/** * @file * \brief Compute real eigen values and eigen vectors of a symmetric matrix * using [QR decomposition](https://en.wikipedia.org/wiki/QR_decomposition) * method. */ #include "qr_decompose.h" #include #include #include #include #define LIMS 9 /**< limit of range of matrix values */ /** * create a square matrix of given size with random elements * \param[out] A matrix to create (must be pre-allocated in memory) * \param[in] N matrix size */ void create_matrix(double **A, int N) { int i, j, tmp, lim2 = LIMS >> 1; srand(time(NULL)); for (i = 0; i < N; i++) { A[i][i] = (rand() % LIMS) - lim2; for (j = i + 1; j < N; j++) { tmp = (rand() % LIMS) - lim2; A[i][j] = tmp; A[j][i] = tmp; } } } /** * Perform multiplication of two matrices. * * R2 must be equal to C1 * * Resultant matrix size should be R1xC2 * \param[in] A first matrix to multiply * \param[in] B second matrix to multiply * \param[out] OUT output matrix (must be pre-allocated) * \param[in] R1 number of rows of first matrix * \param[in] C1 number of columns of first matrix * \param[in] R2 number of rows of second matrix * \param[in] C2 number of columns of second matrix * \returns pointer to resultant matrix */ double **mat_mul(double **A, double **B, double **OUT, int R1, int C1, int R2, int C2) { if (C1 != R2) { perror("Matrix dimensions mismatch!"); return OUT; } for (int i = 0; i < R1; i++) for (int j = 0; j < C2; j++) { OUT[i][j] = 0.f; for (int k = 0; k < C1; k++) OUT[i][j] += A[i][k] * B[k][j]; } return OUT; } /** * main function */ int main(int argc, char **argv) { int mat_size = 5; if (argc == 2) mat_size = atoi(argv[1]); if (mat_size < 2) { fprintf(stderr, "Matrix size should be > 2\n"); return -1; } int i, rows = mat_size, columns = mat_size; double **A = (double **)malloc(sizeof(double *) * mat_size); double **R = (double **)malloc(sizeof(double *) * mat_size); double **Q = (double **)malloc(sizeof(double *) * mat_size); /* number of eigen values = matrix size */ double *eigen_vals = (double *)malloc(sizeof(double) * mat_size); if (!Q || !R || !eigen_vals) { perror("Unable to allocate memory for Q & R!"); return -1; } for (i = 0; i < mat_size; i++) { A[i] = (double *)malloc(sizeof(double) * mat_size); R[i] = (double *)malloc(sizeof(double) * mat_size); Q[i] = (double *)malloc(sizeof(double) * mat_size); if (!Q[i] || !R[i]) { perror("Unable to allocate memory for Q & R."); return -1; } } /* create a random matrix */ create_matrix(A, mat_size); print_matrix(A, mat_size, mat_size); int counter = 0, num_eigs = rows - 1; double last_eig = 0; clock_t t1 = clock(); while (num_eigs > 0) /* continue till all eigen values are found */ { /* iterate with QR decomposition */ while (fabs(A[num_eigs][num_eigs - 1]) > 1e-10) { last_eig = A[num_eigs][num_eigs]; for (int i = 0; i < rows; i++) A[i][i] -= last_eig; /* A - cI */ qr_decompose(A, Q, R, rows, columns); #if defined(DEBUG) || !defined(NDEBUG) print_matrix(A, rows, columns); print_matrix(Q, rows, columns); print_matrix(R, columns, columns); printf("-------------------- %d ---------------------\n", ++counter); #endif mat_mul(R, Q, A, columns, columns, rows, columns); for (int i = 0; i < rows; i++) A[i][i] += last_eig; /* A + cI */ } /* store the converged eigen value */ eigen_vals[num_eigs] = A[num_eigs][num_eigs]; #if defined(DEBUG) || !defined(NDEBUG) printf("========================\n"); printf("Eigen value: % g,\n", last_eig); printf("========================\n"); #endif num_eigs--; rows--; columns--; } eigen_vals[0] = A[0][0]; double dtime = (double)(clock() - t1) / CLOCKS_PER_SEC; #if defined(DEBUG) || !defined(NDEBUG) print_matrix(R, mat_size, mat_size); print_matrix(Q, mat_size, mat_size); #endif printf("Eigen vals: "); for (i = 0; i < mat_size; i++) printf("% 9.4g\t", eigen_vals[i]); printf("\nTime taken to compute: % .4g sec\n", dtime); for (int i = 0; i < mat_size; i++) { free(A[i]); free(R[i]); free(Q[i]); } free(A); free(R); free(Q); free(eigen_vals); return 0; }