Code Duplication - SimonBlanke/Hyperactive - Measure and Improve Code Quality continuously with Scrutinizer

Code Duplication Length = 32-33 lines in 5 locations

tests/_local_test_optimization_strategies/_test_memory_warm_start_smbo.py 1 location


}


@pytest.mark.parametrize(*optimizers_smbo)
def test_memory_Warm_start_smbo_0(Optimizer_smbo):
    optimizer1 = GridSearchOptimizer()
    optimizer2 = Optimizer_smbo()

    opt_strat = CustomOptimizationStrategy()
    opt_strat.add_optimizer(optimizer1, duration=0.8)
    opt_strat.add_optimizer(optimizer2, duration=0.2)

    n_iter = 100

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        optimizer=opt_strat,
        n_iter=n_iter,
        memory=True,
    )
    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) == 80
    assert len(optimizer2.search_data) == 20

    assert optimizer1.best_score <= optimizer2.best_score


tests/test_optimizers/test_optimization_strategies.py 1 location


}


@pytest.mark.parametrize(*optimizers)
def test_strategy_combinations_0(Optimizer):
    """Test custom optimization strategy with multiple optimizers."""
    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


tests/_local_test_optimization_strategies/_test_strategy_combinations.py 3 locations


    assert optimizer1.best_score <= optimizer2.best_score


@pytest.mark.parametrize(*optimizers)
@pytest.mark.parametrize(*optimizers_strat)
def test_strategy_combinations_2(Optimizer, Optimizer_strat):
    optimizer1 = Optimizer()
    optimizer2 = Optimizer_strat()

    opt_strat = CustomOptimizationStrategy()
    opt_strat.add_optimizer(optimizer1, duration=0.9)
    opt_strat.add_optimizer(optimizer2, duration=0.1)

    n_iter = 10

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        optimizer=opt_strat,
        n_iter=n_iter,
        memory=False,
    )
    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) == 9
    assert len(optimizer2.search_data) == 1

    assert optimizer1.best_score <= optimizer2.best_score


@pytest.mark.parametrize(*optimizers)

    assert optimizer1.best_score <= optimizer2.best_score


@pytest.mark.parametrize(*optimizers)
@pytest.mark.parametrize(*optimizers_strat)
def test_strategy_combinations_1(Optimizer, Optimizer_strat):
    optimizer1 = Optimizer()
    optimizer2 = Optimizer_strat()

    opt_strat = CustomOptimizationStrategy()
    opt_strat.add_optimizer(optimizer1, duration=0.1)
    opt_strat.add_optimizer(optimizer2, duration=0.9)

    n_iter = 10

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        optimizer=opt_strat,
        n_iter=n_iter,
        memory=False,
    )
    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) == 1
    assert len(optimizer2.search_data) == 9

    assert optimizer1.best_score <= optimizer2.best_score


@pytest.mark.parametrize(*optimizers)

}


@pytest.mark.parametrize(*optimizers)
@pytest.mark.parametrize(*optimizers_strat)
def test_strategy_combinations_0(Optimizer, Optimizer_strat):
    optimizer1 = Optimizer()
    optimizer2 = Optimizer_strat()

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

    n_iter = 30

    hyper = Hyperactive()
    hyper.add_search(
        objective_function,
        search_space,
        optimizer=opt_strat,
        n_iter=n_iter,
        memory=False,
    )
    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) == 15
    assert len(optimizer2.search_data) == 15

    assert optimizer1.best_score <= optimizer2.best_score


@pytest.mark.parametrize(*optimizers)

		@@ 24-55 (lines=32) @@
21		}
22
23
24		@pytest.mark.parametrize(*optimizers_smbo)
25		def test_memory_Warm_start_smbo_0(Optimizer_smbo):
26		optimizer1 = GridSearchOptimizer()
27		optimizer2 = Optimizer_smbo()
28
29		opt_strat = CustomOptimizationStrategy()
30		opt_strat.add_optimizer(optimizer1, duration=0.8)
31		opt_strat.add_optimizer(optimizer2, duration=0.2)
32
33		n_iter = 100
34
35		hyper = Hyperactive()
36		hyper.add_search(
37		objective_function,
38		search_space,
39		optimizer=opt_strat,
40		n_iter=n_iter,
41		memory=True,
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) == 80
53		assert len(optimizer2.search_data) == 20
54
55		assert optimizer1.best_score <= optimizer2.best_score
56

		@@ 25-57 (lines=33) @@
22		}
23
24
25		@pytest.mark.parametrize(*optimizers)
26		def test_strategy_combinations_0(Optimizer):
27		"""Test custom optimization strategy with multiple optimizers."""
28		optimizer1 = Optimizer()
29		optimizer2 = HillClimbingOptimizer()
30
31		opt_strat = CustomOptimizationStrategy()
32		opt_strat.add_optimizer(optimizer1, duration=0.5)
33		opt_strat.add_optimizer(optimizer2, duration=0.5)
34
35		n_iter = 4
36
37		hyper = Hyperactive()
38		hyper.add_search(
39		objective_function,
40		search_space,
41		optimizer=opt_strat,
42		n_iter=n_iter,
43		memory=False,
44		initialize={"random": 1},
45		)
46		hyper.run()
47
48		search_data = hyper.search_data(objective_function)
49
50		optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"]
51		optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"]
52
53		assert len(search_data) == n_iter
54
55		assert len(optimizer1.search_data) == 2
56		assert len(optimizer2.search_data) == 2
57
58		assert optimizer1.best_score <= optimizer2.best_score
59

		@@ 91-123 (lines=33) @@
88		assert optimizer1.best_score <= optimizer2.best_score
89
90
91		@pytest.mark.parametrize(*optimizers)
92		@pytest.mark.parametrize(*optimizers_strat)
93		def test_strategy_combinations_2(Optimizer, Optimizer_strat):
94		optimizer1 = Optimizer()
95		optimizer2 = Optimizer_strat()
96
97		opt_strat = CustomOptimizationStrategy()
98		opt_strat.add_optimizer(optimizer1, duration=0.9)
99		opt_strat.add_optimizer(optimizer2, duration=0.1)
100
101		n_iter = 10
102
103		hyper = Hyperactive()
104		hyper.add_search(
105		objective_function,
106		search_space,
107		optimizer=opt_strat,
108		n_iter=n_iter,
109		memory=False,
110		)
111		hyper.run()
112
113		search_data = hyper.search_data(objective_function)
114
115		optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"]
116		optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"]
117
118		assert len(search_data) == n_iter
119
120		assert len(optimizer1.search_data) == 9
121		assert len(optimizer2.search_data) == 1
122
123		assert optimizer1.best_score <= optimizer2.best_score
124
125
126		@pytest.mark.parametrize(*optimizers)
		@@ 56-88 (lines=33) @@
53		assert optimizer1.best_score <= optimizer2.best_score
54
55
56		@pytest.mark.parametrize(*optimizers)
57		@pytest.mark.parametrize(*optimizers_strat)
58		def test_strategy_combinations_1(Optimizer, Optimizer_strat):
59		optimizer1 = Optimizer()
60		optimizer2 = Optimizer_strat()
61
62		opt_strat = CustomOptimizationStrategy()
63		opt_strat.add_optimizer(optimizer1, duration=0.1)
64		opt_strat.add_optimizer(optimizer2, duration=0.9)
65
66		n_iter = 10
67
68		hyper = Hyperactive()
69		hyper.add_search(
70		objective_function,
71		search_space,
72		optimizer=opt_strat,
73		n_iter=n_iter,
74		memory=False,
75		)
76		hyper.run()
77
78		search_data = hyper.search_data(objective_function)
79
80		optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"]
81		optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"]
82
83		assert len(search_data) == n_iter
84
85		assert len(optimizer1.search_data) == 1
86		assert len(optimizer2.search_data) == 9
87
88		assert optimizer1.best_score <= optimizer2.best_score
89
90
91		@pytest.mark.parametrize(*optimizers)
		@@ 21-53 (lines=33) @@
18		}
19
20
21		@pytest.mark.parametrize(*optimizers)
22		@pytest.mark.parametrize(*optimizers_strat)
23		def test_strategy_combinations_0(Optimizer, Optimizer_strat):
24		optimizer1 = Optimizer()
25		optimizer2 = Optimizer_strat()
26
27		opt_strat = CustomOptimizationStrategy()
28		opt_strat.add_optimizer(optimizer1, duration=0.5)
29		opt_strat.add_optimizer(optimizer2, duration=0.5)
30
31		n_iter = 30
32
33		hyper = Hyperactive()
34		hyper.add_search(
35		objective_function,
36		search_space,
37		optimizer=opt_strat,
38		n_iter=n_iter,
39		memory=False,
40		)
41		hyper.run()
42
43		search_data = hyper.search_data(objective_function)
44
45		optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"]
46		optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"]
47
48		assert len(search_data) == n_iter
49
50		assert len(optimizer1.search_data) == 15
51		assert len(optimizer2.search_data) == 15
52
53		assert optimizer1.best_score <= optimizer2.best_score
54
55
56		@pytest.mark.parametrize(*optimizers)

SimonBlanke / Hyperactive

Code Duplication Length = 32-33 lines in 5 locations

tests/_local_test_optimization_strategies/_test_memory_warm_start_smbo.py 1 location

tests/test_optimizers/test_optimization_strategies.py 1 location

tests/_local_test_optimization_strategies/_test_strategy_combinations.py 3 locations