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# Author: Simon Blanke |
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# Email: [email protected] |
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# License: MIT License |
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import numpy as np |
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from gradient_free_optimizers import EvolutionStrategyOptimizer |
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n_iter = 100 |
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def get_score(pos_new): |
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return -(pos_new[0] * pos_new[0]) |
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space_dim = np.array([10]) |
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init_positions = [np.array([0]), np.array([1]), np.array([2]), np.array([3])] |
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View Code Duplication |
def _base_test(opt, init_positions): |
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for nth_init in range(len(init_positions)): |
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pos_new = opt.init_pos(nth_init) |
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score_new = get_score(pos_new) |
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opt.evaluate(score_new) |
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for nth_iter in range(len(init_positions), n_iter): |
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pos_new = opt.iterate(nth_iter) |
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score_new = get_score(pos_new) |
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opt.evaluate(score_new) |
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def _test_EvolutionStrategyOptimizer( |
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init_positions=init_positions, space_dim=space_dim, opt_para={} |
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): |
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opt = EvolutionStrategyOptimizer(init_positions, space_dim, opt_para) |
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_base_test(opt, init_positions) |
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View Code Duplication |
def test_individuals(): |
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for init_positions in [ |
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[np.array([0])], |
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[np.array([0]), np.array([0])], |
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[np.array([0]), np.array([0])], |
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[ |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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np.array([0]), |
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], |
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]: |
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_test_EvolutionStrategyOptimizer(init_positions) |
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def test_mutation_rate(): |
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for mutation_rate in [0.1, 0.9]: |
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opt_para = {"mutation_rate": mutation_rate} |
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_test_EvolutionStrategyOptimizer(opt_para=opt_para) |
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def test_crossover_rate(): |
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for crossover_rate in [0.1, 0.9]: |
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opt_para = {"crossover_rate": crossover_rate} |
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_test_EvolutionStrategyOptimizer(opt_para=opt_para) |
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SimonBlanke /
Gradient-Free-Optimizers
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