added schaffer2 function
added output for improvement of fitness added CMAES algorithm, that requires further testing
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43
main.py
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43
main.py
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import functions
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import numpy as np
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import solvers
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from matplotlib import pyplot as plt
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def main():
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plot_rest = True
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f = functions.Rastrigin()
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# f = functions.Sphere()
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# s = solvers.SimpleEvolutionStrategy(f, np.array([2, 2]))
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s = solvers.CMAEvolutionStrategy(f, np.array([2.0, 2.0]), np.array([[2.0, 0.0], [0.0, 2.0]]))
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old_fitness = 100
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fitness = old_fitness * 0.9
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old = None
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plt.set_cmap('Spectral')
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while abs(old_fitness - fitness) > 0.001:
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old_fitness = fitness
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samples = s.sample(2000)
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elite, fitness = s.rank(samples, 150)
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s.update(elite)
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if plot_rest:
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rest = np.setdiff1d(samples, elite, assume_unique=True)
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rest = rest.reshape((int(rest.shape[0]/2), 2))
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plt.pcolormesh(*f.grid())
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if plot_rest:
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plt.scatter(*rest.transpose(), color="dimgrey")
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if old is not None:
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plt.scatter(*old.transpose(), color="orange")
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plt.scatter(*elite.transpose(), color="yellow")
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# plt.scatter(*elite[0].transpose(), color="green")
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print('old fitness: {}\nnew fitness: {}\nimprovement: {}\n'.format(old_fitness, fitness,
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old_fitness - fitness))
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plt.show()
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old = elite
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if __name__ == '__main__':
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main()
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