MatFileIO.cpp 17 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624625626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668
  1. /**
  2. * @file MatFileIO.cpp
  3. * @brief Read and write mat-files
  4. * @author Paul Bodesheim
  5. * @date 06-01-2012 (dd-mm-yyyy)
  6. */
  7. #include "MatFileIO.h"
  8. namespace NICE {
  9. //------------------------------------------------------
  10. // several constructors and destructors
  11. //------------------------------------------------------
  12. // Default constructor
  13. MatFileIO::MatFileIO() { mat = 0; }
  14. // Recommended constructor
  15. MatFileIO::MatFileIO(std::string _filename, const mat_acc mode) {
  16. mat = Mat_Open(_filename.c_str(),mode);
  17. if (mat == NULL && mode == MAT_ACC_RDONLY) {
  18. fthrow(Exception, "MatFileIO::MatFileIO(const char * _filename, int mode): mat-file does not exist");
  19. }
  20. }
  21. // Default destructor
  22. MatFileIO::~MatFileIO() {
  23. Mat_Close(mat);
  24. }
  25. //------------------------------------------------------
  26. // count number of stored variables
  27. //------------------------------------------------------
  28. int MatFileIO::getNumberOfVariables() {
  29. Mat_Rewind(mat); // get back to first variable
  30. int count = 0;
  31. matvar_t * matvar = Mat_VarReadNextInfo(mat);
  32. while (matvar != NULL) {
  33. count++;
  34. matvar = Mat_VarReadNextInfo(mat);
  35. }
  36. Mat_VarFree(matvar);
  37. return count;
  38. }
  39. //------------------------------------------------------
  40. // several methods for reading data
  41. //------------------------------------------------------
  42. matvar_t * MatFileIO::getVariableViaName(std::string _name) {
  43. return Mat_VarRead(mat,_name.c_str());
  44. }
  45. void MatFileIO::getSparseVariableViaName(sparse_t & sparseVariable, std::string _name) {
  46. matvar_t * matvar = getVariableViaName(_name);
  47. if (matvar == NULL) {
  48. fthrow(Exception, "MatFileIO::getSparseVariableViaName(sparse_t & sparseVariable, std::string _name): variable with specified name does not exist");
  49. return;
  50. }
  51. if (matvar->class_type != MAT_C_SPARSE) {
  52. Mat_VarFree(matvar);
  53. fthrow(Exception, "MatFileIO::getSparseVariableViaName(sparse_t & sparseVariable, std::string _name): format of variable is not sparse");
  54. return;
  55. }
  56. sparse_t * sparse_ptr = (sparse_t*) matvar->data;
  57. sparse_ptr->data = (double*) sparse_ptr->data;
  58. sparseVariable = *sparse_ptr;
  59. matvar->data = NULL;
  60. Mat_VarFree(matvar);
  61. free(sparse_ptr);
  62. }
  63. void MatFileIO::getFeatureMatrixViaName(std::vector<std::vector<double> > & features, std::string _name, const feature_matrix_order order) {
  64. matvar_t * matvar = getVariableViaName(_name);
  65. if (matvar == NULL) {
  66. fthrow(Exception, "MatFileIO::getFeatureMatrixViaName(char * _name, feature_matrix_order order): variable with specified name does not exist");
  67. return;
  68. }
  69. if (matvar->rank != 2) {
  70. Mat_VarFree(matvar);
  71. fthrow(Exception, "MatFileIO::getFeatureMatrixViaName(char * _name, feature_matrix_order order): dimension of variable != 2");
  72. return;
  73. }
  74. features.clear();
  75. std::vector<double> currentFeature;
  76. currentFeature.clear();
  77. // case 1: feature vectors in the rows of matrix
  78. if (order == NxD) {
  79. // depending on the class type of data elements, we have to treat several cases and cast the data elements correctly
  80. switch (matvar->data_type) {
  81. case MAT_T_DOUBLE:
  82. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  83. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  84. currentFeature.push_back( ((double*)matvar->data)[matvar->dims[0]*j+i] );
  85. }
  86. features.push_back(currentFeature);
  87. currentFeature.clear();
  88. }
  89. break;
  90. case MAT_T_SINGLE:
  91. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  92. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  93. currentFeature.push_back( ((float*)matvar->data)[matvar->dims[0]*j+i] );
  94. }
  95. features.push_back(currentFeature);
  96. currentFeature.clear();
  97. }
  98. break;
  99. #ifdef HAVE_MAT_INT64_T
  100. case MAT_T_INT64:
  101. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  102. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  103. currentFeature.push_back( ((signed long long*)matvar->data)[matvar->dims[0]*j+i] );
  104. }
  105. features.push_back(currentFeature);
  106. currentFeature.clear();
  107. }
  108. break;
  109. #endif
  110. #ifdef HAVE_MAT_UINT64_T
  111. case MAT_T_UINT64:
  112. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  113. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  114. currentFeature.push_back( ((unsigned long long*)matvar->data)[matvar->dims[0]*j+i] );
  115. }
  116. features.push_back(currentFeature);
  117. currentFeature.clear();
  118. }
  119. break;
  120. #endif
  121. case MAT_T_INT32:
  122. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  123. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  124. currentFeature.push_back( ((signed long*)matvar->data)[matvar->dims[0]*j+i] );
  125. }
  126. features.push_back(currentFeature);
  127. currentFeature.clear();
  128. }
  129. break;
  130. case MAT_T_UINT32:
  131. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  132. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  133. currentFeature.push_back( ((unsigned long*)matvar->data)[matvar->dims[0]*j+i] );
  134. }
  135. features.push_back(currentFeature);
  136. currentFeature.clear();
  137. }
  138. break;
  139. case MAT_T_INT16:
  140. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  141. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  142. currentFeature.push_back( ((signed short*)matvar->data)[matvar->dims[0]*j+i] );
  143. }
  144. features.push_back(currentFeature);
  145. currentFeature.clear();
  146. }
  147. break;
  148. case MAT_T_UINT16:
  149. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  150. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  151. currentFeature.push_back( ((unsigned short*)matvar->data)[matvar->dims[0]*j+i] );
  152. }
  153. features.push_back(currentFeature);
  154. currentFeature.clear();
  155. }
  156. break;
  157. case MAT_T_INT8:
  158. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  159. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  160. currentFeature.push_back( ((signed char*)matvar->data)[matvar->dims[0]*j+i] );
  161. }
  162. features.push_back(currentFeature);
  163. currentFeature.clear();
  164. }
  165. break;
  166. case MAT_T_UINT8:
  167. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  168. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  169. currentFeature.push_back( ((unsigned char*)matvar->data)[matvar->dims[0]*j+i] );
  170. }
  171. features.push_back(currentFeature);
  172. currentFeature.clear();
  173. }
  174. break;
  175. }
  176. // case 2: feature vectors in the columns of matrix
  177. } else if (order == DxN) {
  178. // depending on the class type of data elements, we have to treat several cases and cast the data elements correctly
  179. switch (matvar->data_type) {
  180. case MAT_T_DOUBLE:
  181. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  182. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  183. currentFeature.push_back( ((double*)matvar->data)[matvar->dims[0]*j+i] );
  184. }
  185. features.push_back(currentFeature);
  186. currentFeature.clear();
  187. }
  188. break;
  189. case MAT_T_SINGLE:
  190. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  191. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  192. currentFeature.push_back( ((float*)matvar->data)[matvar->dims[0]*j+i] );
  193. }
  194. features.push_back(currentFeature);
  195. currentFeature.clear();
  196. }
  197. break;
  198. #ifdef HAVE_MAT_INT64_T
  199. case MAT_T_INT64:
  200. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  201. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  202. currentFeature.push_back( ((signed long long*)matvar->data)[matvar->dims[0]*j+i] );
  203. }
  204. features.push_back(currentFeature);
  205. currentFeature.clear();
  206. }
  207. break;
  208. #endif
  209. #ifdef HAVE_MAT_UINT64_T
  210. case MAT_T_UINT64:
  211. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  212. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  213. currentFeature.push_back( ((unsigned long long*)matvar->data)[matvar->dims[0]*j+i] );
  214. }
  215. features.push_back(currentFeature);
  216. currentFeature.clear();
  217. }
  218. break;
  219. #endif
  220. case MAT_T_INT32:
  221. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  222. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  223. currentFeature.push_back( ((signed long*)matvar->data)[matvar->dims[0]*j+i] );
  224. }
  225. features.push_back(currentFeature);
  226. currentFeature.clear();
  227. }
  228. break;
  229. case MAT_T_UINT32:
  230. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  231. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  232. currentFeature.push_back( ((unsigned long*)matvar->data)[matvar->dims[0]*j+i] );
  233. }
  234. features.push_back(currentFeature);
  235. currentFeature.clear();
  236. }
  237. break;
  238. case MAT_T_INT16:
  239. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  240. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  241. currentFeature.push_back( ((signed short*)matvar->data)[matvar->dims[0]*j+i] );
  242. }
  243. features.push_back(currentFeature);
  244. currentFeature.clear();
  245. }
  246. break;
  247. case MAT_T_UINT16:
  248. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  249. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  250. currentFeature.push_back( ((unsigned short*)matvar->data)[matvar->dims[0]*j+i] );
  251. }
  252. features.push_back(currentFeature);
  253. currentFeature.clear();
  254. }
  255. break;
  256. case MAT_T_INT8:
  257. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  258. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  259. currentFeature.push_back( ((signed char*)matvar->data)[matvar->dims[0]*j+i] );
  260. }
  261. features.push_back(currentFeature);
  262. currentFeature.clear();
  263. }
  264. break;
  265. case MAT_T_UINT8:
  266. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  267. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  268. currentFeature.push_back( ((unsigned char*)matvar->data)[matvar->dims[0]*j+i] );
  269. }
  270. features.push_back(currentFeature);
  271. currentFeature.clear();
  272. }
  273. break;
  274. }
  275. } else {
  276. Mat_VarFree(matvar);
  277. fthrow(Exception, "MatFileIO::getFeatureMatrixViaName(char * _name, feature_matrix_order order): wrong feature_matrix_order specified");
  278. return;
  279. }
  280. Mat_VarFree(matvar);
  281. }
  282. void MatFileIO::getVectorViaName(NICE::Vector & vec, std::string _name) {
  283. matvar_t * matvar = getVariableViaName(_name);
  284. if (matvar == NULL) {
  285. fthrow(Exception, "MatFileIO::getVectorViaName(NICE::Vector & vec, std::string _name): variable with specified name does not exist");
  286. return;
  287. }
  288. // it can happen that a vector is treated as (N x 1) or (1 x N) matrix with two dimensions
  289. if (matvar->rank > 2 || ( (matvar->rank == 2) && (matvar->dims[0] != 1) && (matvar->dims[1] != 1) ) ) {
  290. Mat_VarFree(matvar);
  291. fthrow(Exception, "MatFileIO::getVectorViaName(NICE::Vector & vec, std::string _name): dimension of variable > 1");
  292. return;
  293. }
  294. std::vector<double> v;
  295. v.clear();
  296. // vector is stored as a variable with one dimensional
  297. if (matvar->rank == 1) {
  298. switch( matvar->data_type ) {
  299. case MAT_T_DOUBLE:
  300. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  301. v.push_back( ((double*)matvar->data)[i] );
  302. }
  303. break;
  304. case MAT_T_SINGLE:
  305. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  306. v.push_back( ((float*)matvar->data)[i] );
  307. }
  308. break;
  309. #ifdef HAVE_MAT_INT64_T
  310. case MAT_T_INT64:
  311. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  312. v.push_back( ((signed long long*)matvar->data)[i] );
  313. }
  314. break;
  315. #endif
  316. #ifdef HAVE_MAT_UINT64_T
  317. case MAT_T_UINT64:
  318. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  319. v.push_back( ((unsigned long long*)matvar->data)[i] );
  320. }
  321. break;
  322. #endif
  323. case MAT_T_INT32:
  324. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  325. v.push_back( ((signed long*)matvar->data)[i] );
  326. }
  327. break;
  328. case MAT_T_UINT32:
  329. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  330. v.push_back( ((unsigned long*)matvar->data)[i] );
  331. }
  332. break;
  333. case MAT_T_INT16:
  334. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  335. v.push_back( ((signed short*)matvar->data)[i] );
  336. }
  337. break;
  338. case MAT_T_UINT16:
  339. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  340. v.push_back( ((unsigned short*)matvar->data)[i] );
  341. }
  342. break;
  343. case MAT_T_INT8:
  344. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  345. v.push_back( ((signed char*)matvar->data)[i] );
  346. }
  347. break;
  348. case MAT_T_UINT8:
  349. for ( int i = 0; i < matvar->nbytes/matvar->data_size; i++ ) {
  350. v.push_back( ((unsigned char*)matvar->data)[i] );
  351. }
  352. break;
  353. }
  354. // it can happen that a vector is treated as (N x 1) or (1 x N) matrix with two dimensions, here we handle this case
  355. } else {
  356. switch( matvar->data_type ) {
  357. case MAT_T_DOUBLE:
  358. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  359. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  360. v.push_back( ((double*)matvar->data)[matvar->dims[0]*j+i] );
  361. }
  362. }
  363. break;
  364. case MAT_T_SINGLE:
  365. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  366. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  367. v.push_back( ((float*)matvar->data)[matvar->dims[0]*j+i] );
  368. }
  369. }
  370. break;
  371. #ifdef HAVE_MAT_INT64_T
  372. case MAT_T_INT64:
  373. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  374. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  375. v.push_back( ((signed long long*)matvar->data)[matvar->dims[0]*j+i] );
  376. }
  377. }
  378. break;
  379. #endif
  380. #ifdef HAVE_MAT_UINT64_T
  381. case MAT_T_UINT64:
  382. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  383. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  384. v.push_back( ((unsigned long long*)matvar->data)[matvar->dims[0]*j+i] );
  385. }
  386. }
  387. break;
  388. #endif
  389. case MAT_T_INT32:
  390. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  391. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  392. v.push_back( ((signed long*)matvar->data)[matvar->dims[0]*j+i] );
  393. }
  394. }
  395. break;
  396. case MAT_T_UINT32:
  397. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  398. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  399. v.push_back( ((unsigned long*)matvar->data)[matvar->dims[0]*j+i] );
  400. }
  401. }
  402. break;
  403. case MAT_T_INT16:
  404. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  405. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  406. v.push_back( ((signed short*)matvar->data)[matvar->dims[0]*j+i] );
  407. }
  408. }
  409. break;
  410. case MAT_T_UINT16:
  411. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  412. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  413. v.push_back( ((unsigned short*)matvar->data)[matvar->dims[0]*j+i] );
  414. }
  415. }
  416. break;
  417. case MAT_T_INT8:
  418. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  419. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  420. v.push_back( ((signed char*)matvar->data)[matvar->dims[0]*j+i] );
  421. }
  422. }
  423. break;
  424. case MAT_T_UINT8:
  425. for ( int i = 0; i < matvar->dims[0]; i++ ) {
  426. for ( int j = 0; j < matvar->dims[1]; j++ ) {
  427. v.push_back( ((unsigned char*)matvar->data)[matvar->dims[0]*j+i] );
  428. }
  429. }
  430. break;
  431. }
  432. }
  433. vec = NICE::Vector(v);
  434. Mat_VarFree(matvar);
  435. }
  436. }