165 lines
4.7 KiB
C++
165 lines
4.7 KiB
C++
/** @file main.cpp
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* @brief Main program for Project 2
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*
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* The program performs the Jacobi rotation method.
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* The size of the matrix, and number of transformations
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* performed are written to file.
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* Eigenvector correstonding to the 3 smallest eigenvalues
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* for matrices of size 6x6 and 100x100 are written to file.
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*
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* @author Cory Alexander Balaton (coryab)
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* @author Janita Ovidie Sandtrøen Willumsen (janitaws)
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* @bug No known bugs
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*/
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#include <cassert>
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#include <cmath>
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#include <iostream>
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#include "utils.hpp"
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#include "matrix.hpp"
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#include "jacobi.hpp"
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void write_transformation_dense(int N)
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{
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std::ofstream ofile;
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ofile.open("../latex/output/transform_dense.csv");
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ofile << "N,T" << std::endl;
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// Increase size of matrix, start at 5 to avoid logic_error of N=4
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for (int i = 5; i <= N; i++) {
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arma::mat A = arma::mat(i, i).randn();
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A = arma::symmatu(A);
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arma::vec eigval;
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arma::mat eigvec;
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int iters;
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bool converged;
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jacobi_eigensolver(A, 10e-14, eigval, eigvec, 100000, iters, converged);
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// Write size, and number of iterations to file
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ofile << i << "," << iters << std::endl;
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}
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ofile.close();
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}
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void write_transformation_tridiag(int N)
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{
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std::ofstream ofile;
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double h;
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double a, d;
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ofile.open("../latex/output/transform_tridiag.csv");
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// Write header line to file
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ofile << "N,T" << std::endl;
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// Increase size of matrix, start at 5 to avoid logic_error of N=4
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for (int i = 5; i <= N; i++) {
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h = 1. / (double) (i+1);
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a = -1. / (h*h), d = 2. / (h*h);
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arma::mat A = create_symmetric_tridiagonal(i, a, d);
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arma::vec eigval;
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arma::mat eigvec;
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int iters;
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bool converged;
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jacobi_eigensolver(A, 10e-14, eigval, eigvec, 100000, iters, converged);
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// Write size, and number of iterations to file
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ofile << i << "," << iters << std::endl;
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}
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ofile.close();
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}
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void write_eigenvec(int N)
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{
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double h = 1. / (double) (N+1);
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double a = -1. / (h*h);
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double d = 2. / (h*h);
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double x = 0.;
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// Create tridiagonal matrix
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arma::mat A = create_symmetric_tridiagonal(N, a, d);
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arma::mat analytic = arma::mat(N, N);
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arma::vec eigval;
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arma::mat eigvec;
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int iters;
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bool converged;
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// Solve using Jacobi rotation method
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jacobi_eigensolver(A, 10e-14, eigval, eigvec, 100000, iters, converged);
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// Build analytic eigenvectors
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arma::vec v, analytic_vec = arma::vec(N);
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for (int i=0; i < N; i++) {
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v = eigvec.col(i);
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for (int j=0; j < N; j++) {
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analytic_vec(j) = std::sin(((j+1.)*(i+1.)*M_PI) / (N+1.));
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}
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analytic_vec = arma::normalise(analytic_vec);
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// Flip the sign of the analytic vector if they are different
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if (analytic_vec(0)*v(0) < 0.) {
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analytic_vec *= -1;
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}
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analytic.col(i) = analytic_vec;
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}
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std::ofstream ofile;
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// Create file based on matrix size, and write header line to file
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ofile.open("../latex/output/eigenvector_" + std::to_string(N) + ".csv");
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ofile << "x,"
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<< "Vector 1,Vector 2,Vector 3,"
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<< "Analytic 1,Analytic 2,Analytic 3" << std::endl;
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// Add boundary value for x=0
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ofile << scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << std::endl;
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// Add x-value and element i of each eigenvector to same line
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for (int i = 0; i < N; i++) {
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x += h;
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ofile << scientific_format(x, 16)<< ","
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<< scientific_format(eigvec(i,0), 16) << ","
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<< scientific_format(eigvec(i,1), 16) << ","
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<< scientific_format(eigvec(i,2), 16) << ","
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<< scientific_format(analytic(i,0), 16) << ","
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<< scientific_format(analytic(i,1), 16) << ","
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<< scientific_format(analytic(i,2), 16) << std::endl;
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}
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// Add boundary value for x=1
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ofile << scientific_format(1., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << ","
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<< scientific_format(0., 16) << std::endl;
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ofile.close();
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}
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int main()
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{
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write_transformation_tridiag(100);
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write_transformation_dense(100);
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write_eigenvec(10);
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write_eigenvec(100);
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return 0;
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}
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