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‎.gitignore‎

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/cov_reports
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.coverage
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coverage.xml
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.idea/

‎Dockerfile‎

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# Copyright (c) 2016-2020, EPFL/Blue Brain Project
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# Copyright (c) 2016-2022, EPFL/Blue Brain Project
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#
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# This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
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#

‎LICENSE.txt‎

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@@ -6,7 +6,7 @@ Examples and test are BSD-licensed.
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External dependencies are either LGPL or BSD-licensed.
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See file ACKNOWLEDGEMENTS.txt and AUTHORS.txt for further details.
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Copyright (c) Blue Brain Project/EPFL 2016-2021.
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Copyright (c) Blue Brain Project/EPFL 2016-2022.
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This program is free software: you can redistribute it and/or modify it under
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the terms of the GNU Lesser General Public License as published by the

‎README.rst‎

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This work has been partially funded by the European Union Seventh Framework Program (FP7/2007­2013) under grant agreement no. 604102 (HBP), the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 720270, 785907 (Human Brain Project SGA1/SGA2) and by the EBRAINS research infrastructure, funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3).
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This project/research was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
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Copyright (c) 2016-2021 Blue Brain Project/EPFL
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Copyright (c) 2016-2022 Blue Brain Project/EPFL
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..
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The following image is also defined in the index.rst file, as the relative path is

‎bluepyopt/__init__.py‎

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"""Init script"""
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"""
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Copyright (c) 2016-2020, EPFL/Blue Brain Project
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Copyright (c) 2016-2022, EPFL/Blue Brain Project
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This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
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‎bluepyopt/deapext/CMA_MO.py‎

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"""Multi Objective CMA-es class"""
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"""
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Copyright (c) 2016-2020, EPFL/Blue Brain Project
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Copyright (c) 2016-2022, EPFL/Blue Brain Project
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This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
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@@ -51,7 +51,7 @@ def get_hyped(pop, ubound_score=250., threshold_improvement=240.):
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# Remove the dimensions that do not show any improvement
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to_remove = []
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for i, (lb, ub) in enumerate(zip(lbounds, ubounds)):
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for i, lb in enumerate(lbounds):
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if lb >= threshold_improvement:
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to_remove.append(i)
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points = numpy.delete(points, to_remove, axis=1)
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return [0.] * len(pop)
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# Rescale the objective space
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# Note: 2 here is a magic number used to make the hypercube larger than it
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# really is. It makes sure that the individual always have a non-zero
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# hyper-volume contribution and improves the results while avoiding an
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# edge case.
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points = (points - lbounds) / numpy.max(ubounds.flatten())
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ubounds = numpy.max(points, axis=0) + 2.0
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is computed as 1 - weight_hv.
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map_function (map): function used to map (parallelize) the
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evaluation function calls
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use_scoop (bool): use scoop map for parallel computation
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use_scoop (bool): use scoop map for parallel computation
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"""
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if offspring_size is None:
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if self.use_scoop:
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if self.map_function:
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raise Exception(
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"Impossible to use scoop is providing self defined map "
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"Impossible to use scoop and provide self defined map "
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"function: %s" % self.map_function
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)
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from scoop import futures
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if self.weight_hv == 0.0:
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fit = [numpy.sum(ind.fitness.values) for ind in candidates]
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idx_fit = list(numpy.argsort(fit))
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idx_scores = idx_fit[:]
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idx_scores = list(numpy.argsort(fit))
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elif self.weight_hv == 1.0:
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hv = get_hyped(candidates)
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idx_hv = list(numpy.argsort(hv))[::-1]
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idx_scores = idx_hv[:]
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idx_scores = list(numpy.argsort(hv))[::-1]
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hv = get_hyped(candidates)
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if c.criteria_met:
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logger.info(
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"CMA stopped because of termination criteria: " +
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"" + " ".join(c.name)
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" ".join(c.name)
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)
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self.active = False

‎bluepyopt/deapext/CMA_SO.py‎

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"""Single Objective CMA-es class"""
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"""
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Copyright (c) 2016-2020, EPFL/Blue Brain Project
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Copyright (c) 2016-2022, EPFL/Blue Brain Project
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This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
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if c.criteria_met:
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logger.info(
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"CMA stopped because of termination criteria: " +
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"" + " ".join(c.name)
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" ".join(c.name)
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)
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self.active = False

‎bluepyopt/deapext/algorithms.py‎

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"""Optimisation class"""
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"""
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Copyright (c) 2016-2020, EPFL/Blue Brain Project
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Copyright (c) 2016-2022, EPFL/Blue Brain Project
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This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
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‎bluepyopt/deapext/hype.py‎

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"""
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Copyright (c) 2016-2020, EPFL/Blue Brain Project
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Copyright (c) 2016-2022, EPFL/Blue Brain Project
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This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
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‎bluepyopt/deapext/optimisations.py‎

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"""Optimisation class"""
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"""
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Copyright (c) 2016-2020, EPFL/Blue Brain Project
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Copyright (c) 2016-2022, EPFL/Blue Brain Project
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This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
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# Number of parameters
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IND_SIZE = len(self.evaluator.params)
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if IND_SIZE == 0:
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raise Exception(
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raise ValueError(
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"Length of evaluator.params is zero. At least one "
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"non-fix parameter is needed to run an optimization."
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)

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