tests.test_optimizers.test_optimization_strategies.test_strategy_combinations_0() - Code Metrics - Inspection of "add tests for opt. strat." - SimonBlanke/Hyperactive - Measure and Improve Code Quality continuously with Scrutinizer

Passed

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by Simon

created 2023-03-01 11:29 UTC

test_strategy_combinations_0() A

↳ Parent: tests.test_optimizers.test_optimization_strategies

Complexity

Conditions

Size

Total Lines	33
Code Lines	24

Duplication

Lines	33
Ratio	100 %

Importance

Changes

Metric	Value
cc	1
eloc	24
nop	1
dl	33
loc	33
rs	9.304
c	0
b	0
f	0

import pytest
import numpy as np


from hyperactive import Hyperactive
from hyperactive.optimizers.strategies import CustomOptimizationStrategy
from hyperactive.optimizers import HillClimbingOptimizer

from ._parametrize import optimizers


def objective_function(opt):
    score = -(opt["x1"] * opt["x1"] + opt["x2"] * opt["x2"])
    return score


search_space = {
    "x1": list(np.arange(-3, 3, 1)),
    "x2": list(np.arange(-3, 3, 1)),
}


@pytest.mark.parametrize(*optimizers)

def test_strategy_combinations_0(Optimizer):
    optimizer1 = Optimizer()
    optimizer2 = HillClimbingOptimizer()

    opt_strat = CustomOptimizationStrategy()
    opt_strat.add_optimizer(optimizer1, duration=0.5)
    opt_strat.add_optimizer(optimizer2, duration=0.5)

    n_iter = 4

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        optimizer=opt_strat,
        n_iter=n_iter,
        memory=False,
        initialize={"random": 1},
    )
    hyper.run()

    search_data = hyper.search_data(objective_function)

    optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"]
    optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"]

    assert len(search_data) == n_iter

    assert len(optimizer1.search_data) == 2
    assert len(optimizer2.search_data) == 2

    assert optimizer1.best_score <= optimizer2.best_score


1		import pytest
2		import numpy as np
3
4
5		from hyperactive import Hyperactive
6		from hyperactive.optimizers.strategies import CustomOptimizationStrategy
7		from hyperactive.optimizers import HillClimbingOptimizer
8
9		from ._parametrize import optimizers
10
11
12		def objective_function(opt):
13		score = -(opt["x1"] * opt["x1"] + opt["x2"] * opt["x2"])
14		return score
15
16
17		search_space = {
18		"x1": list(np.arange(-3, 3, 1)),
19		"x2": list(np.arange(-3, 3, 1)),
20		}
21
22
23	View Code Duplication	@pytest.mark.parametrize(*optimizers)
		0 ignored issues – show Duplication introduced 2023-03-01 11:33 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
24		def test_strategy_combinations_0(Optimizer):
25		optimizer1 = Optimizer()
26		optimizer2 = HillClimbingOptimizer()
27
28		opt_strat = CustomOptimizationStrategy()
29		opt_strat.add_optimizer(optimizer1, duration=0.5)
30		opt_strat.add_optimizer(optimizer2, duration=0.5)
31
32		n_iter = 4
33
34		hyper = Hyperactive()
35		hyper.add_search(
36		objective_function,
37		search_space,
38		optimizer=opt_strat,
39		n_iter=n_iter,
40		memory=False,
41		initialize={"random": 1},
42		)
43		hyper.run()
44
45		search_data = hyper.search_data(objective_function)
46
47		optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"]
48		optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"]
49
50		assert len(search_data) == n_iter
51
52		assert len(optimizer1.search_data) == 2
53		assert len(optimizer2.search_data) == 2
54
55		assert optimizer1.best_score <= optimizer2.best_score
56

SimonBlanke / Hyperactive

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test_strategy_combinations_0() A

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