Tomaž Vajngerl
8efda4882c
The swarm classes all sat in the global namespace. Wrap them in the sc namespace so the whole family stays in one place: the particle, the swarm, the two per-generation algorithms and the three solvers that drive them. The uses in the solver component and in its test are qualified to match. The classes that only the solver component itself uses stay in an unnamed namespace, now nested inside sc, so they keep the linkage they had before. Particle also gets a short comment saying what one of them holds. Change-Id: I8a2f4e8c7f90d71c774f9b297204e67728994422 Signed-off-by: Tomaž Vajngerl <tomaz.vajngerl@collabora.co.uk> Reviewed-on: https://gerrit.collaboraoffice.com/c/online/+/9311 Reviewed-by: Mike Kaganski <mike.kaganski@collabora.com> Tested-by: Tomaž Vajngerl <tomaz.vajngerl@collabora.com> (cherry picked from commit 2be6d1a30307bebd8baea813295bb3a1221322ee) Reviewed-on: https://gerrit.libreoffice.org/c/core/+/211022 Tested-by: Jenkins Reviewed-by: Xisco Fauli <xiscofauli@libreoffice.org>
80 lines
2.9 KiB
C++
80 lines
2.9 KiB
C++
/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
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/*
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* This file is part of the LibreOffice project.
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*
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* This Source Code Form is subject to the terms of the Mozilla Public
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* License, v. 2.0. If a copy of the MPL was not distributed with this
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* file, You can obtain one at http://mozilla.org/MPL/2.0/.
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*
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*/
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#pragma once
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#include "Swarm.hxx"
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#include <vector>
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#include <random>
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namespace sc
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{
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// One particle swarm generation, a reusable engine any swarm-based solver can
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// drive. Each call advances the bound swarm by one generation: every particle's
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// velocity is pulled by inertia toward its own best and the swarm's best, then
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// its position steps and is clamped.
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template <typename DataProvider> class PSOAlgorithm
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{
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// inertia
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static constexpr double constWeight = 0.729;
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// cognitive coefficient
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static constexpr double constCognitive = 1.49445;
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// social coefficient
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static constexpr double constSocial = 1.49445;
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Swarm<DataProvider>& mrSwarm;
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std::uniform_real_distribution<> maRandom01;
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public:
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explicit PSOAlgorithm(Swarm<DataProvider>& rSwarm)
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: mrSwarm(rSwarm)
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, maRandom01(0.0, 1.0)
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{
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}
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bool next() { return mrSwarm.advance(*this); }
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// Advance one particle: pull its velocity by inertia toward its own best and
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// the swarm's best, then step and clamp its position. The move depends only
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// on the particle and the swarm's best, so the particle index is unused.
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void step(Particle& rParticle, size_t /*nParticleIndex*/)
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{
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DataProvider& rDataProvider = mrSwarm.dataProvider();
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std::mt19937& rGenerator = mrSwarm.generator();
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const std::vector<double>& rGlobalBest = mrSwarm.bestPosition();
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double fRandom1 = maRandom01(rGenerator);
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double fRandom2 = maRandom01(rGenerator);
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const size_t nDimensionality = rParticle.mPosition.size();
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for (size_t nDimension = 0; nDimension < nDimensionality; ++nDimension)
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{
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rParticle.mVelocity[nDimension]
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= (constWeight * rParticle.mVelocity[nDimension])
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+ (constCognitive * fRandom1
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* (rParticle.mBestPosition[nDimension] - rParticle.mPosition[nDimension]))
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+ (constSocial * fRandom2
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* (rGlobalBest[nDimension] - rParticle.mPosition[nDimension]));
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// The inertia weight below one keeps the velocity bounded on its
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// own, so only the position is clamped, which holds the particle
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// inside its bounds.
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rParticle.mPosition[nDimension] = rDataProvider.clampVariable(
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nDimension, rParticle.mPosition[nDimension] + rParticle.mVelocity[nDimension]);
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}
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rParticle.mCurrentFitness = rDataProvider.calculateFitness(rParticle.mPosition);
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}
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};
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} // namespace sc
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/* vim:set shiftwidth=4 softtabstop=4 expandtab: */
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