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- /**** Decompose.c ****/
- /* Ken Shoemake, 1993 */
- #include <math.h>
- #include "Decompose.h"
-
- /******* Matrix Preliminaries *******/
-
- /** 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)
-
- /** 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]);}
-
- /** 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]);}
-
- /** Assign nxn matrix C the element-wise combination of A and B using "op" **/
- #define mat_binop(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]);}
-
- /** 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];
- }
-
- /** Return dot product of length 3 vectors va and vb **/
- float vdot(float *va, float *vb)
- {
- return (va[0]*vb[0] + va[1]*vb[1] + va[2]*vb[2]);
- }
-
- /** Set v to cross product of length 3 vectors va and vb **/
- void vcross(float *va, float *vb, float *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];
- }
-
- /** 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]);
- }
-
- /******* Quaternion Preliminaries *******/
-
- /* Construct a (possibly non-unit) quaternion from real components. */
- Quat Qt_(float x, float y, float z, float w)
- {
- Quat qq;
- qq.x = x; qq.y = y; qq.z = z; qq.w = w;
- 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);
- }
-
- /* 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 product of quaternion q by scalar w. */
- Quat Qt_Scale(Quat q, float 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);
- }
-
- /* 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 Qt_FromMatrix(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;
- register 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);
- }
- /******* Decomp Auxiliaries *******/
-
- static HMatrix mat_id = {{1,0,0,0},{0,1,0,0},{0,0,1,0},{0,0,0,1}};
-
- /** Compute either the 1 or infinity norm of M, depending on tpose **/
- float mat_norm(HMatrix M, int tpose)
- {
- int i;
- float 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;
- }
-
- float norm_inf(HMatrix M) {mat_norm(M, 0);}
- float norm_one(HMatrix M) {mat_norm(M, 1);}
-
- /** Return index of column of M containing maximum abs entry, or -1 if M=0 **/
- int find_max_col(HMatrix M)
- {
- float 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(float *v, float *u)
- {
- float 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, float *u)
- {
- int i, j;
- for (i=0; i<3; i++) {
- float 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, float *u)
- {
- int i, j;
- for (i=0; i<3; i++) {
- float 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)
- {
- float 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)
- {
- float v1[3], v2[3];
- float w, x, y, z, c, s, d;
- int i, j, 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);
- }
-
-
- /******* 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.
- */
- float polar_decomp(HMatrix M, HMatrix Q, HMatrix S)
- {
- #define TOL 1.0e-6
- HMatrix Mk, MadjTk, Ek;
- float det, M_one, M_inf, MadjT_one, MadjT_inf, E_one, gamma, t1, t2, 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);
- mat_copy(Ek,=,Mk,3);
- mat_binop(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);
- }
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- /******* 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 spect_decomp(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--) {
- float 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 SQRTHALF (0.7071067811865475244)
- #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;
- float 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 neg[3], win;
- double mag[3], c, s, t;
- 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};
- 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;
- for (i=0; i<3; i++) if (neg[i] = (mag[i]<0.0)) 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 {
- float qa[4], pa[4];
- unsigned lo, hi, neg[4], par = 0;
- 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;
- if (neg[i] = (qa[i]<0.0)) 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);
- }
-
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- /******* 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 decomp_affine(HMatrix A, AffineParts *parts)
- {
- HMatrix Q, S, U;
- Quat p;
- float det;
- parts->t = Qt_(A[X][W], A[Y][W], A[Z][W], 0);
- det = polar_decomp(A, Q, S);
- if (det<0.0) {
- mat_copy(Q,=,-Q,3);
- parts->f = -1;
- } else parts->f = 1;
- parts->q = Qt_FromMatrix(Q);
- parts->k = spect_decomp(S, U);
- parts->u = Qt_FromMatrix(U);
- p = snuggle(parts->u, &parts->k);
- parts->u = Qt_Mul(parts->u, p);
- }
-
- /******* Invert Affine Decomposition *******/
-
- /* Compute inverse of affine decomposition.
- */
- void invert_affine(AffineParts *parts, AffineParts *inverse)
- {
- Quat t, p;
- inverse->f = parts->f;
- inverse->q = Qt_Conj(parts->q);
- inverse->u = Qt_Mul(parts->q, parts->u);
- inverse->k.x = (parts->k.x==0.0) ? 0.0 : 1.0/parts->k.x;
- inverse->k.y = (parts->k.y==0.0) ? 0.0 : 1.0/parts->k.y;
- inverse->k.z = (parts->k.z==0.0) ? 0.0 : 1.0/parts->k.z;
- inverse->k.w = parts->k.w;
- t = Qt_(-parts->t.x, -parts->t.y, -parts->t.z, 0);
- t = Qt_Mul(Qt_Conj(inverse->u), Qt_Mul(t, inverse->u));
- t = Qt_(inverse->k.x*t.x, inverse->k.y*t.y, inverse->k.z*t.z, 0);
- p = Qt_Mul(inverse->q, inverse->u);
- t = Qt_Mul(p, Qt_Mul(t, Qt_Conj(p)));
- inverse->t = (inverse->f>0.0) ? t : Qt_(-t.x, -t.y, -t.z, 0);
- }
-