cheb_utils.hpp 51 KB

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  1. #ifndef _SCTL_CHEB_UTILS_HPP_
  2. #define _SCTL_CHEB_UTILS_HPP_
  3. //#include SCTL_INCLUDE(kernel.hpp)
  4. #include SCTL_INCLUDE(matrix.hpp)
  5. #include SCTL_INCLUDE(vector.hpp)
  6. #include SCTL_INCLUDE(common.hpp)
  7. #include SCTL_INCLUDE(legendre_rule.hpp)
  8. #include <type_traits>
  9. #include <functional>
  10. namespace SCTL_NAMESPACE {
  11. template <class ValueType, class Derived> class BasisInterface {
  12. public:
  13. template <Integer DIM> static void Nodes(Integer order, Vector<ValueType>& nodes) {
  14. if (DIM == 1) {
  15. Derived::Nodes1D(order, nodes);
  16. return;
  17. }
  18. Vector<ValueType> nodes1d;
  19. Derived::Nodes1D(order, nodes1d);
  20. Integer order_DIM = pow<Integer>(order, DIM);
  21. if (nodes.Dim() != order_DIM * DIM) nodes.ReInit(order_DIM * DIM);
  22. StaticArray<Integer, DIM> idx;
  23. for (Integer i = 0; i < DIM; i++) idx[i] = 0;
  24. Integer itr = 0;
  25. for (Integer j = 0; j < order_DIM; j++) {
  26. for (Integer i = 0; i < DIM; i++) {
  27. if (idx[i] == order) idx[i] = 0;
  28. nodes[itr + i] = nodes1d[idx[i]];
  29. }
  30. itr += DIM;
  31. idx[0]++;
  32. for (Integer i = 1; i < DIM; i++) {
  33. if (idx[i - 1] == order) idx[i]++;
  34. }
  35. }
  36. }
  37. /**
  38. * \brief Computes approximation from function values at node points.
  39. * \param[in] fn_v Function values at node points (dof x order^DIM).
  40. * \param[out] coeff Coefficient values (dof x Ncoeff).
  41. */
  42. template <Integer DIM> static void Approx(Integer order, const Vector<ValueType>& fn_v, Vector<ValueType>& coeff) {
  43. Matrix<ValueType> Mp;
  44. { // Precompute
  45. static Vector<Matrix<ValueType>> precomp(1000);
  46. SCTL_ASSERT(order < precomp.Dim());
  47. if (precomp[order].Dim(0) * precomp[order].Dim(1) == 0) {
  48. #pragma omp critical(BASIS_APPROX)
  49. if (precomp[order].Dim(0) * precomp[order].Dim(1) == 0) {
  50. Vector<ValueType> x, p;
  51. Derived::Nodes1D(order, x);
  52. Derived::EvalBasis1D(order, x, p);
  53. Matrix<ValueType> Mp1(order, order, p.begin(), false);
  54. Mp1.pinv().Swap(precomp[order]);
  55. }
  56. }
  57. Mp.ReInit(precomp[order].Dim(0), precomp[order].Dim(1), precomp[order].begin(), false);
  58. }
  59. Integer order_DIM = pow<Integer>(order, DIM);
  60. Integer order_DIM_ = pow<Integer>(order, DIM - 1);
  61. Long dof = fn_v.Dim() / order_DIM;
  62. SCTL_ASSERT(fn_v.Dim() == dof * order_DIM);
  63. // Create work buffers
  64. Long buff_size = dof * order_DIM;
  65. Vector<ValueType> buff(2 * buff_size);
  66. Iterator<ValueType> buff1 = buff.begin() + buff_size * 0;
  67. Iterator<ValueType> buff2 = buff.begin() + buff_size * 1;
  68. Vector<ValueType> fn(order_DIM * dof, (Iterator<ValueType>)fn_v.begin(), false);
  69. for (Integer k = 0; k < DIM; k++) { // Apply Mp along k-dimension
  70. Matrix<ValueType> Mi(dof * order_DIM_, order, fn.begin(), false);
  71. Matrix<ValueType> Mo(dof * order_DIM_, order, buff2, false);
  72. Matrix<ValueType>::GEMM(Mo, Mi, Mp);
  73. Matrix<ValueType> Mo_t(order, dof * order_DIM_, buff1, false);
  74. for (Long i = 0; i < Mo.Dim(0); i++) {
  75. for (Long j = 0; j < Mo.Dim(1); j++) {
  76. Mo_t[j][i] = Mo[i][j];
  77. }
  78. }
  79. fn.ReInit(order_DIM * dof, buff1, false);
  80. }
  81. { // Rearrange and write to coeff
  82. Vector<ValueType> tensor(order_DIM * dof, buff1, false);
  83. tensor2coeff<DIM>(order, tensor, coeff);
  84. }
  85. }
  86. /**
  87. * \brief Evaluates values from input coefficients at points on a regular
  88. * grid defined by in_x, in_y, in_z the values in the input vector.
  89. * \param[in] coeff Coefficient values (dof x Ncoeff).
  90. * \param[out] out Values at node points (in_x[DIM-1].Dim() x ... x in_x[0].Dim() x dof).
  91. */
  92. template <Integer DIM> static void Eval(Integer order, const Vector<ValueType>& coeff, ConstIterator<Vector<ValueType>> in_x, Vector<ValueType>& out) {
  93. Integer Ncoeff = 1;
  94. for (Integer i = 0; i < DIM; i++) {
  95. Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  96. }
  97. Long dof = coeff.Dim() / Ncoeff;
  98. SCTL_ASSERT(coeff.Dim() == Ncoeff * dof);
  99. // Precomputation
  100. Long buff_size = dof;
  101. StaticArray<Matrix<ValueType>, DIM> Mp;
  102. for (Integer i = 0; i < DIM; i++) {
  103. Integer n = in_x[i].Dim();
  104. if (!n) return;
  105. Mp[i].ReInit(order, n);
  106. Vector<ValueType> p(order * n, Mp[i].begin(), false);
  107. Derived::EvalBasis1D(order, in_x[i], p);
  108. buff_size *= std::max(order, n);
  109. }
  110. // Create work buffers
  111. Vector<ValueType> buff(2 * buff_size);
  112. Iterator<ValueType> buff1 = buff.begin() + buff_size * 0;
  113. Iterator<ValueType> buff2 = buff.begin() + buff_size * 1;
  114. { // Rearrange coefficients into a tensor.
  115. Vector<ValueType> tensor(dof * pow<Integer>(order, DIM), buff1, false);
  116. coeff2tensor<DIM>(order, coeff, tensor);
  117. }
  118. { // ReInit out
  119. Long len = dof;
  120. for (Integer i = 0; i < DIM; i++) len *= in_x[i].Dim();
  121. if (out.Dim() != len) out.ReInit(len);
  122. }
  123. for (Integer k = 0; k < DIM; k++) { // Apply Mp along k-dimension
  124. Integer order_DIM = pow<Integer>(order, DIM - k - 1);
  125. for (Integer i = 0; i < k; i++) order_DIM *= in_x[i].Dim();
  126. Matrix<ValueType> Mi(dof * order_DIM, order, buff1, false);
  127. Matrix<ValueType> Mo(dof * order_DIM, in_x[k].Dim(), buff2, false);
  128. Matrix<ValueType>::GEMM(Mo, Mi, Mp[k]);
  129. Matrix<ValueType> Mo_t(in_x[k].Dim(), dof * order_DIM, buff1, false);
  130. if (k == DIM - 1) Mo_t.ReInit(in_x[k].Dim(), dof * order_DIM, out.begin(), false);
  131. for (Long i = 0; i < Mo.Dim(0); i++) {
  132. for (Long j = 0; j < Mo.Dim(1); j++) {
  133. Mo_t[j][i] = Mo[i][j];
  134. }
  135. }
  136. }
  137. }
  138. /**
  139. * \brief Returns the sum of the absolute value of coefficients of the
  140. * highest order terms as an estimate of truncation error.
  141. * \param[in] coeff Coefficient values (dof x Ncoeff).
  142. */
  143. template <Integer DIM> static ValueType TruncErr(Integer order, const Vector<ValueType>& coeff) {
  144. Integer Ncoeff = 1;
  145. { // Set Ncoeff
  146. for (Integer i = 0; i < DIM; i++) Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  147. }
  148. Long dof = coeff.Dim() / Ncoeff;
  149. SCTL_ASSERT(coeff.Dim() == Ncoeff * dof);
  150. ValueType err = 0;
  151. for (Long l = 0; l < dof; l++) { // TODO: optimize this
  152. Long offset0 = l * Ncoeff;
  153. Integer indx0 = 0;
  154. Integer indx1 = 0;
  155. StaticArray<Integer, DIM + 1> i0;
  156. for (Integer i = 0; i <= DIM; i++) i0[i] = 0;
  157. Integer sum = 0;
  158. while (1) {
  159. if (sum < order) {
  160. if (sum == order - 1) err += fabs<ValueType>(coeff[offset0 + indx0]);
  161. indx0++;
  162. }
  163. indx1++;
  164. sum++;
  165. i0[0]++;
  166. for (Integer j = 0; j < DIM && i0[j] == order; j++) {
  167. i0[j] = 0;
  168. i0[j + 1]++;
  169. sum = sum + 1 - order;
  170. }
  171. if (i0[DIM]) break;
  172. }
  173. }
  174. return err;
  175. }
  176. /**
  177. * \brief Compute gradient.
  178. * \param[in] coeff_in Input coefficients (dof x Ncoeff)
  179. * \param[out] coeff_out Output coefficients (dof x DIM x Ncoeff)
  180. */
  181. template <Integer DIM> static void Grad(Integer order, const Vector<ValueType>& coeff_in, Vector<ValueType>* coeff_out) {
  182. Integer Ncoeff = 1;
  183. for (Integer i = 0; i < DIM; i++) {
  184. Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  185. }
  186. Long dof = coeff_in.Dim() / Ncoeff;
  187. SCTL_ASSERT(coeff_in.Dim() == Ncoeff * dof);
  188. Matrix<ValueType> Mdiff;
  189. { // Precompute
  190. static Vector<Matrix<ValueType>> precomp(1000);
  191. SCTL_ASSERT(order < precomp.Dim());
  192. if (precomp[order].Dim(0) * precomp[order].Dim(1) == 0) {
  193. #pragma omp critical(BASIS_GRAD)
  194. if (precomp[order].Dim(0) * precomp[order].Dim(1) == 0) {
  195. Matrix<ValueType> M;
  196. diff_1d(order, &M);
  197. M.Swap(precomp[order]);
  198. }
  199. }
  200. Mdiff.ReInit(precomp[order].Dim(0), precomp[order].Dim(1), precomp[order].begin(), false);
  201. }
  202. // Create work buffers
  203. Long buff_size = dof * pow<Integer>(order, DIM);
  204. Vector<ValueType> buff((3 + DIM) * buff_size);
  205. Vector<ValueType> buff0(buff_size * 1, buff.begin() + buff_size * 0, false);
  206. Vector<ValueType> buff1(buff_size * 1, buff.begin() + buff_size * 1, false);
  207. Vector<ValueType> buff2(buff_size * 1, buff.begin() + buff_size * 2, false);
  208. Vector<ValueType> buff3(buff_size * DIM, buff.begin() + buff_size * 3, false);
  209. { // buff0 <-- coeff2tensor(coeff_in);
  210. coeff2tensor<DIM>(order, coeff_in, buff0);
  211. }
  212. for (Integer k = 0; k < DIM; k++) { // buff2 <-- Grad(buff0)
  213. Long N0 = pow<Integer>(order, k);
  214. Long N1 = order;
  215. Long N2 = pow<Integer>(order, DIM - k - 1);
  216. for (Long i3 = 0; i3 < dof; i3++) { // buff1 <-- transpose(buff0)
  217. for (Long i2 = 0; i2 < N2; i2++) {
  218. for (Long i1 = 0; i1 < N1; i1++) {
  219. for (Long i0 = 0; i0 < N0; i0++) {
  220. buff1[((i3 * N2 + i2) * N0 + i0) * N1 + i1] = buff0[((i3 * N2 + i2) * N1 + i1) * N0 + i0];
  221. }
  222. }
  223. }
  224. }
  225. { // buff2 <-- buff1 * Mdiff
  226. Matrix<ValueType> Mi(dof * N0 * N2, N1, buff1.begin(), false);
  227. Matrix<ValueType> Mo(dof * N0 * N2, N1, buff2.begin(), false);
  228. Matrix<ValueType>::GEMM(Mo, Mi, Mdiff);
  229. }
  230. for (Long i3 = 0; i3 < dof; i3++) { // buff3 <-- transpose(buff2)
  231. for (Long i2 = 0; i2 < N2; i2++) {
  232. for (Long i1 = 0; i1 < N1; i1++) {
  233. for (Long i0 = 0; i0 < N0; i0++) {
  234. buff3[(((i2 * N1 + i1) * N0 + i0) * dof + i3) * DIM + k] = buff2[((i3 * N2 + i2) * N0 + i0) * N1 + i1];
  235. }
  236. }
  237. }
  238. }
  239. }
  240. { // coeff_out <-- tensor2coeff(buff2);
  241. tensor2coeff<DIM>(order, buff3, *coeff_out);
  242. }
  243. }
  244. template <Integer DIM, Integer SUBDIM, class Kernel> static void Integ(Matrix<ValueType>& Mcoeff, Integer order, ConstIterator<ValueType> trg_, ValueType side, Integer src_face, const Kernel& ker, ValueType tol = -1, Integer Nq = 0) {
  245. if (!Nq) Nq = order;
  246. Integ_<DIM, SUBDIM>(Mcoeff, order, trg_, side, src_face, ker, Nq);
  247. if (tol < 0) tol = 1e-10; //machine_eps() * 256;
  248. ValueType err = tol + 1;
  249. Matrix<ValueType> Mtmp;
  250. while (err > tol) {
  251. err = 0;
  252. ValueType max_val = pow<SUBDIM>(side);
  253. Nq = std::max((Integer)(Nq * 1.26), Nq + 1);
  254. Integ_<DIM, SUBDIM>(Mtmp, order, trg_, side, src_face, ker, Nq);
  255. for (Integer i = 0; i < Mtmp.Dim(0) * Mtmp.Dim(1); i++) {
  256. err = std::max(err, fabs<ValueType>(Mtmp[0][i] - Mcoeff[0][i]));
  257. max_val = std::max(max_val, fabs<ValueType>(Mtmp[0][i]));
  258. }
  259. err /= max_val;
  260. Mcoeff = Mtmp;
  261. if (Nq>200) {
  262. SCTL_WARN("Failed to converge, error = "<<err);
  263. break;
  264. }
  265. }
  266. Mcoeff = Mcoeff.Transpose();
  267. }
  268. template <Integer DIM> static void tensor2coeff(Integer order, const Vector<ValueType>& tensor, Vector<ValueType>& coeff) {
  269. Integer Ncoeff = 1, Ntensor = pow<Integer>(order, DIM);
  270. for (Integer i = 0; i < DIM; i++) Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  271. Long dof = tensor.Dim() / Ntensor;
  272. SCTL_ASSERT(tensor.Dim() == Ntensor * dof);
  273. if (coeff.Dim() != Ncoeff * dof) coeff.ReInit(Ncoeff * dof);
  274. for (Long l = 0; l < dof; l++) { // TODO: optimize this
  275. Long offset0 = l * Ncoeff;
  276. Integer indx0 = 0;
  277. Integer indx1 = 0;
  278. StaticArray<Integer, DIM + 1> i0;
  279. for (Integer i = 0; i <= DIM; i++) i0[i] = 0;
  280. Integer sum = 0;
  281. while (1) {
  282. if (sum < order) {
  283. coeff[offset0 + indx0] = tensor[l + indx1 * dof];
  284. indx0++;
  285. }
  286. indx1++;
  287. sum++;
  288. i0[0]++;
  289. for (Integer j = 0; j < DIM && i0[j] == order; j++) {
  290. i0[j] = 0;
  291. i0[j + 1]++;
  292. sum = sum + 1 - order;
  293. }
  294. if (i0[DIM]) break;
  295. }
  296. }
  297. }
  298. template <Integer DIM> static void coeff2tensor(Integer order, const Vector<ValueType>& coeff, Vector<ValueType>& tensor) {
  299. Integer Ncoeff = 1, Ntensor = pow<Integer>(order, DIM);
  300. for (Integer i = 0; i < DIM; i++) Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  301. Long dof = coeff.Dim() / Ncoeff;
  302. SCTL_ASSERT(coeff.Dim() == Ncoeff * dof);
  303. if (tensor.Dim() != Ntensor * dof) tensor.ReInit(Ntensor * dof);
  304. for (Long l = 0; l < dof; l++) { // TODO: optimize this
  305. Long offset0 = l * Ncoeff;
  306. Long offset1 = l * Ntensor;
  307. Integer indx0 = 0;
  308. Integer indx1 = 0;
  309. StaticArray<Integer, DIM + 1> i0;
  310. for (Integer i = 0; i <= DIM; i++) i0[i] = 0;
  311. Integer sum = 0;
  312. while (1) {
  313. if (sum < order) {
  314. tensor[offset1 + indx1] = coeff[offset0 + indx0];
  315. indx0++;
  316. } else {
  317. tensor[offset1 + indx1] = 0;
  318. }
  319. indx1++;
  320. sum++;
  321. i0[0]++;
  322. for (Integer j = 0; j < DIM && i0[j] == order; j++) {
  323. i0[j] = 0;
  324. i0[j + 1]++;
  325. sum = sum + 1 - order;
  326. }
  327. if (i0[DIM]) break;
  328. }
  329. }
  330. }
  331. template <Integer DIM> static void Truncate(Vector<ValueType> &coeff0, Integer order0, Integer order1) {
  332. SCTL_ASSERT(order1 <= order0);
  333. Integer Ncoeff0 = 1, Ncoeff1 = 1;
  334. for (Integer i = 0; i < DIM; i++) Ncoeff0 = (Ncoeff0 * (order0 + i)) / (i + 1);
  335. for (Integer i = 0; i < DIM; i++) Ncoeff1 = (Ncoeff1 * (order1 + i)) / (i + 1);
  336. Long dof = coeff0.Dim() / Ncoeff0;
  337. SCTL_ASSERT(coeff0.Dim() == Ncoeff0 * dof);
  338. Vector<ValueType> coeff1(dof * Ncoeff1);
  339. coeff1.SetZero();
  340. for (Long l = 0; l < dof; l++) { // TODO: optimize this
  341. Long offset0 = l * Ncoeff0;
  342. Long offset1 = l * Ncoeff1;
  343. Integer indx0 = 0;
  344. Integer indx1 = 0;
  345. StaticArray<Integer, DIM + 1> i0;
  346. for (Integer i = 0; i <= DIM; i++) i0[i] = 0;
  347. Integer sum = 0;
  348. while (1) {
  349. if (sum < order1) coeff1[offset1 + indx1] = coeff0[offset0 + indx0];
  350. if (sum < order0) indx0++;
  351. if (sum < order1) indx1++;
  352. sum++;
  353. i0[0]++;
  354. for (Integer j = 0; j < DIM && i0[j] == order0; j++) {
  355. i0[j] = 0;
  356. i0[j + 1]++;
  357. sum = sum + 1 - order0;
  358. }
  359. if (i0[DIM]) break;
  360. }
  361. }
  362. coeff0 = coeff1;
  363. }
  364. template <Integer DIM> static void Reflect(Vector<ValueType> &coeff, Integer order, Integer dir) {
  365. SCTL_ASSERT(dir < DIM);
  366. Integer Ncoeff = 1;
  367. for (Integer i = 0; i < DIM; i++) Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  368. Long dof = coeff.Dim() / Ncoeff;
  369. SCTL_ASSERT(coeff.Dim() == Ncoeff * dof);
  370. for (Long l = 0; l < dof; l++) { // TODO: optimize this
  371. Long offset = l * Ncoeff;
  372. Integer indx = 0;
  373. StaticArray<Integer, DIM + 1> i0;
  374. for (Integer i = 0; i <= DIM; i++) i0[i] = 0;
  375. Integer sum = 0;
  376. while (1) {
  377. if (sum < order) coeff[offset + indx] = coeff[offset + indx] * (i0[dir] % 2 ? -1 : 1) * (1);
  378. if (sum < order) indx++;
  379. sum++;
  380. i0[0]++;
  381. for (Integer j = 0; j < DIM && i0[j] == order; j++) {
  382. i0[j] = 0;
  383. i0[j + 1]++;
  384. sum = sum + 1 - order;
  385. }
  386. if (i0[DIM]) break;
  387. }
  388. }
  389. }
  390. template <Integer DIM, Integer CONTINUITY> static void MakeContinuous(Vector<ValueType> &coeff0, Vector<ValueType> &coeff1, Integer order, Integer dir0, Integer dir1) {
  391. if (dir0>=2*DIM || dir1>=2*DIM) return;
  392. Integer Ncoeff = 1;
  393. for (Integer i = 0; i < DIM; i++) Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  394. Long dof = coeff0.Dim() / Ncoeff;
  395. SCTL_ASSERT(coeff0.Dim() == Ncoeff * dof);
  396. SCTL_ASSERT(coeff1.Dim() == Ncoeff * dof);
  397. static Matrix<Matrix<ValueType>> M(2*DIM, 2*DIM);
  398. if (M[dir0][dir1].Dim(0) != 2 * Ncoeff) {
  399. Integer Ngrid = pow<Integer>(order, DIM - 1);
  400. Vector<ValueType> nodes;
  401. Nodes<1>(order, nodes);
  402. Matrix<ValueType> M_diff(2*Ncoeff, Ngrid);
  403. { // Set M_diff
  404. M_diff.SetZero();
  405. StaticArray<Vector<ValueType>, DIM> nodes_;
  406. for (Integer i = 0; i < DIM; i++) { // Set nodes_
  407. nodes_[i].ReInit(nodes.Dim(), nodes.begin(), false);
  408. }
  409. Vector<ValueType> nodes0, nodes1;
  410. nodes0.PushBack(0);
  411. nodes1.PushBack(1);
  412. Vector<ValueType> value;
  413. Vector<ValueType> coeff(Ncoeff);
  414. coeff.SetZero();
  415. for (Integer i = 0; i < Ncoeff; i++) {
  416. coeff[i]=0.5;
  417. value.ReInit(Ngrid, M_diff[i + Ncoeff * 0], false);
  418. nodes_[dir0/2].ReInit(1, (dir0 & 1 ? nodes1.begin() : nodes0.begin()), false);
  419. Eval<DIM>(order, coeff, nodes_, value);
  420. nodes_[dir0/2].ReInit(nodes.Dim(), nodes.begin(), false);
  421. coeff[i]=-0.5;
  422. value.ReInit(Ngrid, M_diff[i + Ncoeff * 1], false);
  423. nodes_[dir1/2].ReInit(1, (dir1 & 1 ? nodes1.begin() : nodes0.begin()), false);
  424. Eval<DIM>(order, coeff, nodes_, value);
  425. nodes_[dir1/2].ReInit(nodes.Dim(), nodes.begin(), false);
  426. coeff[i]=0;
  427. }
  428. }
  429. Matrix<ValueType> M_grad(2 * Ncoeff, 2 * Ncoeff);
  430. { // Set M_grad
  431. M_grad.SetZero();
  432. Vector<ValueType> coeff(Ncoeff * Ncoeff), coeff_grad;
  433. coeff.SetZero();
  434. for(Integer i = 0; i < Ncoeff; i++) coeff[i * Ncoeff + i] = 1;
  435. Grad<DIM>(order, coeff, &coeff_grad);
  436. for (Integer i = 0; i < Ncoeff; i++){
  437. for (Integer j = 0; j < Ncoeff; j++){
  438. M_grad[i + Ncoeff * 0][j + Ncoeff * 0] = coeff_grad[j + (i * DIM + dir0/2) * Ncoeff];
  439. M_grad[i + Ncoeff * 1][j + Ncoeff * 1] = coeff_grad[j + (i * DIM + dir1/2) * Ncoeff];
  440. }
  441. }
  442. }
  443. auto fn_perturb = [&](std::function<ValueType(ValueType)> fn, bool even) { // Set M0
  444. Matrix<ValueType> M0(Ngrid, 2 * Ncoeff);
  445. M0.SetZero();
  446. { // dir0
  447. Integer N0=pow<Integer>(order, dir0/2);
  448. Integer N1=pow<Integer>(order, 1);
  449. Integer N2=pow<Integer>(order, DIM - dir0/2 - 1);
  450. SCTL_ASSERT(N0 * N2 == Ngrid);
  451. Vector<ValueType> val(Ngrid * order), coeff;
  452. val.SetZero();
  453. for (Integer i0=0;i0<N0;i0++){
  454. for (Integer i2=0;i2<N2;i2++){
  455. for (Integer i1=0;i1<N1;i1++){
  456. val[(i2*N1+i1)*N0+i0] = (dir0 & 1 ? fn(nodes[i1]) : fn(1.0 - nodes[i1])) * (even ? 1.0 : -1.0);
  457. }
  458. coeff.ReInit(Ncoeff, M0[i2 * N0 + i0] + Ncoeff * 0, false);
  459. Approx<DIM>(order, val, coeff);
  460. for (Integer i1=0;i1<N1;i1++){
  461. val[(i2*N1+i1)*N0+i0] = 0;
  462. }
  463. }
  464. }
  465. }
  466. { // dir1
  467. Integer N0=pow<Integer>(order, dir1/2);
  468. Integer N1=pow<Integer>(order, 1);
  469. Integer N2=pow<Integer>(order, DIM - dir1/2 - 1);
  470. SCTL_ASSERT(N0 * N2 == Ngrid);
  471. Vector<ValueType> val(Ngrid * order), coeff;
  472. val.SetZero();
  473. for (Integer i0=0;i0<N0;i0++){
  474. for (Integer i2=0;i2<N2;i2++){
  475. for (Integer i1=0;i1<N1;i1++){
  476. val[(i2*N1+i1)*N0+i0] = (dir1 & 1 ? fn(nodes[i1]) : fn(1.0 - nodes[i1]));
  477. }
  478. coeff.ReInit(Ncoeff, M0[i2 * N0 + i0] + Ncoeff * 1, false);
  479. Approx<DIM>(order, val, coeff);
  480. for (Integer i1=0;i1<N1;i1++){
  481. val[(i2*N1+i1)*N0+i0] = 0;
  482. }
  483. }
  484. }
  485. }
  486. return M0;
  487. };
  488. if (CONTINUITY == 0) {
  489. auto fn0 = [](ValueType x) {return x;};
  490. Matrix<ValueType> M0 = fn_perturb(fn0, 0);
  491. M[dir0][dir1] = M_diff * M0;
  492. } else if (CONTINUITY == 1) {
  493. auto fn0 = [](ValueType x) {return (-2*x + 3) * x * x;};
  494. auto fn1 = [](ValueType x) {return (1 - x) * x * x;};
  495. Matrix<ValueType> M0 = fn_perturb(fn0, 0);
  496. Matrix<ValueType> M1 = fn_perturb(fn1, 1);
  497. M[dir0][dir1] = M_diff * M0 + M_grad * M_diff * M1;
  498. } else if (CONTINUITY == 2) {
  499. auto fn0 = [](ValueType x) {return x*x*x*(6*x*x-15*x+10);};
  500. auto fn1 = [](ValueType x) {return x*x*x*(-3*x*x+7*x-4);};
  501. auto fn2 = [](ValueType x) {return x*x*x*(0.5*x*x-1*x+0.5);};
  502. Matrix<ValueType> M0 = fn_perturb(fn0, 0);
  503. Matrix<ValueType> M1 = fn_perturb(fn1, 1);
  504. Matrix<ValueType> M2 = fn_perturb(fn2, 0);
  505. M[dir0][dir1] = M_diff * M0 + M_grad * M_diff * M1 + M_grad * M_grad * M_diff * M2;
  506. }
  507. for (Integer i=0;i<2*Ncoeff;i++){
  508. M[dir0][dir1][i][i]+=1.0;
  509. }
  510. if(0){ //// Alternate approach // DOESN'T WORK
  511. //Matrix<ValueType> Mgrid2coeff;
  512. //{ // Set Mgrid2coeff
  513. // Integer Ngrid = pow<Integer>(order, DIM);
  514. // Matrix<ValueType> M(Ngrid, Ncoeff);
  515. // Vector<ValueType> val(Ngrid);
  516. // val.SetZero();
  517. // for (Integer i=0;i<Ngrid;i++) {
  518. // val[i]=1.0;
  519. // Vector<ValueType> coeff(Ncoeff, M[i], false);
  520. // Approx<DIM>(order, val, coeff);
  521. // val[i]=0.0;
  522. // }
  523. // Mgrid2coeff.ReInit(2*Ngrid, 2*Ncoeff);
  524. // Mgrid2coeff.SetZero();
  525. // for(Integer i=0;i<Ngrid;i++){
  526. // for(Integer j=0;j<Ncoeff;j++){
  527. // Mgrid2coeff[i+Ngrid*0][j+Ncoeff*0]=M[i][j];
  528. // Mgrid2coeff[i+Ngrid*1][j+Ncoeff*1]=M[i][j];
  529. // }
  530. // }
  531. //}
  532. //Matrix<ValueType> Mcoeff2grid;
  533. //{ // Set Mgrid2coeff
  534. // StaticArray<Vector<ValueType>, DIM> nodes_;
  535. // for (Integer i = 0; i < DIM; i++) { // Set nodes_
  536. // nodes_[i].ReInit(nodes.Dim(), nodes.begin(), false);
  537. // }
  538. // Integer Ngrid = pow<Integer>(order, DIM);
  539. // Matrix<ValueType> M(Ncoeff, Ngrid);
  540. // Vector<ValueType> coeff(Ncoeff);
  541. // coeff.SetZero();
  542. // for (Integer i=0;i<Ncoeff;i++) {
  543. // coeff[i]=1.0;
  544. // Vector<ValueType> val(Ngrid, M[i], false);
  545. // Eval<DIM>(order, coeff, nodes_, val);
  546. // coeff[i]=0.0;
  547. // }
  548. // Mcoeff2grid.ReInit(2*Ncoeff, 2*Ngrid);
  549. // Mcoeff2grid.SetZero();
  550. // for(Integer i=0;i<Ncoeff;i++){
  551. // for(Integer j=0;j<Ngrid;j++){
  552. // Mcoeff2grid[i+Ncoeff*0][j+Ngrid*0]=M[i][j];
  553. // Mcoeff2grid[i+Ncoeff*1][j+Ngrid*1]=M[i][j];
  554. // }
  555. // }
  556. //}
  557. //if(0){
  558. // Integer Ngrid0 = Ngrid*order;
  559. // Matrix<ValueType> MM(2*Ngrid0 + 2*Ngrid, 2*Ngrid0);
  560. // MM.SetZero();
  561. // for (Integer i=0;i<2*Ngrid0;i++) MM[i][i]=1;
  562. // Matrix<ValueType> M0_(Ngrid, 2 * Ngrid0, MM[2 * Ngrid0 + Ngrid * 0], false); M0_ = (Mgrid2coeff * M_diff).Transpose();
  563. // Matrix<ValueType> M1_(Ngrid, 2 * Ngrid0, MM[2 * Ngrid0 + Ngrid * 1], false); M1_ = (Mgrid2coeff * M_grad * M_diff).Transpose();
  564. // for (Long i=0;i<2*Ngrid*2*Ngrid0;i++) MM[0][2*Ngrid0*2*Ngrid0 +i] *= 10000;
  565. // MM = MM.Transpose().pinv();
  566. // M[dir].ReInit(2 * Ngrid0, 2 * Ngrid0, MM.begin());
  567. // M[dir] = Mcoeff2grid * M[dir] * Mgrid2coeff;
  568. //} else {
  569. // SCTL_ASSERT(DIM==2);
  570. // Vector<ValueType> coeff_weight;
  571. // for (Integer i=0;i<order;i++) {
  572. // for (Integer j=0;j<order;j++) {
  573. // if(i+j<order) coeff_weight.PushBack(pow<ValueType>(1.5, i+j)*1e-4);
  574. // }
  575. // }
  576. // SCTL_ASSERT(coeff_weight.Dim()==Ncoeff);
  577. // auto M0_ = M_diff.Transpose();
  578. // auto M1_ = (M_grad * M_diff).Transpose();
  579. // Matrix<ValueType> MM(2*Ncoeff + 6*Ngrid, 2*Ncoeff);
  580. // MM.SetZero();
  581. // for (Integer i=0;i<Ncoeff;i++) {
  582. // MM[i+Ncoeff*0][i+Ncoeff*0]=coeff_weight[i];
  583. // MM[i+Ncoeff*1][i+Ncoeff*1]=coeff_weight[i];
  584. // }
  585. // for (Integer i=0;i<Ngrid;i++) {
  586. // for (Integer j=0;j<Ncoeff;j++) {
  587. // MM[2 * Ncoeff + 0 * Ngrid +i][0 * Ncoeff + j] = M0_[0 * Ngrid + i][0 * Ncoeff + j];
  588. // MM[2 * Ncoeff + 0 * Ngrid +i][1 * Ncoeff + j] = M0_[0 * Ngrid + i][1 * Ncoeff + j];
  589. // MM[2 * Ncoeff + 1 * Ngrid +i][0 * Ncoeff + j] = M1_[0 * Ngrid + i][0 * Ncoeff + j];
  590. // MM[2 * Ncoeff + 1 * Ngrid +i][1 * Ncoeff + j] = M1_[0 * Ngrid + i][1 * Ncoeff + j];
  591. // MM[2 * Ncoeff + 2 * Ngrid +i][0 * Ncoeff + j] = M0_[0 * Ngrid + i][1 * Ncoeff + j];
  592. // MM[2 * Ncoeff + 3 * Ngrid +i][1 * Ncoeff + j] = M0_[0 * Ngrid + i][0 * Ncoeff + j];
  593. // MM[2 * Ncoeff + 4 * Ngrid +i][0 * Ncoeff + j] = M1_[0 * Ngrid + i][1 * Ncoeff + j];
  594. // MM[2 * Ncoeff + 5 * Ngrid +i][1 * Ncoeff + j] = M1_[0 * Ngrid + i][0 * Ncoeff + j];
  595. // }
  596. // }
  597. // Matrix<ValueType> MMM(2*Ncoeff + 6*Ngrid, 2*Ncoeff);
  598. // MMM.SetZero();
  599. // for (Integer i=0;i<Ncoeff;i++) {
  600. // MMM[i+Ncoeff*0][i+Ncoeff*0]=coeff_weight[i];
  601. // MMM[i+Ncoeff*1][i+Ncoeff*1]=coeff_weight[i];
  602. // }
  603. // for (Integer i=0;i<Ngrid;i++) {
  604. // for (Integer j=0;j<Ncoeff;j++) {
  605. // // MMM[2 * Ncoeff + 0 * Ngrid +i][0 * Ncoeff + j] = M0_[0 * Ngrid + i][0 * Ncoeff + j];
  606. // // MMM[2 * Ncoeff + 0 * Ngrid +i][1 * Ncoeff + j] = M0_[0 * Ngrid + i][1 * Ncoeff + j];
  607. // // MMM[2 * Ncoeff + 1 * Ngrid +i][0 * Ncoeff + j] = M1_[0 * Ngrid + i][0 * Ncoeff + j];
  608. // // MMM[2 * Ncoeff + 1 * Ngrid +i][1 * Ncoeff + j] = M1_[0 * Ngrid + i][1 * Ncoeff + j];
  609. // MMM[2 * Ncoeff + 2 * Ngrid +i][0 * Ncoeff + j] = M0_[0 * Ngrid + i][1 * Ncoeff + j];
  610. // MMM[2 * Ncoeff + 3 * Ngrid +i][1 * Ncoeff + j] = M0_[0 * Ngrid + i][0 * Ncoeff + j];
  611. // MMM[2 * Ncoeff + 4 * Ngrid +i][0 * Ncoeff + j] = M1_[0 * Ngrid + i][1 * Ncoeff + j];
  612. // MMM[2 * Ncoeff + 5 * Ngrid +i][1 * Ncoeff + j] = M1_[0 * Ngrid + i][0 * Ncoeff + j];
  613. // }
  614. // }
  615. // M[dir] = (MM.pinv(1e-10) * MMM).Transpose();
  616. //}
  617. //M[dir]=M[dir]*M[dir];
  618. ////M[dir]=M[dir]*M[dir];
  619. ////M[dir]=M[dir]*M[dir];
  620. ////M[dir]=M[dir]*M[dir];
  621. ////M[dir]=M[dir]*M[dir];
  622. ////M[dir]=M[dir]*M[dir];
  623. ////M[dir]=M[dir]*M[dir];
  624. ////M[dir]=M[dir]*M[dir];
  625. ////M[dir]=M[dir]*M[dir];
  626. ////M[dir]=M[dir]*M[dir];
  627. ////M[dir]=M[dir]*M[dir];
  628. ////M[dir]=M[dir]*M[dir];
  629. ////M[dir]=M[dir]*M[dir];
  630. ////M[dir]=M[dir]*M[dir];
  631. ////M[dir]=M[dir]*M[dir];
  632. ////M[dir]=M[dir]*M[dir];
  633. }
  634. }
  635. Matrix<ValueType> x(dof, 2 * Ncoeff), y(dof, 2 * Ncoeff);
  636. for (Long i = 0; i < dof; i++) {
  637. for (Integer j = 0; j < Ncoeff; j++) {
  638. x[i][Ncoeff * 0 + j] = coeff0[i * Ncoeff + j];
  639. x[i][Ncoeff * 1 + j] = coeff1[i * Ncoeff + j];
  640. }
  641. }
  642. Matrix<ValueType>::GEMM(y, x, M[dir0][dir1]);
  643. for (Long i = 0; i < dof; i++) {
  644. for (Integer j = 0; j < Ncoeff; j++) {
  645. coeff0[i * Ncoeff + j] = y[i][Ncoeff * 0 + j];
  646. coeff1[i * Ncoeff + j] = y[i][Ncoeff * 1 + j];
  647. }
  648. }
  649. }
  650. template <Integer DIM, Integer CONTINUITY> static void MakeContinuousEdge(Vector<ValueType> &coeff0, Vector<ValueType> &coeff1, Integer order, Integer dir0, Integer dir1, Integer norm0, Integer norm1) {
  651. SCTL_ASSERT(DIM==2);
  652. if (dir0>=2*DIM || dir1>=2*DIM) return;
  653. Integer Ncoeff = 1;
  654. for (Integer i = 0; i < DIM; i++) Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  655. Long dof = coeff0.Dim() / Ncoeff;
  656. SCTL_ASSERT(coeff0.Dim() == Ncoeff * dof);
  657. SCTL_ASSERT(coeff1.Dim() == Ncoeff * dof);
  658. static Matrix<Matrix<ValueType>> M(2*DIM, 2*DIM);
  659. static Matrix<Matrix<ValueType>> MM(2*DIM, 2*DIM);
  660. if (M[dir0][dir1].Dim(0) != 2 * Ncoeff) {
  661. Integer Ngrid = pow<Integer>(order, DIM - 1);
  662. Vector<ValueType> nodes;
  663. Nodes<1>(order, nodes);
  664. Matrix<ValueType> Mtrunc(2*Ncoeff, 2*Ncoeff);
  665. { // Set Mtrunc
  666. Vector<ValueType> w;
  667. w.SetZero();
  668. for (Integer i=0;i<order;i++){
  669. for (Integer j=0;j<order;j++){
  670. if (i+j<order) {
  671. w.PushBack(i<order-CONTINUITY*2-1 && j<order-CONTINUITY*2-1);
  672. }
  673. }
  674. }
  675. Mtrunc.SetZero();
  676. for (Integer i=0;i<Ncoeff;i++){
  677. Mtrunc[i + Ncoeff * 0][i + Ncoeff * 0] = w[i];
  678. Mtrunc[i + Ncoeff * 1][i + Ncoeff * 1] = w[i];
  679. }
  680. }
  681. Matrix<ValueType> M_diff(2*Ncoeff, Ngrid);
  682. { // Set M_diff
  683. M_diff.SetZero();
  684. StaticArray<Vector<ValueType>, DIM> nodes_;
  685. for (Integer i = 0; i < DIM; i++) { // Set nodes_
  686. nodes_[i].ReInit(nodes.Dim(), nodes.begin(), false);
  687. }
  688. Vector<ValueType> nodes0, nodes1;
  689. nodes0.PushBack(0);
  690. nodes1.PushBack(1);
  691. Vector<ValueType> value;
  692. Vector<ValueType> coeff(Ncoeff);
  693. coeff.SetZero();
  694. for (Integer i = 0; i < Ncoeff; i++) {
  695. coeff[i]=0.5;
  696. value.ReInit(Ngrid, M_diff[i + Ncoeff * 0], false);
  697. nodes_[dir0/2].ReInit(1, (dir0 & 1 ? nodes1.begin() : nodes0.begin()), false);
  698. Eval<DIM>(order, coeff, nodes_, value);
  699. nodes_[dir0/2].ReInit(nodes.Dim(), nodes.begin(), false);
  700. coeff[i]=-0.5;
  701. value.ReInit(Ngrid, M_diff[i + Ncoeff * 1], false);
  702. nodes_[dir1/2].ReInit(1, (dir1 & 1 ? nodes1.begin() : nodes0.begin()), false);
  703. Eval<DIM>(order, coeff, nodes_, value);
  704. nodes_[dir1/2].ReInit(nodes.Dim(), nodes.begin(), false);
  705. coeff[i]=0;
  706. }
  707. }
  708. Matrix<ValueType> M_grad(2 * Ncoeff, 2 * Ncoeff);
  709. { // Set M_grad
  710. M_grad.SetZero();
  711. Vector<ValueType> coeff(Ncoeff * Ncoeff), coeff_grad;
  712. coeff.SetZero();
  713. for(Integer i = 0; i < Ncoeff; i++) coeff[i * Ncoeff + i] = 1;
  714. Grad<DIM>(order, coeff, &coeff_grad);
  715. for (Integer i = 0; i < Ncoeff; i++){
  716. for (Integer j = 0; j < Ncoeff; j++){
  717. M_grad[i + Ncoeff * 0][j + Ncoeff * 0] = coeff_grad[j + (i * DIM + dir0/2) * Ncoeff];
  718. M_grad[i + Ncoeff * 1][j + Ncoeff * 1] = coeff_grad[j + (i * DIM + dir1/2) * Ncoeff];
  719. }
  720. }
  721. }
  722. auto fn_perturb = [&](std::function<ValueType(ValueType)> fn, bool even) { // Set M0
  723. Matrix<ValueType> M0(Ngrid, 2 * Ncoeff);
  724. M0.SetZero();
  725. { // dir0
  726. Integer N0=pow<Integer>(order, dir0/2);
  727. Integer N1=pow<Integer>(order, 1);
  728. Integer N2=pow<Integer>(order, DIM - dir0/2 - 1);
  729. SCTL_ASSERT(N0 * N2 == Ngrid);
  730. Vector<ValueType> val(Ngrid * order), coeff;
  731. val.SetZero();
  732. for (Integer i0=0;i0<N0;i0++){
  733. for (Integer i2=0;i2<N2;i2++){
  734. for (Integer i1=0;i1<N1;i1++){
  735. val[(i2*N1+i1)*N0+i0] = (dir0 & 1 ? fn(nodes[i1]) : fn(1.0 - nodes[i1])) * (even ? 1.0 : -1.0);
  736. }
  737. coeff.ReInit(Ncoeff, M0[i2 * N0 + i0] + Ncoeff * 0, false);
  738. Approx<DIM>(order, val, coeff);
  739. for (Integer i1=0;i1<N1;i1++){
  740. val[(i2*N1+i1)*N0+i0] = 0;
  741. }
  742. }
  743. }
  744. }
  745. { // dir1
  746. Integer N0=pow<Integer>(order, dir1/2);
  747. Integer N1=pow<Integer>(order, 1);
  748. Integer N2=pow<Integer>(order, DIM - dir1/2 - 1);
  749. SCTL_ASSERT(N0 * N2 == Ngrid);
  750. Vector<ValueType> val(Ngrid * order), coeff;
  751. val.SetZero();
  752. for (Integer i0=0;i0<N0;i0++){
  753. for (Integer i2=0;i2<N2;i2++){
  754. for (Integer i1=0;i1<N1;i1++){
  755. val[(i2*N1+i1)*N0+i0] = (dir1 & 1 ? fn(nodes[i1]) : fn(1.0 - nodes[i1]));
  756. }
  757. coeff.ReInit(Ncoeff, M0[i2 * N0 + i0] + Ncoeff * 1, false);
  758. Approx<DIM>(order, val, coeff);
  759. for (Integer i1=0;i1<N1;i1++){
  760. val[(i2*N1+i1)*N0+i0] = 0;
  761. }
  762. }
  763. }
  764. }
  765. return M0;
  766. };
  767. Matrix<ValueType> Mfilter[2];
  768. { // Set Mfilter
  769. Mfilter[0].ReInit(2*Ncoeff, 2*Ncoeff);
  770. Mfilter[1].ReInit(2*Ncoeff, 2*Ncoeff);
  771. Mfilter[0].SetZero();
  772. Mfilter[1].SetZero();
  773. for (Integer i=0;i<Ncoeff;i++) {
  774. Mfilter[0][i + Ncoeff * 0][i + Ncoeff * 0] = 1;
  775. Mfilter[1][i + Ncoeff * 1][i + Ncoeff * 1] = 1;
  776. }
  777. }
  778. if (CONTINUITY == 0) {
  779. auto fn0 = [](ValueType x) {return x;};
  780. Matrix<ValueType> M0 = fn_perturb(fn0, 0);
  781. M[dir0][dir1] = M_diff * M0;
  782. } else if (CONTINUITY == 1) {
  783. auto fn0 = [](ValueType x) {return (-2*x + 3) * x * x;};
  784. auto fn1 = [](ValueType x) {return (1 - x) * x * x;};
  785. Matrix<ValueType> M0 = fn_perturb(fn0, 0);
  786. Matrix<ValueType> M1 = fn_perturb(fn1, 1);
  787. M[dir0][dir1] = M_diff * M0;
  788. if (dir0 & 1) M[dir0][dir1] += (M_grad+M_grad) * (Mfilter[0] * M_diff * M1 * Mfilter[0]);
  789. else M[dir0][dir1] -= (M_grad+M_grad) * (Mfilter[0] * M_diff * M1 * Mfilter[0]);
  790. if (dir1 & 1) M[dir0][dir1] -= (M_grad+M_grad) * (Mfilter[1] * M_diff * M1 * Mfilter[1]);
  791. else M[dir0][dir1] += (M_grad+M_grad) * (Mfilter[1] * M_diff * M1 * Mfilter[1]);
  792. }
  793. if (CONTINUITY == 1) {
  794. auto fn1 = [](ValueType x) {return (1 - x) * x * x;};
  795. Matrix<ValueType> M1 = fn_perturb(fn1, 1);
  796. MM[dir0][dir1] = M_grad * M_diff * M1;
  797. for (Integer i=0;i<Ncoeff;i++){
  798. for (Integer j=0;j<2*Ncoeff;j++){
  799. MM[dir0][dir1][i + Ncoeff*1][j]*=-1;
  800. }
  801. }
  802. for (Integer i=0;i<2*Ncoeff;i++){
  803. for (Integer j=0;j<Ncoeff;j++){
  804. MM[dir0][dir1][i][j + Ncoeff*0]*=(dir0 & 1 ? 1.0 : -1.0);
  805. MM[dir0][dir1][i][j + Ncoeff*1]*=(dir1 & 1 ? 1.0 : -1.0);
  806. }
  807. }
  808. }
  809. for (Integer i=0;i<2*Ncoeff;i++){
  810. M[dir0][dir1][i][i]+=1.0;
  811. MM[dir0][dir1][i][i]+=1.0;
  812. }
  813. M[dir0][dir1] = Mtrunc * M[dir0][dir1] * Mtrunc;
  814. MM[dir0][dir1] = Mtrunc * MM[dir0][dir1] * Mtrunc;
  815. for (Integer i=0;i<10;i++) {
  816. M[dir0][dir1]=M[dir0][dir1]*M[dir0][dir1];
  817. }
  818. }
  819. Matrix<ValueType> x(dof, 2 * Ncoeff), y(dof, 2 * Ncoeff);
  820. for (Long i = 0; i < dof; i++) {
  821. for (Integer j = 0; j < Ncoeff; j++) {
  822. x[i][Ncoeff * 0 + j] = coeff0[i * Ncoeff + j];
  823. x[i][Ncoeff * 1 + j] = coeff1[i * Ncoeff + j];
  824. }
  825. }
  826. Matrix<ValueType>::GEMM(y, x, M[dir0][dir1]);
  827. { ////
  828. Matrix<ValueType> xx(1, 2*Ncoeff), yy(1, 2*Ncoeff);
  829. for (Integer j = 0; j < Ncoeff; j++) {
  830. xx[0][Ncoeff * 0 + j] = coeff0[norm0 * Ncoeff + j];
  831. xx[0][Ncoeff * 1 + j] = coeff1[norm1 * Ncoeff + j];
  832. }
  833. Matrix<ValueType>::GEMM(yy, xx, MM[dir0][dir1]);
  834. for (Integer j = 0; j < Ncoeff; j++) {
  835. y[norm0][Ncoeff * 0 + j] = yy[0][Ncoeff * 0 + j];
  836. y[norm1][Ncoeff * 1 + j] = yy[0][Ncoeff * 1 + j];
  837. }
  838. }
  839. for (Long i = 0; i < dof; i++) {
  840. for (Integer j = 0; j < Ncoeff; j++) {
  841. coeff0[i * Ncoeff + j] = y[i][Ncoeff * 0 + j];
  842. coeff1[i * Ncoeff + j] = y[i][Ncoeff * 1 + j];
  843. }
  844. }
  845. }
  846. static void quad_rule(Integer order, Vector<ValueType>& x, Vector<ValueType>& w) {
  847. static Vector<Vector<ValueType>> x_lst(10000);
  848. static Vector<Vector<ValueType>> w_lst(x_lst.Dim());
  849. SCTL_ASSERT(order < x_lst.Dim());
  850. if (x.Dim() != order) x.ReInit(order);
  851. if (w.Dim() != order) w.ReInit(order);
  852. if (!order) return;
  853. bool done = false;
  854. #pragma omp critical(QUAD_RULE)
  855. if (x_lst[order].Dim()) {
  856. Vector<ValueType>& x_ = x_lst[order];
  857. Vector<ValueType>& w_ = w_lst[order];
  858. for (Integer i = 0; i < order; i++) {
  859. x[i] = x_[i];
  860. w[i] = w_[i];
  861. }
  862. done = true;
  863. }
  864. if (done) return;
  865. Vector<ValueType> x_(order);
  866. Vector<ValueType> w_(order);
  867. if (std::is_same<ValueType, double>::value || std::is_same<ValueType, float>::value) { // Gauss-Legendre quadrature nodes and weights
  868. Vector<double> xd(order);
  869. Vector<double> wd(order);
  870. int kind = 1;
  871. double alpha = 0.0, beta = 0.0, a = -1.0, b = 1.0;
  872. cgqf(order, kind, (double)alpha, (double)beta, (double)a, (double)b, &xd[0], &wd[0]);
  873. for (Integer i = 0; i < order; i++) {
  874. x_[i] = (ValueType)(0.5 * xd[i] + 0.5);
  875. w_[i] = (ValueType)(0.5 * wd[i]);
  876. }
  877. } else { // Chebyshev quadrature nodes and weights
  878. cheb_nodes_1d(order, x_);
  879. for (Integer i = 0; i < order; i++) w_[i] = 0;
  880. Vector<ValueType> V_cheb(order * order);
  881. cheb_basis_1d(order, x_, V_cheb);
  882. for (Integer i = 0; i < order; i++) V_cheb[i] /= 2.0;
  883. Matrix<ValueType> M(order, order, V_cheb.begin());
  884. Vector<ValueType> w_sample(order);
  885. w_sample.SetZero();
  886. for (Integer i = 0; i < order; i += 2) w_sample[i] = -((ValueType)2.0 / (i + 1) / (i - 1));
  887. for (Integer i = 0; i < order; i++) {
  888. for (Integer j = 0; j < order; j++) {
  889. w_[j] += M[i][j] * w_sample[i] / order;
  890. }
  891. }
  892. }
  893. #pragma omp critical(QUAD_RULE)
  894. if (!x_lst[order].Dim()) { // Set x_lst, w_lst
  895. x_lst[order].Swap(x_);
  896. w_lst[order].Swap(w_);
  897. }
  898. quad_rule(order, x, w);
  899. }
  900. private:
  901. BasisInterface() {
  902. void (*EvalBasis1D)(Integer, const Vector<ValueType>&, Vector<ValueType>&) = Derived::EvalBasis1D;
  903. void (*Nodes1D)(Integer, Vector<ValueType>&) = Derived::Nodes1D;
  904. }
  905. static void cheb_nodes_1d(Integer order, Vector<ValueType>& nodes) {
  906. if (nodes.Dim() != order) nodes.ReInit(order);
  907. for (Integer i = 0; i < order; i++) {
  908. nodes[i] = -cos<ValueType>((i + (ValueType)0.5) * const_pi<ValueType>() / order) * (ValueType)0.5 + (ValueType)0.5;
  909. }
  910. }
  911. static void cheb_basis_1d(Integer order, const Vector<ValueType>& x, Vector<ValueType>& y) {
  912. Integer n = x.Dim();
  913. if (y.Dim() != order * n) y.ReInit(order * n);
  914. if (order > 0) {
  915. for (Long i = 0; i < n; i++) {
  916. y[i] = 1.0;
  917. }
  918. }
  919. if (order > 1) {
  920. for (Long i = 0; i < n; i++) {
  921. y[i + n] = x[i] * 2 - 1;
  922. }
  923. }
  924. for (Integer i = 2; i < order; i++) {
  925. for (Long j = 0; j < n; j++) {
  926. y[i * n + j] = 2 * y[n + j] * y[i * n - 1 * n + j] - y[i * n - 2 * n + j];
  927. }
  928. }
  929. }
  930. static ValueType machine_eps() {
  931. ValueType eps = 1.0;
  932. while (eps + (ValueType)1.0 > 1.0) eps *= 0.5;
  933. return eps;
  934. }
  935. template <Integer DIM, Integer SUBDIM, class Kernel> static void Integ_(Matrix<ValueType>& Mcoeff, Integer order, ConstIterator<ValueType> trg_, ValueType side, Integer src_face, const Kernel& ker, Integer Nq = 0) {
  936. static const ValueType eps = machine_eps() * 64;
  937. ValueType side_inv = 1.0 / side;
  938. if (!Nq) Nq = order;
  939. Vector<ValueType> qp, qw;
  940. quad_rule(Nq, qp, qw);
  941. Integer Ncoeff;
  942. { // Set Ncoeff
  943. Ncoeff = 1;
  944. for (Integer i = 0; i < SUBDIM; i++) Ncoeff = (Ncoeff * (order + i)) / (i + 1);
  945. }
  946. StaticArray<Integer, 2> kdim;
  947. kdim[0] = ker.Dim(0);
  948. kdim[1] = ker.Dim(1);
  949. StaticArray<Integer, DIM> perm0;
  950. StaticArray<ValueType, DIM> trg; // target after rotation
  951. { // Set perm0
  952. SCTL_ASSERT(0 <= src_face && src_face < 2 * DIM);
  953. if (SUBDIM == DIM - 1) {
  954. for (Integer i = 0; i < DIM; i++) {
  955. perm0[i] = (i + (src_face >> 1) + 1) % DIM;
  956. }
  957. } else {
  958. for (Integer i = 0; i < DIM; i++) {
  959. perm0[i] = i;
  960. }
  961. }
  962. for (Integer i = 0; i < DIM; i++) trg[i] = trg_[perm0[i]];
  963. if (SUBDIM == DIM - 1) trg[DIM - 1] -= side * (src_face & 1);
  964. }
  965. Vector<ValueType> r;
  966. { // Set r
  967. Vector<ValueType> r_;
  968. r_.PushBack(0);
  969. for (Integer i = 0; i < SUBDIM; i++) {
  970. r_.PushBack(fabs(trg[i] - 0.0));
  971. r_.PushBack(fabs(trg[i] - side));
  972. }
  973. std::sort(r_.begin(), r_.begin() + r_.Dim());
  974. ValueType r0, r1 = r_[r_.Dim() - 1];
  975. r0 = (r1 > side ? r1 - side : 0.0);
  976. for (Integer i = SUBDIM; i < DIM; i++) r0 = std::max(r0, fabs(trg[i]));
  977. if (r0 > eps) r.PushBack(-r0);
  978. r.PushBack(r0);
  979. for (Integer i = 0; i < r_.Dim(); i++) {
  980. if (r_[i] > r0) {
  981. while (r[r.Dim() - 1] > 0.0 && 3.0 * r[r.Dim() - 1] < r_[i]) r.PushBack(3.0 * r[r.Dim() - 1]);
  982. r.PushBack(r_[i]);
  983. }
  984. }
  985. }
  986. // Work vectors
  987. StaticArray<Vector<ValueType>, SUBDIM> eval_mesh;
  988. StaticArray<Vector<ValueType>, SUBDIM> eval_poly;
  989. Vector<ValueType> eval_coord_tmp;
  990. Vector<ValueType> eval_coord;
  991. Vector<ValueType> kern_value;
  992. // Temporary vectors
  993. Vector<ValueType> r_src, n_src, v_src;
  994. { // Init r_src, n_src, v_src
  995. r_src.ReInit(DIM);
  996. for (Integer k = 0; k < DIM; k++) r_src[k] = 0.0;
  997. if (SUBDIM == DIM - 1) {
  998. n_src.ReInit(DIM);
  999. for (Integer k = 0; k < DIM; k++) n_src[k] = 0.0;
  1000. n_src[src_face >> 1] = (src_face & 1 ? -1.0 : 1.0);
  1001. }
  1002. v_src.ReInit(kdim[0]);
  1003. }
  1004. Vector<ValueType> v0;
  1005. Vector<ValueType> v1;
  1006. Matrix<ValueType> Mtensor(kdim[1] * kdim[0], pow<Integer>(order, SUBDIM));
  1007. Mtensor.SetZero();
  1008. for (Integer i0 = 0; i0 < r.Dim() - 1; i0++) { // for each layer
  1009. for (Integer i1 = 0; i1 < 2 * SUBDIM; i1++) { // for each direction
  1010. StaticArray<ValueType, 2 * SUBDIM> range0;
  1011. StaticArray<ValueType, 2 * SUBDIM> range1;
  1012. { // Set range0, range1
  1013. for (Integer k = 0; k < SUBDIM; k++) {
  1014. if (i1 >> 1 == k) {
  1015. ValueType s = (i1 & 1 ? 1.0 : -1.0);
  1016. range0[k * 2 + 0] = trg[k] + s * r[i0 + 0];
  1017. range0[k * 2 + 1] = trg[k] + s * r[i0 + 0];
  1018. range1[k * 2 + 0] = trg[k] + s * r[i0 + 1];
  1019. range1[k * 2 + 1] = trg[k] + s * r[i0 + 1];
  1020. } else {
  1021. range0[k * 2 + 0] = trg[k] - fabs(r[i0 + 0]);
  1022. range0[k * 2 + 1] = trg[k] + fabs(r[i0 + 0]);
  1023. range1[k * 2 + 0] = trg[k] - fabs(r[i0 + 1]);
  1024. range1[k * 2 + 1] = trg[k] + fabs(r[i0 + 1]);
  1025. }
  1026. }
  1027. for (Integer k = 0; k < 2 * SUBDIM; k++) {
  1028. if (range0[k] > side) range0[k] = side;
  1029. if (range0[k] < 0.0) range0[k] = 0.0;
  1030. if (range1[k] > side) range1[k] = side;
  1031. if (range1[k] < 0.0) range1[k] = 0.0;
  1032. }
  1033. bool continue_flag = false;
  1034. for (Integer k = 0; k < SUBDIM; k++) { // continue if volume if 0
  1035. if (i1 >> 1 == k) {
  1036. if (fabs(range0[2 * k + 0] - range1[2 * k + 0]) < eps && fabs(range0[2 * k + 1] - range1[2 * k + 1]) < eps) {
  1037. continue_flag = true;
  1038. break;
  1039. }
  1040. } else {
  1041. if (fabs(range0[2 * k + 0] - range0[2 * k + 1]) < eps && fabs(range1[2 * k + 0] - range1[2 * k + 1]) < eps) {
  1042. continue_flag = true;
  1043. break;
  1044. }
  1045. }
  1046. }
  1047. if (continue_flag) continue;
  1048. }
  1049. for (Integer i2 = 0; i2 < Nq; i2++) { // for each quadrature point
  1050. StaticArray<ValueType, 2 * SUBDIM> range;
  1051. for (Integer k = 0; k < 2 * SUBDIM; k++) { // Set range
  1052. range[k] = range0[k] + (range1[k] - range0[k]) * qp[i2];
  1053. }
  1054. for (Integer k = 0; k < SUBDIM; k++) { // Set eval_mesh
  1055. if (k == (i1 >> 1)) {
  1056. eval_mesh[k].ReInit(1);
  1057. eval_mesh[k][0] = range[2 * k];
  1058. } else {
  1059. eval_mesh[k].ReInit(Nq);
  1060. for (Integer l = 0; l < Nq; l++) eval_mesh[k][l] = range[2 * k + 0] + (range[2 * k + 1] - range[2 * k + 0]) * qp[l];
  1061. }
  1062. }
  1063. { // Set eval_coord
  1064. Integer N = 1;
  1065. eval_coord.ReInit(0);
  1066. for (Integer k = 0; k < SUBDIM; k++) {
  1067. Integer Nk = eval_mesh[k].Dim();
  1068. eval_coord_tmp.Swap(eval_coord);
  1069. eval_coord.ReInit(Nk * N * DIM);
  1070. for (Integer l0 = 0; l0 < Nk; l0++) {
  1071. for (Integer l1 = 0; l1 < N; l1++) {
  1072. for (Integer l2 = 0; l2 < k; l2++) {
  1073. eval_coord[DIM * (N * l0 + l1) + l2] = eval_coord_tmp[DIM * l1 + l2];
  1074. }
  1075. eval_coord[DIM * (N * l0 + l1) + k] = trg[k] - eval_mesh[k][l0];
  1076. }
  1077. }
  1078. N *= Nk;
  1079. }
  1080. StaticArray<ValueType, DIM> c;
  1081. for (Integer k = 0; k < N; k++) { // Rotate
  1082. for (Integer l = 0; l < SUBDIM; l++) c[l] = eval_coord[k * DIM + l];
  1083. for (Integer l = SUBDIM; l < DIM; l++) c[l] = trg[l];
  1084. for (Integer l = 0; l < DIM; l++) eval_coord[k * DIM + perm0[l]] = c[l];
  1085. }
  1086. }
  1087. for (Integer k = 0; k < SUBDIM; k++) { // Set eval_poly
  1088. Integer N = eval_mesh[k].Dim();
  1089. for (Integer l = 0; l < eval_mesh[k].Dim(); l++) { // Scale eval_mesh to [0, 1]
  1090. eval_mesh[k][l] *= side_inv;
  1091. }
  1092. Derived::EvalBasis1D(order, eval_mesh[k], eval_poly[k]);
  1093. if (k == (i1 >> 1)) {
  1094. assert(N == 1);
  1095. ValueType qscal = fabs(range1[i1] - range0[i1]);
  1096. for (Integer l0 = 0; l0 < order; l0++) {
  1097. eval_poly[k][l0] *= qscal * qw[i2];
  1098. }
  1099. } else {
  1100. assert(N == Nq);
  1101. ValueType qscal = (range[2 * k + 1] - range[2 * k + 0]);
  1102. for (Integer l0 = 0; l0 < order; l0++) {
  1103. for (Integer l1 = 0; l1 < N; l1++) {
  1104. eval_poly[k][N * l0 + l1] *= qscal * qw[l1];
  1105. }
  1106. }
  1107. }
  1108. }
  1109. { // Set kern_value
  1110. Integer N = eval_coord.Dim() / DIM;
  1111. kern_value.ReInit(kdim[0] * N * kdim[1]);
  1112. kern_value.SetZero();
  1113. for (Integer j = 0; j < kdim[0]; j++) { // Evaluate ker
  1114. for (Integer k = 0; k < kdim[0]; k++) v_src[k] = 0.0;
  1115. v_src[j] = 1.0;
  1116. Vector<ValueType> ker_value(N * kdim[1], kern_value.begin() + j * N * kdim[1], false);
  1117. ker(r_src, n_src, v_src, eval_coord, ker_value);
  1118. }
  1119. { // Transpose
  1120. v0.ReInit(kern_value.Dim());
  1121. for (Integer k = 0; k < v0.Dim(); k++) v0[k] = kern_value[k];
  1122. Matrix<ValueType> M0(kdim[0], N * kdim[1], v0.begin(), false);
  1123. Matrix<ValueType> M1(N * kdim[1], kdim[0], kern_value.begin(), false);
  1124. for (Integer l0 = 0; l0 < M1.Dim(0); l0++) { // Transpose
  1125. for (Integer l1 = 0; l1 < M1.Dim(1); l1++) {
  1126. M1[l0][l1] = M0[l1][l0];
  1127. }
  1128. }
  1129. }
  1130. }
  1131. { // Set Update M
  1132. Matrix<ValueType> Mkern(eval_mesh[SUBDIM - 1].Dim(), kern_value.Dim() / eval_mesh[SUBDIM - 1].Dim(), kern_value.begin(), false);
  1133. for (Integer k = SUBDIM - 1; k >= 0; k--) { // Compute v0
  1134. Matrix<ValueType> Mpoly(order, eval_mesh[k].Dim(), eval_poly[k].begin(), false);
  1135. v1.ReInit(Mpoly.Dim(0) * Mkern.Dim(1));
  1136. Matrix<ValueType> Mcoef(Mpoly.Dim(0), Mkern.Dim(1), v1.begin(), false);
  1137. Matrix<ValueType>::GEMM(Mcoef, Mpoly, Mkern);
  1138. v0.ReInit(v1.Dim());
  1139. Matrix<ValueType> Mt(Mkern.Dim(1), Mpoly.Dim(0), v0.begin(), false);
  1140. for (Integer l0 = 0; l0 < Mt.Dim(0); l0++) { // Transpose
  1141. for (Integer l1 = 0; l1 < Mt.Dim(1); l1++) {
  1142. Mt[l0][l1] = Mcoef[l1][l0];
  1143. }
  1144. }
  1145. if (k > 0) { // Reinit Mkern
  1146. Mkern.ReInit(eval_mesh[k - 1].Dim(), v0.Dim() / eval_mesh[k - 1].Dim(), v0.begin(), false);
  1147. }
  1148. }
  1149. assert(v0.Dim() == Mtensor.Dim(0) * Mtensor.Dim(1));
  1150. for (Integer k = 0; k < v0.Dim(); k++) { // Update M
  1151. Mtensor[0][k] += v0[k];
  1152. }
  1153. }
  1154. }
  1155. if (r[i0] < 0.0) break;
  1156. }
  1157. }
  1158. Mtensor = Mtensor.Transpose();
  1159. { // Set Mcoeff
  1160. if (Mcoeff.Dim(0) != kdim[1] || Mcoeff.Dim(1) != kdim[0] * Ncoeff) {
  1161. Mcoeff.ReInit(kdim[1], kdim[0] * Ncoeff);
  1162. }
  1163. Vector<ValueType> Mtensor_(Mtensor.Dim(0) * Mtensor.Dim(1), Mtensor.begin(), false);
  1164. Vector<ValueType> Mcoeff_(Mcoeff.Dim(0) * Mcoeff.Dim(1), Mcoeff.begin(), false);
  1165. tensor2coeff<SUBDIM>(order, Mtensor_, Mcoeff_);
  1166. }
  1167. }
  1168. static void diff_1d(Integer order, Matrix<ValueType>* M) {
  1169. Vector<ValueType> nodes;
  1170. Nodes<1>(order, nodes);
  1171. Integer N = nodes.Dim();
  1172. Matrix<ValueType> M0(N, N);
  1173. for (Integer i = 0; i < N; i++) {
  1174. for (Integer j = 0; j < N; j++) {
  1175. M0[i][j] = 0;
  1176. for (Integer l = 0; l < N; l++) {
  1177. if (l != i) {
  1178. ValueType Mij = 1;
  1179. for (Integer k = 0; k < N; k++) {
  1180. if (k != i) {
  1181. if (l == k) {
  1182. Mij *= 1 / (nodes[i] - nodes[k]);
  1183. } else {
  1184. Mij *= (nodes[j] - nodes[k]) / (nodes[i] - nodes[k]);
  1185. }
  1186. }
  1187. }
  1188. M0[i][j] += Mij;
  1189. }
  1190. }
  1191. }
  1192. }
  1193. Vector<ValueType> p;
  1194. Derived::EvalBasis1D(order, nodes, p);
  1195. Matrix<ValueType> Mp(order, N, p.begin(), false);
  1196. M0 = Mp * M0;
  1197. Vector<ValueType> coeff;
  1198. Approx<1>(order, Vector<ValueType>(M0.Dim(0) * M0.Dim(1), M0.begin(), false), coeff);
  1199. (*M) = Matrix<ValueType>(M0.Dim(0), coeff.Dim() / M0.Dim(0), coeff.begin(), false);
  1200. }
  1201. template <Integer DIM> static void Approx_deprecated(Integer order, const Vector<ValueType>& fn_v, Vector<ValueType>& coeff, ValueType scale) {
  1202. Matrix<ValueType> Mp;
  1203. { // Precompute
  1204. static Vector<Matrix<ValueType>> precomp(1000);
  1205. SCTL_ASSERT(order < precomp.Dim());
  1206. if (precomp[order].Dim(0) * precomp[order].Dim(1) == 0) {
  1207. #pragma omp critical(BASIS_APPROX)
  1208. if (precomp[order].Dim(0) * precomp[order].Dim(1) == 0) {
  1209. Vector<ValueType> x, p;
  1210. Derived::Nodes1D(order, x);
  1211. for (Integer i = 0; i < order; i++) x[i] = (x[i] - 0.5) * scale + 0.5;
  1212. Derived::EvalBasis1D(order, x, p);
  1213. Matrix<ValueType> Mp1(order, order, p.begin(), false);
  1214. Mp1.pinv().Swap(precomp[order]);
  1215. }
  1216. }
  1217. Mp.ReInit(precomp[order].Dim(0), precomp[order].Dim(1), precomp[order].begin(), false);
  1218. }
  1219. Integer order_DIM = pow<Integer>(order, DIM);
  1220. Integer order_DIM_ = pow<Integer>(order, DIM - 1);
  1221. Long dof = fn_v.Dim() / order_DIM;
  1222. SCTL_ASSERT(fn_v.Dim() == dof * order_DIM);
  1223. // Create work buffers
  1224. Long buff_size = dof * order_DIM;
  1225. Vector<ValueType> buff(2 * buff_size);
  1226. Iterator<ValueType> buff1 = buff.begin() + buff_size * 0;
  1227. Iterator<ValueType> buff2 = buff.begin() + buff_size * 1;
  1228. Vector<ValueType> fn(order_DIM * dof, (Iterator<ValueType>)fn_v.begin(), false);
  1229. for (Integer k = 0; k < DIM; k++) { // Apply Mp along k-dimension
  1230. Matrix<ValueType> Mi(dof * order_DIM_, order, fn.begin(), false);
  1231. Matrix<ValueType> Mo(dof * order_DIM_, order, buff2, false);
  1232. Matrix<ValueType>::GEMM(Mo, Mi, Mp);
  1233. Matrix<ValueType> Mo_t(order, dof * order_DIM_, buff1, false);
  1234. for (Long i = 0; i < Mo.Dim(0); i++) {
  1235. for (Long j = 0; j < Mo.Dim(1); j++) {
  1236. Mo_t[j][i] = Mo[i][j];
  1237. }
  1238. }
  1239. fn.ReInit(order_DIM * dof, buff1, false);
  1240. }
  1241. { // Rearrange and write to coeff
  1242. Vector<ValueType> tensor(order_DIM * dof, buff1, false);
  1243. tensor2coeff<DIM>(order, tensor, coeff);
  1244. }
  1245. }
  1246. friend Derived;
  1247. };
  1248. template <class ValueType> class ChebBasis : public BasisInterface<ValueType, ChebBasis<ValueType>> {
  1249. private:
  1250. ChebBasis();
  1251. static void Nodes1D(Integer order, Vector<ValueType>& nodes) { BasisInterface<ValueType, ChebBasis<ValueType>>::cheb_nodes_1d(order, nodes); }
  1252. /**
  1253. * \brief Returns the values of all Chebyshev polynomials up to degree d,
  1254. * evaluated at points in the input vector. Output format:
  1255. * { T0[x[0]], ..., T0[x[n-1]], T1[x[0]], ..., Td[x[n-1]] }
  1256. */
  1257. static void EvalBasis1D(Integer order, const Vector<ValueType>& x, Vector<ValueType>& y) { BasisInterface<ValueType, ChebBasis<ValueType>>::cheb_basis_1d(order, x, y); }
  1258. friend BasisInterface<ValueType, ChebBasis<ValueType>>;
  1259. };
  1260. } // end namespace
  1261. #endif //_SCTL_CHEB_UTILS_HPP_