Merge branch 'coryab/create-code-structure' of github.uio.no:FYS3150-G2-2023/Project-2 into coryab/create-code-structure

latex/output/eigenvector_100.csv

@@ -0,0 +1,103 @@
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latex/output/eigenvector_6.csv

@@ -0,0 +1,9 @@
+x,Vector 1,Vector 2,Vector 3
+0.0000000000e+00,0.0000000000e+00,0.0000000000e+00,0.0000000000e+00
+1.4285714286e-01,2.3192061397e-01,-4.1790650593e-01,-5.2112088916e-01
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+1.0000000000e+00,0.0000000000e+00,0.0000000000e+00,0.0000000000e+00

latex/output/transform_dense.csv

@@ -0,0 +1,97 @@
+N,T
+5,32
+6,53
+7,73
+8,98
+9,130
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+11,201
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latex/output/transform_tridiag.csv

@@ -0,0 +1,97 @@
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src/Makefile

@@ -33,3 +33,4 @@ test_suite: test_suite.o $(LIBOBJS)
 clean:
 	rm *.o
 	rm test_suite
+	# rm main 

src/main.cpp

@@ -0,0 +1,134 @@
+/** @file main.cpp
+ *  @brief Main program for Project 2
+ *
+ *  The program performs the Jacobi rotation method. 
+ *  The size of the matrix, and number of transformations
+ *  performed are written to file. 
+ *  Eigenvector correstonding to the 3 smallest eigenvalues 
+ *  for matrices of size 6x6 and 100x100 are written to file.
+ *
+ *  @author Cory Alexander Balaton (coryab)
+ *  @author Janita Ovidie Sandtrøen Willumsen (janitaws)
+ *  @bug No known bugs
+ */
+#include <cassert>
+#include <cmath>
+#include <iostream>
+
+#include "utils.hpp"
+#include "matrix.hpp"
+#include "jacobi.hpp"
+
+
+void write_transformation_dense(int N)
+{   
+    std::ofstream ofile;
+
+    ofile.open("../latex/output/transform_dense.csv");
+    ofile << "N,T" << std::endl;
+
+    // Increase size of matrix, start at 5 to avoid logic_error of N=4
+    for (int i = 5; i <= N; i++) {
+        arma::mat A = arma::mat(i, i).randn();
+        A = arma::symmatu(A);
+        arma::vec eigval;
+        arma::mat eigvec;
+
+        int iters;
+        bool converged;
+        
+        jacobi_eigensolver(A, 10e-14, eigval, eigvec, 100000, iters, converged);
+
+        // Write size, and number of iterations to file
+        ofile << i << "," << iters << std::endl;
+    }
+    ofile.close();
+}
+
+    
+void write_transformation_tridiag(int N)
+{   
+    std::ofstream ofile;
+
+    double h;
+    double a, d;
+
+    ofile.open("../latex/output/transform_tridiag.csv");
+    // Write header line to file 
+    ofile << "N,T" << std::endl;
+
+    // Increase size of matrix, start at 5 to avoid logic_error of N=4
+    for (int i = 5; i <= N; i++) {
+        h = 1. / (double) (i+1);
+        a = -1. / (h*h), d = 2. / (h*h);
+
+        arma::mat A = create_symmetric_tridiagonal(i, a, d);
+        arma::vec eigval;
+        arma::mat eigvec;
+
+        int iters;
+        bool converged;
+        
+        jacobi_eigensolver(A, 10e-14, eigval, eigvec, 100000, iters, converged);
+
+        // Write size, and number of iterations to file
+        ofile << i << "," << iters << std::endl;
+    }
+    ofile.close();
+}
+
+
+void write_eigenvec(int N)
+{
+    double h = 1. / (double) (N+1);
+    double a = -1. / (h*h);
+    double d = 2. / (h*h);
+    double x = 0.;
+
+    // Create tridiagonal matrix
+    arma::mat A = create_symmetric_tridiagonal(N, a, d);
+    arma::vec eigval;
+    arma::mat eigvec;
+
+    int iters;
+    bool converged;
+    
+    // Solve using Jacobi rotation method
+    jacobi_eigensolver(A, 10e-14, eigval, eigvec, 100000, iters, converged);
+
+    std::ofstream ofile;
+    // Create file based on matrix size, and write header line to file 
+    ofile.open("../latex/output/eigenvector_" + std::to_string(N) + ".csv");
+    ofile << "x,Vector 1,Vector 2,Vector 3" << std::endl;
+
+    // Add boundary value for x=0
+    ofile << scientific_format(0., 16) << "," 
+            << scientific_format(0., 16) << "," 
+            << scientific_format(0., 16) << "," 
+            << scientific_format(0., 16) << std::endl;
+
+    // Add x-value and element i of each eigenvector to same line
+    for (int i = 0; i < N; i++) {
+        x += h;
+        ofile << scientific_format(x, 16)<< "," 
+            << scientific_format(eigvec(i,0), 16) << "," 
+            << scientific_format(eigvec(i,1), 16) << "," 
+            << scientific_format(eigvec(i,2), 16) << std::endl;
+    }
+    // Add boundary value for x=1
+    ofile << scientific_format(1., 16) << "," 
+            << scientific_format(0., 16) << "," 
+            << scientific_format(0., 16) << "," 
+            << scientific_format(0., 16) << std::endl;
+    ofile.close();
+}
+
+
+int main()
+{
+    write_transformation_tridiag(100);
+    write_transformation_dense(100);
+    write_eigenvec(6);
+    write_eigenvec(100);
+    return 0;
+}

src/plot.py

@@ -0,0 +1,52 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+import seaborn as sns
+
+sns.set_theme()
+plt.rcParams['text.usetex'] = True
+
+
+def plot_transformations(save: bool=False) -> None:
+    # Load data
+    tridiag = pd.read_csv("../latex/output/transform_tridiag.csv", header=0)
+    dense = pd.read_csv("../latex/output/transform_dense.csv", header=0)
+
+    fig, ax = plt.subplots()
+    ax.loglog(dense['N'], dense['T'], '--', label='Dense')
+    ax.loglog(tridiag['N'], tridiag['T'], label='Tridiagonal')
+    ax.set_xlabel('N')
+    ax.set_ylabel('Similarity transformations')
+    ax.legend()
+
+    # Save to file
+    if save is True:
+        fig.savefig("../latex/images/transform.pdf")
+
+
+
+def plot_eigenvectors(N: int, save: bool=False) -> None:
+    # Load data based on matrix size
+    path = f"../latex/output/eigenvector_{N}.csv"
+    eigvec = pd.read_csv(path, header=0)
+
+    fig, ax = plt.subplots()
+    ax.plot(eigvec['x'], eigvec['Vector 1'], label='Vector 1')
+    ax.plot(eigvec['x'], eigvec['Vector 2'], label='Vector 2')
+    ax.plot(eigvec['x'], eigvec['Vector 3'], label='Vector 3')
+    ax.set_xlabel(r'Element $\hat{x}_{i}$')
+    ax.set_ylabel(r'Value of element $v_{i}$')
+    ax.legend()
+
+    # Save to file
+    if save is True:
+        fig.savefig(f"../latex/images/eigenvector_{N}.pdf")
+
+     
+
+
+if __name__ == '__main__':
+    plot_transformations(True)
+    plot_eigenvectors(6, True)
+    plot_eigenvectors(100, True)
+    # plt.show()