OpenSceneGraph/src/osg/MatrixDecomposition.cpp
2009-02-03 17:14:34 +00:00

687 lines
22 KiB
C++

/* -*-c++-*- OpenSceneGraph - Copyright (C) 1998-2006 Robert Osfield
*
* This library is open source and may be redistributed and/or modified under
* the terms of the OpenSceneGraph Public License (OSGPL) version 0.0 or
* (at your option) any later version. The full license is in LICENSE file
* included with this distribution, and on the openscenegraph.org website.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* OpenSceneGraph Public License for more details.
*/
//osgManipulator - Copyright (C) 2007 Fugro-Jason B.V.
// Matrix decomposition code taken from Graphics Gems IV
// http://www.acm.org/pubs/tog/GraphicsGems/gemsiv/polar_decomp
// Copyright (C) 1993 Ken Shoemake <shoemake@graphics.cis.upenn.edu>
#include <osg/Matrixf>
#include <osg/Matrixd>
/** Copy nxn matrix A to C using "gets" for assignment **/
#define matrixCopy(C, gets, A, n) {int i, j; for (i=0;i<n;i++) for (j=0;j<n;j++)\
C[i][j] gets (A[i][j]);}
/** Copy transpose of nxn matrix A to C using "gets" for assignment **/
#define mat_tpose(AT,gets,A,n) {int i,j; for(i=0;i<n;i++) for(j=0;j<n;j++)\
AT[i][j] gets (A[j][i]);}
/** Fill out 3x3 matrix to 4x4 **/
#define mat_pad(A) (A[W][X]=A[X][W]=A[W][Y]=A[Y][W]=A[W][Z]=A[Z][W]=0,A[W][W]=1)
/** Assign nxn matrix C the element-wise combination of A and B using "op" **/
#define matBinop(C,gets,A,op,B,n) {int i,j; for(i=0;i<n;i++) for(j=0;j<n;j++)\
C[i][j] gets (A[i][j]) op (B[i][j]);}
/** Copy nxn matrix A to C using "gets" for assignment **/
#define mat_copy(C,gets,A,n) {int i,j; for(i=0;i<n;i++) for(j=0;j<n;j++)\
C[i][j] gets (A[i][j]);}
namespace MatrixDecomposition
{
typedef struct {double x, y, z, w;} Quat; // Quaternion
enum QuatPart {X, Y, Z, W};
typedef double _HMatrix[4][4];
typedef Quat HVect; // Homogeneous 3D vector
typedef struct
{
osg::Vec4d t; // Translation Component;
Quat q; // Essential Rotation
Quat u; //Stretch rotation
HVect k; //Sign of determinant
double f; // Sign of determinant
} _affineParts;
HVect spectDecomp(_HMatrix S, _HMatrix U);
Quat snuggle(Quat q, HVect* k);
double polarDecomp(_HMatrix M, _HMatrix Q, _HMatrix S);
static _HMatrix mat_id = {{1,0,0,0},{0,1,0,0},{0,0,1,0},{0,0,0,1}};
#define SQRTHALF (0.7071067811865475244)
static Quat qxtoz = {0,SQRTHALF,0,SQRTHALF};
static Quat qytoz = {SQRTHALF,0,0,SQRTHALF};
static Quat qppmm = { 0.5, 0.5,-0.5,-0.5};
static Quat qpppp = { 0.5, 0.5, 0.5, 0.5};
static Quat qmpmm = {-0.5, 0.5,-0.5,-0.5};
static Quat qpppm = { 0.5, 0.5, 0.5,-0.5};
static Quat q0001 = { 0.0, 0.0, 0.0, 1.0};
static Quat q1000 = { 1.0, 0.0, 0.0, 0.0};
/* Return product of quaternion q by scalar w. */
Quat Qt_Scale(Quat q, double w)
{
Quat qq;
qq.w = q.w*w; qq.x = q.x*w; qq.y = q.y*w; qq.z = q.z*w;
return (qq);
}
/* Return quaternion product qL * qR. Note: order is important!
* To combine rotations, use the product Mul(qSecond, qFirst),
* which gives the effect of rotating by qFirst then qSecond. */
Quat Qt_Mul(Quat qL, Quat qR)
{
Quat qq;
qq.w = qL.w*qR.w - qL.x*qR.x - qL.y*qR.y - qL.z*qR.z;
qq.x = qL.w*qR.x + qL.x*qR.w + qL.y*qR.z - qL.z*qR.y;
qq.y = qL.w*qR.y + qL.y*qR.w + qL.z*qR.x - qL.x*qR.z;
qq.z = qL.w*qR.z + qL.z*qR.w + qL.x*qR.y - qL.y*qR.x;
return (qq);
}
/* Return conjugate of quaternion. */
Quat Qt_Conj(Quat q)
{
Quat qq;
qq.x = -q.x; qq.y = -q.y; qq.z = -q.z; qq.w = q.w;
return (qq);
}
/* Construct a (possibly non-unit) quaternion from real components. */
Quat Qt_(double x, double y, double z, double w)
{
Quat qq;
qq.x = x; qq.y = y; qq.z = z; qq.w = w;
return (qq);
}
/** Multiply the upper left 3x3 parts of A and B to get AB **/
void mat_mult(_HMatrix A, _HMatrix B, _HMatrix AB)
{
int i, j;
for (i=0; i<3; i++) for (j=0; j<3; j++)
AB[i][j] = A[i][0]*B[0][j] + A[i][1]*B[1][j] + A[i][2]*B[2][j];
}
/** Set v to cross product of length 3 vectors va and vb **/
void vcross(double *va, double *vb, double *v)
{
v[0] = va[1]*vb[2] - va[2]*vb[1];
v[1] = va[2]*vb[0] - va[0]*vb[2];
v[2] = va[0]*vb[1] - va[1]*vb[0];
}
/** Return dot product of length 3 vectors va and vb **/
double vdot(double *va, double *vb)
{
return (va[0]*vb[0] + va[1]*vb[1] + va[2]*vb[2]);
}
/** Set MadjT to transpose of inverse of M times determinant of M **/
void adjoint_transpose(_HMatrix M, _HMatrix MadjT)
{
vcross(M[1], M[2], MadjT[0]);
vcross(M[2], M[0], MadjT[1]);
vcross(M[0], M[1], MadjT[2]);
}
/** Return index of column of M containing maximum abs entry, or -1 if M=0 **/
int find_max_col(_HMatrix M)
{
double abs, max;
int i, j, col;
max = 0.0; col = -1;
for (i=0; i<3; i++) for (j=0; j<3; j++) {
abs = M[i][j]; if (abs<0.0) abs = -abs;
if (abs>max) {max = abs; col = j;}
}
return col;
}
/** Setup u for Household reflection to zero all v components but first **/
void make_reflector(double *v, double *u)
{
double s = sqrt(vdot(v, v));
u[0] = v[0]; u[1] = v[1];
u[2] = v[2] + ((v[2]<0.0) ? -s : s);
s = sqrt(2.0/vdot(u, u));
u[0] = u[0]*s; u[1] = u[1]*s; u[2] = u[2]*s;
}
/** Apply Householder reflection represented by u to column vectors of M **/
void reflect_cols(_HMatrix M, double *u)
{
int i, j;
for (i=0; i<3; i++) {
double s = u[0]*M[0][i] + u[1]*M[1][i] + u[2]*M[2][i];
for (j=0; j<3; j++) M[j][i] -= u[j]*s;
}
}
/** Apply Householder reflection represented by u to row vectors of M **/
void reflect_rows(_HMatrix M, double *u)
{
int i, j;
for (i=0; i<3; i++) {
double s = vdot(u, M[i]);
for (j=0; j<3; j++) M[i][j] -= u[j]*s;
}
}
/** Find orthogonal factor Q of rank 1 (or less) M **/
void do_rank1(_HMatrix M, _HMatrix Q)
{
double v1[3], v2[3], s;
int col;
mat_copy(Q,=,mat_id,4);
/* If rank(M) is 1, we should find a non-zero column in M */
col = find_max_col(M);
if (col<0) return; /* Rank is 0 */
v1[0] = M[0][col]; v1[1] = M[1][col]; v1[2] = M[2][col];
make_reflector(v1, v1); reflect_cols(M, v1);
v2[0] = M[2][0]; v2[1] = M[2][1]; v2[2] = M[2][2];
make_reflector(v2, v2); reflect_rows(M, v2);
s = M[2][2];
if (s<0.0) Q[2][2] = -1.0;
reflect_cols(Q, v1); reflect_rows(Q, v2);
}
/** Find orthogonal factor Q of rank 2 (or less) M using adjoint transpose **/
void do_rank2(_HMatrix M, _HMatrix MadjT, _HMatrix Q)
{
double v1[3], v2[3];
double w, x, y, z, c, s, d;
int col;
/* If rank(M) is 2, we should find a non-zero column in MadjT */
col = find_max_col(MadjT);
if (col<0) {do_rank1(M, Q); return;} /* Rank<2 */
v1[0] = MadjT[0][col]; v1[1] = MadjT[1][col]; v1[2] = MadjT[2][col];
make_reflector(v1, v1); reflect_cols(M, v1);
vcross(M[0], M[1], v2);
make_reflector(v2, v2); reflect_rows(M, v2);
w = M[0][0]; x = M[0][1]; y = M[1][0]; z = M[1][1];
if (w*z>x*y) {
c = z+w; s = y-x; d = sqrt(c*c+s*s); c = c/d; s = s/d;
Q[0][0] = Q[1][1] = c; Q[0][1] = -(Q[1][0] = s);
} else {
c = z-w; s = y+x; d = sqrt(c*c+s*s); c = c/d; s = s/d;
Q[0][0] = -(Q[1][1] = c); Q[0][1] = Q[1][0] = s;
}
Q[0][2] = Q[2][0] = Q[1][2] = Q[2][1] = 0.0; Q[2][2] = 1.0;
reflect_cols(Q, v1); reflect_rows(Q, v2);
}
double mat_norm(_HMatrix M, int tpose)
{
int i;
double sum, max;
max = 0.0;
for (i=0; i<3; i++) {
if (tpose) sum = fabs(M[0][i])+fabs(M[1][i])+fabs(M[2][i]);
else sum = fabs(M[i][0])+fabs(M[i][1])+fabs(M[i][2]);
if (max<sum) max = sum;
}
return max;
}
double norm_inf(_HMatrix M) {return mat_norm(M, 0);}
double norm_one(_HMatrix M) {return mat_norm(M, 1);}
/* Construct a unit quaternion from rotation matrix. Assumes matrix is
* used to multiply column vector on the left: vnew = mat vold. Works
* correctly for right-handed coordinate system and right-handed rotations.
* Translation and perspective components ignored. */
Quat quatFromMatrix(_HMatrix mat)
{
/* This algorithm avoids near-zero divides by looking for a large component
* - first w, then x, y, or z. When the trace is greater than zero,
* |w| is greater than 1/2, which is as small as a largest component can be.
* Otherwise, the largest diagonal entry corresponds to the largest of |x|,
* |y|, or |z|, one of which must be larger than |w|, and at least 1/2. */
Quat qu = q0001;
double tr, s;
tr = mat[X][X] + mat[Y][Y]+ mat[Z][Z];
if (tr >= 0.0)
{
s = sqrt(tr + mat[W][W]);
qu.w = s*0.5;
s = 0.5 / s;
qu.x = (mat[Z][Y] - mat[Y][Z]) * s;
qu.y = (mat[X][Z] - mat[Z][X]) * s;
qu.z = (mat[Y][X] - mat[X][Y]) * s;
}
else
{
int h = X;
if (mat[Y][Y] > mat[X][X]) h = Y;
if (mat[Z][Z] > mat[h][h]) h = Z;
switch (h) {
#define caseMacro(i,j,k,I,J,K) \
case I:\
s = sqrt( (mat[I][I] - (mat[J][J]+mat[K][K])) + mat[W][W] );\
qu.i = s*0.5;\
s = 0.5 / s;\
qu.j = (mat[I][J] + mat[J][I]) * s;\
qu.k = (mat[K][I] + mat[I][K]) * s;\
qu.w = (mat[K][J] - mat[J][K]) * s;\
break
caseMacro(x,y,z,X,Y,Z);
caseMacro(y,z,x,Y,Z,X);
caseMacro(z,x,y,Z,X,Y);
}
}
if (mat[W][W] != 1.0) qu = Qt_Scale(qu, 1/sqrt(mat[W][W]));
return (qu);
}
/******* Decompose Affine Matrix *******/
/* Decompose 4x4 affine matrix A as TFRUK(U transpose), where t contains the
* translation components, q contains the rotation R, u contains U, k contains
* scale factors, and f contains the sign of the determinant.
* Assumes A transforms column vectors in right-handed coordinates.
* See Ken Shoemake and Tom Duff. Matrix Animation and Polar Decomposition.
* Proceedings of Graphics Interface 1992.
*/
void decompAffine(_HMatrix A, _affineParts * parts)
{
_HMatrix Q, S, U;
Quat p;
//Translation component.
parts->t = osg::Vec4d(A[X][W], A[Y][W], A[Z][W], 0);
double det = polarDecomp(A, Q, S);
if (det<0.0)
{
matrixCopy(Q, =, -Q, 3);
parts->f = -1;
}
else
parts->f = 1;
parts->q = quatFromMatrix(Q);
parts->k = spectDecomp(S, U);
parts->u = quatFromMatrix(U);
p = snuggle(parts->u, &parts->k);
parts->u = Qt_Mul(parts->u, p);
}
/******* Polar Decomposition *******/
/* Polar Decomposition of 3x3 matrix in 4x4,
* M = QS. See Nicholas Higham and Robert S. Schreiber,
* Fast Polar Decomposition of An Arbitrary Matrix,
* Technical Report 88-942, October 1988,
* Department of Computer Science, Cornell University.
*/
double polarDecomp( _HMatrix M, _HMatrix Q, _HMatrix S)
{
#define TOL 1.0e-6
_HMatrix Mk, MadjTk, Ek;
double det, M_one, M_inf, MadjT_one, MadjT_inf, E_one, gamma, g1, g2;
int i, j;
mat_tpose(Mk,=,M,3);
M_one = norm_one(Mk); M_inf = norm_inf(Mk);
do
{
adjoint_transpose(Mk, MadjTk);
det = vdot(Mk[0], MadjTk[0]);
if (det==0.0)
{
do_rank2(Mk, MadjTk, Mk);
break;
}
MadjT_one = norm_one(MadjTk);
MadjT_inf = norm_inf(MadjTk);
gamma = sqrt(sqrt((MadjT_one*MadjT_inf)/(M_one*M_inf))/fabs(det));
g1 = gamma*0.5;
g2 = 0.5/(gamma*det);
matrixCopy(Ek,=,Mk,3);
matBinop(Mk,=,g1*Mk,+,g2*MadjTk,3);
mat_copy(Ek,-=,Mk,3);
E_one = norm_one(Ek);
M_one = norm_one(Mk);
M_inf = norm_inf(Mk);
} while(E_one>(M_one*TOL));
mat_tpose(Q,=,Mk,3); mat_pad(Q);
mat_mult(Mk, M, S); mat_pad(S);
for (i=0; i<3; i++)
for (j=i; j<3; j++)
S[i][j] = S[j][i] = 0.5*(S[i][j]+S[j][i]);
return (det);
}
/******* Spectral Decomposition *******/
/* Compute the spectral decomposition of symmetric positive semi-definite S.
* Returns rotation in U and scale factors in result, so that if K is a diagonal
* matrix of the scale factors, then S = U K (U transpose). Uses Jacobi method.
* See Gene H. Golub and Charles F. Van Loan. Matrix Computations. Hopkins 1983.
*/
HVect spectDecomp(_HMatrix S, _HMatrix U)
{
HVect kv;
double Diag[3],OffD[3]; /* OffD is off-diag (by omitted index) */
double g,h,fabsh,fabsOffDi,t,theta,c,s,tau,ta,OffDq,a,b;
static char nxt[] = {Y,Z,X};
int sweep, i, j;
mat_copy(U,=,mat_id,4);
Diag[X] = S[X][X]; Diag[Y] = S[Y][Y]; Diag[Z] = S[Z][Z];
OffD[X] = S[Y][Z]; OffD[Y] = S[Z][X]; OffD[Z] = S[X][Y];
for (sweep=20; sweep>0; sweep--) {
double sm = fabs(OffD[X])+fabs(OffD[Y])+fabs(OffD[Z]);
if (sm==0.0) break;
for (i=Z; i>=X; i--) {
int p = nxt[i]; int q = nxt[p];
fabsOffDi = fabs(OffD[i]);
g = 100.0*fabsOffDi;
if (fabsOffDi>0.0) {
h = Diag[q] - Diag[p];
fabsh = fabs(h);
if (fabsh+g==fabsh) {
t = OffD[i]/h;
} else {
theta = 0.5*h/OffD[i];
t = 1.0/(fabs(theta)+sqrt(theta*theta+1.0));
if (theta<0.0) t = -t;
}
c = 1.0/sqrt(t*t+1.0); s = t*c;
tau = s/(c+1.0);
ta = t*OffD[i]; OffD[i] = 0.0;
Diag[p] -= ta; Diag[q] += ta;
OffDq = OffD[q];
OffD[q] -= s*(OffD[p] + tau*OffD[q]);
OffD[p] += s*(OffDq - tau*OffD[p]);
for (j=Z; j>=X; j--) {
a = U[j][p]; b = U[j][q];
U[j][p] -= s*(b + tau*a);
U[j][q] += s*(a - tau*b);
}
}
}
}
kv.x = Diag[X]; kv.y = Diag[Y]; kv.z = Diag[Z]; kv.w = 1.0;
return (kv);
}
/******* Spectral Axis Adjustment *******/
/* Given a unit quaternion, q, and a scale vector, k, find a unit quaternion, p,
* which permutes the axes and turns freely in the plane of duplicate scale
* factors, such that q p has the largest possible w component, i.e. the
* smallest possible angle. Permutes k's components to go with q p instead of q.
* See Ken Shoemake and Tom Duff. Matrix Animation and Polar Decomposition.
* Proceedings of Graphics Interface 1992. Details on p. 262-263.
*/
Quat snuggle(Quat q, HVect *k)
{
#define sgn(n,v) ((n)?-(v):(v))
#define swap(a,i,j) {a[3]=a[i]; a[i]=a[j]; a[j]=a[3];}
#define cycle(a,p) if (p) {a[3]=a[0]; a[0]=a[1]; a[1]=a[2]; a[2]=a[3];}\
else {a[3]=a[2]; a[2]=a[1]; a[1]=a[0]; a[0]=a[3];}
Quat p = q0001;
double ka[4];
int i, turn = -1;
ka[X] = k->x; ka[Y] = k->y; ka[Z] = k->z;
if (ka[X]==ka[Y]) {
if (ka[X]==ka[Z])
turn = W;
else turn = Z;
}
else {
if (ka[X]==ka[Z])
turn = Y;
else if (ka[Y]==ka[Z])
turn = X;
}
if (turn>=0) {
Quat qtoz, qp;
unsigned int win;
double mag[3], t;
switch (turn) {
default: return (Qt_Conj(q));
case X: q = Qt_Mul(q, qtoz = qxtoz); swap(ka,X,Z) break;
case Y: q = Qt_Mul(q, qtoz = qytoz); swap(ka,Y,Z) break;
case Z: qtoz = q0001; break;
}
q = Qt_Conj(q);
mag[0] = (double)q.z*q.z+(double)q.w*q.w-0.5;
mag[1] = (double)q.x*q.z-(double)q.y*q.w;
mag[2] = (double)q.y*q.z+(double)q.x*q.w;
bool neg[3];
for (i=0; i<3; i++)
{
neg[i] = (mag[i]<0.0);
if (neg[i]) mag[i] = -mag[i];
}
if (mag[0]>mag[1]) {
if (mag[0]>mag[2])
win = 0;
else win = 2;
}
else {
if (mag[1]>mag[2]) win = 1;
else win = 2;
}
switch (win) {
case 0: if (neg[0]) p = q1000; else p = q0001; break;
case 1: if (neg[1]) p = qppmm; else p = qpppp; cycle(ka,0) break;
case 2: if (neg[2]) p = qmpmm; else p = qpppm; cycle(ka,1) break;
}
qp = Qt_Mul(q, p);
t = sqrt(mag[win]+0.5);
p = Qt_Mul(p, Qt_(0.0,0.0,-qp.z/t,qp.w/t));
p = Qt_Mul(qtoz, Qt_Conj(p));
}
else {
double qa[4], pa[4];
unsigned int lo, hi;
bool par = false;
bool neg[4];
double all, big, two;
qa[0] = q.x; qa[1] = q.y; qa[2] = q.z; qa[3] = q.w;
for (i=0; i<4; i++) {
pa[i] = 0.0;
neg[i] = (qa[i]<0.0);
if (neg[i]) qa[i] = -qa[i];
par ^= neg[i];
}
/* Find two largest components, indices in hi and lo */
if (qa[0]>qa[1]) lo = 0;
else lo = 1;
if (qa[2]>qa[3]) hi = 2;
else hi = 3;
if (qa[lo]>qa[hi]) {
if (qa[lo^1]>qa[hi]) {
hi = lo; lo ^= 1;
}
else {
hi ^= lo; lo ^= hi; hi ^= lo;
}
}
else {
if (qa[hi^1]>qa[lo]) lo = hi^1;
}
all = (qa[0]+qa[1]+qa[2]+qa[3])*0.5;
two = (qa[hi]+qa[lo])*SQRTHALF;
big = qa[hi];
if (all>two) {
if (all>big) {/*all*/
{int i; for (i=0; i<4; i++) pa[i] = sgn(neg[i], 0.5);}
cycle(ka,par);
}
else {/*big*/ pa[hi] = sgn(neg[hi],1.0);}
} else {
if (two>big) { /*two*/
pa[hi] = sgn(neg[hi],SQRTHALF);
pa[lo] = sgn(neg[lo], SQRTHALF);
if (lo>hi) {
hi ^= lo; lo ^= hi; hi ^= lo;
}
if (hi==W) {
hi = "\001\002\000"[lo];
lo = 3-hi-lo;
}
swap(ka,hi,lo);
}
else {/*big*/
pa[hi] = sgn(neg[hi],1.0);
}
}
p.x = -pa[0]; p.y = -pa[1]; p.z = -pa[2]; p.w = pa[3];
}
k->x = ka[X]; k->y = ka[Y]; k->z = ka[Z];
return (p);
}
}
void osg::Matrixf::decompose(osg::Vec3f& t,
osg::Quat& r,
osg::Vec3f& s,
osg::Quat& so) const
{
Vec3d temp_trans;
Vec3d temp_scale;
decompose(temp_trans, r, temp_scale, so);
t = temp_trans;
s = temp_scale;
}
void osg::Matrixf::decompose(osg::Vec3d& t,
osg::Quat& r,
osg::Vec3d& s,
osg::Quat& so) const
{
MatrixDecomposition::_affineParts parts;
MatrixDecomposition::_HMatrix hmatrix;
// Transpose copy of LTW
for ( int i =0; i<4; i++)
{
for ( int j=0; j<4; j++)
{
hmatrix[i][j] = (*this)(j,i);
}
}
MatrixDecomposition::decompAffine(hmatrix, &parts);
double mul = 1.0;
if (parts.t[MatrixDecomposition::W] != 0.0)
mul = 1.0 / parts.t[MatrixDecomposition::W];
t[0] = parts.t[MatrixDecomposition::X] * mul;
t[1] = parts.t[MatrixDecomposition::Y] * mul;
t[2] = parts.t[MatrixDecomposition::Z] * mul;
r.set(parts.q.x, parts.q.y, parts.q.z, parts.q.w);
mul = 1.0;
if (parts.k.w != 0.0)
mul = 1.0 / parts.k.w;
// mul be sign of determinant to support negative scales.
mul *= parts.f;
s[0] = parts.k.x * mul;
s[1] = parts.k.y * mul;
s[2] = parts.k.z * mul;
so.set(parts.u.x, parts.u.y, parts.u.z, parts.u.w);
}
void osg::Matrixd::decompose(osg::Vec3f& t,
osg::Quat& r,
osg::Vec3f& s,
osg::Quat& so) const
{
Vec3d temp_trans;
Vec3d temp_scale;
decompose(temp_trans, r, temp_scale, so);
t = temp_trans;
s = temp_scale;
}
void osg::Matrixd::decompose(osg::Vec3d& t,
osg::Quat& r,
osg::Vec3d& s,
osg::Quat& so) const
{
MatrixDecomposition::_affineParts parts;
MatrixDecomposition::_HMatrix hmatrix;
// Transpose copy of LTW
for ( int i =0; i<4; i++)
{
for ( int j=0; j<4; j++)
{
hmatrix[i][j] = (*this)(j,i);
}
}
MatrixDecomposition::decompAffine(hmatrix, &parts);
double mul = 1.0;
if (parts.t[MatrixDecomposition::W] != 0.0)
mul = 1.0 / parts.t[MatrixDecomposition::W];
t[0] = parts.t[MatrixDecomposition::X] * mul;
t[1] = parts.t[MatrixDecomposition::Y] * mul;
t[2] = parts.t[MatrixDecomposition::Z] * mul;
r.set(parts.q.x, parts.q.y, parts.q.z, parts.q.w);
mul = 1.0;
if (parts.k.w != 0.0)
mul = 1.0 / parts.k.w;
// mul be sign of determinant to support negative scales.
mul *= parts.f;
s[0] = parts.k.x * mul;
s[1] = parts.k.y * mul;
s[2] = parts.k.z * mul;
so.set(parts.u.x, parts.u.y, parts.u.z, parts.u.w);
}