TheAlgorithms · siriak · Mar 5, 2022 · Feb 24, 2022 · Feb 24, 2022 · Feb 24, 2022
@@ -142,8 +142,10 @@ public double abs() {
          */
         public Complex divide(Complex z) {
             Complex temp = new Complex();
-            temp.real = (this.real * z.real + this.img * z.img) / (z.abs() * z.abs());
-            temp.img = (this.img * z.real - this.real * z.img) / (z.abs() * z.abs());
+            double d = z.abs() * z.abs();
+            d = (double)Math.round(d * 1000000000d) / 1000000000d;
+            temp.real = (this.real * z.real + this.img * z.img) / (d);
+            temp.img = (this.img * z.real - this.real * z.img) / (d);
             return temp;
         }
 

@@ -1,58 +1,53 @@
-/**
- * \file
- * \brief [Gaussian elimination
- * method](https://en.wikipedia.org/wiki/Gaussian_elimination)
- * @author [Sachwin Kohli](https://github.com/Sachwin-Kohli)
- */
 package com.thealgorithms.maths;
 
-import java.util.*;
+import java.util.ArrayList;
 
-/**
- * Main function
- */
 public class Gaussian {
 
-    public static void main(String[] args) {
-        int mat_size, i, j, step;
-        Scanner sc = new Scanner(System.in);
-
-        System.out.println("Matrix Size : ");
-        mat_size = sc.nextInt();
+    public static ArrayList<Double> gaussian(int mat_size, ArrayList<Double> matrix) {
+        ArrayList<Double> answerArray = new ArrayList<Double>();
+        int i, j = 0;
 
         double[][] mat = new double[mat_size + 1][mat_size + 1];
         double[][] x = new double[mat_size][mat_size + 1];
 
-        System.out.println("Enter value of the matrix");
-        System.out.println(' ');
+        // Values from arraylist to matrix
         for (i = 0; i < mat_size; i++) {
             for (j = 0; j <= mat_size; j++) {
-                mat[i][j] = sc.nextInt();
+                mat[i][j] = matrix.get(i);
             }
         }
 
-        // perform Gaussian elimination
+        mat = gaussianElimination(mat_size, i, mat);
+        answerArray = valueOfGaussian(mat_size, x, mat);
+        return answerArray;
+    }
+
+    // Perform Gaussian elimination
+    public static double[][] gaussianElimination(int mat_size, int i, double[][] mat) {
+        int step = 0;
         for (step = 0; step < mat_size - 1; step++) {
             for (i = step; i < mat_size - 1; i++) {
                 double a = (mat[i + 1][step] / mat[step][step]);
 
-                for (j = step; j <= mat_size; j++) {
+                for (int j = step; j <= mat_size; j++) {
                     mat[i + 1][j] = mat[i + 1][j] - (a * mat[step][j]);
                 }
             }
         }
+        return mat;
+    }
+
+    // calcilate the x_1, x_2,... values of the gaussian and save it in an arraylist.
+    public static ArrayList<Double> valueOfGaussian(int mat_size, double[][] x, double[][] mat) {
+        ArrayList<Double> answerArray = new ArrayList<Double>();
+        int i, j;
 
-        System.out.println("Matrix using Gaussian Elimination method: ");
-        System.out.println(" ");
         for (i = 0; i < mat_size; i++) {
             for (j = 0; j <= mat_size; j++) {
                 x[i][j] = mat[i][j];
-                System.out.print(mat[i][j] + " ");
             }
-            System.out.println();
         }
-        System.out.println("Value of the Gaussian Elimination method: ");
-        System.out.println(" ");
 
         for (i = mat_size - 1; i >= 0; i--) {
             double sum = 0;
@@ -65,8 +60,8 @@ public static void main(String[] args) {
             } else {
                 x[i][i] = (x[i][mat_size] - sum) / (x[i][i]);
             }
-            System.out.print("x" + i + "=" + x[i][i]);
-            System.out.println(" ");
+            answerArray.add(x[i][j]);
         }
+        return answerArray;
     }
-}
+}
@@ -0,0 +1,32 @@
+package com.thealgorithms.maths;
+
+import org.junit.jupiter.api.Test;
+import java.util.ArrayList;
+
+import static com.thealgorithms.maths.Gaussian.gaussian;
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+public class GaussianTest {
+
+    // easy pass test for the whole class. Matrix of 2*3.
+    @Test
+    void passTest1()
+    {
+        ArrayList<Double> list = new ArrayList<Double>();
+        ArrayList<Double> gaussian = new ArrayList<Double>();
+        ArrayList<Double> answer = new ArrayList<Double>();
+        answer.add(0.0);
+        answer.add(1.0);
+
+        int matrixSize = 2;
+        list.add(1.0);
+        list.add(1.0);
+        list.add(1.0);
+        list.add(2.0);
+        list.add(1.0);
+        list.add(1.0);
+        gaussian=gaussian(matrixSize,list);
+
+        assertEquals(answer,gaussian);
+    }
+}