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"""Test module for exception catching functionality.""" |
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import math |
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import numpy as np |
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from hyperactive import Hyperactive |
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search_space = { |
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"x1": list(np.arange(-100, 100, 1)), |
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} |
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def test_catch_1(): |
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"""Test catching TypeError exceptions in objective function.""" |
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def objective_function(access): |
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1 + "str" # Intentional TypeError for testing |
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return 0 |
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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=100, |
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catch={TypeError: np.nan}, |
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) |
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hyper.run() |
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def test_catch_2(): |
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"""Test catching ValueError exceptions in objective function.""" |
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def objective_function(access): |
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math.sqrt(-10) |
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return 0 |
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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=100, |
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catch={ValueError: np.nan}, |
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) |
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hyper.run() |
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def test_catch_3(): |
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"""Test catching ZeroDivisionError exceptions in objective function.""" |
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def objective_function(access): |
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1 / 0 # Intentional ZeroDivisionError for testing |
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return 0 |
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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=100, |
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catch={ZeroDivisionError: np.nan}, |
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) |
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hyper.run() |
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def test_catch_all_0(): |
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"""Test catching multiple exception types returning NaN values.""" |
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def objective_function(access): |
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1 + "str" # Intentional TypeError for testing |
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math.sqrt(-10) # Intentional ValueError for testing |
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1 / 0 # Intentional ZeroDivisionError for testing |
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return 0 |
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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=100, |
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catch={ |
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TypeError: np.nan, |
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ValueError: np.nan, |
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ZeroDivisionError: np.nan, |
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}, |
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) |
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hyper.run() |
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nan_ = hyper.search_data(objective_function)["score"].values[0] |
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assert math.isnan(nan_) |
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def test_catch_all_1(): |
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"""Test catching multiple exception types returning tuple values.""" |
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def objective_function(access): |
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1 + "str" # Intentional TypeError for testing |
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math.sqrt(-10) # Intentional ValueError for testing |
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1 / 0 # Intentional ZeroDivisionError for testing |
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return 0, {"error": False} |
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catch_return = (np.nan, {"error": True}) |
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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=100, |
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catch={ |
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TypeError: catch_return, |
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ValueError: catch_return, |
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ZeroDivisionError: catch_return, |
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}, |
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) |
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hyper.run() |
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nan_ = hyper.search_data(objective_function)["score"].values[0] |
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error_ = hyper.search_data(objective_function)["error"].values[0] |
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assert math.isnan(nan_) |
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assert error_ |
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