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# encoding=utf8 |
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# pylint: disable=mixed-indentation, multiple-statements, logging-not-lazy, attribute-defined-outside-init, line-too-long, arguments-differ, singleton-comparison, bad-continuation, dangerous-default-value, consider-using-enumerate |
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import logging |
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# from numpy import random as rand, argmin, argmax, mean, asarray, cos |
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# from NiaPy.algorithms.algorithm import Individual |
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from NiaPy.algorithms.basic.de import DifferentialEvolution # , CrossBest1, CrossRand1, CrossCurr2Best1, CrossBest2, CrossCurr2Rand1, proportional |
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logging.basicConfig() |
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logger = logging.getLogger('NiaPy.algorithms.modified') |
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logger.setLevel('INFO') |
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__all__ = [ |
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'StrategyAdaptationDifferentialEvolution', |
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'StrategyAdaptationDifferentialEvolutionV1' |
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] |
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View Code Duplication |
class StrategyAdaptationDifferentialEvolution(DifferentialEvolution): |
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r"""Implementation of Differential Evolution Algorithm With Strategy Adaptation algorihtm. |
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Algorithm: |
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Differential Evolution Algorithm With StrategyAdaptation |
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Date: |
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2019 |
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Author: |
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Klemen Berkovič |
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License: |
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MIT |
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Reference URL: |
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https://ieeexplore.ieee.org/document/1554904 |
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Reference paper: |
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Qin, A. Kai, and Ponnuthurai N. Suganthan. "Self-adaptive differential evolution algorithm for numerical optimization." 2005 IEEE congress on evolutionary computation. Vol. 2. IEEE, 2005. |
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Attributes: |
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Name (List[str]): List of strings representing algorithm name. |
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See Also: |
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:class:`NiaPy.algorithms.basic.DifferentialEvolution` |
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""" |
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Name = ['StrategyAdaptationDifferentialEvolution', 'SADE', 'SaDE'] |
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@staticmethod |
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def algorithmInfo(): |
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r"""Geg basic algorithm information. |
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Returns: |
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str: Basic algorithm information. |
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See Also: |
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:func:`NiaPy.algorithms.algorithm.Algorithm.algorithmInfo` |
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""" |
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return r"""Qin, A. Kai, and Ponnuthurai N. Suganthan. "Self-adaptive differential evolution algorithm for numerical optimization." 2005 IEEE congress on evolutionary computation. Vol. 2. IEEE, 2005.""" |
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def setParameters(self, **kwargs): |
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DifferentialEvolution.setParameters(self, **kwargs) |
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# TODO add parameters of the algorithm |
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def getParameters(self): |
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d = DifferentialEvolution.getParameters(self) |
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# TODO add paramters values |
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return d |
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def runIteration(self, task, pop, fpop, xb, fxb, **dparams): |
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# TODO implemnt algorithm |
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return pop, fpop, xb, fxb, dparams |
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View Code Duplication |
class StrategyAdaptationDifferentialEvolutionV1(DifferentialEvolution): |
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r"""Implementation of Differential Evolution Algorithm With Strategy Adaptation algorihtm. |
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Algorithm: |
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Differential Evolution Algorithm With StrategyAdaptation |
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Date: |
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2019 |
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Author: |
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Klemen Berkovič |
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License: |
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MIT |
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Reference URL: |
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https://ieeexplore.ieee.org/document/4632146 |
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Reference paper: |
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Qin, A. Kai, Vicky Ling Huang, and Ponnuthurai N. Suganthan. "Differential evolution algorithm with strategy adaptation for global numerical optimization." IEEE transactions on Evolutionary Computation 13.2 (2009): 398-417. |
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Attributes: |
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Name (List[str]): List of strings representing algorithm name. |
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See Also: |
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:class:`NiaPy.algorithms.basic.DifferentialEvolution` |
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""" |
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Name = ['StrategyAdaptationDifferentialEvolutionV1', 'SADEV1', 'SaDEV1'] |
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@staticmethod |
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def algorithmInfo(): |
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r"""Get algorithm information. |
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Returns: |
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str: Get algorithm information. |
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See Also: |
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:func:`NiaPy.algorithms.algorithm.Algorithm.algorithmInfo` |
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""" |
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return r"""Qin, A. Kai, Vicky Ling Huang, and Ponnuthurai N. Suganthan. "Differential evolution algorithm with strategy adaptation for global numerical optimization." IEEE transactions on Evolutionary Computation 13.2 (2009): 398-417.""" |
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def setParameters(self, **kwargs): |
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DifferentialEvolution.setParameters(self, **kwargs) |
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# TODO add parameters of the algorithm |
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def getParameters(self): |
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d = DifferentialEvolution.getParameters(self) |
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# TODO add paramters values |
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return d |
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def runIteration(self, task, pop, fpop, xb, fxb, **dparams): |
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# TODO implement algorithm |
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return pop, fpop, xb, fxb, dparams |
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# vim: tabstop=3 noexpandtab shiftwidth=3 softtabstop=3 |
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NiaOrg /
NiaPy
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