exercise10 n = 5 tries = 100 A norm: estimate = 1.0 np.linalg.norm = 1.0 Ainv norm: estimate = 1.0 np.linalg.norm = 1.0000000000000002 A cond: estimate = 1.0 np.linalg.cond = 1.0000000000000002 n = 10 tries = 100 A norm: estimate = 1.0000000000000002 np.linalg.norm = 1.0000000000000002 Ainv norm: estimate = 1.0 np.linalg.norm = 1.0000000000000002 A cond: estimate = 1.0000000000000002 np.linalg.cond = 1.0000000000000004 n = 15 tries = 100 A norm: estimate = 0.9999999999999999 np.linalg.norm = 1.0000000000000004 Ainv norm: estimate = 1.0 np.linalg.norm = 1.0000000000000004 A cond: estimate = 0.9999999999999999 np.linalg.cond = 1.0000000000000009 n = 20 tries = 100 A norm: estimate = 1.0000000000000002 np.linalg.norm = 1.0000000000000004 Ainv norm: estimate = 1.0 np.linalg.norm = 1.0000000000000004 A cond: estimate = 1.0000000000000002 np.linalg.cond = 1.0000000000000007 n = 25 tries = 100 A norm: estimate = 1.0 np.linalg.norm = 1.0000000000000004 Ainv norm: estimate = 0.9999999999999999 np.linalg.norm = 1.0000000000000004 A cond: estimate = 0.9999999999999999 np.linalg.cond = 1.0000000000000009 n = 30 tries = 100 A norm: estimate = 1.0000000000000002 np.linalg.norm = 1.0000000000000004 Ainv norm: estimate = 0.9999999999999999 np.linalg.norm = 1.0000000000000004 A cond: estimate = 1.0 np.linalg.cond = 1.0000000000000009 n = 5 tries = 100 A norm: estimate = 3.732050807568877 np.linalg.norm = 3.732050807568877 Ainv norm: estimate = 3.7320508075688776 np.linalg.norm = 3.7320508075688767 A cond: estimate = 13.92820323027551 np.linalg.cond = 13.928203230275507 n = 10 tries = 100 A norm: estimate = 3.918977980029259 np.linalg.norm = 3.918985947228995 Ainv norm: estimate = 12.34353751967706 np.linalg.norm = 12.343537519677058 A cond: estimate = 48.37405173527937 np.linalg.cond = 48.374150078708404 n = 15 tries = 100 A norm: estimate = 3.9613821387687773 np.linalg.norm = 3.9615705608064613 Ainv norm: estimate = 26.021717229954366 np.linalg.norm = 26.02171722995436 A cond: estimate = 103.08196585483297 np.linalg.cond = 103.0868689198178 n = 20 tries = 100 A norm: estimate = 3.975291290528627 np.linalg.norm = 3.977661652450257 Ainv norm: estimate = 44.76606865271506 np.linalg.norm = 44.76606865271504 A cond: estimate = 177.95816282634476 np.linalg.cond = 178.0642746108618 n = 25 tries = 100 A norm: estimate = 3.906546530562556 np.linalg.norm = 3.985417748196109 Ainv norm: estimate = 68.57651434417681 np.linalg.norm = 68.57651434417679 A cond: estimate = 267.8973441893173 np.linalg.cond = 273.30605737670663 n = 30 tries = 100 A norm: estimate = 3.987239001728478 np.linalg.norm = 3.9897386467837896 Ainv norm: estimate = 97.45303362331518 np.linalg.norm = 97.45303362331512 A cond: estimate = 388.56853649963904 np.linalg.cond = 388.8121344932645 n = 5 tries = 100 A norm: estimate = 7.487499930704985 np.linalg.norm = 7.487499930704985 Ainv norm: estimate = 115.65677868544822 np.linalg.norm = 115.65677868544822 A cond: estimate = 865.9801223928553 np.linalg.cond = 865.9801223928544 n = 10 tries = 100 A norm: estimate = 31.589809741896936 np.linalg.norm = 31.589809741896925 Ainv norm: estimate = 116511.99995639746 np.linalg.norm = 116511.99995639747 A cond: estimate = 3680591.9112704997 np.linalg.cond = 3680591.911002071 n = 15 tries = 100 A norm: estimate = 76.09201283263069 np.linalg.norm = 76.09201283263072 Ainv norm: estimate = 119304652.33333325 np.linalg.norm = 119304652.33333322 A cond: estimate = 9078131136.340536 np.linalg.cond = 9078131498.682262 n = 20 tries = 100 A norm: estimate = 140.89914669943323 np.linalg.norm = 140.8991466994332 Ainv norm: estimate = 122167958648.66666 np.linalg.norm = 122167958648.66666 A cond: estimate = 17213361127608.775 np.linalg.cond = 17211383215691.842 n = 25 tries = 100 A norm: estimate = 225.98645700983147 np.linalg.norm = 225.9864570098314 Ainv norm: estimate = 125099989649189.02 np.linalg.norm = 125099989649189.02 A cond: estimate = 2.8270903432786816e+16 np.linalg.cond = 3.116911086989939e+16 n = 30 tries = 100 A norm: estimate = 331.3457707363301 np.linalg.norm = 331.3457707363301 Ainv norm: estimate = 1.2810238940076077e+17 np.linalg.norm = 1.2810238940076078e+17 A cond: estimate = 4.244618494916056e+19 np.linalg.cond = 3.7850955922033165e+17 n = 5 tries = 100 A norm: estimate = 10.062902755702238 np.linalg.norm = 10.895619817649804 Ainv norm: estimate = 10.062902755702195 np.linalg.norm = 59.42464165603012 A cond: estimate = 101.26201187071926 np.linalg.cond = 647.4683032841803 n = 10 tries = 100 A norm: estimate = 25.575278721804455 np.linalg.norm = 34.72779921724885 Ainv norm: estimate = 25.575278711984982 np.linalg.norm = 821912.6741932059 A cond: estimate = 654.0948814468479 np.linalg.cond = 28543218.332289208 n = 15 tries = 100 A norm: estimate = 42.47629018610939 np.linalg.norm = 70.973205144322 Ainv norm: estimate = 42.46239724055971 np.linalg.norm = 193169372991.38367 A cond: estimate = 1803.6451071878648 np.linalg.cond = 13711897518805.227 n = 20 tries = 100 A norm: estimate = 60.033243242931725 np.linalg.norm = 119.64429934846746 Ainv norm: estimate = 36.68258249207942 np.linalg.norm = 5119496891727284.0 A cond: estimate = 2202.1743975259124 np.linalg.cond = 3.158317197308093e+17 n = 25 tries = 100 A norm: estimate = 77.98368606763356 np.linalg.norm = 180.75460141852253 Ainv norm: estimate = 6.018935526714121 np.linalg.norm = 2.5649060676592144e+16 A cond: estimate = 469.37877857660067 np.linalg.cond = 3.5116530399476716e+18 n = 30 tries = 100 A norm: estimate = 96.20062232657385 np.linalg.norm = 254.31201671904503 Ainv norm: estimate = 2.4237675542753587 np.linalg.norm = 2.4934132555478744e+16 A cond: estimate = 233.16794709624736 np.linalg.cond = 7.912411307116426e+17