SimonBlanke /
Gradient-Free-Optimizers
| @@ 51-78 (lines=28) @@ | ||
| 48 | assert -100 > opt.best_score > max_score |
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| 49 | ||
| 50 | ||
| 51 | @pytest.mark.parametrize(*optimizers) |
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| 52 | def test_max_score_1(Optimizer): |
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| 53 | def objective_function(para): |
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| 54 | score = -para["x1"] * para["x1"] |
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| 55 | time.sleep(0.01) |
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| 56 | return score |
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| 57 | ||
| 58 | search_space = { |
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| 59 | "x1": np.arange(0, 100, 0.1), |
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| 60 | } |
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| 61 | ||
| 62 | max_score = -9999 |
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| 63 | ||
| 64 | c_time = time.time() |
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| 65 | opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 99}]}) |
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| 66 | opt.search( |
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| 67 | objective_function, |
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| 68 | n_iter=100000, |
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| 69 | max_score=max_score, |
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| 70 | ) |
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| 71 | diff_time = time.time() - c_time |
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| 72 | ||
| 73 | print("\n Results head \n", opt.results.head()) |
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| 74 | print("\n Results tail \n", opt.results.tail()) |
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| 75 | ||
| 76 | print("\nN iter:", len(opt.results)) |
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| 77 | ||
| 78 | assert diff_time < 1 |
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| 79 | ||
| @@ 21-48 (lines=28) @@ | ||
| 18 | } |
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| 19 | ||
| 20 | ||
| 21 | @pytest.mark.parametrize(*optimizers) |
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| 22 | def test_max_score_0(Optimizer): |
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| 23 | def objective_function(para): |
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| 24 | score = -para["x1"] * para["x1"] |
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| 25 | return score |
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| 26 | ||
| 27 | search_space = { |
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| 28 | "x1": np.arange(0, 100, 0.1), |
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| 29 | } |
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| 30 | ||
| 31 | max_score = -9999 |
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| 32 | ||
| 33 | opt = Optimizer( |
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| 34 | search_space, |
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| 35 | initialize={"warm_start": [{"x1": 99}]}, |
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| 36 | ) |
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| 37 | opt.search( |
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| 38 | objective_function, |
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| 39 | n_iter=100, |
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| 40 | max_score=max_score, |
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| 41 | ) |
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| 42 | ||
| 43 | print("\n Results head \n", opt.results.head()) |
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| 44 | print("\n Results tail \n", opt.results.tail()) |
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| 45 | ||
| 46 | print("\nN iter:", len(opt.results)) |
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| 47 | ||
| 48 | assert -100 > opt.best_score > max_score |
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| 49 | ||
| 50 | ||
| 51 | @pytest.mark.parametrize(*optimizers) |
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