SimonBlanke /
Hyperactive
| Total Complexity | 1 |
| Total Lines | 21 |
| Duplicated Lines | 0 % |
| Changes | 0 | ||
| 1 | import numpy as np |
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| 2 | from hyperactive import Hyperactive |
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| 3 | |||
| 4 | |||
| 5 | def rosen(para, X, y): |
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| 6 | """The Rosenbrock function""" |
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| 7 | x = np.array([para["x1"], para["x2"], para["x3"], para["x4"]]) |
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| 8 | y = np.array([para["x0"], para["x1"], para["x2"], para["x3"]]) |
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| 9 | |||
| 10 | return -sum(100.0 * (x - y ** 2.0) ** 2.0 + (1 - y) ** 2.0) |
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| 11 | |||
| 12 | |||
| 13 | x_range = np.arange(0, 3, 0.1) |
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| 14 | |||
| 15 | search_config = { |
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| 16 | rosen: {"x0": x_range, "x1": x_range, "x2": x_range, "x3": x_range, "x4": x_range} |
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| 17 | } |
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| 18 | |||
| 19 | opt = Hyperactive(0, 0) |
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| 20 | opt.search(search_config, n_iter=1000000) |
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| 21 |
