#include <iostream>
#include <string>
#include <random>
#include <array>
#include <chrono>
#include <iomanip>

using namespace std;


array<float, 1600> randomnumbers = {
0.087689608335 , 0.019256826490 , 0.069453619421 , 0.067025110126 , 0.021043231711 , 0.033587388694 , 0.083239227533 , 0.011742727831 ,
0.050024010241 , 0.033509049565 , 0.026612102985 , 0.029627762735 , 0.043801158667 , 0.026102619246 , 0.016713805497 , 0.078916274011 ,
0.075892351568 , 0.012752453797 , 0.010492545553 , 0.098215453327 , 0.077127024531 , 0.063857689500 , 0.066082894802 , 0.025198820978 ,
0.036578901112 , 0.051618985832 , 0.020236346871 , 0.062257833779 , 0.087350353599 , 0.077401287854 , 0.083397977054 , 0.069831058383 ,
0.020533673465 , 0.019459091127 , 0.048951141536 , 0.091810673475 , 0.071908190846 , 0.010920760222 , 0.095227859914 , 0.084559679031 ,
0.064516827464 , 0.074339732528 , 0.017835870385 , 0.037455156446 , 0.018784150481 , 0.045206874609 , 0.071962803602 , 0.028839532286 ,
0.026009963825 , 0.079459398985 , 0.024113021791 , 0.057558842003 , 0.041398443282 , 0.053615272045 , 0.091859295964 , 0.079091019928 ,
0.042793452740 , 0.099563740194 , 0.057780340314 , 0.074154675007 , 0.057579360902 , 0.026275074109 , 0.035156831145 , 0.090875029564 ,
0.096631355584 , 0.093221917748 , 0.030689291656 , 0.064897559583 , 0.083190895617 , 0.099413029850 , 0.044733747840 , 0.040033459663 ,
0.062338255346 , 0.088953837752 , 0.027152974159 , 0.030029930174 , 0.053023055196 , 0.038526661694 , 0.027532642707 , 0.021131597459 ,
0.078735113144 , 0.090938992798 , 0.091561265290 , 0.020117569715 , 0.045997880399 , 0.046296872199 , 0.031501196325 , 0.030569467694 ,
0.031045878306 , 0.028074115515 , 0.031649973243 , 0.011071201414 , 0.013690388761 , 0.024367623031 , 0.016608621925 , 0.021105695516 ,
0.093413427472 , 0.099525645375 , 0.047419846058 , 0.095260165632 , 0.087628625333 , 0.074282482266 , 0.045628927648 , 0.055375993252 ,
0.074262984097 , 0.077898144722 , 0.064189933240 , 0.070275001228 , 0.011893828399 , 0.069569855928 , 0.040555670857 , 0.019180923700 ,
0.053778052330 , 0.037701986730 , 0.027224821970 , 0.067582748830 , 0.033238366246 , 0.067163296044 , 0.093539983034 , 0.066578544676 ,
0.075627349317 , 0.058851882815 , 0.083491317928 , 0.018568858504 , 0.026787340641 , 0.094813704491 , 0.053884223104 , 0.022072382271 ,
0.050509676337 , 0.096110798419 , 0.074125207961 , 0.012316224165 , 0.058780744672 , 0.057857200503 , 0.015935737640 , 0.051939815283 ,
0.012505761348 , 0.094335451722 , 0.025935405865 , 0.086372375488 , 0.020469410345 , 0.019377402961 , 0.025991059840 , 0.031742695719 ,
0.039473034441 , 0.093248769641 , 0.031997419894 , 0.090658470988 , 0.056987650692 , 0.071375899017 , 0.064772821963 , 0.056840211153 ,
0.023425381631 , 0.020372580737 , 0.011946289800 , 0.051302857697 , 0.017166655511 , 0.039981104434 , 0.082383789122 , 0.034305211157 ,
0.087662264705 , 0.099666669965 , 0.077774532139 , 0.056564308703 , 0.066337756813 , 0.078602336347 , 0.019442321733 , 0.037101827562 ,
0.020384581760 , 0.033673152328 , 0.084622830153 , 0.045915722847 , 0.015553466044 , 0.017102912068 , 0.048641391098 , 0.015817685053 ,
0.047826074064 , 0.082837969065 , 0.017671193928 , 0.059765636921 , 0.051028974354 , 0.093908667564 , 0.052930861712 , 0.018997114152 ,
0.024472419173 , 0.067919254303 , 0.018820807338 , 0.031308054924 , 0.024490779266 , 0.016529111192 , 0.034775137901 , 0.065709173679 ,
0.044011794031 , 0.056200779974 , 0.076547980309 , 0.051838420331 , 0.018259227276 , 0.042833514512 , 0.052902288735 , 0.078768119216 ,
0.015807593241 , 0.058219335973 , 0.072438940406 , 0.021168895066 , 0.075613193214 , 0.091001234949 , 0.057779505849 , 0.060114398599 ,
0.062733568251 , 0.072995215654 , 0.010579665191 , 0.032434128225 , 0.050419859588 , 0.026591762900 , 0.047753170133 , 0.027524374425 ,
0.062176369131 , 0.068191073835 , 0.087344743311 , 0.073131494224 , 0.051009126008 , 0.030384417623 , 0.070897139609 , 0.028169376776 ,
0.012707940303 , 0.072351671755 , 0.084563799202 , 0.043817996979 , 0.039092317224 , 0.084510996938 , 0.056402817369 , 0.052101008594 ,
0.021578749642 , 0.034041799605 , 0.070500403643 , 0.020203258842 , 0.046155162156 , 0.079813838005 , 0.041232720017 , 0.058274157345 ,
0.093776732683 , 0.085549131036 , 0.044253975153 , 0.076494060457 , 0.045693948865 , 0.068187117577 , 0.020804718137 , 0.074910566211 ,
0.071891665459 , 0.093203298748 , 0.077861644328 , 0.080598443747 , 0.087969549000 , 0.044162921607 , 0.076142489910 , 0.076775923371 ,
0.012924431823 , 0.020933188498 , 0.074101209641 , 0.058980137110 , 0.079153753817 , 0.017107056454 , 0.028302494437 , 0.089993149042 ,
0.034789972007 , 0.045105189085 , 0.072953298688 , 0.026070488617 , 0.016689864919 , 0.036557860672 , 0.057965859771 , 0.042219161987 ,
0.077433779836 , 0.089552074671 , 0.091792792082 , 0.041440881789 , 0.046881213784 , 0.042603954673 , 0.064635917544 , 0.095878966153 ,
0.047704346478 , 0.016925331205 , 0.034059152007 , 0.092132054269 , 0.073341496289 , 0.070594519377 , 0.072084665298 , 0.096970237792 ,
0.028746547177 , 0.083197347820 , 0.027834381908 , 0.052435740829 , 0.067467637360 , 0.078556828201 , 0.064634568989 , 0.073207303882 ,
0.065093517303 , 0.046759836376 , 0.072597488761 , 0.076015695930 , 0.015801768750 , 0.050338931382 , 0.016406899318 , 0.050762914121 ,
0.032324798405 , 0.012874213047 , 0.076905287802 , 0.027092160657 , 0.087940700352 , 0.099288582802 , 0.023223511875 , 0.047537028790 ,
0.084756754339 , 0.046800263226 , 0.031998582184 , 0.020120307803 , 0.092005424201 , 0.015130603686 , 0.020055877045 , 0.089129485190 ,
0.099234022200 , 0.096219725907 , 0.014837726951 , 0.047675259411 , 0.067990988493 , 0.054597198963 , 0.035076208413 , 0.085831388831 ,
0.018129512668 , 0.022714538500 , 0.043245300651 , 0.043737694621 , 0.039417404681 , 0.058301068842 , 0.096034362912 , 0.049474515021 ,
0.068088412285 , 0.071890942752 , 0.081054270267 , 0.099122352898 , 0.019344689324 , 0.016196757555 , 0.028924938291 , 0.021418366581 ,
0.038477282971 , 0.097647145391 , 0.065536484122 , 0.021624978632 , 0.091035209596 , 0.088731065392 , 0.062980979681 , 0.091323882341 ,
0.080427832901 , 0.010585856624 , 0.046493299305 , 0.092904880643 , 0.012287507765 , 0.026147721335 , 0.054729990661 , 0.016949009150 ,
0.071996927261 , 0.062254287302 , 0.027764605358 , 0.049712769687 , 0.022501658648 , 0.065397657454 , 0.028482327238 , 0.052452348173 ,
0.076647371054 , 0.012443380430 , 0.035894207656 , 0.063945233822 , 0.097500972450 , 0.038787595928 , 0.093092821538 , 0.020959112793 ,
0.059815920889 , 0.086221203208 , 0.089794456959 , 0.025374084711 , 0.012242406607 , 0.078137874603 , 0.043242871761 , 0.092884749174 ,
0.034001696855 , 0.026523688808 , 0.073624230921 , 0.052444271743 , 0.030842103064 , 0.023228317499 , 0.038330040872 , 0.053020559251 ,
0.086550243199 , 0.039867449552 , 0.062210217118 , 0.097098544240 , 0.025171816349 , 0.032723758370 , 0.058200292289 , 0.022243540734 ,
0.047196023166 , 0.023541532457 , 0.082516930997 , 0.022110946476 , 0.068678855896 , 0.095518037677 , 0.011730105616 , 0.017891444266 ,
0.071492098272 , 0.037694804370 , 0.086599498987 , 0.057746194303 , 0.040201075375 , 0.089448004961 , 0.052595272660 , 0.048706613481 ,
0.032011911273 , 0.064207494259 , 0.095363005996 , 0.016065448523 , 0.071987658739 , 0.086484260857 , 0.010913499631 , 0.063195899129 ,
0.013436457142 , 0.076534986496 , 0.013436224312 , 0.072635576129 , 0.086048662663 , 0.069839842618 , 0.078206934035 , 0.033891476691 ,
0.063981935382 , 0.084381885827 , 0.046425402164 , 0.031740646809 , 0.095036923885 , 0.025665557012 , 0.051023714244 , 0.095491513610 ,
0.015815360472 , 0.098766468465 , 0.067991033196 , 0.055297344923 , 0.012446735054 , 0.092283509672 , 0.098970316350 , 0.074071593583 ,
0.011334107257 , 0.022349059582 , 0.020654974505 , 0.078157536685 , 0.013660829514 , 0.067570365965 , 0.095077052712 , 0.070050805807 ,
0.023875277489 , 0.021800221875 , 0.066323988140 , 0.027220658958 , 0.087604679167 , 0.031782485545 , 0.078183852136 , 0.095942422748 ,
0.034223325551 , 0.061475448310 , 0.077884025872 , 0.096821092069 , 0.042029425502 , 0.038503006101 , 0.080018199980 , 0.055888324976 ,
0.045003883541 , 0.080206379294 , 0.068524137139 , 0.015192532912 , 0.070905387402 , 0.076834402978 , 0.095830790699 , 0.048100568354 ,
0.016246678308 , 0.057917281985 , 0.035699144006 , 0.025496367365 , 0.087430931628 , 0.081651799381 , 0.061860375106 , 0.067295081913 ,
0.058373294771 , 0.049987114966 , 0.043400689960 , 0.045421220362 , 0.074457168579 , 0.011581941508 , 0.047699622810 , 0.027522042394 ,
0.022960387170 , 0.035219132900 , 0.057976558805 , 0.041982956231 , 0.067574270070 , 0.070641525090 , 0.052086442709 , 0.046789333224 ,
0.028242394328 , 0.069923341274 , 0.041529022157 , 0.088231660426 , 0.039484284818 , 0.012308175676 , 0.013515014201 , 0.046857252717 ,
0.089802481234 , 0.070355243981 , 0.010528378189 , 0.070461608469 , 0.088308647275 , 0.073445379734 , 0.016519522294 , 0.053608201444 ,
0.063030116260 , 0.017176842317 , 0.031177608296 , 0.082053720951 , 0.066916614771 , 0.087416000664 , 0.010703342967 , 0.041083216667 ,
0.065553665161 , 0.040391240269 , 0.045558460057 , 0.040949858725 , 0.074265502393 , 0.030320435762 , 0.075562916696 , 0.056031584740 ,
0.022828411311 , 0.067086547613 , 0.063498020172 , 0.051229991019 , 0.052455306053 , 0.036319069564 , 0.094638772309 , 0.083748638630 ,
0.023324012756 , 0.026654325426 , 0.019245054573 , 0.051628991961 , 0.098446309566 , 0.087107814848 , 0.050970800221 , 0.016264678910 ,
0.090456850827 , 0.088314235210 , 0.077297478914 , 0.048736624420 , 0.086398795247 , 0.014509113505 , 0.014679096639 , 0.081569038332 ,
0.020741552114 , 0.093251056969 , 0.070469580591 , 0.042279027402 , 0.093626014888 , 0.072415903211 , 0.084009446204 , 0.086702041328 ,
0.071115754545 , 0.012449936010 , 0.056081421673 , 0.050518363714 , 0.062163993716 , 0.040235441178 , 0.037045326084 , 0.060774654150 ,
0.089556269348 , 0.072204053402 , 0.033513337374 , 0.098615251482 , 0.046486325562 , 0.065657727420 , 0.079421825707 , 0.022591702640 ,
0.048757642508 , 0.079654648900 , 0.065668180585 , 0.074976988137 , 0.018286611885 , 0.053085073829 , 0.090839855373 , 0.045434698462 ,
0.031035721302 , 0.037363629788 , 0.010476679541 , 0.011550312862 , 0.056109845638 , 0.078176394105 , 0.060665413737 , 0.053587011993 ,
0.066858865321 , 0.016876321286 , 0.020341143012 , 0.023575499654 , 0.023449476808 , 0.065340697765 , 0.061148241162 , 0.068430840969 ,
0.067111916840 , 0.039879791439 , 0.089658699930 , 0.083749286830 , 0.034303780645 , 0.063648074865 , 0.053063668311 , 0.091072067618 ,
0.078259021044 , 0.099329493940 , 0.080803781748 , 0.029153268784 , 0.078970529139 , 0.087671808898 , 0.080032035708 , 0.018353324383 ,
0.094302162528 , 0.096414417028 , 0.047076135874 , 0.078564271331 , 0.099635459483 , 0.093190453947 , 0.041954338551 , 0.036590889096 ,
0.073049299419 , 0.019589524716 , 0.081121243536 , 0.054669223726 , 0.075569786131 , 0.081370592117 , 0.015465967357 , 0.076508954167 ,
0.025981707498 , 0.054544202983 , 0.044344834983 , 0.073648490012 , 0.010110139847 , 0.061119623482 , 0.037510856986 , 0.054975770414 ,
0.097785986960 , 0.059056684375 , 0.015590736642 , 0.013519637287 , 0.034551024437 , 0.079102188349 , 0.050397634506 , 0.012945006602 ,
0.096725508571 , 0.055563986301 , 0.083818569779 , 0.028759522364 , 0.031302295625 , 0.017652843148 , 0.021330457181 , 0.090998075902 ,
0.094618342817 , 0.010480793193 , 0.080690182745 , 0.099868617952 , 0.051825836301 , 0.076833851635 , 0.086571104825 , 0.030481904745 ,
0.089365780354 , 0.020600195974 , 0.057469874620 , 0.076124653220 , 0.047063700855 , 0.049650691450 , 0.059110768139 , 0.024742174894 ,
0.011725334451 , 0.027700664476 , 0.055061094463 , 0.091774374247 , 0.091858282685 , 0.062095202506 , 0.054017342627 , 0.099490009248 ,
0.078567355871 , 0.061494238675 , 0.033620737493 , 0.013716056012 , 0.095749035478 , 0.024007152766 , 0.078191600740 , 0.046275414526 ,
0.030901543796 , 0.032242283225 , 0.066049955785 , 0.011591747403 , 0.032496895641 , 0.025319501758 , 0.084880091250 , 0.049692504108 ,
0.041881561279 , 0.073312938213 , 0.040533170104 , 0.090959258378 , 0.072336331010 , 0.096650503576 , 0.054932415485 , 0.089062571526 ,
0.054603546858 , 0.051754236221 , 0.043491072953 , 0.034478172660 , 0.024616234004 , 0.055023901165 , 0.096633262932 , 0.035292729735 ,
0.034922167659 , 0.016830790788 , 0.065114989877 , 0.047670818865 , 0.083497889340 , 0.038991339505 , 0.097386389971 , 0.092972710729 ,
0.072355031967 , 0.051008045673 , 0.012238353491 , 0.010012303479 , 0.036781441420 , 0.035685062408 , 0.058890350163 , 0.010173564777 ,
0.047111734748 , 0.046937078238 , 0.081450358033 , 0.096148148179 , 0.071854174137 , 0.093166798353 , 0.094409614801 , 0.012296372093 ,
0.085125476122 , 0.033880900592 , 0.066274911165 , 0.012372131459 , 0.098414637148 , 0.094701670110 , 0.060918472707 , 0.076778545976 ,
0.057029470801 , 0.054246000946 , 0.072558112442 , 0.044279582798 , 0.056954160333 , 0.048464059830 , 0.095414489508 , 0.071373179555 ,
0.018927283585 , 0.020838692784 , 0.015900867060 , 0.095870293677 , 0.082039959729 , 0.015612412244 , 0.017802456394 , 0.015876688063 ,
0.049518786371 , 0.092218577862 , 0.087687678635 , 0.076859883964 , 0.074041113257 , 0.039018098265 , 0.097168140113 , 0.024918809533 ,
0.010445792228 , 0.032435692847 , 0.076683126390 , 0.073208950460 , 0.092757068574 , 0.048118077219 , 0.040505640209 , 0.078290998936 ,
0.096845157444 , 0.086616478860 , 0.073130048811 , 0.026723042130 , 0.094158656895 , 0.024465780705 , 0.046358503401 , 0.077365852892 ,
0.027910986915 , 0.079944781959 , 0.081926442683 , 0.087622396648 , 0.059638679028 , 0.077271133661 , 0.055962681770 , 0.034703575075 ,
0.032979898155 , 0.043166078627 , 0.062236316502 , 0.085789941251 , 0.041495226324 , 0.060292705894 , 0.089458487928 , 0.048874534667 ,
0.064277678728 , 0.014943756163 , 0.029702907428 , 0.046754345298 , 0.070228099823 , 0.033632561564 , 0.032439470291 , 0.050127431750 ,
0.061657778919 , 0.082189336419 , 0.096239514649 , 0.077460378408 , 0.086555786431 , 0.043085612357 , 0.059866480529 , 0.035858035088 ,
0.085990130901 , 0.076079778373 , 0.012897620909 , 0.020317457616 , 0.075488403440 , 0.063586242497 , 0.093968048692 , 0.060985475779 ,
0.032814957201 , 0.060943216085 , 0.042532734573 , 0.037664897740 , 0.033960871398 , 0.060355685651 , 0.068001858890 , 0.057210884988 ,
0.043386869133 , 0.083042852581 , 0.041282199323 , 0.079924821854 , 0.016404585913 , 0.011883625761 , 0.078108504415 , 0.089646987617 ,
0.066885419190 , 0.013303850777 , 0.097822003067 , 0.034337274730 , 0.086603581905 , 0.036402858794 , 0.062816806138 , 0.032024852931 ,
0.011704565957 , 0.038641467690 , 0.067094795406 , 0.022162344307 , 0.032514441758 , 0.050199724734 , 0.016723435372 , 0.060788996518 ,
0.060649141669 , 0.050075359643 , 0.086584612727 , 0.077659182250 , 0.097788259387 , 0.097184397280 , 0.028233235702 , 0.095967777073 ,
0.010398717597 , 0.051252685487 , 0.073865666986 , 0.060201816261 , 0.091966673732 , 0.083864293993 , 0.077199727297 , 0.025830430910 ,
0.032042097300 , 0.031529501081 , 0.056281313300 , 0.080045521259 , 0.065050214529 , 0.038935203105 , 0.053943946958 , 0.035894397646 ,
0.067154355347 , 0.033255621791 , 0.087193906307 , 0.057992912829 , 0.046837143600 , 0.021840685979 , 0.026395639405 , 0.081482954323 ,
0.014072334394 , 0.053717456758 , 0.099329724908 , 0.084732070565 , 0.081915274262 , 0.079949900508 , 0.077932521701 , 0.011891505681 ,
0.030537717044 , 0.037406377494 , 0.098981752992 , 0.086321115494 , 0.058969527483 , 0.080833211541 , 0.073850087821 , 0.068390518427 ,
0.019370324910 , 0.087047778070 , 0.032007563859 , 0.081131584942 , 0.048619821668 , 0.013387368061 , 0.061494871974 , 0.044201128185 ,
0.088336467743 , 0.091028057039 , 0.058533996344 , 0.050892189145 , 0.045009821653 , 0.090047761798 , 0.052664369345 , 0.040068041533 ,
0.013570840470 , 0.085120432079 , 0.039118736982 , 0.078621841967 , 0.077383004129 , 0.046131357551 , 0.039707303047 , 0.070674009621 ,
0.058060221374 , 0.098120428622 , 0.010002977215 , 0.060046419501 , 0.090224683285 , 0.056237258017 , 0.059547096491 , 0.068048685789 ,
0.034223303199 , 0.061032399535 , 0.011529838666 , 0.072003804147 , 0.087845452130 , 0.028549697250 , 0.014738662168 , 0.092692598701 ,
0.044472254813 , 0.055236838758 , 0.075559295714 , 0.085139930248 , 0.096744567156 , 0.015886161476 , 0.028703613207 , 0.081637412310 ,
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240, 114, 16, 16, 92, 216, 241, 242, 248, 254,
185, 25, 15, 34, 81, 97, 97, 96, 135, 232,
189, 26, 14, 16, 16, 16, 15, 15, 18, 173,
243, 174, 97, 63, 59, 60, 65, 77, 121, 229},

{238, 132, 42, 28, 28, 37, 62, 129, 231, 255,
231, 99, 26, 22, 21, 18, 16, 19, 136, 248,
251, 218, 170, 159, 154, 126, 48, 15, 55, 222,
255, 255, 246, 193, 139, 99, 33, 15, 68, 228,
255, 255, 202, 41, 16, 15, 15, 26, 161, 250,
255, 255, 196, 33, 15, 14, 14, 26, 158, 248,
255, 255, 244, 180, 114, 67, 22, 21, 100, 234,
253, 232, 196, 178, 156, 84, 20, 23, 112, 237,
240, 135, 44, 30, 22, 16, 16, 48, 196, 252,
239, 126, 29, 21, 25, 47, 108, 196, 248, 255},

{160, 23, 73, 221, 245, 137, 34, 129, 241, 255,
144, 23, 44, 199, 251, 114, 20, 43, 201, 255,
147, 23, 38, 191, 252, 128, 21, 25, 162, 255,
149, 23, 30, 93, 111, 78, 22, 21, 136, 255,
162, 24, 20, 20, 20, 20, 20, 20, 120, 255,
231, 120, 61, 71, 85, 71, 24, 20, 114, 253,
254, 244, 226, 230, 238, 171, 29, 21, 112, 252,
255, 255, 255, 255, 255, 179, 30, 21, 120, 255,
255, 255, 255, 255, 255, 185, 34, 22, 137, 255,
255, 255, 255, 255, 255, 213, 72, 48, 192, 255},

{242, 175, 127, 102, 85, 78, 73, 69, 124, 232,
182, 16, 4, 5, 7, 8, 9, 13, 46, 211,
145, 9, 43, 127, 151, 154, 157, 166, 200, 246,
121, 6, 65, 139, 147, 147, 149, 174, 238, 255,
147, 7, 5, 4, 4, 4, 4, 11, 161, 253,
220, 101, 75, 86, 92, 82, 30, 2, 140, 254,
252, 235, 227, 232, 235, 211, 75, 3, 148, 255,
229, 170, 148, 158, 182, 166, 64, 2, 150, 255,
136, 13, 5, 7, 22, 20, 8, 3, 167, 255,
200, 69, 19, 16, 23, 30, 47, 132, 235, 255},

{255, 255, 253, 205, 65, 13, 81, 228, 255, 255,
255, 246, 179, 58, 3, 3, 98, 238, 255, 255,
250, 174, 20, 5, 15, 82, 215, 253, 255, 255,
210, 50, 10, 71, 154, 225, 254, 255, 255, 255,
140, 2, 27, 179, 179, 157, 158, 197, 246, 255,
145, 6, 18, 52, 12, 18, 7, 30, 170, 249,
136, 3, 17, 65, 182, 207, 98, 9, 53, 215,
152, 6, 26, 217, 255, 255, 205, 12, 35, 203,
202, 34, 5, 87, 217, 209, 66, 2, 80, 233,
246, 164, 39, 7, 16, 13, 6, 65, 205, 253},

{235, 137, 81, 93, 109, 122, 125, 121, 161, 239,
203, 21, 4, 3, 2, 1, 2, 1, 8, 173,
245, 190, 155, 144, 140, 129, 70, 9, 21, 185,
255, 255, 255, 255, 252, 192, 45, 2, 102, 235,
255, 251, 222, 187, 149, 51, 7, 44, 198, 254,
255, 228, 99, 29, 8, 0, 1, 38, 209, 255,
255, 226, 90, 21, 3, 3, 30, 112, 231, 255,
255, 241, 149, 28, 4, 89, 193, 231, 252, 255,
250, 187, 45, 8, 73, 216, 254, 255, 255, 255,
242, 130, 14, 55, 194, 252, 255, 255, 255, 255},

{255, 242, 160, 65, 30, 24, 29, 65, 188, 250,
255, 184, 16, 5, 22, 30, 20, 2, 57, 217,
255, 159, 7, 83, 173, 189, 127, 15, 27, 192,
255, 165, 11, 42, 170, 202, 83, 4, 57, 214,
255, 218, 64, 1, 23, 35, 9, 25, 158, 246,
255, 248, 174, 37, 1, 0, 13, 117, 230, 254,
254, 220, 86, 5, 5, 11, 6, 29, 159, 246,
247, 132, 9, 25, 120, 163, 70, 3, 54, 215,
238, 95, 3, 41, 119, 136, 75, 8, 42, 206,
246, 152, 24, 6, 2, 1, 1, 17, 136, 241},

{255, 251, 198, 66, 11, 4, 9, 51, 180, 249,
249, 195, 65, 19, 86, 134, 43, 3, 38, 208,
225, 72, 8, 72, 242, 253, 195, 20, 5, 165,
243, 153, 37, 44, 219, 251, 195, 28, 13, 179,
254, 207, 46, 5, 57, 115, 49, 9, 88, 231,
255, 244, 151, 23, 3, 0, 8, 82, 213, 253,
255, 245, 180, 57, 5, 7, 110, 224, 253, 255,
243, 162, 44, 14, 28, 117, 229, 255, 255, 255,
200, 45, 8, 53, 152, 231, 254, 255, 255, 255,
204, 67, 131, 206, 244, 254, 255, 255, 253, 255},

{255, 255, 251, 154, 101, 119, 193, 247, 255, 255,
255, 232, 24, 3, 5, 9, 10, 116, 255, 255,
255, 170, 2, 127, 234, 239, 29, 19, 255, 255,
255, 90, 8, 251, 255, 255, 56, 20, 255, 255,
255, 44, 25, 255, 255, 255, 70, 14, 255, 255,
255, 34, 29, 255, 255, 255, 53, 17, 255, 255,
255, 45, 19, 255, 255, 255, 38, 27, 255, 255,
255, 41, 21, 255, 255, 255, 27, 40, 255, 255,
255, 138, 0, 102, 184, 118, 2, 139, 255, 255,
255, 255, 64, 4, 3, 5, 46, 255, 255, 255},

{255, 255, 242, 185, 142, 220, 253, 255, 255, 255,
254, 231, 132, 22, 3, 117, 245, 255, 255, 255,
247, 148, 14, 3, 2, 88, 236, 255, 255, 255,
246, 164, 60, 79, 4, 86, 233, 255, 255, 255,
254, 240, 218, 144, 5, 87, 232, 255, 255, 255,
255, 255, 255, 152, 6, 79, 227, 255, 255, 255,
255, 255, 255, 156, 7, 73, 223, 255, 255, 255,
255, 255, 255, 164, 10, 82, 225, 255, 255, 255,
255, 255, 255, 193, 40, 137, 239, 255, 255, 255,
255, 255, 255, 215, 77, 184, 248, 255, 255, 255},

{252, 219, 128, 44, 17, 15, 27, 126, 237, 255,
224, 83, 15, 12, 20, 27, 16, 31, 189, 255,
177, 17, 13, 75, 157, 150, 50, 19, 167, 255,
217, 91, 98, 214, 237, 127, 27, 35, 191, 255,
250, 229, 232, 232, 143, 28, 21, 119, 237, 255,
255, 249, 203, 106, 27, 18, 110, 228, 254, 255,
235, 154, 54, 15, 25, 113, 226, 254, 255, 255,
126, 18, 12, 47, 109, 154, 166, 165, 162, 185,
40, 13, 18, 22, 22, 21, 22, 21, 19, 30,
74, 33, 49, 59, 66, 68, 68, 70, 85, 129},

{255, 252, 229, 195, 167, 186, 209, 247, 255, 255,
249, 206, 108, 31, 19, 17, 47, 190, 250, 255,
230, 101, 55, 118, 172, 130, 38, 108, 234, 255,
244, 190, 181, 222, 212, 132, 8, 155, 247, 255,
254, 249, 246, 197, 74, 34, 66, 204, 253, 255,
255, 255, 246, 146, 13, 11, 32, 157, 244, 255,
252, 237, 234, 228, 174, 149, 64, 68, 218, 255,
238, 149, 120, 184, 201, 170, 67, 79, 220, 255,
242, 148, 32, 43, 49, 36, 22, 130, 238, 255,
253, 234, 186, 136, 128, 142, 179, 231, 253, 255},

{255, 253, 242, 135, 23, 10, 25, 203, 255, 255,
253, 239, 132, 29, 11, 12, 12, 179, 255, 255,
241, 193, 47, 28, 145, 77, 14, 177, 255, 255,
175, 61, 22, 105, 233, 192, 23, 188, 255, 255,
26, 19, 43, 185, 223, 118, 20, 197, 255, 255,
19, 18, 21, 58, 74, 29, 14, 204, 255, 255,
140, 128, 142, 167, 212, 74, 15, 208, 255, 255,
253, 254, 252, 254, 255, 156, 12, 195, 255, 255,
255, 255, 255, 255, 255, 156, 13, 191, 255, 255,
255, 255, 255, 255, 255, 197, 79, 217, 255, 255},

{196, 38, 15, 19, 15, 13, 12, 12, 20, 184,
167, 31, 100, 186, 185, 174, 162, 148, 169, 218,
160, 59, 227, 252, 252, 252, 252, 252, 252, 249,
157, 28, 123, 195, 200, 198, 205, 232, 251, 255,
158, 31, 38, 32, 44, 35, 25, 68, 210, 254,
203, 167, 183, 178, 207, 203, 90, 16, 136, 248,
241, 247, 251, 252, 252, 252, 211, 31, 103, 239,
193, 141, 211, 250, 251, 234, 113, 21, 139, 246,
142, 28, 44, 127, 181, 79, 22, 70, 219, 252,
221, 126, 37, 21, 23, 29, 64, 193, 249, 252},

{253, 200, 61, 22, 16, 25, 73, 223, 255, 255,
236, 91, 15, 23, 102, 152, 206, 249, 255, 255,
224, 57, 16, 99, 230, 246, 253, 255, 255, 255,
221, 59, 23, 167, 251, 252, 255, 255, 255, 255,
216, 59, 26, 152, 143, 121, 136, 174, 229, 253,
210, 54, 25, 55, 23, 20, 20, 27, 93, 217,
175, 34, 20, 33, 82, 120, 57, 20, 20, 128,
187, 31, 16, 70, 224, 245, 183, 34, 18, 130,
235, 94, 15, 27, 75, 109, 49, 20, 27, 179,
252, 211, 90, 27, 18, 17, 18, 32, 138, 239},

{168, 18, 6, 7, 8, 9, 9, 10, 16, 89,
60, 0, 2, 10, 12, 11, 10, 6, 0, 5,
58, 0, 15, 138, 165, 163, 130, 27, 0, 23,
109, 0, 61, 229, 255, 221, 73, 2, 6, 133,
224, 131, 207, 249, 221, 82, 2, 4, 98, 234,
255, 253, 253, 216, 74, 2, 3, 86, 226, 255,
255, 253, 209, 66, 2, 3, 88, 225, 254, 255,
251, 199, 55, 1, 5, 90, 226, 251, 253, 255,
205, 39, 1, 7, 109, 230, 254, 255, 255, 255,
124, 0, 2, 101, 238, 255, 255, 255, 255, 255},

{255, 253, 221, 126, 53, 27, 35, 110, 224, 254,
255, 233, 105, 19, 17, 38, 23, 13, 136, 247,
255, 203, 42, 23, 114, 148, 54, 20, 107, 237,
255, 228, 90, 19, 97, 60, 17, 32, 170, 250,
255, 248, 138, 15, 13, 15, 47, 143, 236, 255,
255, 252, 163, 19, 10, 20, 67, 125, 222, 254,
255, 242, 116, 17, 38, 80, 31, 22, 124, 240,
255, 239, 111, 16, 72, 185, 117, 18, 66, 219,
255, 252, 183, 38, 14, 82, 86, 23, 71, 219,
255, 255, 242, 145, 29, 17, 35, 94, 166, 242},

{255, 255, 233, 145, 59, 8, 26, 67, 144, 236,
255, 250, 149, 10, 5, 13, 19, 1, 3, 157,
255, 242, 102, 3, 63, 159, 157, 34, 0, 111,
255, 235, 92, 6, 100, 170, 149, 45, 0, 96,
255, 244, 127, 9, 15, 18, 10, 4, 1, 113,
255, 251, 210, 97, 76, 123, 103, 61, 1, 131,
255, 255, 252, 234, 241, 254, 235, 76, 2, 132,
255, 255, 255, 255, 251, 228, 96, 11, 59, 209,
255, 255, 255, 255, 208, 57, 6, 45, 211, 253,
255, 255, 255, 255, 190, 24, 23, 167, 251, 255}}};

void cleandata(array<array<float, 100>, 30>& pngimage){
    for ( int index1 = 0; index1 <30; ++index1){
        for (int index2 = 0; index2 <100; ++index2){
            pngimage[index1][index2] = 256 - pngimage[index1][index2];
            pngimage[index1][index2] = pngimage[index1][index2] / 255;
        }
    }
}

class ineuron {
public:
    array<float,100> weights;
    array<float,100> negweights;
    array<float,100> inputs;
    string typeset;
    float bias;
    float output;
    float error;
    bool activestate;
    bool firstfire;
    float inputsum;
    float neginputsum;
    float weightssum;
    int consecutivecorrect;
    int expectedoutput;
    int totalcorrect;
    int testvar;

    ineuron(float& x, array<float, 100>& y,array<float,100>& z)
        : bias(x), weights(y), negweights(z),typeset("inputneuron"), error(0), activestate(false),firstfire(true), inputsum(0),neginputsum(0),weightssum(0),consecutivecorrect(0),expectedoutput(0),totalcorrect(0),output(0),testvar(0) {}

     ineuron() : bias(0.1), typeset("inputneuron"), error(0), activestate(false),firstfire(true),consecutivecorrect(0), inputsum(0),neginputsum(0),weightssum(0),expectedoutput(0),totalcorrect(0),output(0),testvar(0){
        weights.fill(0);
        negweights.fill(0);
        inputs.fill(0);
     }
};
class outputneuron {
public:
    float bias;
    array<float,10> weights;
    string typeset;
    float output;
    float error;
    int activity = 0;
    int targets = 0;
    float totallayererror = 0;
    float highestincoming = 0;
    float lowestincoming = 100000;
    bool correct;
    int totalcorrect = 0;

    outputneuron(float x, const array<float,10>& y, const string& z)
        :bias(x),weights(y),typeset(z),output(0),error(0),activity(0),targets(0),totallayererror(0),highestincoming(0),lowestincoming(100000),correct(false),totalcorrect(0){}
};

void buildineurons(array<ineuron, 10>& ineurons, const array<float, 1600>& randomnumbers) {
    for (int index1 = 0; index1 < 10; ++index1) {
        ineurons[index1].expectedoutput = index1;
        for (int index2 = 0; index2 < 100; ++index2) {
            int index3 = (index1 * 100) + index2;
            ineurons[index1].weights[index2] = randomnumbers[index3];
            ineurons[index1].negweights[index2] = (randomnumbers[index3]) / 2;
        }
    }
}
unsigned seed = std::chrono::system_clock::now().time_since_epoch().count();
std::default_random_engine generator(seed);
std::uniform_real_distribution<float> distribution(0.01, 0.1);
float random_float = distribution(generator);



void adjustbias(array<ineuron,10>& ineurons,outputneuron& finaloutput){
    float biasgap  = finaloutput.highestincoming - finaloutput.lowestincoming;
    if (finaloutput.activity == 0){
        for(int index1 = 0; index1 <10; index1++){
            float bias = ineurons[index1].bias;
            float individualerror = 1 - ineurons[index1].bias;
            float adjustment = (0.8-ineurons[index1].bias) *individualerror;
            ineurons[index1].bias += abs(adjustment) + 0.1 + distribution(generator);
        }
        //cout << "test1";
    }
    if (finaloutput.activity > 1){
        for(int index = 0; index <10; index++){
            if ((ineurons[index].activestate) && (ineurons[index].output != finaloutput.highestincoming)){
                float individualerror = ineurons[index].bias - 0.3;
                float adjustment = (1-ineurons[index].bias) *individualerror;
                ineurons[index].bias = ineurons[index].bias - abs(adjustment);
            }
        }
        //cout << "test2";
    }
    return;
}

void resetvariables(array<ineuron,10>& ineurons,outputneuron& finaloutput){
    finaloutput.totallayererror = 0;
    finaloutput.highestincoming = 0;
    finaloutput.lowestincoming = 10000000;
    finaloutput.activity = 0;
    finaloutput.targets = 0;
    finaloutput.correct = false;
}
void feedforward(array<ineuron, 10>& ineurons,array<array<float, 100>, 30>& pngimage,outputneuron& finaloutput,int image) {
    for (int index1 = 0; index1 < 10; ++index1) {
        float calc = 0;
        float negcalc = 0;
        ineurons[index1].inputsum = 0;
        ineurons[index1].neginputsum = 0;
        ineurons[index1].activestate = false;
        for (int index2 = 0; index2 < 100; ++index2) {
            calc += (ineurons[index1].weights[index2] * ineurons[index1].weights[index2]) * (pngimage[image][index2]);
            negcalc += (ineurons[index1].negweights[index2] * ineurons[index1].negweights[index2]) * (pngimage[image][index2]);
            ineurons[index1].inputs[index2] = pngimage[image][index2];
            }
        ineurons[index1].inputsum = calc;
        ineurons[index1].neginputsum = negcalc;
        ineurons[index1].output = (calc-negcalc)/100 + ineurons[index1].bias;

        if (ineurons[index1].output >= finaloutput.highestincoming){
            finaloutput.highestincoming = ineurons[index1].output;
        }
        if (ineurons[index1].output < finaloutput.lowestincoming){
            finaloutput.lowestincoming = ineurons[index1].output;
        }
        if ((ineurons[index1].output >0.8)&&(ineurons[index1].output >= finaloutput.highestincoming)){
            finaloutput.targets = index1;
            finaloutput.activity += 1;
            ineurons[index1].activestate = true;
        }
    }
}
void feedforwardoutputlayer(array<ineuron,10>& ineurons,outputneuron& finaloutput,int expected){
    finaloutput.correct = false;
    if (ineurons[finaloutput.targets].expectedoutput == expected){
        finaloutput.correct = true;
    }
}
/*
void biaserroradjust(array<ineuron,10>& ineurons,outputneuron& finaloutput,int expected){
    for(int index1 = 0; index1 <10; ++index1){
        float inputsum = ineurons[index1].inputsum;
        float neginputsum = ineurons[index1].neginputsum;
        if (ineurons[index1].expectedoutput == expected){
            float bias  = ineurons[index1].bias;
            float output = ineurons[index1].output;
            for (int index2 = 0; index2 <100; ++index2){
                float weight = ineurons[index1].weights[index2];
                float negweight = ineurons[index1].negweights[index2];
                float input = ineurons[index1].inputs[index2];
                float indiverror =  bias / 2;
                float adjustment =( ( (weight * weight) * input ) / ineurons[index1].inputsum ) * indiverror;
                float adjustment2 = ( ( (negweight * negweight) * input) / ineurons[index1].neginputsum) * indiverror;
                ineurons[index1].weights[index2] += sqrt(abs(adjustment));
                ineurons[index1].negweights[index2] += sqrt(abs(adjustment2));
            }
            ineurons[index1].bias = ineurons[index1].bias /10;
        }
    }
}
*/
int main() {
//Create random number availability

// Create and Declare first layer
cleandata(pngimage);
array<ineuron, 10> ineurons;
buildineurons(ineurons,randomnumbers);

// Create and Declare last layer
array<float,10> outputweights;
copy(randomnumbers.begin(), randomnumbers.begin() + 10, outputweights.begin());
outputneuron finaloutput(0,outputweights,"outputneuron");
int loopcount = 0;
//Feed Forward
for (int extraloop = 0; extraloop < 100; ++extraloop){
for (int mainloop =0; mainloop <30; ++mainloop){
    int expected = mainloop % 10;
    ++loopcount;
    resetvariables(ineurons,finaloutput);
    //Bias Adjustments forcing an output
    int test = 0;
    //Perform calculations for first layer

    while (finaloutput.activity == 0){
        test++;
        resetvariables(ineurons,finaloutput);
        feedforward(ineurons,pngimage,finaloutput,expected);
        if (finaloutput.activity ==0){
            adjustbias(ineurons,finaloutput);
        }
        //biaserroradjust(ineurons,finaloutput,expected);
    }
    //Perform calculations for output layer
    feedforwardoutputlayer(ineurons,finaloutput,expected);


    if (finaloutput.correct == true){
        cout << " \n Yep this fired";
        int self = finaloutput.targets;
        ineurons[self].totalcorrect += 1;
        //biaserroradjust(ineurons,finaloutput,expected);
        finaloutput.totalcorrect +=1;
        ineurons[self].consecutivecorrect +=1;
        if (ineurons[self].expectedoutput == expected){
            float bias = ineurons[self].bias;
            float output = ineurons[self].output;
            float inputsum = ineurons[self].inputsum;
            float neginputsum = ineurons[self].neginputsum;
            float error = 1 - output - bias;
            float poserror1  =( inputsum / (inputsum + neginputsum))*abs(error);
            float negerror1 = (neginputsum / (inputsum + neginputsum))*abs(error);
            float poserror = (1.25 - inputsum/100);
            float negerror = (0.25 - neginputsum/100);
            ineurons[self].weightssum = bias;
            ineurons[self].bias = 0.5;
            for(int index2 = 0; index2 <100; ++index2){
                float weights = ineurons[self].weights[index2];
                float negweights = ineurons[self].negweights[index2];
                float input = ineurons[self].inputs[index2];
                float indiverror = (((weights * weights) * input) / (inputsum)) * (poserror);
                float negindiverror = (((negweights * negweights) * input) / (neginputsum)) * (negerror);
                float adjustment = abs((indiverror *input) / input);
                float negadjustment = abs((negindiverror *(1-input)) / input);
                ineurons[self].weights[index2] += copysign(sqrt(adjustment),(poserror));// if input is small decrease this more
                ineurons[self].negweights[index2] += copysign(sqrt(negadjustment),(negerror));//if input is big decrease this more
                ineurons[self].weights[index2] = ineurons[self].weights[index2] *0.95;
                ineurons[self].negweights[index2] = ineurons[self].negweights[index2] *0.95;
                //cout << "  \n input " << input << " signalvar " << signalvar << " bigbalancepos " << bigbalancedownerrorpos << " small balance " << smallbalancedownerrorpos << " error " << error;
                //ineurons[self].weights[index2] = ineurons[self].weights[index2] *0.9;
               //ineurons[self].negweights[index2] = ineurons[self].negweights[index2] * 0.9;

            }
        }
    }

    if (finaloutput.correct == false){
        cout << " NOPE DIDNT CORRECT HERE!" ;
        ineurons[finaloutput.targets].consecutivecorrect = 0;
        for (int index1 = 0; index1<10; ++index1){
            int self = index1;
            if ((ineurons[self].activestate)&&(ineurons[self].expectedoutput != expected)){
                float bias = ineurons[self].bias;
                float output = ineurons[self].output;
                float inputsum = ineurons[self].inputsum;
                float neginputsum = ineurons[self].neginputsum;
                float error = (output) - ineurons[self].bias;
                float poserror1  = (inputsum / (inputsum + neginputsum) ) * abs(error);
                float negerror1 = (neginputsum / (inputsum + neginputsum))* abs(error);
                float poserror = (0.5 - inputsum/100);
                float negerror = (0.5 - neginputsum/100);
                float balanceerror = poserror + negerror;

                ineurons[self].bias = ineurons[self].bias / 2;
                for(int index2 = 0; index2 <100; ++index2){
                    float weights = ineurons[self].weights[index2];
                    float negweights = ineurons[self].negweights[index2];
                    float input = ineurons[self].inputs[index2];
                    //float balance1 = input
                    //float balance2 = 1-input
                    //float signalvar = input - 0.5;
                    //float bigbalancedownerrorpos  =  copysign(input,signalvar) +  ((1 - copysign(1,signalvar))/2);
                    //float smallbalancedownerrorpos = -1* (copysign(input,signalvar)) + ((1 - (-1*(copysign(1,signalvar))))/2);
                    float indiverror = (((weights * weights) * input) / (inputsum)) * (poserror);
                    float negindiverror = (((negweights * negweights) * input) / (neginputsum)) * (negerror);
                    float indivbalance = indiverror + negindiverror;
                    float balanceadjustment = 1-input;
                    float adjustment = abs((indiverror *(1-input)) / input);
                    float negadjustment = abs((negindiverror * input) / input);
                    ineurons[self].weights[index2] += copysign(sqrt(adjustment),(poserror));// if input is small decrease this more
                    ineurons[self].negweights[index2] += copysign(sqrt(negadjustment),(negerror));//if input is big decrease this more
                    //cout << "  \n input " << input << " signalvar " << signalvar << " bigbalancepos " << bigbalancedownerrorpos << " small balance " << smallbalancedownerrorpos << " error " << error;
                }
            }
            if (ineurons[self].expectedoutput == expected){
                float bias = ineurons[self].bias;
                float output = ineurons[self].output;
                float inputsum = ineurons[self].inputsum;
                float neginputsum = ineurons[self].neginputsum;
                float error = 1 - (output) - ineurons[self].bias;
                float poserror1  = (inputsum / (inputsum + neginputsum))*abs(error);
                float negerror1 = (neginputsum / (inputsum + neginputsum))*abs(error);
                float poserror = (1.25 - inputsum/100) ;
                float negerror = (0.25 - neginputsum/100) ;
                ineurons[self].bias = 0.5;
                for(int index2 = 0; index2 <100; ++index2){
                    float weights = ineurons[self].weights[index2];
                    float negweights = ineurons[self].negweights[index2];
                    float input = ineurons[self].inputs[index2];
                    float indiverror = (((weights * weights) * input) / (inputsum)) * (poserror);
                    float negindiverror = (((negweights * negweights) * input) / (neginputsum)) * (negerror);
                    float adjustment = abs((indiverror *input)/ input);
                    float negadjustment = abs((negindiverror * (1- input))/ input);
                    ineurons[self].weights[index2] += copysign(sqrt(adjustment),(poserror));// if input is small decrease this more
                    ineurons[self].negweights[index2] += copysign(sqrt(negadjustment),(negerror));//if input is big decrease this more
                    //cout << "  \n input " << input << " signalvar " << signalvar << " bigbalancepos " << bigbalancedownerrorpos << " small balance " << smallbalancedownerrorpos << " error " << error;
                }
            }

        }
    }

    cout << " \n Current Neuron " << finaloutput.targets << " Previous Output " << ineurons[finaloutput.targets].output << " Inputsum " << ineurons[finaloutput.targets].inputsum << " Neginputsum " << ineurons[finaloutput.targets].neginputsum  << " Bias " << ineurons[finaloutput.targets].bias;
    feedforward(ineurons,pngimage,finaloutput,expected);
    cout << "  \n Current Neuron " << finaloutput.targets << " Afterwards Output " << ineurons[finaloutput.targets].output << " Inputsum " << ineurons[finaloutput.targets].inputsum << " Neginputsum " << ineurons[finaloutput.targets].neginputsum << " Bias " << ineurons[finaloutput.targets].bias;
    cout << fixed;
    cout << setprecision(12);

    for (int index = 0; index <10; ++index){
        cout << " \n Neuron " << index <<" Solo OutPut "<< (ineurons[index].output - ineurons[index].bias) <<  " bias " << ineurons[index].bias << " Expected " << ineurons[index].expectedoutput << " Output " << ineurons[index].output;
        cout << " Total correct " << ineurons[index].totalcorrect << " Consecutive Correct " << ineurons[index].consecutivecorrect;
        //for (int index2 = 0; index2<100; ++index2){
            //cout << " \n Neuron " << index2 << " Value " << ineurons[index].weights[index2] << " Neg Weight " << ineurons[index].negweights[index2] ;
        //}
    }
    cout << "\n The current saved target is " << finaloutput.targets << " mainloop is " << mainloop << " and expected is " << expected << " Total Correct is "<< finaloutput.totalcorrect << " Total loops " << loopcount << "\n";
    cout << "The value finaloutput is "  << ineurons[finaloutput.targets].expectedoutput << " But the model is expecting" << expected << "\n";
    cout << "It took " << test << " iterations to arrive here \n \n";
    }

    }

    for (int index = 0; index <10; ++index){
        for (int index2 = 0; index2<100; ++index2){
            cout << " \n Weight " << index2 << " Value " << ineurons[index].weights[index2] << " Neg Weight " << ineurons[index].negweights[index2] << " Input " << ineurons[index].inputs[index2];
        }
    }
    cout << "Exited without Errors";
    return 0;
}




/*
float floatnumber = 0.48573;
int xyz = -5;
cout << "the value of xyz is " << xyz << "\n";
cout << sqrt(64) <<"\n";
cout << round(2.6)<<"\n";
cout << log(2)<<"\n";
cout << abs(xyz) << "\n";
cout << floatnumber << "\n";
cout << ineurons[0].bias << "\n";
cout << ineurons[0].weights[5] << "\n";
cout << ineurons[0].typeset << "\n";
cout << ineurons[0].calcweights(ineurons[0].bias,ineurons[0].weights[5]) << "\n";
cout << pngimage[0][12] << "\n"; */


                    // These next 3 statements flip the values of what will be applied to the weights, according to error and input
                    // It handles 4 cases, Error up /down, and Input being high/low
                    //float signalvar = input - 0.5;
                    //float bigbalancedownerrorpos  =  copysign(input,signalvar) +  ((1 - copysign(1,signalvar))/2);
                    //float smallbalancedownerrorpos = -1* (copysign(input,signalvar)) + ((1 - (-1*(copysign(1,signalvar))))/2);