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Nov 11th, 2013
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  1. x = 1
  2. x =
  3.  
  4. 1.00000
  5. 1.00000
  6.  
  7. x =
  8.  
  9. 1.00000
  10. 1.00000
  11. 1.00000
  12.  
  13. x =
  14.  
  15. 1.00000
  16. 1.00000
  17. 1.00000
  18. 1.00000
  19.  
  20. x =
  21.  
  22. 1.00000
  23. 1.00000
  24. 1.00000
  25. 1.00000
  26. 1.00000
  27.  
  28. x =
  29.  
  30. 1.00000
  31. 1.00000
  32. 1.00000
  33. 1.00000
  34. 1.00000
  35. 1.00000
  36.  
  37. x =
  38.  
  39. 1.00000
  40. 1.00000
  41. 1.00000
  42. 1.00000
  43. 1.00000
  44. 1.00000
  45. 1.00000
  46.  
  47. x =
  48.  
  49. 1.00000
  50. 1.00000
  51. 1.00000
  52. 1.00000
  53. 1.00000
  54. 1.00000
  55. 1.00000
  56. 1.00000
  57.  
  58. x =
  59.  
  60. 1.00000
  61. 1.00000
  62. 1.00000
  63. 1.00000
  64. 0.99999
  65. 1.00002
  66. 0.99998
  67. 1.00001
  68. 1.00000
  69.  
  70. x =
  71.  
  72. 1.00000
  73. 1.00000
  74. 1.00000
  75. 1.00002
  76. 0.99992
  77. 1.00023
  78. 0.99962
  79. 1.00037
  80. 0.99981
  81. 1.00004
  82.  
  83. x =
  84.  
  85. 1.00000
  86. 1.00000
  87. 0.99999
  88. 1.00011
  89. 0.99936
  90. 1.00225
  91. 0.99513
  92. 1.00662
  93. 0.99452
  94. 1.00253
  95. 0.99950
  96.  
  97. warning: matrix singular to machine precision, rcond = 2.40932e-17
  98. warning: matrix singular to machine precision, rcond = 2.63277e-17
  99. x =
  100.  
  101. 1.00000
  102. 1.00000
  103. 1.00000
  104. 1.00004
  105. 0.99980
  106. 1.00059
  107. 0.99906
  108. 1.00065
  109. 1.00028
  110. 0.99914
  111. 1.00059
  112. 0.99986
  113.  
  114. warning: matrix singular to machine precision, rcond = 2.33995e-18
  115. x =
  116.  
  117. 1.00000
  118. 1.00000
  119. 1.00005
  120. 0.99940
  121. 1.00404
  122. 0.98418
  123. 1.03669
  124. 0.95259
  125. 1.02186
  126. 1.02534
  127. 0.95500
  128. 1.02675
  129. 0.99409
  130.  
  131. warning: matrix singular to machine precision, rcond = 1.70819e-19
  132. x =
  133.  
  134. 1.00000
  135. 1.00000
  136. 0.99997
  137. 1.00036
  138. 0.99784
  139. 1.00736
  140. 0.98608
  141. 1.01190
  142. 1.00272
  143. 0.98795
  144. 1.00135
  145. 1.01224
  146. 0.98948
  147. 1.00277
  148.  
  149. warning: matrix singular to machine precision, rcond = 1.5434e-18
  150. x =
  151.  
  152. 1.00000
  153. 1.00000
  154. 0.99999
  155. 1.00007
  156. 0.99964
  157. 1.00106
  158. 0.99838
  159. 1.00079
  160. 1.00094
  161. 0.99914
  162. 0.99913
  163. 1.00077
  164. 1.00094
  165. 0.99876
  166. 1.00038
  167.  
  168. warning: matrix singular to machine precision, rcond = 4.6391e-19
  169. x =
  170.  
  171. 1.00000
  172. 1.00000
  173. 1.00004
  174. 0.99942
  175. 1.00412
  176. 0.98358
  177. 1.03729
  178. 0.95762
  179. 1.00584
  180. 1.03373
  181. 0.98828
  182. 0.96860
  183. 1.01155
  184. 1.03422
  185. 0.96659
  186. 1.00911
  187.  
  188. warning: matrix singular to machine precision, rcond = 4.70916e-19
  189. x =
  190.  
  191. 1.00000
  192. 1.00000
  193. 1.00000
  194. 0.99998
  195. 1.00011
  196. 0.99957
  197. 1.00089
  198. 0.99918
  199. 0.99982
  200. 1.00077
  201. 1.00017
  202. 0.99930
  203. 0.99962
  204. 1.00063
  205. 1.00055
  206. 0.99911
  207. 1.00029
  208.  
  209. warning: matrix singular to machine precision, rcond = 5.83708e-20
  210. x =
  211.  
  212. 1.00000
  213. 1.00000
  214. 0.99999
  215. 1.00013
  216. 0.99924
  217. 1.00245
  218. 0.99585
  219. 1.00246
  220. 1.00213
  221. 0.99778
  222. 0.99778
  223. 1.00119
  224. 1.00263
  225. 1.00022
  226. 0.99741
  227. 0.99869
  228. 1.00317
  229. 0.99887
  230.  
  231. warning: matrix singular to machine precision, rcond = 2.20517e-19
  232. x =
  233.  
  234. 1.00000
  235. 1.00000
  236. 0.99997
  237. 1.00039
  238. 0.99777
  239. 1.00691
  240. 0.98930
  241. 1.00451
  242. 1.00698
  243. 0.99645
  244. 0.99290
  245. 0.99971
  246. 1.00638
  247. 1.00478
  248. 0.99714
  249. 0.99289
  250. 0.99883
  251. 1.00876
  252. 0.99633
  253.  
  254. warning: matrix singular to machine precision, rcond = 1.99525e-19
  255. x =
  256.  
  257. 1.00000
  258. 1.00000
  259. 0.99990
  260. 1.00145
  261. 0.98955
  262. 1.04203
  263. 0.90607
  264. 1.09790
  265. 1.00511
  266. 0.91738
  267. 0.99031
  268. 1.07035
  269. 1.04208
  270. 0.95451
  271. 0.93490
  272. 0.99866
  273. 1.07084
  274. 1.03788
  275. 0.90837
  276. 1.03270
  277.  
  278. x = 1
  279. x =
  280.  
  281. 1.00000
  282. 1.00000
  283.  
  284. x =
  285.  
  286. 1.00000
  287. 1.00000
  288. 1.00000
  289.  
  290. x =
  291.  
  292. 1.00000
  293. 1.00000
  294. 1.00000
  295. 1.00000
  296.  
  297. x =
  298.  
  299. 1.00000
  300. 1.00000
  301. 1.00000
  302. 1.00000
  303. 1.00000
  304.  
  305. x =
  306.  
  307. 1.00000
  308. 1.00000
  309. 1.00000
  310. 1.00000
  311. 1.00000
  312. 1.00000
  313.  
  314. x =
  315.  
  316. 1.00000
  317. 1.00000
  318. 1.00000
  319. 1.00000
  320. 1.00000
  321. 1.00000
  322. 1.00000
  323.  
  324. x =
  325.  
  326. 1.00000
  327. 1.00000
  328. 1.00000
  329. 1.00000
  330. 1.00000
  331. 1.00000
  332. 1.00000
  333. 1.00000
  334.  
  335. x =
  336.  
  337. 1.00000
  338. 1.00000
  339. 1.00000
  340. 1.00002
  341. 0.99990
  342. 1.00020
  343. 0.99975
  344. 1.00014
  345. 0.99997
  346.  
  347. x =
  348.  
  349. 1.00000
  350. 1.00000
  351. 0.99996
  352. 1.00043
  353. 0.99789
  354. 1.00531
  355. 0.99103
  356. 1.00809
  357. 0.99573
  358. 1.00100
  359.  
  360. x =
  361.  
  362. 1.00000
  363. 1.00000
  364. 0.99995
  365. 1.00026
  366. 0.99902
  367. 1.00586
  368. 1.00684
  369. 1.02441
  370. 1.01074
  371. 0.99756
  372. 0.99915
  373.  
  374. warning: inverse: matrix singular to machine precision, rcond = 2.40932e-17
  375. x =
  376.  
  377. 1.00000
  378. 0.99966
  379. 1.01082
  380. 0.84851
  381. 2.11133
  382. -4.08984
  383. 15.62500
  384. -26.18750
  385. 32.78125
  386. -22.21875
  387. 10.99219
  388. -0.76855
  389.  
  390. warning: inverse: matrix singular to machine precision, rcond = 2.33995e-18
  391. x =
  392.  
  393. 1.00000
  394. 1.00000
  395. 1.00017
  396. 1.00171
  397. 0.90625
  398. 1.28906
  399. 2.43750
  400. 2.00000
  401. 2.87500
  402. -0.75000
  403. 0.12500
  404. 0.31250
  405. 1.18750
  406.  
  407. warning: inverse: matrix singular to machine precision, rcond = 1.70819e-19
  408. x =
  409.  
  410. 1.00000
  411. 1.00022
  412. 0.99878
  413. 1.06250
  414. 0.82031
  415. 1.84375
  416. 0.11719
  417. -12.00000
  418. 51.00000
  419. -54.00000
  420. 110.00000
  421. -70.00000
  422. 12.00000
  423. -6.37500
  424.  
  425. warning: inverse: matrix singular to machine precision, rcond = 1.5434e-18
  426. x =
  427.  
  428. 1.00000
  429. 1.00001
  430. 0.99907
  431. 1.00806
  432. 1.00781
  433. 1.38672
  434. 1.84180
  435. 0.81250
  436. 0.37500
  437. -8.00000
  438. 13.00000
  439. -6.25000
  440. 7.18750
  441. 1.51562
  442. 0.71875
  443.  
  444. warning: inverse: matrix singular to machine precision, rcond = 4.6391e-19
  445. x =
  446.  
  447. 1.00000
  448. 1.00000
  449. 1.00024
  450. 0.98047
  451. 1.32812
  452. 0.12500
  453. 6.00000
  454. -5.00000
  455. 9.25000
  456. -3.75000
  457. 9.25000
  458. -10.50000
  459. 57.00000
  460. -23.00000
  461. 4.50000
  462. 0.50000
  463.  
  464. warning: inverse: matrix singular to machine precision, rcond = 4.70916e-19
  465. x =
  466.  
  467. 1.00000
  468. 0.99996
  469. 1.00061
  470. 1.00977
  471. 1.12500
  472. 0.84375
  473. 2.37500
  474. -0.50000
  475. 1.87500
  476. -13.00000
  477. 15.00000
  478. -0.87500
  479. 10.00000
  480. 0.12500
  481. 6.75000
  482. -3.12500
  483. 2.18750
  484.  
  485. warning: inverse: matrix singular to machine precision, rcond = 5.83708e-20
  486. x =
  487.  
  488. 1.00000
  489. 0.99998
  490. 0.99951
  491. 0.99414
  492. 0.89062
  493. -0.25000
  494. 12.00000
  495. -18.00000
  496. 26.00000
  497. -21.00000
  498. 7.00000
  499. -7.93750
  500. -7.00000
  501. -12.00000
  502. 48.00000
  503. -48.00000
  504. 88.00000
  505. 2.00000
  506.  
  507. warning: inverse: matrix singular to machine precision, rcond = 2.20517e-19
  508. x =
  509.  
  510. 1.00000
  511. 1.00000
  512. 1.00118
  513. 0.99292
  514. 1.23828
  515. 0.92188
  516. 11.25000
  517. -3.00000
  518. 8.75000
  519. -8.87500
  520. -0.25000
  521. -12.56250
  522. 1.71875
  523. -16.00000
  524. -6.00000
  525. 120.00000
  526. -3.50000
  527. 23.68750
  528. 1.75000
  529.  
  530. warning: inverse: matrix singular to machine precision, rcond = 1.99525e-19
  531. x =
  532.  
  533. 1.00000
  534. 1.00002
  535. 0.99854
  536. 1.01270
  537. 0.88281
  538. -0.31250
  539. 1.50000
  540. -7.75000
  541. 7.25000
  542. -11.75000
  543. -4.25000
  544. 5.50000
  545. 8.00000
  546. 15.00000
  547. -8.00000
  548. -40.00000
  549. -20.00000
  550. -60.00000
  551. 18.00000
  552. 3.37500
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