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285 lines
8.2 KiB
285 lines
8.2 KiB
/*
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* Copyright(C) 1999-2020, 2023 National Technology & Engineering Solutions
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* of Sandia, LLC (NTESS). Under the terms of Contract DE-NA0003525 with
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* NTESS, the U.S. Government retains certain rights in this software.
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*
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* See packages/seacas/LICENSE for details
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*/
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#include "defs.h"
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#include <math.h>
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/* Find eigenvalues of 3x3 symmetric system by solving cubic. */
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void ch_evals3(double H[3][3], /* 3x3 sym matrix for lowest eigenvalue */
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double *eval1, /* smallest eigenvalue */
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double *eval2, /* middle eigenvalue */
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double *eval3 /* largest eigenvalue */
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)
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{
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double mat[3][3] = {{0.0}}; /* scaled version of H */
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double a1, a2, a3; /* coefficients of cubic equation */
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double q, r; /* intermediate terms */
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double q3, r2; /* powers of q and r */
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double theta; /* angular parameter */
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double root1, root2, root3; /* three roots of cubic */
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double tol = 1.0e-6; /* allowed deviation */
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double xmax; /* largest matrix element for scaling */
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int i, j; /* loop indices */
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/* This first requires solving a cubic equation. */
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/* Normalize to avoid any numerical problems. */
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xmax = 0.0;
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for (i = 0; i < 3; i++) {
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for (j = i; j < 3; j++) {
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if (fabs(H[i][j]) > xmax) {
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xmax = fabs(H[i][j]);
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}
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}
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}
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if (xmax != 0) {
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for (i = 0; i < 3; i++) {
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for (j = 0; j < 3; j++) {
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mat[i][j] = H[i][j] / xmax;
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}
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}
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}
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a1 = -(mat[0][0] + mat[1][1] + mat[2][2]);
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a2 = (mat[0][0] * mat[1][1] - mat[0][1] * mat[1][0]) +
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(mat[0][0] * mat[2][2] - mat[0][2] * mat[2][0]) +
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(mat[1][1] * mat[2][2] - mat[1][2] * mat[2][1]);
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a3 = -determinant(mat, 3);
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if (a3 == 0) {
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root1 = 0;
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/* Solve quadratic. */
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q = -.5 * (a1 + sign(a1) * sqrt(a1 * a1 - 4 * a2));
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root2 = q;
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root3 = a2 / q;
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}
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else { /* solve cubic */
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q = (a1 * a1 - 3 * a2) / 9;
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r = (2 * a1 * a1 * a1 - 9 * a1 * a2 + 27 * a3) / 54;
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q3 = q * q * q;
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r2 = r * r;
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/* To avoid missing a root, check for roundoff. */
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if ((q3 < r2) && fabs(q3 - r2) < tol * (fabs(q3) + fabs(r2))) {
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q3 = r2;
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}
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if (q3 >= r2) { /* Three real roots. */
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if (r == 0) {
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theta = HALFPI;
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}
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else {
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q3 = sqrt(q3);
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if (q3 < fabs(r)) {
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q3 = fabs(r);
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}
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theta = acos(r / q3);
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}
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q = -2 * sqrt(q);
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root1 = q * cos(theta / 3) - a1 / 3;
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root2 = q * cos((theta + TWOPI) / 3) - a1 / 3;
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root3 = q * cos((theta + 2 * TWOPI) / 3) - a1 / 3;
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}
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else { /* Only one real root. */
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theta = sqrt(r2 - q3) + fabs(r);
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theta = pow(theta, 1.0 / 3.0);
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root1 = root2 = root3 = -sign(r) * (theta + q / theta) - a1 / 3;
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}
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}
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root1 *= xmax;
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root2 *= xmax;
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root3 *= xmax;
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*eval1 = min(root1, root2);
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*eval1 = min(*eval1, root3);
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*eval3 = max(root1, root2);
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*eval3 = max(*eval3, root3);
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if (root1 != *eval1 && root1 != *eval3) {
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*eval2 = root1;
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}
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else if (root2 != *eval1 && root2 != *eval3) {
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*eval2 = root2;
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}
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else {
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*eval2 = root3;
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}
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}
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void kramer3( /* Use Kramer's rule to solve 3x3 */
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double A[3][3], double b[3], double x[3] /* Solve Ax=b */
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)
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{
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double det = 1.0 / determinant(A, 3);
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x[0] = (b[0] * (A[1][1] * A[2][2] - A[1][2] * A[2][1]) -
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b[1] * (A[0][1] * A[2][2] - A[0][2] * A[2][1]) +
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b[2] * (A[0][1] * A[1][2] - A[0][2] * A[1][1])) *
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det;
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x[1] = -(b[0] * (A[1][0] * A[2][2] - A[1][2] * A[2][0]) -
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b[1] * (A[0][0] * A[2][2] - A[0][2] * A[2][0]) +
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b[2] * (A[0][0] * A[1][2] - A[0][2] * A[1][0])) *
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det;
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x[2] = (b[0] * (A[1][0] * A[2][1] - A[1][1] * A[2][0]) -
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b[1] * (A[0][0] * A[2][1] - A[0][1] * A[2][0]) +
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b[2] * (A[0][0] * A[1][1] - A[0][1] * A[1][0])) *
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det;
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}
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/* Find the eigenvector of symmetric 3x3 matrix w/ given eigenvalue. */
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void ch_eigenvec3(double A[3][3], /* matrix to find eigenvector of */
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double eval, /* eigenvalue */
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double evec[3], /* eigenvector returned */
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double *res /* returned error estimate */
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)
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{
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double mat[3][3]; /* copy of A to write over */
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int ind[3]; /* permutation indices */
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double ex, ey, ez; /* elements of eigenvector returned */
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double xmax; /* maximum value in matrix */
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double tmp; /* intermediate values */
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double norm; /* norm of eigenvector */
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double res1, res2, res3; /* elements of residual vector */
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double tol = 1.0e-6; /* smaller value assumed to be zero */
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int imax = -1, jmax = -1; /* indices of max value in matrix */
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int i, j; /* loop counters */
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for (i = 0; i < 3; i++) {
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for (j = 0; j < 3; j++) {
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mat[i][j] = A[i][j];
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}
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}
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for (i = 0; i < 3; i++) {
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mat[i][i] -= eval;
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}
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ind[0] = 0;
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ind[1] = 1;
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ind[2] = 2;
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/* Find the largest element in the matrix. */
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xmax = 0.0;
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for (i = 0; i < 3; i++) {
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for (j = i; j < 3; j++) {
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if (fabs(mat[i][j]) > xmax) {
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imax = i;
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jmax = j;
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xmax = fabs(mat[i][j]);
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}
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}
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}
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if (xmax == 0.0) { /* Handle completely degenerate case first. */
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evec[0] = 1.0;
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evec[1] = evec[2] = 0.0;
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}
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else {
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/* Scale the matrix so largest value is 1.0 */
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for (i = 0; i < 3; i++) {
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for (j = 0; j < 3; j++) {
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mat[i][j] /= xmax;
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}
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}
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/* Swap rows if necessary to move max element to first row. */
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if (imax != 0) {
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for (j = 0; j < 3; j++) {
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tmp = mat[0][j];
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mat[0][j] = mat[imax][j];
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mat[imax][j] = tmp;
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}
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}
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/* Swap columns if necessary to move max element to first position. */
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if (jmax != 0) {
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for (i = 0; i < 3; i++) {
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tmp = mat[i][0];
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mat[i][0] = mat[i][jmax];
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mat[i][jmax] = tmp;
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}
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ind[0] = jmax;
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ind[jmax] = 0;
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}
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/* Reduce matrix to 2x2 by subtracting off first row. */
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for (i = 1; i < 3; i++) {
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for (j = 1; j < 3; j++) {
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mat[i][j] = mat[0][0] * mat[i][j] - mat[i][0] * mat[0][j];
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}
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}
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/* Find maximum element in reduced 2x2 matrix. */
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xmax = 0.0;
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for (i = 1; i < 3; i++) {
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for (j = i; j < 3; j++) {
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if (fabs(mat[i][j]) > xmax) {
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imax = i;
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jmax = j;
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xmax = fabs(mat[i][j]);
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}
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}
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}
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if (xmax < tol) { /* Handle 2-fold degenerate case - skip to end. */
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ey = 1.0;
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ex = ez = 0;
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}
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else {
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/* Swap rows 2 and 3 to move max element to 2nd row. */
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if (imax != 1) {
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for (j = 0; j < 3; j++) {
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tmp = mat[1][j];
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mat[1][j] = mat[imax][j];
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mat[imax][j] = tmp;
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}
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}
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/* Swap columns to move max element to (1,1) position. */
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if (jmax != 1) {
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for (i = 0; i < 3; i++) {
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tmp = mat[i][1];
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mat[i][1] = mat[i][2];
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mat[i][2] = tmp;
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}
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i = ind[1];
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ind[1] = ind[2];
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ind[2] = i;
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}
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/* Compute eigenvector from numerically stabilized matrix. */
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ez = mat[0][0] * mat[1][1];
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ey = -mat[1][2] * mat[0][0];
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ex = mat[0][1] * mat[1][2] - mat[0][2] * mat[1][1];
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}
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/* Reorder the e-vector to undo pivoting - end of 3-D case. */
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evec[ind[0]] = ex;
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evec[ind[1]] = ey;
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evec[ind[2]] = ez;
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}
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/* Normalize eigenvector and calculate a normalized eigen-residual. */
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norm = sqrt(evec[0] * evec[0] + evec[1] * evec[1] + evec[2] * evec[2]);
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for (i = 0; i < 3; i++) {
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evec[i] /= norm;
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}
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res1 = (A[0][0] - eval) * evec[0] + A[0][1] * evec[1] + A[0][2] * evec[2];
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res2 = A[1][0] * evec[0] + (A[1][1] - eval) * evec[1] + A[1][2] * evec[2];
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res3 = A[2][0] * evec[0] + A[2][1] * evec[1] + (A[2][2] - eval) * evec[2];
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*res = sqrt(res1 * res1 + res2 * res2 + res3 * res3);
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/* Now normalize the residual */
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res1 = fabs(A[0][0]) + fabs(A[0][1]) + fabs(A[0][2]);
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res2 = fabs(A[1][0]) + fabs(A[1][1]) + fabs(A[1][2]);
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res3 = fabs(A[2][0]) + fabs(A[2][1]) + fabs(A[2][2]);
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res2 = max(res2, res3);
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*res /= max(res1, res2);
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}
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