conjugate_frame_fields.cpp 20 KB

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  1. // This file is part of libigl, a simple c++ geometry processing library.
  2. //
  3. // Copyright (C) 2014 Olga Diamanti <olga.diam@gmail.com>
  4. //
  5. // This Source Code Form is subject to the terms of the Mozilla Public License
  6. // v. 2.0. If a copy of the MPL was not distributed with this file, You can
  7. // obtain one at http://mozilla.org/MPL/2.0/.
  8. #include <igl/conjugate_frame_fields.h>
  9. #include <igl/speye.h>
  10. #include <igl/slice.h>
  11. #include <igl/polyroots.h>
  12. #include <Eigen/Sparse>
  13. #include <iostream>
  14. namespace igl {
  15. template <typename DerivedV, typename DerivedF, typename DerivedO>
  16. class ConjugateFFSolver
  17. {
  18. public:
  19. IGL_INLINE ConjugateFFSolver(const ConjugateFFSolverData<DerivedV, DerivedF> &_data,
  20. int _maxIter = 50,
  21. const typename DerivedV::Scalar _lambdaOrtho = .1,
  22. const typename DerivedV::Scalar _lambdaInit = 100,
  23. const typename DerivedV::Scalar _lambdaMultFactor = 1.01,
  24. bool _doHardConstraints = true);
  25. IGL_INLINE typename DerivedV::Scalar solve(const Eigen::VectorXi &isConstrained,
  26. const Eigen::PlainObjectBase<DerivedO> &initialSolution,
  27. Eigen::PlainObjectBase<DerivedO> &output);
  28. private:
  29. const ConjugateFFSolverData<DerivedV, DerivedF> &data;
  30. //polyVF data
  31. Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> Acoeff, Bcoeff;
  32. Eigen::Matrix<typename DerivedV::Scalar, Eigen::Dynamic, 2> pvU, pvV;
  33. typename DerivedV::Scalar lambda;
  34. //parameters
  35. typename DerivedV::Scalar lambdaOrtho;
  36. typename DerivedV::Scalar lambdaInit,lambdaMultFactor;
  37. int maxIter;
  38. bool doHardConstraints;
  39. IGL_INLINE void localStep();
  40. IGL_INLINE void getPolyCoeffsForLocalSolve(const Eigen::Matrix<typename DerivedV::Scalar, 4, 1> &s,
  41. const Eigen::Matrix<typename DerivedV::Scalar, 4, 1> &z,
  42. Eigen::Matrix<typename DerivedV::Scalar, Eigen::Dynamic, 1> &polyCoeff);
  43. IGL_INLINE void globalStep(const Eigen::Matrix<int, Eigen::Dynamic, 1> &isConstrained,
  44. const Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> &Ak,
  45. const Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> &Bk);
  46. IGL_INLINE void minQuadWithKnownMini(const Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > &Q,
  47. const Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > &f,
  48. const Eigen::VectorXi isConstrained,
  49. const Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> &xknown,
  50. Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> &x);
  51. IGL_INLINE void setFieldFromCoefficients();
  52. IGL_INLINE void setCoefficientsFromField();
  53. };
  54. }
  55. //Implementation
  56. /***************************** Solver ***********************************/
  57. template <typename DerivedV, typename DerivedF, typename DerivedO>
  58. IGL_INLINE igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO>::
  59. ConjugateFFSolver(const ConjugateFFSolverData<DerivedV, DerivedF> &_data,
  60. int _maxIter,
  61. const typename DerivedV::Scalar _lambdaOrtho,
  62. const typename DerivedV::Scalar _lambdaInit,
  63. const typename DerivedV::Scalar _lambdaMultFactor,
  64. bool _doHardConstraints):
  65. data(_data),
  66. lambdaOrtho(_lambdaOrtho),
  67. lambdaInit(_lambdaInit),
  68. maxIter(_maxIter),
  69. lambdaMultFactor(_lambdaMultFactor),
  70. doHardConstraints(_doHardConstraints)
  71. {
  72. Acoeff.resize(data.numF,1);
  73. Bcoeff.resize(data.numF,1);
  74. pvU.setZero(data.numF, 2);
  75. pvV.setZero(data.numF, 2);
  76. };
  77. template<typename DerivedV, typename DerivedF, typename DerivedO>
  78. IGL_INLINE void igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO>::
  79. getPolyCoeffsForLocalSolve(const Eigen::Matrix<typename DerivedV::Scalar, 4, 1> &s,
  80. const Eigen::Matrix<typename DerivedV::Scalar, 4, 1> &z,
  81. Eigen::Matrix<typename DerivedV::Scalar, Eigen::Dynamic, 1> &polyCoeff)
  82. {
  83. typename DerivedV::Scalar s0 = s(0);
  84. typename DerivedV::Scalar s1 = s(1);
  85. typename DerivedV::Scalar s2 = s(2);
  86. typename DerivedV::Scalar s3 = s(3);
  87. typename DerivedV::Scalar z0 = z(0);
  88. typename DerivedV::Scalar z1 = z(1);
  89. typename DerivedV::Scalar z2 = z(2);
  90. typename DerivedV::Scalar z3 = z(3);
  91. polyCoeff.resize(7,1);
  92. polyCoeff(0) = s0*s0* s1*s1* s2*s2* s3* z3*z3 + s0*s0* s1*s1* s2* s3*s3* z2*z2 + s0*s0* s1* s2*s2* s3*s3* z1*z1 + s0* s1*s1* s2*s2* s3*s3* z0*z0 ;
  93. polyCoeff(1) = 2* s0*s0* s1*s1* s2* s3* z2*z2 + 2* s0*s0* s1*s1* s2* s3* z3*z3 + 2* s0*s0* s1* s2*s2* s3* z1*z1 + 2* s0*s0* s1* s2*s2* s3* z3*z3 + 2* s0*s0* s1* s2* s3*s3* z1*z1 + 2* s0*s0* s1* s2* s3*s3* z2*z2 + 2* s0* s1*s1* s2*s2* s3* z0*z0 + 2* s0* s1*s1* s2*s2* s3* z3*z3 + 2* s0* s1*s1* s2* s3*s3* z0*z0 + 2* s0* s1*s1* s2* s3*s3* z2*z2 + 2* s0* s1* s2*s2* s3*s3* z0*z0 + 2* s0* s1* s2*s2* s3*s3* z1*z1 ;
  94. polyCoeff(2) = s0*s0* s1*s1* s2* z2*z2 + s0*s0* s1*s1* s3* z3*z3 + s0*s0* s1* s2*s2* z1*z1 + 4* s0*s0* s1* s2* s3* z1*z1 + 4* s0*s0* s1* s2* s3* z2*z2 + 4* s0*s0* s1* s2* s3* z3*z3 + s0*s0* s1* s3*s3* z1*z1 + s0*s0* s2*s2* s3* z3*z3 + s0*s0* s2* s3*s3* z2*z2 + s0* s1*s1* s2*s2* z0*z0 + 4* s0* s1*s1* s2* s3* z0*z0 + 4* s0* s1*s1* s2* s3* z2*z2 + 4* s0* s1*s1* s2* s3* z3*z3 + s0* s1*s1* s3*s3* z0*z0 + 4* s0* s1* s2*s2* s3* z0*z0 + 4* s0* s1* s2*s2* s3* z1*z1 + 4* s0* s1* s2*s2* s3* z3*z3 + 4* s0* s1* s2* s3*s3* z0*z0 + 4* s0* s1* s2* s3*s3* z1*z1 + 4* s0* s1* s2* s3*s3* z2*z2 + s0* s2*s2* s3*s3* z0*z0 + s1*s1* s2*s2* s3* z3*z3 + s1*s1* s2* s3*s3* z2*z2 + s1* s2*s2* s3*s3* z1*z1;
  95. polyCoeff(3) = 2* s0*s0* s1* s2* z1*z1 + 2* s0*s0* s1* s2* z2*z2 + 2* s0*s0* s1* s3* z1*z1 + 2* s0*s0* s1* s3* z3*z3 + 2* s0*s0* s2* s3* z2*z2 + 2* s0*s0* s2* s3* z3*z3 + 2* s0* s1*s1* s2* z0*z0 + 2* s0* s1*s1* s2* z2*z2 + 2* s0* s1*s1* s3* z0*z0 + 2* s0* s1*s1* s3* z3*z3 + 2* s0* s1* s2*s2* z0*z0 + 2* s0* s1* s2*s2* z1*z1 + 8* s0* s1* s2* s3* z0*z0 + 8* s0* s1* s2* s3* z1*z1 + 8* s0* s1* s2* s3* z2*z2 + 8* s0* s1* s2* s3* z3*z3 + 2* s0* s1* s3*s3* z0*z0 + 2* s0* s1* s3*s3* z1*z1 + 2* s0* s2*s2* s3* z0*z0 + 2* s0* s2*s2* s3* z3*z3 + 2* s0* s2* s3*s3* z0*z0 + 2* s0* s2* s3*s3* z2*z2 + 2* s1*s1* s2* s3* z2*z2 + 2* s1*s1* s2* s3* z3*z3 + 2* s1* s2*s2* s3* z1*z1 + 2* s1* s2*s2* s3* z3*z3 + 2* s1* s2* s3*s3* z1*z1 + 2* s1* s2* s3*s3* z2*z2 ;
  96. polyCoeff(4) = s0*s0* s1* z1*z1 + s0*s0* s2* z2*z2 + s0*s0* s3* z3*z3 + s0* s1*s1* z0*z0 + 4* s0* s1* s2* z0*z0 + 4* s0* s1* s2* z1*z1 + 4* s0* s1* s2* z2*z2 + 4* s0* s1* s3* z0*z0 + 4* s0* s1* s3* z1*z1 + 4* s0* s1* s3* z3*z3 + s0* s2*s2* z0*z0 + 4* s0* s2* s3* z0*z0 + 4* s0* s2* s3* z2*z2 + 4* s0* s2* s3* z3*z3 + s0* s3*s3* z0*z0 + s1*s1* s2* z2*z2 + s1*s1* s3* z3*z3 + s1* s2*s2* z1*z1 + 4* s1* s2* s3* z1*z1 + 4* s1* s2* s3* z2*z2 + 4* s1* s2* s3* z3*z3 + s1* s3*s3* z1*z1 + s2*s2* s3* z3*z3 + s2* s3*s3* z2*z2;
  97. polyCoeff(5) = 2* s0* s1* z0*z0 + 2* s0* s1* z1*z1 + 2* s0* s2* z0*z0 + 2* s0* s2* z2*z2 + 2* s0* s3* z0*z0 + 2* s0* s3* z3*z3 + 2* s1* s2* z1*z1 + 2* s1* s2* z2*z2 + 2* s1* s3* z1*z1 + 2* s1* s3* z3*z3 + 2* s2* s3* z2*z2 + 2* s2* s3* z3*z3 ;
  98. polyCoeff(6) = s0* z0*z0 + s1* z1*z1 + s2* z2*z2 + s3* z3*z3;
  99. }
  100. template<typename DerivedV, typename DerivedF, typename DerivedO>
  101. IGL_INLINE void igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO>::
  102. localStep()
  103. {
  104. for (int j =0; j<data.numF; ++j)
  105. {
  106. Eigen::Matrix<typename DerivedV::Scalar, 4, 1> xproj; xproj << pvU.row(j).transpose(),pvV.row(j).transpose();
  107. Eigen::Matrix<typename DerivedV::Scalar, 4, 1> z = data.UH[j].transpose()*xproj;
  108. Eigen::Matrix<typename DerivedV::Scalar, 4, 1> x;
  109. Eigen::Matrix<typename DerivedV::Scalar, Eigen::Dynamic, 1> polyCoeff;
  110. getPolyCoeffsForLocalSolve(data.s[j], z, polyCoeff);
  111. Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> roots;
  112. igl::polyRoots<typename DerivedV::Scalar, typename DerivedV::Scalar> (polyCoeff, roots );
  113. // find closest real root to xproj
  114. typename DerivedV::Scalar minDist = 1e10;
  115. for (int i =0; i< 6; ++i)
  116. {
  117. if (fabs(imag(roots[i]))>1e-10)
  118. continue;
  119. Eigen::Matrix<typename DerivedV::Scalar, 4, 4> D = ((Eigen::Matrix<typename DerivedV::Scalar, 4, 1>::Ones()+real(roots(i))*data.s[j]).array().inverse()).matrix().asDiagonal();
  120. Eigen::Matrix<typename DerivedV::Scalar, 4, 1> candidate = data.UH[j]*D*z;
  121. typename DerivedV::Scalar dist = (candidate-xproj).norm();
  122. if (dist<minDist)
  123. {
  124. minDist = dist;
  125. x = candidate;
  126. }
  127. }
  128. pvU.row(j) << x(0),x(1);
  129. pvV.row(j) << x(2),x(3);
  130. }
  131. }
  132. template<typename DerivedV, typename DerivedF, typename DerivedO>
  133. IGL_INLINE void igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO>::
  134. setCoefficientsFromField()
  135. {
  136. for (int i = 0; i <data.numF; ++i)
  137. {
  138. std::complex<typename DerivedV::Scalar> u(pvU(i,0),pvU(i,1));
  139. std::complex<typename DerivedV::Scalar> v(pvV(i,0),pvV(i,1));
  140. Acoeff(i) = u*u+v*v;
  141. Bcoeff(i) = u*u*v*v;
  142. }
  143. }
  144. template<typename DerivedV, typename DerivedF, typename DerivedO>
  145. IGL_INLINE void igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO>::
  146. globalStep(const Eigen::Matrix<int, Eigen::Dynamic, 1> &isConstrained,
  147. const Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> &Ak,
  148. const Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> &Bk)
  149. {
  150. setCoefficientsFromField();
  151. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > I;
  152. igl::speye(data.numF, data.numF, I);
  153. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > QA = data.DDA+lambda*data.planarityWeight+lambdaOrtho*I;
  154. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > fA = (-2*lambda*data.planarityWeight*Acoeff).sparseView();
  155. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > QB = data.DDB+lambda*data.planarityWeight;
  156. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > fB = (-2*lambda*data.planarityWeight*Bcoeff).sparseView();
  157. if(doHardConstraints)
  158. {
  159. minQuadWithKnownMini(QA, fA, isConstrained, Ak, Acoeff);
  160. minQuadWithKnownMini(QB, fB, isConstrained, Bk, Bcoeff);
  161. }
  162. else
  163. {
  164. Eigen::Matrix<int, Eigen::Dynamic, 1>isknown_; isknown_.setZero(data.numF,1);
  165. Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> xknown_; xknown_.setZero(0,1);
  166. minQuadWithKnownMini(QA, fA, isknown_, xknown_, Acoeff);
  167. minQuadWithKnownMini(QB, fB, isknown_, xknown_, Bcoeff);
  168. }
  169. setFieldFromCoefficients();
  170. }
  171. template<typename DerivedV, typename DerivedF, typename DerivedO>
  172. IGL_INLINE void igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO>::
  173. setFieldFromCoefficients()
  174. {
  175. for (int i = 0; i <data.numF; ++i)
  176. {
  177. // poly coefficients: 1, 0, -Acoeff, 0, Bcoeff
  178. // matlab code from roots (given there are no trailing zeros in the polynomial coefficients)
  179. Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> polyCoeff(5,1);
  180. polyCoeff<<1., 0., -Acoeff(i), 0., Bcoeff(i);
  181. Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> roots;
  182. polyRoots<std::complex<typename DerivedV::Scalar>>(polyCoeff,roots);
  183. std::complex<typename DerivedV::Scalar> u = roots[0];
  184. int maxi = -1;
  185. float maxd = -1;
  186. for (int k =1; k<4; ++k)
  187. {
  188. float dist = abs(roots[k]+u);
  189. if (dist>maxd)
  190. {
  191. maxd = dist;
  192. maxi = k;
  193. }
  194. }
  195. std::complex<typename DerivedV::Scalar> v = roots[maxi];
  196. pvU(i,0) = real(u); pvU(i,1) = imag(u);
  197. pvV(i,0) = real(v); pvV(i,1) = imag(v);
  198. }
  199. }
  200. template<typename DerivedV, typename DerivedF, typename DerivedO>
  201. IGL_INLINE void igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO>::
  202. minQuadWithKnownMini(const Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > &Q,
  203. const Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > &f,
  204. const Eigen::VectorXi isConstrained,
  205. const Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> &xknown,
  206. Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> &x)
  207. {
  208. int N = Q.rows();
  209. int nc = xknown.rows();
  210. Eigen::VectorXi known; known.setZero(nc,1);
  211. Eigen::VectorXi unknown; unknown.setZero(N-nc,1);
  212. int indk = 0, indu = 0;
  213. for (int i = 0; i<N; ++i)
  214. if (isConstrained[i])
  215. {
  216. known[indk] = i;
  217. indk++;
  218. }
  219. else
  220. {
  221. unknown[indu] = i;
  222. indu++;
  223. }
  224. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar>> Quu, Quk;
  225. igl::slice(Q,unknown, unknown, Quu);
  226. igl::slice(Q,unknown, known, Quk);
  227. std::vector<typename Eigen::Triplet<std::complex<typename DerivedV::Scalar> > > tripletList;
  228. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > fu(N-nc,1);
  229. igl::slice(f,unknown, Eigen::VectorXi::Zero(1,1), fu);
  230. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar> > rhs = (Quk*xknown).sparseView()+.5*fu;
  231. Eigen::SparseLU< Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar>>> solver;
  232. solver.compute(-Quu);
  233. if(solver.info()!=Eigen::Success)
  234. {
  235. std::cerr<<"Decomposition failed!"<<std::endl;
  236. return;
  237. }
  238. Eigen::SparseMatrix<std::complex<typename DerivedV::Scalar>> b = solver.solve(rhs);
  239. if(solver.info()!=Eigen::Success)
  240. {
  241. std::cerr<<"Solving failed!"<<std::endl;
  242. return;
  243. }
  244. indk = 0, indu = 0;
  245. x.setZero(N,1);
  246. for (int i = 0; i<N; ++i)
  247. if (isConstrained[i])
  248. x[i] = xknown[indk++];
  249. else
  250. x[i] = b.coeff(indu++,0);
  251. }
  252. template<typename DerivedV, typename DerivedF, typename DerivedO>
  253. IGL_INLINE typename DerivedV::Scalar igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO>::
  254. solve(const Eigen::VectorXi &isConstrained,
  255. const Eigen::PlainObjectBase<DerivedO> &initialSolution,
  256. Eigen::PlainObjectBase<DerivedO> &output)
  257. {
  258. int numConstrained = isConstrained.sum();
  259. // coefficient values
  260. Eigen::Matrix<std::complex<typename DerivedV::Scalar>, Eigen::Dynamic, 1> Ak, Bk;
  261. pvU.resize(data.numF,2);
  262. pvV.resize(data.numF,2);
  263. for (int fi = 0; fi <data.numF; ++fi)
  264. {
  265. const Eigen::Matrix<typename DerivedV::Scalar, 1, 3> &b1 = data.B1.row(fi);
  266. const Eigen::Matrix<typename DerivedV::Scalar, 1, 3> &b2 = data.B2.row(fi);
  267. const Eigen::Matrix<typename DerivedV::Scalar, 1, 3> &u3 = initialSolution.block(fi,0,1,3);
  268. const Eigen::Matrix<typename DerivedV::Scalar, 1, 3> &v3 = initialSolution.block(fi,3,1,3);
  269. pvU.row(fi)<< u3.dot(b1), u3.dot(b2);
  270. pvV.row(fi)<< v3.dot(b1), v3.dot(b2);
  271. }
  272. setCoefficientsFromField();
  273. Ak.resize(numConstrained,1);
  274. Bk.resize(numConstrained,1);
  275. int ind = 0;
  276. for (int i = 0; i <data.numF; ++i)
  277. {
  278. if(isConstrained[i])
  279. {
  280. Ak(ind) = Acoeff[i];
  281. Bk(ind) = Bcoeff[i];
  282. ind ++;
  283. }
  284. }
  285. typename DerivedV::Scalar smoothnessValue;
  286. Eigen::Matrix<typename DerivedV::Scalar, Eigen::Dynamic, 1> conjValues;
  287. typename DerivedV::Scalar meanConj;
  288. typename DerivedV::Scalar maxConj;
  289. data.evaluateConjugacy(pvU, pvV, conjValues);
  290. meanConj = conjValues.cwiseAbs().mean();
  291. maxConj = conjValues.cwiseAbs().maxCoeff();
  292. printf("Initial max non-conjugacy: %.5g\n",maxConj);
  293. smoothnessValue = (Acoeff.adjoint()*data.DDA*Acoeff + Bcoeff.adjoint()*data.DDB*Bcoeff).real()[0];
  294. printf("\n\nInitial smoothness: %.5g\n",smoothnessValue);
  295. lambda = lambdaInit;
  296. bool doit = false;
  297. for (int iter = 0; iter<maxIter; ++iter)
  298. {
  299. printf("\n\n--- Iteration %d ---\n",iter);
  300. typename DerivedV::Scalar oldMeanConj = meanConj;
  301. localStep();
  302. globalStep(isConstrained, Ak, Bk);
  303. smoothnessValue = (Acoeff.adjoint()*data.DDA*Acoeff + Bcoeff.adjoint()*data.DDB*Bcoeff).real()[0];
  304. printf("Smoothness: %.5g\n",smoothnessValue);
  305. data.evaluateConjugacy(pvU, pvV, conjValues);
  306. meanConj = conjValues.cwiseAbs().mean();
  307. maxConj = conjValues.cwiseAbs().maxCoeff();
  308. printf("Mean/Max non-conjugacy: %.5g, %.5g\n",meanConj,maxConj);
  309. typename DerivedV::Scalar diffMeanConj = fabs(oldMeanConj-meanConj);
  310. if (diffMeanConj<1e-4)
  311. doit = true;
  312. if (doit)
  313. lambda = lambda*lambdaMultFactor;
  314. printf(" %d %.5g %.5g\n",iter, smoothnessValue,maxConj);
  315. }
  316. output.setZero(data.numF,6);
  317. for (int fi=0; fi<data.numF; ++fi)
  318. {
  319. const Eigen::Matrix<typename DerivedV::Scalar, 1, 3> &b1 = data.B1.row(fi);
  320. const Eigen::Matrix<typename DerivedV::Scalar, 1, 3> &b2 = data.B2.row(fi);
  321. output.block(fi,0, 1, 3) = pvU(fi,0)*b1 + pvU(fi,1)*b2;
  322. output.block(fi,3, 1, 3) = pvV(fi,0)*b1 + pvV(fi,1)*b2;
  323. }
  324. return lambda;
  325. }
  326. template <typename DerivedV, typename DerivedF, typename DerivedO>
  327. IGL_INLINE void igl::conjugate_frame_fields(const Eigen::PlainObjectBase<DerivedV> &V,
  328. const Eigen::PlainObjectBase<DerivedF> &F,
  329. const Eigen::VectorXi &isConstrained,
  330. const Eigen::PlainObjectBase<DerivedO> &initialSolution,
  331. Eigen::PlainObjectBase<DerivedO> &output,
  332. int maxIter,
  333. const typename DerivedV::Scalar lambdaOrtho,
  334. const typename DerivedV::Scalar lambdaInit,
  335. const typename DerivedV::Scalar lambdaMultFactor,
  336. bool doHardConstraints)
  337. {
  338. igl::ConjugateFFSolverData<DerivedV, DerivedF> csdata(V, F);
  339. igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO> cs(csdata, maxIter, lambdaOrtho, lambdaInit, lambdaMultFactor, doHardConstraints);
  340. cs.solve(isConstrained, initialSolution, output);
  341. }
  342. template <typename DerivedV, typename DerivedF, typename DerivedO>
  343. IGL_INLINE typename DerivedV::Scalar igl::conjugate_frame_fields(const igl::ConjugateFFSolverData<DerivedV, DerivedF> &csdata,
  344. const Eigen::VectorXi &isConstrained,
  345. const Eigen::PlainObjectBase<DerivedO> &initialSolution,
  346. Eigen::PlainObjectBase<DerivedO> &output,
  347. int maxIter,
  348. const typename DerivedV::Scalar lambdaOrtho,
  349. const typename DerivedV::Scalar lambdaInit,
  350. const typename DerivedV::Scalar lambdaMultFactor,
  351. bool doHardConstraints)
  352. {
  353. igl::ConjugateFFSolver<DerivedV, DerivedF, DerivedO> cs(csdata, maxIter, lambdaOrtho, lambdaInit, lambdaMultFactor, doHardConstraints);
  354. typename DerivedV::Scalar lambdaOut = cs.solve(isConstrained, initialSolution, output);
  355. return lambdaOut;
  356. }
  357. #ifdef IGL_STATIC_LIBRARY
  358. // Explicit template specialization
  359. template Eigen::Matrix<double, -1, -1, 0, -1, -1>::Scalar igl::conjugate_frame_fields<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<int, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1> >(igl::ConjugateFFSolverData<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<int, -1, -1, 0, -1, -1> > const&, Eigen::Matrix<int, -1, 1, 0, -1, 1> const&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >&, int, Eigen::Matrix<double, -1, -1, 0, -1, -1>::Scalar, Eigen::Matrix<double, -1, -1, 0, -1, -1>::Scalar, Eigen::Matrix<double, -1, -1, 0, -1, -1>::Scalar, bool);
  360. #endif