test_random_state_n_jobs_2()   A
last analyzed

Complexity

Conditions 1

Size

Total Lines 21
Code Lines 16

Duplication

Lines 21
Ratio 100 %

Importance

Changes 0
Metric Value
cc 1
eloc 16
nop 0
dl 21
loc 21
rs 9.6
c 0
b 0
f 0
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import numpy as np
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from hyperactive import Hyperactive
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def objective_function(opt):
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    score = -(opt["x1"] * opt["x1"] + opt["x2"] * opt["x2"])
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    return score
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search_space = {
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    "x1": list(np.arange(-1000, 1000, 0.1)),
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    "x2": list(np.arange(-1000, 1000, 0.1)),
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}
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err = 0.001
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def test_random_state_n_jobs_0():
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    n_jobs = 2
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    hyper = Hyperactive()
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    hyper.add_search(
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        objective_function,
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        search_space,
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        n_iter=5,
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        initialize={"random": 1},
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        random_state=1,
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        n_jobs=n_jobs,
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    )
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    hyper.run()
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    results = hyper.search_data(objective_function)
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    no_dup = results.drop_duplicates(subset=list(search_space.keys()))
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    print("no_dup", no_dup)
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    print("results", results)
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    print(int(len(results) / n_jobs))
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    print(len(no_dup))
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    assert int(len(results) / n_jobs) != len(no_dup)
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def test_random_state_n_jobs_1():
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    n_jobs = 3
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    hyper = Hyperactive()
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    hyper.add_search(
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        objective_function,
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        search_space,
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        n_iter=5,
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        initialize={"random": 1},
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        random_state=1,
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        n_jobs=n_jobs,
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    )
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    hyper.run()
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    results = hyper.search_data(objective_function)
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    no_dup = results.drop_duplicates(subset=list(search_space.keys()))
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    print("no_dup", no_dup)
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    print("results", results)
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    assert int(len(results) / n_jobs) != len(no_dup)
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def test_random_state_n_jobs_2():
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    n_jobs = 4
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    hyper = Hyperactive()
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    hyper.add_search(
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        objective_function,
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        search_space,
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        n_iter=5,
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        initialize={"random": 1},
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        random_state=1,
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        n_jobs=n_jobs,
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    )
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    hyper.run()
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    results = hyper.search_data(objective_function)
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    no_dup = results.drop_duplicates(subset=list(search_space.keys()))
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    print("no_dup", no_dup)
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    print("results", results)
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    assert int(len(results) / n_jobs) != len(no_dup)
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def test_random_state_0():
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    hyper0 = Hyperactive()
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    hyper0.add_search(
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        objective_function,
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        search_space,
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        n_iter=10,
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        initialize={"random": 1},
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        random_state=1,
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    )
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    hyper0.run()
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    hyper1 = Hyperactive()
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    hyper1.add_search(
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        objective_function,
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        search_space,
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        n_iter=10,
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        initialize={"random": 1},
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        random_state=1,
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    )
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    hyper1.run()
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    best_score0 = hyper0.best_score(objective_function)
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    best_score1 = hyper1.best_score(objective_function)
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    assert abs(best_score0 - best_score1) < err
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def test_random_state_1():
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    hyper0 = Hyperactive()
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    hyper0.add_search(
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        objective_function,
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        search_space,
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        n_iter=10,
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        initialize={"random": 1},
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        random_state=10,
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    )
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    hyper0.run()
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    hyper1 = Hyperactive()
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    hyper1.add_search(
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        objective_function,
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        search_space,
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        n_iter=10,
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        initialize={"random": 1},
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        random_state=10,
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    )
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    hyper1.run()
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    best_score0 = hyper0.best_score(objective_function)
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    best_score1 = hyper1.best_score(objective_function)
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    assert abs(best_score0 - best_score1) < err
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145 View Code Duplication
def test_random_state_2():
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    hyper0 = Hyperactive()
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    hyper0.add_search(
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        objective_function,
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        search_space,
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        n_iter=10,
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        initialize={"random": 1},
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        random_state=1,
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    )
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    hyper0.run()
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    hyper1 = Hyperactive()
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    hyper1.add_search(
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        objective_function,
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        search_space,
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        n_iter=10,
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        initialize={"random": 1},
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        random_state=10,
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    )
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    hyper1.run()
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    best_score0 = hyper0.best_score(objective_function)
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    best_score1 = hyper1.best_score(objective_function)
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    assert abs(best_score0 - best_score1) > err
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def test_no_random_state_0():
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    hyper0 = Hyperactive()
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    hyper0.add_search(
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        objective_function,
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        search_space,
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        n_iter=10,
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        initialize={"random": 1},
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    )
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    hyper0.run()
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    hyper1 = Hyperactive()
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    hyper1.add_search(
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        objective_function,
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        search_space,
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        n_iter=10,
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        initialize={"random": 1},
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    )
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    hyper1.run()
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    best_score0 = hyper0.best_score(objective_function)
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    best_score1 = hyper1.best_score(objective_function)
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    assert abs(best_score0 - best_score1) > err
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