SimonBlanke /
Hyperactive
| Total Complexity | 5 |
| Total Lines | 117 |
| Duplicated Lines | 0 % |
| Changes | 0 | ||
| 1 | import copy |
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| 2 | import pytest |
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| 3 | import math |
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| 4 | import numpy as np |
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| 5 | import pandas as pd |
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| 6 | |||
| 7 | from hyperactive import Hyperactive |
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| 8 | |||
| 9 | |||
| 10 | search_space = { |
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| 11 | "x1": list(np.arange(-100, 100, 1)), |
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| 12 | } |
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| 13 | |||
| 14 | |||
| 15 | def test_catch_1(): |
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| 16 | def objective_function(access): |
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| 17 | a = 1 + "str" |
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| 18 | |||
| 19 | return 0 |
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| 20 | |||
| 21 | hyper = Hyperactive() |
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| 22 | hyper.add_search( |
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| 23 | objective_function, |
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| 24 | search_space, |
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| 25 | n_iter=100, |
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| 26 | catch={TypeError: np.nan}, |
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| 27 | ) |
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| 28 | hyper.run() |
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| 29 | |||
| 30 | |||
| 31 | def test_catch_2(): |
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| 32 | def objective_function(access): |
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| 33 | math.sqrt(-10) |
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| 34 | |||
| 35 | return 0 |
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| 36 | |||
| 37 | hyper = Hyperactive() |
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| 38 | hyper.add_search( |
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| 39 | objective_function, |
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| 40 | search_space, |
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| 41 | n_iter=100, |
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| 42 | catch={ValueError: np.nan}, |
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| 43 | ) |
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| 44 | hyper.run() |
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| 45 | |||
| 46 | |||
| 47 | def test_catch_3(): |
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| 48 | def objective_function(access): |
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| 49 | x = 1 / 0 |
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| 50 | |||
| 51 | return 0 |
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| 52 | |||
| 53 | hyper = Hyperactive() |
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| 54 | hyper.add_search( |
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| 55 | objective_function, |
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| 56 | search_space, |
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| 57 | n_iter=100, |
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| 58 | catch={ZeroDivisionError: np.nan}, |
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| 59 | ) |
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| 60 | hyper.run() |
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| 61 | |||
| 62 | |||
| 63 | def test_catch_all_0(): |
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| 64 | def objective_function(access): |
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| 65 | a = 1 + "str" |
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| 66 | math.sqrt(-10) |
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| 67 | x = 1 / 0 |
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| 68 | |||
| 69 | return 0 |
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| 70 | |||
| 71 | hyper = Hyperactive() |
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| 72 | hyper.add_search( |
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| 73 | objective_function, |
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| 74 | search_space, |
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| 75 | n_iter=100, |
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| 76 | catch={ |
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| 77 | TypeError: np.nan, |
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| 78 | ValueError: np.nan, |
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| 79 | ZeroDivisionError: np.nan, |
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| 80 | }, |
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| 81 | ) |
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| 82 | hyper.run() |
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| 83 | |||
| 84 | nan_ = hyper.search_data(objective_function)["score"].values[0] |
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| 85 | |||
| 86 | assert math.isnan(nan_) |
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| 87 | |||
| 88 | |||
| 89 | def test_catch_all_1(): |
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| 90 | def objective_function(access): |
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| 91 | a = 1 + "str" |
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| 92 | math.sqrt(-10) |
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| 93 | x = 1 / 0 |
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| 94 | |||
| 95 | return 0, {"error": False} |
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| 96 | |||
| 97 | catch_return = (np.nan, {"error": True}) |
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| 98 | |||
| 99 | hyper = Hyperactive() |
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| 100 | hyper.add_search( |
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| 101 | objective_function, |
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| 102 | search_space, |
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| 103 | n_iter=100, |
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| 104 | catch={ |
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| 105 | TypeError: catch_return, |
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| 106 | ValueError: catch_return, |
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| 107 | ZeroDivisionError: catch_return, |
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| 108 | }, |
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| 109 | ) |
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| 110 | hyper.run() |
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| 111 | |||
| 112 | nan_ = hyper.search_data(objective_function)["score"].values[0] |
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| 113 | error_ = hyper.search_data(objective_function)["error"].values[0] |
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| 114 | |||
| 115 | assert math.isnan(nan_) |
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| 116 | assert error_ == True |
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| 117 |
