
last analyzed 2025-08-06 16:49 UTC