mirror of
https://github.com/TheAlgorithms/C
synced 2024-11-24 22:39:52 +03:00
126 lines
3.1 KiB
C
126 lines
3.1 KiB
C
/**
|
|
* \file
|
|
* \brief [LU decomposition](https://en.wikipedia.org/wiki/LU_decompositon) of a
|
|
* square matrix
|
|
* \author [Krishna Vedala](https://github.com/kvedala)
|
|
*/
|
|
#include <stdio.h>
|
|
#include <stdlib.h>
|
|
#include <time.h>
|
|
#ifdef _OPENMP
|
|
#include <omp.h>
|
|
#endif
|
|
|
|
/** Perform LU decomposition on matrix
|
|
* \param[in] A matrix to decompose
|
|
* \param[out] L output L matrix
|
|
* \param[out] U output U matrix
|
|
* \param[in] mat_size input square matrix size
|
|
*/
|
|
int lu_decomposition(double **A, double **L, double **U, int mat_size)
|
|
{
|
|
int row, col, j;
|
|
|
|
// regularize each row
|
|
for (row = 0; row < mat_size; row++)
|
|
{
|
|
// Upper triangular matrix
|
|
#ifdef _OPENMP
|
|
#pragma omp for
|
|
#endif
|
|
for (col = row; col < mat_size; col++)
|
|
{
|
|
// Summation of L[i,j] * U[j,k]
|
|
double lu_sum = 0.;
|
|
for (j = 0; j < row; j++) lu_sum += L[row][j] * U[j][col];
|
|
|
|
// Evaluate U[i,k]
|
|
U[row][col] = A[row][col] - lu_sum;
|
|
}
|
|
|
|
// Lower triangular matrix
|
|
#ifdef _OPENMP
|
|
#pragma omp for
|
|
#endif
|
|
for (col = row; col < mat_size; col++)
|
|
{
|
|
if (row == col)
|
|
{
|
|
L[row][col] = 1.;
|
|
continue;
|
|
}
|
|
|
|
// Summation of L[i,j] * U[j,k]
|
|
double lu_sum = 0.;
|
|
for (j = 0; j < row; j++) lu_sum += L[col][j] * U[j][row];
|
|
|
|
// Evaluate U[i,k]
|
|
L[col][row] = (A[col][row] - lu_sum) / U[row][row];
|
|
}
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
/** Function to display square matrix */
|
|
void display(double **A, int N)
|
|
{
|
|
for (int i = 0; i < N; i++)
|
|
{
|
|
for (int j = 0; j < N; j++)
|
|
{
|
|
printf("% 3.3g \t", A[i][j]);
|
|
}
|
|
putchar('\n');
|
|
}
|
|
}
|
|
|
|
/** Main function */
|
|
int main(int argc, char **argv)
|
|
{
|
|
int mat_size = 3; // default matrix size
|
|
const int range = 10;
|
|
const int range2 = range >> 1;
|
|
|
|
if (argc == 2)
|
|
mat_size = atoi(argv[1]);
|
|
|
|
srand(time(NULL)); // random number initializer
|
|
|
|
/* Create a square matrix with random values */
|
|
double **A = (double **)malloc(mat_size * sizeof(double *));
|
|
double **L = (double **)malloc(mat_size * sizeof(double *)); // output
|
|
double **U = (double **)malloc(mat_size * sizeof(double *)); // output
|
|
for (int i = 0; i < mat_size; i++)
|
|
{
|
|
// calloc so that all valeus are '0' by default
|
|
A[i] = (double *)calloc(mat_size, sizeof(double));
|
|
L[i] = (double *)calloc(mat_size, sizeof(double));
|
|
U[i] = (double *)calloc(mat_size, sizeof(double));
|
|
for (int j = 0; j < mat_size; j++)
|
|
/* create random values in the limits [-range2, range-1] */
|
|
A[i][j] = (double)(rand() % range - range2);
|
|
}
|
|
|
|
lu_decomposition(A, L, U, mat_size);
|
|
|
|
printf("A = \n");
|
|
display(A, mat_size);
|
|
printf("\nL = \n");
|
|
display(L, mat_size);
|
|
printf("\nU = \n");
|
|
display(U, mat_size);
|
|
|
|
/* Free dynamically allocated memory */
|
|
for (int i = 0; i < mat_size; i++)
|
|
{
|
|
free(A[i]);
|
|
free(L[i]);
|
|
free(U[i]);
|
|
}
|
|
free(A);
|
|
free(L);
|
|
free(U);
|
|
|
|
return 0;
|
|
} |