/* Copyright (C) 2018 Wildfire Games. * This file is part of 0 A.D. * * 0 A.D. is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 2 of the License, or * (at your option) any later version. * * 0 A.D. 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 * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with 0 A.D. If not, see . */ #include "precompiled.h" #ifdef _MSC_VER # pragma warning(disable: 4244 4305 4127 4701) #endif /**** Decompose.c ****/ /* Ken Shoemake, 1993 */ #include #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) {for (int i = 0; i < n; ++i) for (int 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) {for (int i = 0; i < n; ++i) for (int 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) {for (int i = 0; i < n; ++i) for (int 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; 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 (maxmax) {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 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, g1, g2; 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 (int i = 0; i < 3; i++) for (int 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 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}; 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 (int sweep = 20; sweep > 0; --sweep) { float sm = fabs(OffD[X]) + fabs(OffD[Y]) + fabs(OffD[Z]); if (sm == 0.0) break; for (int 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 (int 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 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], t; static Quat qxtoz = {.0f, static_cast(SQRTHALF), .0f, static_cast(SQRTHALF)}; static Quat qytoz = {static_cast(SQRTHALF), .0f, .0f, static_cast(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 (int i = 0; i < 3; ++i) if ((neg[i] = (mag[i] < 0.0)) != 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 (int i = 0; i < 4; ++i) { pa[i] = 0.0; if ((neg[i] = (qa[i]<0.0)) != 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); } /******* 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); }