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72 lines
2.7 KiB
Java
72 lines
2.7 KiB
Java
package com.thealgorithms.matrix;
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/**
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* This class implements an algorithm for solving a system of equations of the form Ax=b using gaussian elimination and back substitution.
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*
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* @link <a href="https://en.wikipedia.org/wiki/Gaussian_elimination">Gaussian Elimination Wiki</a>
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* @see InverseOfMatrix finds the full of inverse of a matrice, but is not required to solve a system.
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*/
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public final class SolveSystem {
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private SolveSystem() {
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}
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/**
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* Problem: Given a matrix A and vector b, solve the linear system Ax = b for the vector x.\
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* <p>
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* <b>This OVERWRITES the input matrix to save on memory</b>
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*
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* @param matrix - a square matrix of doubles
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* @param constants - an array of constant
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* @return solutions
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*/
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public static double[] solveSystem(double[][] matrix, double[] constants) {
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final double tol = 0.00000001; // tolerance for round off
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for (int k = 0; k < matrix.length - 1; k++) {
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// find the largest value in column (to avoid zero pivots)
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double maxVal = Math.abs(matrix[k][k]);
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int maxIdx = k;
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for (int j = k + 1; j < matrix.length; j++) {
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if (Math.abs(matrix[j][k]) > maxVal) {
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maxVal = matrix[j][k];
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maxIdx = j;
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}
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}
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if (Math.abs(maxVal) < tol) {
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// hope the matrix works out
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continue;
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}
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// swap rows
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double[] temp = matrix[k];
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matrix[k] = matrix[maxIdx];
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matrix[maxIdx] = temp;
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double tempConst = constants[k];
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constants[k] = constants[maxIdx];
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constants[maxIdx] = tempConst;
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for (int i = k + 1; i < matrix.length; i++) {
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// compute multipliers and save them in the column
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matrix[i][k] /= matrix[k][k];
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for (int j = k + 1; j < matrix.length; j++) {
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matrix[i][j] -= matrix[i][k] * matrix[k][j];
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}
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constants[i] -= matrix[i][k] * constants[k];
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}
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}
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// back substitution
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double[] x = new double[constants.length];
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System.arraycopy(constants, 0, x, 0, constants.length);
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for (int i = matrix.length - 1; i >= 0; i--) {
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double sum = 0;
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for (int j = i + 1; j < matrix.length; j++) {
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sum += matrix[i][j] * x[j];
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}
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x[i] = constants[i] - sum;
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if (Math.abs(matrix[i][i]) > tol) {
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x[i] /= matrix[i][i];
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} else {
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throw new IllegalArgumentException("Matrix was found to be singular");
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}
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}
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return x;
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}
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}
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