SimonBlanke /
Gradient-Free-Optimizers
| @@ 50-64 (lines=15) @@ | ||
| 47 | assert opt.best_para == init |
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| 48 | ||
| 49 | ||
| 50 | @pytest.mark.parametrize(*optimizers) |
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| 51 | def test_initialize_warm_start_2(Optimizer): |
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| 52 | search_space = { |
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| 53 | "x1": np.arange(-10, 10, 1), |
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| 54 | } |
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| 55 | init = { |
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| 56 | "x1": -10, |
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| 57 | } |
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| 58 | ||
| 59 | initialize = {"warm_start": [init], "random": 0, "vertices": 0, "grid": 0} |
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| 60 | ||
| 61 | opt = Optimizer(search_space, initialize=initialize) |
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| 62 | opt.search(objective_function, n_iter=1) |
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| 63 | ||
| 64 | assert opt.best_para == init |
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| 65 | ||
| 66 | ||
| 67 | @pytest.mark.parametrize(*optimizers) |
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| @@ 33-47 (lines=15) @@ | ||
| 30 | assert abs(opt.best_score) < 0.001 |
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| 31 | ||
| 32 | ||
| 33 | @pytest.mark.parametrize(*optimizers) |
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| 34 | def test_initialize_warm_start_1(Optimizer): |
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| 35 | search_space = { |
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| 36 | "x1": np.arange(-10, 10, 1), |
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| 37 | } |
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| 38 | init = { |
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| 39 | "x1": -10, |
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| 40 | } |
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| 41 | ||
| 42 | initialize = {"warm_start": [init]} |
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| 43 | ||
| 44 | opt = Optimizer(search_space, initialize=initialize) |
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| 45 | opt.search(objective_function, n_iter=1) |
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| 46 | ||
| 47 | assert opt.best_para == init |
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| 48 | ||
| 49 | ||
| 50 | @pytest.mark.parametrize(*optimizers) |
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