176 lines
5.8 KiB
Java
176 lines
5.8 KiB
Java
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/*
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This is java program to solve the system of linear equations. This can be done by first representing equations(vectors)
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to matrix form, then finding the inverse of the matrix formed by the coefficients of variable and multiplying it with constants.
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*/
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//This is a sample program to solve the linear equations.
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import java.util.Scanner;
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public class Solve_Linear_Equation
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{
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public static void main(String args[])
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{
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char []var = {'x', 'y', 'z', 'w'};
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System.out.println("Enter the number of variables in the equations: ");
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Scanner input = new Scanner(System.in);
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int n = input.nextInt();
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System.out.println("Enter the coefficients of each variable for each equations");
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System.out.println("ax + by + cz + ... = d");
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double [][]mat = new double[n][n];
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double [][]constants = new double[n][1];
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//input
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for(int i=0; i<n; i++)
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{
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for(int j=0; j<n; j++)
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{
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mat[i][j] = input.nextDouble();
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}
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constants[i][0] = input.nextDouble();
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}
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//Matrix representation
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for(int i=0; i<n; i++)
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{
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for(int j=0; j<n; j++)
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{
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System.out.print(" "+mat[i][j]);
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}
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System.out.print(" "+ var[i]);
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System.out.print(" = "+ constants[i][0]);
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System.out.println();
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}
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//inverse of matrix mat[][]
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double inverted_mat[][] = invert(mat);
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System.out.println("The inverse is: ");
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for (int i=0; i<n; ++i)
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{
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for (int j=0; j<n; ++j)
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{
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System.out.print(inverted_mat[i][j]+" ");
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}
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System.out.println();
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}
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//Multiplication of mat inverse and constants
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double result[][] = new double[n][1];
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for (int i = 0; i < n; i++)
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{
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for (int j = 0; j < 1; j++)
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{
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for (int k = 0; k < n; k++)
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{
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result[i][j] = result[i][j] + inverted_mat[i][k] * constants[k][j];
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}
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}
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}
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System.out.println("The product is:");
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for(int i=0; i<n; i++)
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{
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System.out.println(result[i][0] + " ");
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}
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input.close();
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}
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public static double[][] invert(double a[][])
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{
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int n = a.length;
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double x[][] = new double[n][n];
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double b[][] = new double[n][n];
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int index[] = new int[n];
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for (int i=0; i<n; ++i)
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b[i][i] = 1;
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// Transform the matrix into an upper triangle
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gaussian(a, index);
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// Update the matrix b[i][j] with the ratios stored
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for (int i=0; i<n-1; ++i)
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for (int j=i+1; j<n; ++j)
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for (int k=0; k<n; ++k)
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b[index[j]][k]
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-= a[index[j]][i]*b[index[i]][k];
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// Perform backward substitutions
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for (int i=0; i<n; ++i)
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{
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x[n-1][i] = b[index[n-1]][i]/a[index[n-1]][n-1];
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for (int j=n-2; j>=0; --j)
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{
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x[j][i] = b[index[j]][i];
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for (int k=j+1; k<n; ++k)
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{
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x[j][i] -= a[index[j]][k]*x[k][i];
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}
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x[j][i] /= a[index[j]][j];
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}
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}
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return x;
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}
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// Method to carry out the partial-pivoting Gaussian
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// elimination. Here index[] stores pivoting order.
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public static void gaussian(double a[][], int index[])
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{
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int n = index.length;
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double c[] = new double[n];
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// Initialize the index
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for (int i=0; i<n; ++i)
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index[i] = i;
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// Find the rescaling factors, one from each row
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for (int i=0; i<n; ++i)
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{
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double c1 = 0;
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for (int j=0; j<n; ++j)
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{
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double c0 = Math.abs(a[i][j]);
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if (c0 > c1) c1 = c0;
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}
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c[i] = c1;
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}
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// Search the pivoting element from each column
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int k = 0;
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for (int j=0; j<n-1; ++j)
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{
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double pi1 = 0;
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for (int i=j; i<n; ++i)
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{
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double pi0 = Math.abs(a[index[i]][j]);
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pi0 /= c[index[i]];
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if (pi0 > pi1)
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{
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pi1 = pi0;
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k = i;
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}
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}
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// Interchange rows according to the pivoting order
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int itmp = index[j];
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index[j] = index[k];
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index[k] = itmp;
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for (int i=j+1; i<n; ++i)
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{
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double pj = a[index[i]][j]/a[index[j]][j];
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// Record pivoting ratios below the diagonal
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a[index[i]][j] = pj;
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// Modify other elements accordingly
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for (int l=j+1; l<n; ++l)
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a[index[i]][l] -= pj*a[index[j]][l];
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}
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}
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}
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}
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/*
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Enter the number of variables in the equations:
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2
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Enter the coefficients of each variable for each equations
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ax + by + cz + ... = d
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1 2 3
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3 2 1
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1.0 2.0 x = 3.0
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3.0 2.0 y = 1.0
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The inverse is:
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-0.49999999999999994 0.5
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0.7499999999999999 -0.24999999999999997
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The product is:
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-0.9999999999999998
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1.9999999999999996
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