Issues (58)

tests/test_search_spaces.py (3 issues)

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import numpy as np
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import pandas as pd
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from hyperactive import Hyperactive
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7 View Code Duplication
def test_search_space_0():
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    def objective_function(opt):
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        score = -opt["x1"] * opt["x1"]
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        return score
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    search_space = {
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        "x1": list(range(0, 3, 1)),
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    }
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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=15,
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    )
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    hyper.run()
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    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
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    assert hyper.best_para(objective_function)["x1"] in search_space["x1"]
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28 View Code Duplication
def test_search_space_1():
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    def objective_function(opt):
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        score = -opt["x1"] * opt["x1"]
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        return score
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    search_space = {
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        "x1": list(np.arange(0, 0.003, 0.001)),
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    }
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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=15,
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    )
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    hyper.run()
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    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
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    assert hyper.best_para(objective_function)["x1"] in search_space["x1"]
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49 View Code Duplication
def test_search_space_2():
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50
    def objective_function(opt):
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        score = -opt["x1"] * opt["x1"]
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        return score
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    search_space = {
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        "x1": list(range(0, 100, 1)),
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        "str1": ["0", "1", "2"],
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    }
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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=15,
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    )
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    hyper.run()
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    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
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    assert hyper.best_para(objective_function)["str1"] in search_space["str1"]
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def test_search_space_3():
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    def func1():
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        pass
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    def func2():
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        pass
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    def func3():
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        pass
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    def objective_function(opt):
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        score = -opt["x1"] * opt["x1"]
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        return score
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    search_space = {
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        "x1": list(range(0, 100, 1)),
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        "func1": [func1, func2, func3],
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    }
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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=15,
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    )
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    hyper.run()
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    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
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    assert hyper.best_para(objective_function)["func1"] in search_space["func1"]
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def test_search_space_4():
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    class class1:
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        pass
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    class class2:
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        pass
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    class class3:
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        pass
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    def objective_function(opt):
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        score = -opt["x1"] * opt["x1"]
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        return score
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    search_space = {
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        "x1": list(range(0, 100, 1)),
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        "class1": [class1, class2, class3],
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    }
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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=15,
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    )
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    hyper.run()
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    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
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    assert hyper.best_para(objective_function)["class1"] in search_space["class1"]
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def test_search_space_5():
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    class class1:
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        def __init__(self):
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            pass
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    class class2:
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        def __init__(self):
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            pass
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    class class3:
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        def __init__(self):
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            pass
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    def class_f1():
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        return class1
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    def class_f2():
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        return class2
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    def class_f3():
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        return class3
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    def objective_function(opt):
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        score = -opt["x1"] * opt["x1"]
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        return score
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    search_space = {
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        "x1": list(range(0, 100, 1)),
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        "class1": [class_f1, class_f2, class_f3],
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    }
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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=15,
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    )
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    hyper.run()
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    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
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    assert hyper.best_para(objective_function)["class1"] in search_space["class1"]
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def test_search_space_6():
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    def objective_function(opt):
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        score = -opt["x1"] * opt["x1"]
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        return score
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    def list_f1():
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        return [0, 1]
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    def list_f2():
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        return [1, 0]
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    search_space = {
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        "x1": list(range(0, 100, 1)),
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        "list1": [list_f1, list_f2],
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    }
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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=15,
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    )
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    hyper.run()
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    assert isinstance(hyper.search_data(objective_function), pd.DataFrame)
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    assert hyper.best_para(objective_function)["list1"] in search_space["list1"]
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