2024-02-27 13:20:47 -05:00
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#pragma once
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/**
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* @file Solvers.hpp
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*
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* @brief Implémentation de plusieurs algorihtmes de solveurs pour un système
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* d'équations linéaires
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*
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* Nom:
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* Code permanent :
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* Email :
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*
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*/
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#include "Math3D.h"
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2024-03-09 16:19:14 -05:00
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namespace gti320 {
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// Identification des solveurs
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enum eSolverType {
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kNone, kGaussSeidel, kColorGaussSeidel, kCholesky
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};
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2024-02-27 13:20:47 -05:00
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// Paramètres de convergences pour les algorithmes itératifs
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static const float eps = 1e-4f;
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static const float tau = 1e-5f;
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/**
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* Résout Ax = b avec la méthode Gauss-Seidel
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*/
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static void gaussSeidel(const Matrix<float, Dynamic, Dynamic> &A,
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const Vector<float, Dynamic> &b,
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Vector<float, Dynamic> &x, int k_max) {
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// TODO
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//
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// Implémenter la méthode de Gauss-Seidel
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int n = b.size();
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x.resize(n);
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x.setZero();
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bool converged = false;
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int k = 0;
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do {
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Vector<float, Dynamic> nx = x;
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for (int i = 0; i < n; i++) {
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nx(i) = b(i);
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for (int j = 0; j < i; j++) {
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nx(i) = nx(i) - A(i, j) * nx(j);
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}
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for (int j = i + 1; j < n; j++) {
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nx(i) = nx(i) - A(i, j) * x(j);
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}
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nx(i) = nx(i) / A(i, i);
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}
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k++;
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Vector<float, Dynamic> r = A * x - b;
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converged = k >= k_max ||
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(nx - x).norm() / nx.norm() < tau ||
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r.norm() / b.norm() < eps;
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x = nx;
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} while (!converged);
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}
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/**
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* Résout Ax = b avec la méthode Gauss-Seidel (coloration de graphe)
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*/
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static void gaussSeidelColor(const Matrix<float, Dynamic, Dynamic> &A, const Vector<float, Dynamic> &b,
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Vector<float, Dynamic> &x, const Partitions &P, const int maxIter) {
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// TODO
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//
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// Implémenter la méthode de Gauss-Seidel avec coloration de graphe.
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// Les partitions avec l'index de chaque particule sont stockées dans la table des tables, P.
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}
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/**
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* Résout Ax = b avec la méthode de Cholesky
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*/
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static void cholesky(const Matrix<float, Dynamic, Dynamic> &A,
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const Vector<float, Dynamic> &b,
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Vector<float, Dynamic> &x) {
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int n = A.rows();
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x.resize(n);
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x.setZero();
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// TODO
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//
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// Calculer la matrice L de la factorisation de Cholesky
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auto L = Matrix<float, Dynamic, Dynamic>(n, n);
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for (int j = 0; j < n; j++) {
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for (int i = j; i < n; i++) {
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float s = 0;
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for (int k = 0; k < j; k++) {
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s += L(i, k) * L(j, k);
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}
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if (i == j) {
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L(i, i) = std::sqrt(A(i, i) - s);
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} else {
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L(i, j) = (A(i, j) - s) / L(j, j);
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}
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}
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}
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// TODO
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//
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// Résoudre Ly = b
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auto y = Vector<float, Dynamic>(n);
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for (int i = 0; i < n; i++) {
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y(i) = b(i);
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for (int j = 0; j < i; j++) {
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y(i) -= L(i, j) * y(j);
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}
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y(i) /= L(i, i);
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}
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// TODO
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//
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// Résoudre L^t x = y
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//
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// Remarque : ne pas calculer la transposée de L, c'est inutilement
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// coûteux.
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for (int i = n - 1; i >= 0; i--) {
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x(i) = y(i);
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for (int j = i + 1; j < n; j++) {
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x(i) -= L(j, i) * x(j);
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}
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x(i) /= L(i, i);
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}
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}
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}
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