1997-05-30 19:25:54 +00:00
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/* Copyright 1988, Brown Computer Graphics Group. All Rights Reserved. */
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/* --------------------------------------------------------------------------
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* This file contains routines that operate solely on matrices.
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* -------------------------------------------------------------------------*/
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1998-01-19 19:27:10 +00:00
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#include <Math/mat3defs.h>
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1997-05-30 19:25:54 +00:00
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/* -------------------------- Static Routines ---------------------------- */
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#define SMALL 1e-20 /* Small enough to be considered zero */
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/*
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* Shuffles rows in inverse of 3x3. See comment in MAT3_inv3_second_col().
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*/
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static void
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MAT3_inv3_swap( register double inv[3][3], int row0, int row1, int row2)
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{
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register int i, tempi;
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double temp;
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#define SWAP_ROWS(a, b) \
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for (i = 0; i < 3; i++) SWAP(inv[a][i], inv[b][i], temp); \
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SWAP(a, b, tempi)
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if (row0 != 0){
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if (row1 == 0) {
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SWAP_ROWS(row0, row1);
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}
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else {
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SWAP_ROWS(row0, row2);
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}
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}
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if (row1 != 1) {
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SWAP_ROWS(row1, row2);
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}
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}
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/*
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* Does Gaussian elimination on second column.
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*/
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static int
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MAT3_inv3_second_col (register double source[3][3], register double inv[3][3], int row0)
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{
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register int row1, row2, i1, i2, i;
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double temp;
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double a, b;
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/* Find which row to use */
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if (row0 == 0) i1 = 1, i2 = 2;
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else if (row0 == 1) i1 = 0, i2 = 2;
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else i1 = 0, i2 = 1;
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/* Find which is larger in abs. val.:the entry in [i1][1] or [i2][1] */
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/* and use that value for pivoting. */
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a = source[i1][1]; if (a < 0) a = -a;
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b = source[i2][1]; if (b < 0) b = -b;
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if (a > b) row1 = i1;
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else row1 = i2;
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row2 = (row1 == i1 ? i2 : i1);
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/* Scale row1 in source */
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if ((source[row1][1] < SMALL) && (source[row1][1] > -SMALL)) return(FALSE);
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temp = 1.0 / source[row1][1];
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source[row1][1] = 1.0;
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source[row1][2] *= temp; /* source[row1][0] is zero already */
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/* Scale row1 in inv */
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inv[row1][row1] = temp; /* it used to be a 1.0 */
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inv[row1][row0] *= temp;
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/* Clear column one, source, and make corresponding changes in inv */
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for (i = 0; i < 3; i++) if (i != row1) { /* for i = all rows but row1 */
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temp = -source[i][1];
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source[i][1] = 0.0;
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source[i][2] += temp * source[row1][2];
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inv[i][row1] = temp * inv[row1][row1];
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inv[i][row0] += temp * inv[row1][row0];
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}
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/* Scale row2 in source */
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if ((source[row2][2] < SMALL) && (source[row2][2] > -SMALL)) return(FALSE);
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temp = 1.0 / source[row2][2];
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source[row2][2] = 1.0; /* source[row2][*] is zero already */
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/* Scale row2 in inv */
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inv[row2][row2] = temp; /* it used to be a 1.0 */
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inv[row2][row0] *= temp;
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inv[row2][row1] *= temp;
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/* Clear column one, source, and make corresponding changes in inv */
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for (i = 0; i < 3; i++) if (i != row2) { /* for i = all rows but row2 */
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temp = -source[i][2];
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source[i][2] = 0.0;
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inv[i][row0] += temp * inv[row2][row0];
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inv[i][row1] += temp * inv[row2][row1];
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inv[i][row2] += temp * inv[row2][row2];
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}
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/*
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* Now all is done except that the inverse needs to have its rows shuffled.
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* row0 needs to be moved to inv[0][*], row1 to inv[1][*], etc.
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*
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* We *didn't* do the swapping before the elimination so that we could more
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* easily keep track of what ops are needed to be done in the inverse.
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*/
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MAT3_inv3_swap(inv, row0, row1, row2);
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return(TRUE);
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}
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/*
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* Fast inversion routine for 3 x 3 matrices. - Written by jfh.
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*
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* This takes 30 multiplies/divides, as opposed to 39 for Cramer's Rule.
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* The algorithm consists of performing fast gaussian elimination, by never
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* doing any operations where the result is guaranteed to be zero, or where
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* one operand is guaranteed to be zero. This is done at the cost of clarity,
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* alas.
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*
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* Returns 1 if the inverse was successful, 0 if it failed.
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*/
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static int
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MAT3_invert3 (register double source[3][3], register double inv[3][3])
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{
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register int i, row0;
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double temp;
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double a, b, c;
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inv[0][0] = inv[1][1] = inv[2][2] = 1.0;
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inv[0][1] = inv[0][2] = inv[1][0] = inv[1][2] = inv[2][0] = inv[2][1] = 0.0;
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/* attempt to find the largest entry in first column to use as pivot */
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a = source[0][0]; if (a < 0) a = -a;
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b = source[1][0]; if (b < 0) b = -b;
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c = source[2][0]; if (c < 0) c = -c;
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if (a > b) {
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if (a > c) row0 = 0;
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else row0 = 2;
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}
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else {
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if (b > c) row0 = 1;
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else row0 = 2;
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}
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/* Scale row0 of source */
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if ((source[row0][0] < SMALL) && (source[row0][0] > -SMALL)) return(FALSE);
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temp = 1.0 / source[row0][0];
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source[row0][0] = 1.0;
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source[row0][1] *= temp;
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source[row0][2] *= temp;
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/* Scale row0 of inverse */
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inv[row0][row0] = temp; /* other entries are zero -- no effort */
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/* Clear column zero of source, and make corresponding changes in inverse */
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for (i = 0; i < 3; i++) if (i != row0) { /* for i = all rows but row0 */
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temp = -source[i][0];
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source[i][0] = 0.0;
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source[i][1] += temp * source[row0][1];
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source[i][2] += temp * source[row0][2];
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inv[i][row0] = temp * inv[row0][row0];
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}
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/*
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* We've now done gaussian elimination so that the source and
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* inverse look like this:
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*
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* 1 * * * 0 0
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* 0 * * * 1 0
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* 0 * * * 0 1
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*
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* We now proceed to do elimination on the second column.
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*/
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if (! MAT3_inv3_second_col(source, inv, row0)) return(FALSE);
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return(TRUE);
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}
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/*
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* Finds a new pivot for a non-simple 4x4. See comments in MAT3invert().
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*/
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static int
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MAT3_inv4_pivot (register MAT3mat src, MAT3vec r, double *s, int *swap)
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{
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register int i, j;
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double temp, max;
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*swap = -1;
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if (MAT3_IS_ZERO(src[3][3])) {
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/* Look for a different pivot element: one with largest abs value */
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max = 0.0;
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for (i = 0; i < 4; i++) {
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if (src[i][3] > max) max = src[*swap = i][3];
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else if (src[i][3] < -max) max = -src[*swap = i][3];
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}
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/* No pivot element available ! */
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if (*swap < 0) return(FALSE);
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else for (j = 0; j < 4; j++) SWAP(src[*swap][j], src[3][j], temp);
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}
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MAT3_SET_VEC (r, -src[0][3], -src[1][3], -src[2][3]);
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*s = 1.0 / src[3][3];
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src[0][3] = src[1][3] = src[2][3] = 0.0;
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src[3][3] = 1.0;
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MAT3_SCALE_VEC(src[3], src[3], *s);
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for (i = 0; i < 3; i++) {
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src[0][i] += r[0] * src[3][i];
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src[1][i] += r[1] * src[3][i];
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src[2][i] += r[2] * src[3][i];
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}
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return(TRUE);
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}
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/* ------------------------- Internal Routines --------------------------- */
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/* -------------------------- Public Routines ---------------------------- */
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/*
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* This returns the inverse of the given matrix. The result matrix
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* may be the same as the one to invert.
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*
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* Fast inversion routine for 4 x 4 matrices, written by jfh.
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*
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* Returns 1 if the inverse was successful, 0 if it failed.
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*
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* This routine has been specially tweaked to notice the following:
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* If the matrix has the form
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* * * * 0
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* * * * 0
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* * * * 0
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* * * * 1
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*
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* (as do many matrices in graphics), then we compute the inverse of
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* the upper left 3x3 matrix and use this to find the general inverse.
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*
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* In the event that the right column is not 0-0-0-1, we do gaussian
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* elimination to make it so, then use the 3x3 inverse, and then do
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* our gaussian elimination.
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*/
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int
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1998-01-19 18:40:33 +00:00
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MAT3invert(double (*result_mat)[4], double (*mat)[4])
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1997-05-30 19:25:54 +00:00
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{
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MAT3mat src, inv;
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register int i, j, simple;
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double m[3][3], inv3[3][3], s, temp;
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MAT3vec r, t;
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int swap;
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MAT3copy(src, mat);
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MAT3identity(inv);
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/* If last column is not (0,0,0,1), use special code */
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simple = (mat[0][3] == 0.0 && mat[1][3] == 0.0 &&
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mat[2][3] == 0.0 && mat[3][3] == 1.0);
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if (! simple && ! MAT3_inv4_pivot(src, r, &s, &swap)) return(FALSE);
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MAT3_COPY_VEC(t, src[3]); /* Translation vector */
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/* Copy upper-left 3x3 matrix */
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for (i = 0; i < 3; i++) for (j = 0; j < 3; j++) m[i][j] = src[i][j];
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if (! MAT3_invert3(m, inv3)) return(FALSE);
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for (i = 0; i < 3; i++) for (j = 0; j < 3; j++) inv[i][j] = inv3[i][j];
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for (i = 0; i < 3; i++) for (j = 0; j < 3; j++)
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inv[3][i] -= t[j] * inv3[j][i];
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if (! simple) {
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/* We still have to undo our gaussian elimination from earlier on */
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/* add r0 * first col to last col */
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/* add r1 * 2nd col to last col */
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/* add r2 * 3rd col to last col */
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for (i = 0; i < 4; i++) {
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inv[i][3] += r[0] * inv[i][0] + r[1] * inv[i][1] + r[2] * inv[i][2];
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inv[i][3] *= s;
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}
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if (swap >= 0)
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for (i = 0; i < 4; i++) SWAP(inv[i][swap], inv[i][3], temp);
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}
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MAT3copy(result_mat, inv);
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return(TRUE);
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}
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