123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624625626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668669670671672673674675676677678679680681682683684685686687688689690691692693694695696697698699700701702703704705706707708709710711712713714715716717718719720721722723724725726727728729730731732733734735736737738739740741742743744745746747748749750751752753754755756757758759760761762763764765766767768769770771772773774775776777778779780781782783784785786787788789790791792793794795796797798799800801802803804805806807808809810811812813814815816817818819820821822823824825826827828829830831832833834835836837838839840841842843844845846847848849850851852853854855856857858859860861862863864865866867868869870871872873874875876877878879880881882883884885886887888889890891892893894895896897898899900901902903904905906907908909910911912913914915916917918919920921922923924925926927928929930931932933934935936937938939940941942943944945946947948949950951952953954955956957958959960961962963964965966967968969970971972973974975976977978979980981982983984985986987988989990991992993994995996997998999100010011002100310041005100610071008100910101011101210131014101510161017101810191020102110221023102410251026102710281029103010311032103310341035103610371038103910401041104210431044104510461047104810491050105110521053105410551056105710581059106010611062106310641065106610671068106910701071107210731074107510761077107810791080108110821083108410851086108710881089109010911092109310941095109610971098109911001101110211031104110511061107110811091110111111121113111411151116111711181119112011211122112311241125112611271128112911301131113211331134113511361137113811391140114111421143114411451146114711481149115011511152115311541155115611571158115911601161116211631164116511661167116811691170117111721173117411751176117711781179118011811182118311841185118611871188118911901191119211931194119511961197119811991200120112021203120412051206120712081209121012111212121312141215121612171218121912201221122212231224122512261227122812291230123112321233123412351236123712381239124012411242124312441245124612471248124912501251125212531254125512561257125812591260126112621263126412651266126712681269127012711272127312741275127612771278127912801281128212831284128512861287128812891290129112921293129412951296129712981299130013011302130313041305130613071308130913101311131213131314131513161317131813191320132113221323132413251326132713281329133013311332133313341335133613371338133913401341134213431344134513461347134813491350135113521353135413551356135713581359136013611362136313641365136613671368136913701371137213731374137513761377137813791380138113821383138413851386138713881389139013911392139313941395139613971398139914001401140214031404140514061407140814091410141114121413141414151416141714181419142014211422142314241425142614271428142914301431143214331434143514361437143814391440144114421443144414451446144714481449145014511452145314541455145614571458145914601461146214631464146514661467146814691470147114721473147414751476147714781479148014811482148314841485148614871488148914901491149214931494149514961497149814991500150115021503150415051506150715081509151015111512151315141515151615171518151915201521152215231524152515261527152815291530153115321533153415351536153715381539154015411542154315441545154615471548154915501551155215531554155515561557155815591560156115621563156415651566156715681569157015711572157315741575157615771578157915801581158215831584158515861587158815891590159115921593159415951596159715981599160016011602160316041605160616071608160916101611161216131614161516161617161816191620162116221623162416251626162716281629163016311632163316341635163616371638163916401641164216431644164516461647164816491650165116521653165416551656165716581659166016611662166316641665166616671668166916701671167216731674167516761677167816791680168116821683168416851686168716881689169016911692169316941695169616971698169917001701170217031704170517061707170817091710171117121713171417151716171717181719172017211722172317241725172617271728172917301731173217331734173517361737173817391740174117421743174417451746174717481749175017511752175317541755175617571758175917601761176217631764176517661767176817691770177117721773177417751776177717781779178017811782178317841785178617871788178917901791179217931794179517961797179817991800180118021803180418051806180718081809181018111812181318141815181618171818181918201821182218231824182518261827182818291830183118321833183418351836183718381839184018411842184318441845184618471848184918501851185218531854185518561857185818591860186118621863186418651866186718681869187018711872187318741875187618771878187918801881188218831884188518861887188818891890189118921893189418951896189718981899190019011902190319041905190619071908190919101911191219131914191519161917191819191920192119221923192419251926192719281929193019311932193319341935193619371938193919401941194219431944194519461947194819491950195119521953195419551956195719581959196019611962196319641965196619671968196919701971197219731974197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022202320242025202620272028202920302031203220332034203520362037203820392040204120422043204420452046204720482049205020512052205320542055205620572058205920602061206220632064206520662067206820692070207120722073207420752076207720782079208020812082208320842085208620872088208920902091209220932094209520962097209820992100210121022103210421052106210721082109211021112112211321142115211621172118211921202121212221232124212521262127212821292130213121322133213421352136213721382139214021412142214321442145214621472148214921502151215221532154215521562157215821592160216121622163216421652166216721682169217021712172217321742175217621772178217921802181218221832184218521862187218821892190219121922193219421952196219721982199220022012202220322042205220622072208220922102211221222132214221522162217221822192220222122222223222422252226222722282229223022312232223322342235223622372238223922402241224222432244224522462247224822492250225122522253225422552256225722582259226022612262226322642265226622672268226922702271227222732274227522762277227822792280228122822283228422852286228722882289229022912292229322942295229622972298229923002301230223032304230523062307230823092310231123122313231423152316231723182319232023212322232323242325232623272328232923302331233223332334233523362337233823392340234123422343234423452346234723482349235023512352235323542355235623572358235923602361236223632364236523662367236823692370237123722373237423752376237723782379238023812382238323842385238623872388238923902391239223932394239523962397239823992400240124022403240424052406240724082409241024112412241324142415241624172418241924202421242224232424242524262427242824292430243124322433243424352436243724382439244024412442244324442445244624472448244924502451245224532454245524562457245824592460246124622463246424652466246724682469247024712472247324742475247624772478247924802481248224832484248524862487248824892490249124922493249424952496249724982499250025012502250325042505250625072508250925102511251225132514251525162517251825192520252125222523252425252526252725282529253025312532253325342535253625372538253925402541254225432544254525462547254825492550255125522553255425552556255725582559256025612562256325642565256625672568256925702571257225732574257525762577257825792580258125822583258425852586258725882589259025912592259325942595259625972598259926002601260226032604260526062607260826092610261126122613261426152616261726182619262026212622262326242625262626272628262926302631263226332634263526362637263826392640264126422643264426452646264726482649265026512652265326542655265626572658265926602661266226632664266526662667266826692670267126722673267426752676267726782679268026812682268326842685268626872688268926902691269226932694269526962697269826992700270127022703270427052706270727082709271027112712271327142715271627172718271927202721272227232724272527262727272827292730273127322733273427352736273727382739274027412742274327442745274627472748274927502751275227532754275527562757275827592760276127622763276427652766276727682769277027712772277327742775277627772778277927802781278227832784278527862787278827892790279127922793279427952796279727982799280028012802280328042805280628072808280928102811281228132814281528162817281828192820282128222823282428252826282728282829283028312832283328342835283628372838283928402841284228432844284528462847284828492850285128522853285428552856285728582859286028612862286328642865286628672868286928702871287228732874287528762877287828792880288128822883288428852886288728882889289028912892289328942895289628972898289929002901290229032904290529062907290829092910291129122913291429152916291729182919292029212922292329242925292629272928292929302931293229332934293529362937293829392940294129422943294429452946294729482949295029512952295329542955295629572958295929602961296229632964296529662967296829692970297129722973297429752976297729782979298029812982298329842985298629872988298929902991299229932994299529962997299829993000300130023003300430053006300730083009301030113012301330143015301630173018301930203021302230233024302530263027302830293030303130323033303430353036303730383039304030413042304330443045304630473048304930503051305230533054305530563057305830593060306130623063306430653066306730683069307030713072307330743075307630773078307930803081308230833084308530863087308830893090309130923093309430953096309730983099310031013102310331043105310631073108310931103111311231133114311531163117311831193120312131223123312431253126312731283129313031313132313331343135313631373138313931403141314231433144314531463147314831493150315131523153315431553156315731583159316031613162316331643165316631673168316931703171317231733174317531763177317831793180318131823183318431853186318731883189319031913192319331943195319631973198319932003201320232033204320532063207320832093210321132123213321432153216321732183219322032213222322332243225322632273228322932303231323232333234323532363237323832393240324132423243324432453246324732483249325032513252325332543255325632573258325932603261326232633264326532663267326832693270327132723273327432753276327732783279328032813282328332843285328632873288328932903291329232933294329532963297329832993300330133023303330433053306330733083309331033113312331333143315331633173318331933203321332233233324332533263327332833293330333133323333333433353336333733383339334033413342334333443345334633473348334933503351335233533354335533563357335833593360336133623363336433653366336733683369337033713372337333743375337633773378337933803381338233833384338533863387338833893390339133923393339433953396339733983399340034013402340334043405340634073408340934103411341234133414341534163417341834193420342134223423342434253426342734283429343034313432343334343435343634373438343934403441344234433444344534463447344834493450345134523453345434553456345734583459346034613462346334643465346634673468346934703471347234733474347534763477347834793480348134823483348434853486348734883489349034913492349334943495349634973498349935003501350235033504350535063507350835093510351135123513351435153516351735183519352035213522352335243525352635273528352935303531353235333534353535363537353835393540354135423543354435453546354735483549355035513552355335543555355635573558355935603561356235633564356535663567356835693570357135723573357435753576357735783579358035813582358335843585358635873588358935903591359235933594359535963597359835993600360136023603360436053606360736083609361036113612361336143615361636173618361936203621362236233624362536263627362836293630363136323633363436353636363736383639364036413642364336443645364636473648364936503651365236533654365536563657365836593660366136623663366436653666366736683669367036713672367336743675367636773678367936803681368236833684368536863687368836893690369136923693369436953696369736983699370037013702370337043705370637073708370937103711371237133714371537163717371837193720372137223723372437253726372737283729373037313732373337343735373637373738373937403741374237433744374537463747374837493750375137523753375437553756375737583759376037613762376337643765376637673768376937703771377237733774377537763777377837793780378137823783378437853786378737883789379037913792379337943795379637973798379938003801380238033804380538063807380838093810381138123813381438153816381738183819382038213822382338243825382638273828382938303831383238333834383538363837383838393840384138423843384438453846384738483849385038513852385338543855385638573858385938603861386238633864386538663867386838693870387138723873387438753876387738783879388038813882388338843885388638873888388938903891389238933894389538963897389838993900390139023903390439053906390739083909391039113912391339143915391639173918391939203921392239233924392539263927392839293930393139323933393439353936393739383939394039413942394339443945394639473948394939503951395239533954395539563957395839593960396139623963396439653966396739683969397039713972397339743975397639773978397939803981398239833984398539863987398839893990399139923993399439953996399739983999400040014002400340044005400640074008400940104011401240134014401540164017401840194020402140224023402440254026402740284029403040314032403340344035403640374038403940404041404240434044404540464047404840494050405140524053405440554056405740584059406040614062406340644065406640674068406940704071407240734074407540764077407840794080408140824083408440854086408740884089409040914092409340944095409640974098409941004101410241034104410541064107410841094110411141124113411441154116411741184119412041214122412341244125412641274128412941304131413241334134413541364137413841394140414141424143414441454146414741484149415041514152415341544155415641574158415941604161416241634164416541664167416841694170417141724173417441754176417741784179418041814182418341844185418641874188418941904191419241934194419541964197419841994200420142024203420442054206420742084209421042114212421342144215421642174218421942204221422242234224422542264227422842294230423142324233423442354236423742384239424042414242424342444245424642474248424942504251425242534254425542564257425842594260426142624263426442654266426742684269427042714272427342744275427642774278427942804281428242834284428542864287428842894290429142924293429442954296429742984299430043014302430343044305430643074308430943104311431243134314431543164317431843194320432143224323432443254326432743284329433043314332433343344335433643374338433943404341434243434344434543464347434843494350435143524353435443554356435743584359436043614362436343644365436643674368436943704371437243734374437543764377437843794380438143824383438443854386438743884389439043914392439343944395439643974398439944004401440244034404440544064407440844094410441144124413441444154416441744184419442044214422442344244425442644274428442944304431443244334434443544364437443844394440444144424443444444454446444744484449445044514452445344544455445644574458445944604461446244634464446544664467446844694470447144724473447444754476447744784479448044814482448344844485448644874488448944904491449244934494449544964497449844994500450145024503450445054506450745084509451045114512451345144515451645174518451945204521452245234524452545264527452845294530453145324533453445354536453745384539454045414542454345444545454645474548454945504551455245534554455545564557455845594560456145624563456445654566456745684569457045714572457345744575457645774578457945804581458245834584458545864587458845894590459145924593459445954596459745984599460046014602460346044605460646074608460946104611461246134614461546164617461846194620462146224623462446254626462746284629463046314632463346344635463646374638463946404641464246434644464546464647464846494650465146524653465446554656465746584659466046614662466346644665466646674668466946704671467246734674467546764677467846794680468146824683468446854686468746884689469046914692469346944695469646974698469947004701470247034704470547064707470847094710471147124713471447154716471747184719472047214722472347244725472647274728472947304731473247334734473547364737473847394740474147424743474447454746474747484749475047514752475347544755475647574758475947604761476247634764476547664767476847694770477147724773477447754776477747784779478047814782478347844785478647874788478947904791479247934794479547964797479847994800480148024803480448054806480748084809481048114812481348144815481648174818481948204821482248234824482548264827482848294830483148324833483448354836483748384839484048414842484348444845484648474848484948504851485248534854485548564857485848594860486148624863486448654866486748684869487048714872487348744875487648774878487948804881488248834884488548864887488848894890489148924893489448954896489748984899490049014902490349044905490649074908490949104911491249134914491549164917491849194920492149224923492449254926492749284929493049314932493349344935493649374938493949404941494249434944494549464947494849494950495149524953495449554956495749584959496049614962496349644965496649674968496949704971497249734974497549764977497849794980498149824983498449854986498749884989499049914992499349944995499649974998499950005001500250035004500550065007500850095010501150125013501450155016501750185019502050215022502350245025502650275028502950305031503250335034503550365037503850395040504150425043504450455046504750485049505050515052505350545055505650575058505950605061506250635064506550665067506850695070507150725073507450755076507750785079508050815082508350845085508650875088508950905091509250935094509550965097509850995100510151025103510451055106510751085109511051115112511351145115511651175118511951205121512251235124512551265127512851295130513151325133513451355136513751385139514051415142514351445145514651475148514951505151515251535154515551565157515851595160516151625163516451655166516751685169517051715172517351745175517651775178517951805181518251835184518551865187518851895190519151925193519451955196519751985199520052015202520352045205520652075208520952105211521252135214521552165217521852195220522152225223522452255226522752285229523052315232523352345235523652375238523952405241524252435244524552465247524852495250525152525253525452555256525752585259526052615262526352645265526652675268526952705271527252735274527552765277527852795280528152825283528452855286528752885289529052915292529352945295529652975298529953005301530253035304530553065307530853095310531153125313531453155316531753185319532053215322532353245325532653275328532953305331533253335334533553365337533853395340534153425343534453455346534753485349535053515352535353545355535653575358535953605361536253635364536553665367536853695370537153725373537453755376537753785379538053815382538353845385538653875388538953905391539253935394539553965397539853995400540154025403540454055406540754085409541054115412541354145415541654175418541954205421542254235424542554265427542854295430543154325433543454355436543754385439544054415442544354445445544654475448544954505451545254535454545554565457545854595460546154625463546454655466546754685469547054715472547354745475547654775478547954805481548254835484548554865487548854895490549154925493549454955496549754985499550055015502550355045505550655075508550955105511551255135514551555165517551855195520552155225523552455255526552755285529553055315532553355345535553655375538553955405541554255435544554555465547554855495550555155525553555455555556555755585559556055615562556355645565556655675568556955705571557255735574557555765577557855795580558155825583558455855586558755885589559055915592559355945595559655975598559956005601560256035604560556065607560856095610561156125613561456155616561756185619562056215622562356245625562656275628562956305631563256335634563556365637563856395640564156425643564456455646564756485649565056515652565356545655565656575658565956605661566256635664566556665667566856695670567156725673567456755676567756785679568056815682568356845685568656875688568956905691569256935694569556965697569856995700570157025703570457055706570757085709571057115712571357145715571657175718571957205721572257235724572557265727572857295730573157325733573457355736573757385739574057415742574357445745574657475748574957505751575257535754575557565757575857595760576157625763576457655766576757685769577057715772577357745775577657775778577957805781578257835784578557865787578857895790579157925793579457955796579757985799580058015802580358045805580658075808580958105811581258135814581558165817581858195820582158225823582458255826582758285829583058315832583358345835583658375838583958405841584258435844584558465847584858495850585158525853585458555856585758585859586058615862586358645865586658675868586958705871587258735874587558765877587858795880588158825883588458855886588758885889589058915892589358945895589658975898589959005901590259035904590559065907590859095910591159125913591459155916591759185919592059215922592359245925592659275928592959305931593259335934593559365937593859395940594159425943594459455946594759485949595059515952595359545955595659575958595959605961596259635964596559665967596859695970597159725973597459755976597759785979598059815982598359845985598659875988598959905991599259935994599559965997599859996000600160026003600460056006600760086009601060116012601360146015601660176018601960206021602260236024602560266027602860296030603160326033603460356036603760386039604060416042604360446045604660476048604960506051605260536054605560566057605860596060606160626063606460656066606760686069607060716072607360746075607660776078607960806081608260836084608560866087608860896090609160926093609460956096609760986099610061016102610361046105610661076108610961106111611261136114 |
- // random number generation -*- C++ -*-
- // Copyright (C) 2009-2022 Free Software Foundation, Inc.
- //
- // This file is part of the GNU ISO C++ Library. This library is free
- // software; you can redistribute it and/or modify it under the
- // terms of the GNU General Public License as published by the
- // Free Software Foundation; either version 3, or (at your option)
- // any later version.
- // This library is distributed in the hope that it will be useful,
- // but WITHOUT ANY WARRANTY; without even the implied warranty of
- // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- // GNU General Public License for more details.
- // Under Section 7 of GPL version 3, you are granted additional
- // permissions described in the GCC Runtime Library Exception, version
- // 3.1, as published by the Free Software Foundation.
- // You should have received a copy of the GNU General Public License and
- // a copy of the GCC Runtime Library Exception along with this program;
- // see the files COPYING3 and COPYING.RUNTIME respectively. If not, see
- // <http://www.gnu.org/licenses/>.
- /**
- * @file bits/random.h
- * This is an internal header file, included by other library headers.
- * Do not attempt to use it directly. @headername{random}
- */
- #ifndef _RANDOM_H
- #define _RANDOM_H 1
- #include <vector>
- #include <bits/uniform_int_dist.h>
- namespace std _GLIBCXX_VISIBILITY(default)
- {
- _GLIBCXX_BEGIN_NAMESPACE_VERSION
- // [26.4] Random number generation
- /**
- * @defgroup random Random Number Generation
- * @ingroup numerics
- *
- * A facility for generating random numbers on selected distributions.
- * @{
- */
- // std::uniform_random_bit_generator is defined in <bits/uniform_int_dist.h>
- /**
- * @brief A function template for converting the output of a (integral)
- * uniform random number generator to a floatng point result in the range
- * [0-1).
- */
- template<typename _RealType, size_t __bits,
- typename _UniformRandomNumberGenerator>
- _RealType
- generate_canonical(_UniformRandomNumberGenerator& __g);
- /// @cond undocumented
- // Implementation-space details.
- namespace __detail
- {
- template<typename _UIntType, size_t __w,
- bool = __w < static_cast<size_t>
- (std::numeric_limits<_UIntType>::digits)>
- struct _Shift
- { static constexpr _UIntType __value = 0; };
- template<typename _UIntType, size_t __w>
- struct _Shift<_UIntType, __w, true>
- { static constexpr _UIntType __value = _UIntType(1) << __w; };
- template<int __s,
- int __which = ((__s <= __CHAR_BIT__ * sizeof (int))
- + (__s <= __CHAR_BIT__ * sizeof (long))
- + (__s <= __CHAR_BIT__ * sizeof (long long))
- /* assume long long no bigger than __int128 */
- + (__s <= 128))>
- struct _Select_uint_least_t
- {
- static_assert(__which < 0, /* needs to be dependent */
- "sorry, would be too much trouble for a slow result");
- };
- template<int __s>
- struct _Select_uint_least_t<__s, 4>
- { using type = unsigned int; };
- template<int __s>
- struct _Select_uint_least_t<__s, 3>
- { using type = unsigned long; };
- template<int __s>
- struct _Select_uint_least_t<__s, 2>
- { using type = unsigned long long; };
- #if __SIZEOF_INT128__ > __SIZEOF_LONG_LONG__
- template<int __s>
- struct _Select_uint_least_t<__s, 1>
- { __extension__ using type = unsigned __int128; };
- #endif
- // Assume a != 0, a < m, c < m, x < m.
- template<typename _Tp, _Tp __m, _Tp __a, _Tp __c,
- bool __big_enough = (!(__m & (__m - 1))
- || (_Tp(-1) - __c) / __a >= __m - 1),
- bool __schrage_ok = __m % __a < __m / __a>
- struct _Mod
- {
- static _Tp
- __calc(_Tp __x)
- {
- using _Tp2
- = typename _Select_uint_least_t<std::__lg(__a)
- + std::__lg(__m) + 2>::type;
- return static_cast<_Tp>((_Tp2(__a) * __x + __c) % __m);
- }
- };
- // Schrage.
- template<typename _Tp, _Tp __m, _Tp __a, _Tp __c>
- struct _Mod<_Tp, __m, __a, __c, false, true>
- {
- static _Tp
- __calc(_Tp __x);
- };
- // Special cases:
- // - for m == 2^n or m == 0, unsigned integer overflow is safe.
- // - a * (m - 1) + c fits in _Tp, there is no overflow.
- template<typename _Tp, _Tp __m, _Tp __a, _Tp __c, bool __s>
- struct _Mod<_Tp, __m, __a, __c, true, __s>
- {
- static _Tp
- __calc(_Tp __x)
- {
- _Tp __res = __a * __x + __c;
- if (__m)
- __res %= __m;
- return __res;
- }
- };
- template<typename _Tp, _Tp __m, _Tp __a = 1, _Tp __c = 0>
- inline _Tp
- __mod(_Tp __x)
- {
- if _GLIBCXX17_CONSTEXPR (__a == 0)
- return __c;
- else
- {
- // _Mod must not be instantiated with a == 0
- constexpr _Tp __a1 = __a ? __a : 1;
- return _Mod<_Tp, __m, __a1, __c>::__calc(__x);
- }
- }
- /*
- * An adaptor class for converting the output of any Generator into
- * the input for a specific Distribution.
- */
- template<typename _Engine, typename _DInputType>
- struct _Adaptor
- {
- static_assert(std::is_floating_point<_DInputType>::value,
- "template argument must be a floating point type");
- public:
- _Adaptor(_Engine& __g)
- : _M_g(__g) { }
- _DInputType
- min() const
- { return _DInputType(0); }
- _DInputType
- max() const
- { return _DInputType(1); }
- /*
- * Converts a value generated by the adapted random number generator
- * into a value in the input domain for the dependent random number
- * distribution.
- */
- _DInputType
- operator()()
- {
- return std::generate_canonical<_DInputType,
- std::numeric_limits<_DInputType>::digits,
- _Engine>(_M_g);
- }
- private:
- _Engine& _M_g;
- };
- template<typename _Sseq>
- using __seed_seq_generate_t = decltype(
- std::declval<_Sseq&>().generate(std::declval<uint_least32_t*>(),
- std::declval<uint_least32_t*>()));
- // Detect whether _Sseq is a valid seed sequence for
- // a random number engine _Engine with result type _Res.
- template<typename _Sseq, typename _Engine, typename _Res,
- typename _GenerateCheck = __seed_seq_generate_t<_Sseq>>
- using __is_seed_seq = __and_<
- __not_<is_same<__remove_cvref_t<_Sseq>, _Engine>>,
- is_unsigned<typename _Sseq::result_type>,
- __not_<is_convertible<_Sseq, _Res>>
- >;
- } // namespace __detail
- /// @endcond
- /**
- * @addtogroup random_generators Random Number Generators
- * @ingroup random
- *
- * These classes define objects which provide random or pseudorandom
- * numbers, either from a discrete or a continuous interval. The
- * random number generator supplied as a part of this library are
- * all uniform random number generators which provide a sequence of
- * random number uniformly distributed over their range.
- *
- * A number generator is a function object with an operator() that
- * takes zero arguments and returns a number.
- *
- * A compliant random number generator must satisfy the following
- * requirements. <table border=1 cellpadding=10 cellspacing=0>
- * <caption align=top>Random Number Generator Requirements</caption>
- * <tr><td>To be documented.</td></tr> </table>
- *
- * @{
- */
- /**
- * @brief A model of a linear congruential random number generator.
- *
- * A random number generator that produces pseudorandom numbers via
- * linear function:
- * @f[
- * x_{i+1}\leftarrow(ax_{i} + c) \bmod m
- * @f]
- *
- * The template parameter @p _UIntType must be an unsigned integral type
- * large enough to store values up to (__m-1). If the template parameter
- * @p __m is 0, the modulus @p __m used is
- * std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template
- * parameters @p __a and @p __c must be less than @p __m.
- *
- * The size of the state is @f$1@f$.
- */
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- class linear_congruential_engine
- {
- static_assert(std::is_unsigned<_UIntType>::value,
- "result_type must be an unsigned integral type");
- static_assert(__m == 0u || (__a < __m && __c < __m),
- "template argument substituting __m out of bounds");
- template<typename _Sseq>
- using _If_seed_seq = typename enable_if<__detail::__is_seed_seq<
- _Sseq, linear_congruential_engine, _UIntType>::value>::type;
- public:
- /** The type of the generated random value. */
- typedef _UIntType result_type;
- /** The multiplier. */
- static constexpr result_type multiplier = __a;
- /** An increment. */
- static constexpr result_type increment = __c;
- /** The modulus. */
- static constexpr result_type modulus = __m;
- static constexpr result_type default_seed = 1u;
- /**
- * @brief Constructs a %linear_congruential_engine random number
- * generator engine with seed 1.
- */
- linear_congruential_engine() : linear_congruential_engine(default_seed)
- { }
- /**
- * @brief Constructs a %linear_congruential_engine random number
- * generator engine with seed @p __s. The default seed value
- * is 1.
- *
- * @param __s The initial seed value.
- */
- explicit
- linear_congruential_engine(result_type __s)
- { seed(__s); }
- /**
- * @brief Constructs a %linear_congruential_engine random number
- * generator engine seeded from the seed sequence @p __q.
- *
- * @param __q the seed sequence.
- */
- template<typename _Sseq, typename = _If_seed_seq<_Sseq>>
- explicit
- linear_congruential_engine(_Sseq& __q)
- { seed(__q); }
- /**
- * @brief Reseeds the %linear_congruential_engine random number generator
- * engine sequence to the seed @p __s.
- *
- * @param __s The new seed.
- */
- void
- seed(result_type __s = default_seed);
- /**
- * @brief Reseeds the %linear_congruential_engine random number generator
- * engine
- * sequence using values from the seed sequence @p __q.
- *
- * @param __q the seed sequence.
- */
- template<typename _Sseq>
- _If_seed_seq<_Sseq>
- seed(_Sseq& __q);
- /**
- * @brief Gets the smallest possible value in the output range.
- *
- * The minimum depends on the @p __c parameter: if it is zero, the
- * minimum generated must be > 0, otherwise 0 is allowed.
- */
- static constexpr result_type
- min()
- { return __c == 0u ? 1u : 0u; }
- /**
- * @brief Gets the largest possible value in the output range.
- */
- static constexpr result_type
- max()
- { return __m - 1u; }
- /**
- * @brief Discard a sequence of random numbers.
- */
- void
- discard(unsigned long long __z)
- {
- for (; __z != 0ULL; --__z)
- (*this)();
- }
- /**
- * @brief Gets the next random number in the sequence.
- */
- result_type
- operator()()
- {
- _M_x = __detail::__mod<_UIntType, __m, __a, __c>(_M_x);
- return _M_x;
- }
- /**
- * @brief Compares two linear congruential random number generator
- * objects of the same type for equality.
- *
- * @param __lhs A linear congruential random number generator object.
- * @param __rhs Another linear congruential random number generator
- * object.
- *
- * @returns true if the infinite sequences of generated values
- * would be equal, false otherwise.
- */
- friend bool
- operator==(const linear_congruential_engine& __lhs,
- const linear_congruential_engine& __rhs)
- { return __lhs._M_x == __rhs._M_x; }
- /**
- * @brief Writes the textual representation of the state x(i) of x to
- * @p __os.
- *
- * @param __os The output stream.
- * @param __lcr A % linear_congruential_engine random number generator.
- * @returns __os.
- */
- template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
- _UIntType1 __m1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::linear_congruential_engine<_UIntType1,
- __a1, __c1, __m1>& __lcr);
- /**
- * @brief Sets the state of the engine by reading its textual
- * representation from @p __is.
- *
- * The textual representation must have been previously written using
- * an output stream whose imbued locale and whose type's template
- * specialization arguments _CharT and _Traits were the same as those
- * of @p __is.
- *
- * @param __is The input stream.
- * @param __lcr A % linear_congruential_engine random number generator.
- * @returns __is.
- */
- template<typename _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
- _UIntType1 __m1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::linear_congruential_engine<_UIntType1, __a1,
- __c1, __m1>& __lcr);
- private:
- _UIntType _M_x;
- };
- /**
- * @brief Compares two linear congruential random number generator
- * objects of the same type for inequality.
- *
- * @param __lhs A linear congruential random number generator object.
- * @param __rhs Another linear congruential random number generator
- * object.
- *
- * @returns true if the infinite sequences of generated values
- * would be different, false otherwise.
- */
- template<typename _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
- inline bool
- operator!=(const std::linear_congruential_engine<_UIntType, __a,
- __c, __m>& __lhs,
- const std::linear_congruential_engine<_UIntType, __a,
- __c, __m>& __rhs)
- { return !(__lhs == __rhs); }
- /**
- * A generalized feedback shift register discrete random number generator.
- *
- * This algorithm avoids multiplication and division and is designed to be
- * friendly to a pipelined architecture. If the parameters are chosen
- * correctly, this generator will produce numbers with a very long period and
- * fairly good apparent entropy, although still not cryptographically strong.
- *
- * The best way to use this generator is with the predefined mt19937 class.
- *
- * This algorithm was originally invented by Makoto Matsumoto and
- * Takuji Nishimura.
- *
- * @tparam __w Word size, the number of bits in each element of
- * the state vector.
- * @tparam __n The degree of recursion.
- * @tparam __m The period parameter.
- * @tparam __r The separation point bit index.
- * @tparam __a The last row of the twist matrix.
- * @tparam __u The first right-shift tempering matrix parameter.
- * @tparam __d The first right-shift tempering matrix mask.
- * @tparam __s The first left-shift tempering matrix parameter.
- * @tparam __b The first left-shift tempering matrix mask.
- * @tparam __t The second left-shift tempering matrix parameter.
- * @tparam __c The second left-shift tempering matrix mask.
- * @tparam __l The second right-shift tempering matrix parameter.
- * @tparam __f Initialization multiplier.
- */
- template<typename _UIntType, size_t __w,
- size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t,
- _UIntType __c, size_t __l, _UIntType __f>
- class mersenne_twister_engine
- {
- static_assert(std::is_unsigned<_UIntType>::value,
- "result_type must be an unsigned integral type");
- static_assert(1u <= __m && __m <= __n,
- "template argument substituting __m out of bounds");
- static_assert(__r <= __w, "template argument substituting "
- "__r out of bound");
- static_assert(__u <= __w, "template argument substituting "
- "__u out of bound");
- static_assert(__s <= __w, "template argument substituting "
- "__s out of bound");
- static_assert(__t <= __w, "template argument substituting "
- "__t out of bound");
- static_assert(__l <= __w, "template argument substituting "
- "__l out of bound");
- static_assert(__w <= std::numeric_limits<_UIntType>::digits,
- "template argument substituting __w out of bound");
- static_assert(__a <= (__detail::_Shift<_UIntType, __w>::__value - 1),
- "template argument substituting __a out of bound");
- static_assert(__b <= (__detail::_Shift<_UIntType, __w>::__value - 1),
- "template argument substituting __b out of bound");
- static_assert(__c <= (__detail::_Shift<_UIntType, __w>::__value - 1),
- "template argument substituting __c out of bound");
- static_assert(__d <= (__detail::_Shift<_UIntType, __w>::__value - 1),
- "template argument substituting __d out of bound");
- static_assert(__f <= (__detail::_Shift<_UIntType, __w>::__value - 1),
- "template argument substituting __f out of bound");
- template<typename _Sseq>
- using _If_seed_seq = typename enable_if<__detail::__is_seed_seq<
- _Sseq, mersenne_twister_engine, _UIntType>::value>::type;
- public:
- /** The type of the generated random value. */
- typedef _UIntType result_type;
- // parameter values
- static constexpr size_t word_size = __w;
- static constexpr size_t state_size = __n;
- static constexpr size_t shift_size = __m;
- static constexpr size_t mask_bits = __r;
- static constexpr result_type xor_mask = __a;
- static constexpr size_t tempering_u = __u;
- static constexpr result_type tempering_d = __d;
- static constexpr size_t tempering_s = __s;
- static constexpr result_type tempering_b = __b;
- static constexpr size_t tempering_t = __t;
- static constexpr result_type tempering_c = __c;
- static constexpr size_t tempering_l = __l;
- static constexpr result_type initialization_multiplier = __f;
- static constexpr result_type default_seed = 5489u;
- // constructors and member functions
- mersenne_twister_engine() : mersenne_twister_engine(default_seed) { }
- explicit
- mersenne_twister_engine(result_type __sd)
- { seed(__sd); }
- /**
- * @brief Constructs a %mersenne_twister_engine random number generator
- * engine seeded from the seed sequence @p __q.
- *
- * @param __q the seed sequence.
- */
- template<typename _Sseq, typename = _If_seed_seq<_Sseq>>
- explicit
- mersenne_twister_engine(_Sseq& __q)
- { seed(__q); }
- void
- seed(result_type __sd = default_seed);
- template<typename _Sseq>
- _If_seed_seq<_Sseq>
- seed(_Sseq& __q);
- /**
- * @brief Gets the smallest possible value in the output range.
- */
- static constexpr result_type
- min()
- { return 0; }
- /**
- * @brief Gets the largest possible value in the output range.
- */
- static constexpr result_type
- max()
- { return __detail::_Shift<_UIntType, __w>::__value - 1; }
- /**
- * @brief Discard a sequence of random numbers.
- */
- void
- discard(unsigned long long __z);
- result_type
- operator()();
- /**
- * @brief Compares two % mersenne_twister_engine random number generator
- * objects of the same type for equality.
- *
- * @param __lhs A % mersenne_twister_engine random number generator
- * object.
- * @param __rhs Another % mersenne_twister_engine random number
- * generator object.
- *
- * @returns true if the infinite sequences of generated values
- * would be equal, false otherwise.
- */
- friend bool
- operator==(const mersenne_twister_engine& __lhs,
- const mersenne_twister_engine& __rhs)
- { return (std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x)
- && __lhs._M_p == __rhs._M_p); }
- /**
- * @brief Inserts the current state of a % mersenne_twister_engine
- * random number generator engine @p __x into the output stream
- * @p __os.
- *
- * @param __os An output stream.
- * @param __x A % mersenne_twister_engine random number generator
- * engine.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _UIntType1,
- size_t __w1, size_t __n1,
- size_t __m1, size_t __r1,
- _UIntType1 __a1, size_t __u1,
- _UIntType1 __d1, size_t __s1,
- _UIntType1 __b1, size_t __t1,
- _UIntType1 __c1, size_t __l1, _UIntType1 __f1,
- typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::mersenne_twister_engine<_UIntType1, __w1, __n1,
- __m1, __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1,
- __l1, __f1>& __x);
- /**
- * @brief Extracts the current state of a % mersenne_twister_engine
- * random number generator engine @p __x from the input stream
- * @p __is.
- *
- * @param __is An input stream.
- * @param __x A % mersenne_twister_engine random number generator
- * engine.
- *
- * @returns The input stream with the state of @p __x extracted or in
- * an error state.
- */
- template<typename _UIntType1,
- size_t __w1, size_t __n1,
- size_t __m1, size_t __r1,
- _UIntType1 __a1, size_t __u1,
- _UIntType1 __d1, size_t __s1,
- _UIntType1 __b1, size_t __t1,
- _UIntType1 __c1, size_t __l1, _UIntType1 __f1,
- typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::mersenne_twister_engine<_UIntType1, __w1, __n1, __m1,
- __r1, __a1, __u1, __d1, __s1, __b1, __t1, __c1,
- __l1, __f1>& __x);
- private:
- void _M_gen_rand();
- _UIntType _M_x[state_size];
- size_t _M_p;
- };
- /**
- * @brief Compares two % mersenne_twister_engine random number generator
- * objects of the same type for inequality.
- *
- * @param __lhs A % mersenne_twister_engine random number generator
- * object.
- * @param __rhs Another % mersenne_twister_engine random number
- * generator object.
- *
- * @returns true if the infinite sequences of generated values
- * would be different, false otherwise.
- */
- template<typename _UIntType, size_t __w,
- size_t __n, size_t __m, size_t __r,
- _UIntType __a, size_t __u, _UIntType __d, size_t __s,
- _UIntType __b, size_t __t,
- _UIntType __c, size_t __l, _UIntType __f>
- inline bool
- operator!=(const std::mersenne_twister_engine<_UIntType, __w, __n, __m,
- __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __lhs,
- const std::mersenne_twister_engine<_UIntType, __w, __n, __m,
- __r, __a, __u, __d, __s, __b, __t, __c, __l, __f>& __rhs)
- { return !(__lhs == __rhs); }
- /**
- * @brief The Marsaglia-Zaman generator.
- *
- * This is a model of a Generalized Fibonacci discrete random number
- * generator, sometimes referred to as the SWC generator.
- *
- * A discrete random number generator that produces pseudorandom
- * numbers using:
- * @f[
- * x_{i}\leftarrow(x_{i - s} - x_{i - r} - carry_{i-1}) \bmod m
- * @f]
- *
- * The size of the state is @f$r@f$
- * and the maximum period of the generator is @f$(m^r - m^s - 1)@f$.
- */
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- class subtract_with_carry_engine
- {
- static_assert(std::is_unsigned<_UIntType>::value,
- "result_type must be an unsigned integral type");
- static_assert(0u < __s && __s < __r,
- "0 < s < r");
- static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits,
- "template argument substituting __w out of bounds");
- template<typename _Sseq>
- using _If_seed_seq = typename enable_if<__detail::__is_seed_seq<
- _Sseq, subtract_with_carry_engine, _UIntType>::value>::type;
- public:
- /** The type of the generated random value. */
- typedef _UIntType result_type;
- // parameter values
- static constexpr size_t word_size = __w;
- static constexpr size_t short_lag = __s;
- static constexpr size_t long_lag = __r;
- static constexpr result_type default_seed = 19780503u;
- subtract_with_carry_engine() : subtract_with_carry_engine(default_seed)
- { }
- /**
- * @brief Constructs an explicitly seeded %subtract_with_carry_engine
- * random number generator.
- */
- explicit
- subtract_with_carry_engine(result_type __sd)
- { seed(__sd); }
- /**
- * @brief Constructs a %subtract_with_carry_engine random number engine
- * seeded from the seed sequence @p __q.
- *
- * @param __q the seed sequence.
- */
- template<typename _Sseq, typename = _If_seed_seq<_Sseq>>
- explicit
- subtract_with_carry_engine(_Sseq& __q)
- { seed(__q); }
- /**
- * @brief Seeds the initial state @f$x_0@f$ of the random number
- * generator.
- *
- * N1688[4.19] modifies this as follows. If @p __value == 0,
- * sets value to 19780503. In any case, with a linear
- * congruential generator lcg(i) having parameters @f$ m_{lcg} =
- * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value
- * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m
- * \dots lcg(r) \bmod m @f$ respectively. If @f$ x_{-1} = 0 @f$
- * set carry to 1, otherwise sets carry to 0.
- */
- void
- seed(result_type __sd = default_seed);
- /**
- * @brief Seeds the initial state @f$x_0@f$ of the
- * % subtract_with_carry_engine random number generator.
- */
- template<typename _Sseq>
- _If_seed_seq<_Sseq>
- seed(_Sseq& __q);
- /**
- * @brief Gets the inclusive minimum value of the range of random
- * integers returned by this generator.
- */
- static constexpr result_type
- min()
- { return 0; }
- /**
- * @brief Gets the inclusive maximum value of the range of random
- * integers returned by this generator.
- */
- static constexpr result_type
- max()
- { return __detail::_Shift<_UIntType, __w>::__value - 1; }
- /**
- * @brief Discard a sequence of random numbers.
- */
- void
- discard(unsigned long long __z)
- {
- for (; __z != 0ULL; --__z)
- (*this)();
- }
- /**
- * @brief Gets the next random number in the sequence.
- */
- result_type
- operator()();
- /**
- * @brief Compares two % subtract_with_carry_engine random number
- * generator objects of the same type for equality.
- *
- * @param __lhs A % subtract_with_carry_engine random number generator
- * object.
- * @param __rhs Another % subtract_with_carry_engine random number
- * generator object.
- *
- * @returns true if the infinite sequences of generated values
- * would be equal, false otherwise.
- */
- friend bool
- operator==(const subtract_with_carry_engine& __lhs,
- const subtract_with_carry_engine& __rhs)
- { return (std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x)
- && __lhs._M_carry == __rhs._M_carry
- && __lhs._M_p == __rhs._M_p); }
- /**
- * @brief Inserts the current state of a % subtract_with_carry_engine
- * random number generator engine @p __x into the output stream
- * @p __os.
- *
- * @param __os An output stream.
- * @param __x A % subtract_with_carry_engine random number generator
- * engine.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1,
- typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::subtract_with_carry_engine<_UIntType1, __w1,
- __s1, __r1>& __x);
- /**
- * @brief Extracts the current state of a % subtract_with_carry_engine
- * random number generator engine @p __x from the input stream
- * @p __is.
- *
- * @param __is An input stream.
- * @param __x A % subtract_with_carry_engine random number generator
- * engine.
- *
- * @returns The input stream with the state of @p __x extracted or in
- * an error state.
- */
- template<typename _UIntType1, size_t __w1, size_t __s1, size_t __r1,
- typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::subtract_with_carry_engine<_UIntType1, __w1,
- __s1, __r1>& __x);
- private:
- /// The state of the generator. This is a ring buffer.
- _UIntType _M_x[long_lag];
- _UIntType _M_carry; ///< The carry
- size_t _M_p; ///< Current index of x(i - r).
- };
- /**
- * @brief Compares two % subtract_with_carry_engine random number
- * generator objects of the same type for inequality.
- *
- * @param __lhs A % subtract_with_carry_engine random number generator
- * object.
- * @param __rhs Another % subtract_with_carry_engine random number
- * generator object.
- *
- * @returns true if the infinite sequences of generated values
- * would be different, false otherwise.
- */
- template<typename _UIntType, size_t __w, size_t __s, size_t __r>
- inline bool
- operator!=(const std::subtract_with_carry_engine<_UIntType, __w,
- __s, __r>& __lhs,
- const std::subtract_with_carry_engine<_UIntType, __w,
- __s, __r>& __rhs)
- { return !(__lhs == __rhs); }
- /**
- * Produces random numbers from some base engine by discarding blocks of
- * data.
- *
- * 0 <= @p __r <= @p __p
- */
- template<typename _RandomNumberEngine, size_t __p, size_t __r>
- class discard_block_engine
- {
- static_assert(1 <= __r && __r <= __p,
- "template argument substituting __r out of bounds");
- public:
- /** The type of the generated random value. */
- typedef typename _RandomNumberEngine::result_type result_type;
- template<typename _Sseq>
- using _If_seed_seq = typename enable_if<__detail::__is_seed_seq<
- _Sseq, discard_block_engine, result_type>::value>::type;
- // parameter values
- static constexpr size_t block_size = __p;
- static constexpr size_t used_block = __r;
- /**
- * @brief Constructs a default %discard_block_engine engine.
- *
- * The underlying engine is default constructed as well.
- */
- discard_block_engine()
- : _M_b(), _M_n(0) { }
- /**
- * @brief Copy constructs a %discard_block_engine engine.
- *
- * Copies an existing base class random number generator.
- * @param __rng An existing (base class) engine object.
- */
- explicit
- discard_block_engine(const _RandomNumberEngine& __rng)
- : _M_b(__rng), _M_n(0) { }
- /**
- * @brief Move constructs a %discard_block_engine engine.
- *
- * Copies an existing base class random number generator.
- * @param __rng An existing (base class) engine object.
- */
- explicit
- discard_block_engine(_RandomNumberEngine&& __rng)
- : _M_b(std::move(__rng)), _M_n(0) { }
- /**
- * @brief Seed constructs a %discard_block_engine engine.
- *
- * Constructs the underlying generator engine seeded with @p __s.
- * @param __s A seed value for the base class engine.
- */
- explicit
- discard_block_engine(result_type __s)
- : _M_b(__s), _M_n(0) { }
- /**
- * @brief Generator construct a %discard_block_engine engine.
- *
- * @param __q A seed sequence.
- */
- template<typename _Sseq, typename = _If_seed_seq<_Sseq>>
- explicit
- discard_block_engine(_Sseq& __q)
- : _M_b(__q), _M_n(0)
- { }
- /**
- * @brief Reseeds the %discard_block_engine object with the default
- * seed for the underlying base class generator engine.
- */
- void
- seed()
- {
- _M_b.seed();
- _M_n = 0;
- }
- /**
- * @brief Reseeds the %discard_block_engine object with the default
- * seed for the underlying base class generator engine.
- */
- void
- seed(result_type __s)
- {
- _M_b.seed(__s);
- _M_n = 0;
- }
- /**
- * @brief Reseeds the %discard_block_engine object with the given seed
- * sequence.
- * @param __q A seed generator function.
- */
- template<typename _Sseq>
- _If_seed_seq<_Sseq>
- seed(_Sseq& __q)
- {
- _M_b.seed(__q);
- _M_n = 0;
- }
- /**
- * @brief Gets a const reference to the underlying generator engine
- * object.
- */
- const _RandomNumberEngine&
- base() const noexcept
- { return _M_b; }
- /**
- * @brief Gets the minimum value in the generated random number range.
- */
- static constexpr result_type
- min()
- { return _RandomNumberEngine::min(); }
- /**
- * @brief Gets the maximum value in the generated random number range.
- */
- static constexpr result_type
- max()
- { return _RandomNumberEngine::max(); }
- /**
- * @brief Discard a sequence of random numbers.
- */
- void
- discard(unsigned long long __z)
- {
- for (; __z != 0ULL; --__z)
- (*this)();
- }
- /**
- * @brief Gets the next value in the generated random number sequence.
- */
- result_type
- operator()();
- /**
- * @brief Compares two %discard_block_engine random number generator
- * objects of the same type for equality.
- *
- * @param __lhs A %discard_block_engine random number generator object.
- * @param __rhs Another %discard_block_engine random number generator
- * object.
- *
- * @returns true if the infinite sequences of generated values
- * would be equal, false otherwise.
- */
- friend bool
- operator==(const discard_block_engine& __lhs,
- const discard_block_engine& __rhs)
- { return __lhs._M_b == __rhs._M_b && __lhs._M_n == __rhs._M_n; }
- /**
- * @brief Inserts the current state of a %discard_block_engine random
- * number generator engine @p __x into the output stream
- * @p __os.
- *
- * @param __os An output stream.
- * @param __x A %discard_block_engine random number generator engine.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RandomNumberEngine1, size_t __p1, size_t __r1,
- typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::discard_block_engine<_RandomNumberEngine1,
- __p1, __r1>& __x);
- /**
- * @brief Extracts the current state of a % subtract_with_carry_engine
- * random number generator engine @p __x from the input stream
- * @p __is.
- *
- * @param __is An input stream.
- * @param __x A %discard_block_engine random number generator engine.
- *
- * @returns The input stream with the state of @p __x extracted or in
- * an error state.
- */
- template<typename _RandomNumberEngine1, size_t __p1, size_t __r1,
- typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::discard_block_engine<_RandomNumberEngine1,
- __p1, __r1>& __x);
- private:
- _RandomNumberEngine _M_b;
- size_t _M_n;
- };
- /**
- * @brief Compares two %discard_block_engine random number generator
- * objects of the same type for inequality.
- *
- * @param __lhs A %discard_block_engine random number generator object.
- * @param __rhs Another %discard_block_engine random number generator
- * object.
- *
- * @returns true if the infinite sequences of generated values
- * would be different, false otherwise.
- */
- template<typename _RandomNumberEngine, size_t __p, size_t __r>
- inline bool
- operator!=(const std::discard_block_engine<_RandomNumberEngine, __p,
- __r>& __lhs,
- const std::discard_block_engine<_RandomNumberEngine, __p,
- __r>& __rhs)
- { return !(__lhs == __rhs); }
- /**
- * Produces random numbers by combining random numbers from some base
- * engine to produce random numbers with a specified number of bits @p __w.
- */
- template<typename _RandomNumberEngine, size_t __w, typename _UIntType>
- class independent_bits_engine
- {
- static_assert(std::is_unsigned<_UIntType>::value,
- "result_type must be an unsigned integral type");
- static_assert(0u < __w && __w <= std::numeric_limits<_UIntType>::digits,
- "template argument substituting __w out of bounds");
- template<typename _Sseq>
- using _If_seed_seq = typename enable_if<__detail::__is_seed_seq<
- _Sseq, independent_bits_engine, _UIntType>::value>::type;
- public:
- /** The type of the generated random value. */
- typedef _UIntType result_type;
- /**
- * @brief Constructs a default %independent_bits_engine engine.
- *
- * The underlying engine is default constructed as well.
- */
- independent_bits_engine()
- : _M_b() { }
- /**
- * @brief Copy constructs a %independent_bits_engine engine.
- *
- * Copies an existing base class random number generator.
- * @param __rng An existing (base class) engine object.
- */
- explicit
- independent_bits_engine(const _RandomNumberEngine& __rng)
- : _M_b(__rng) { }
- /**
- * @brief Move constructs a %independent_bits_engine engine.
- *
- * Copies an existing base class random number generator.
- * @param __rng An existing (base class) engine object.
- */
- explicit
- independent_bits_engine(_RandomNumberEngine&& __rng)
- : _M_b(std::move(__rng)) { }
- /**
- * @brief Seed constructs a %independent_bits_engine engine.
- *
- * Constructs the underlying generator engine seeded with @p __s.
- * @param __s A seed value for the base class engine.
- */
- explicit
- independent_bits_engine(result_type __s)
- : _M_b(__s) { }
- /**
- * @brief Generator construct a %independent_bits_engine engine.
- *
- * @param __q A seed sequence.
- */
- template<typename _Sseq, typename = _If_seed_seq<_Sseq>>
- explicit
- independent_bits_engine(_Sseq& __q)
- : _M_b(__q)
- { }
- /**
- * @brief Reseeds the %independent_bits_engine object with the default
- * seed for the underlying base class generator engine.
- */
- void
- seed()
- { _M_b.seed(); }
- /**
- * @brief Reseeds the %independent_bits_engine object with the default
- * seed for the underlying base class generator engine.
- */
- void
- seed(result_type __s)
- { _M_b.seed(__s); }
- /**
- * @brief Reseeds the %independent_bits_engine object with the given
- * seed sequence.
- * @param __q A seed generator function.
- */
- template<typename _Sseq>
- _If_seed_seq<_Sseq>
- seed(_Sseq& __q)
- { _M_b.seed(__q); }
- /**
- * @brief Gets a const reference to the underlying generator engine
- * object.
- */
- const _RandomNumberEngine&
- base() const noexcept
- { return _M_b; }
- /**
- * @brief Gets the minimum value in the generated random number range.
- */
- static constexpr result_type
- min()
- { return 0U; }
- /**
- * @brief Gets the maximum value in the generated random number range.
- */
- static constexpr result_type
- max()
- { return __detail::_Shift<_UIntType, __w>::__value - 1; }
- /**
- * @brief Discard a sequence of random numbers.
- */
- void
- discard(unsigned long long __z)
- {
- for (; __z != 0ULL; --__z)
- (*this)();
- }
- /**
- * @brief Gets the next value in the generated random number sequence.
- */
- result_type
- operator()();
- /**
- * @brief Compares two %independent_bits_engine random number generator
- * objects of the same type for equality.
- *
- * @param __lhs A %independent_bits_engine random number generator
- * object.
- * @param __rhs Another %independent_bits_engine random number generator
- * object.
- *
- * @returns true if the infinite sequences of generated values
- * would be equal, false otherwise.
- */
- friend bool
- operator==(const independent_bits_engine& __lhs,
- const independent_bits_engine& __rhs)
- { return __lhs._M_b == __rhs._M_b; }
- /**
- * @brief Extracts the current state of a % subtract_with_carry_engine
- * random number generator engine @p __x from the input stream
- * @p __is.
- *
- * @param __is An input stream.
- * @param __x A %independent_bits_engine random number generator
- * engine.
- *
- * @returns The input stream with the state of @p __x extracted or in
- * an error state.
- */
- template<typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::independent_bits_engine<_RandomNumberEngine,
- __w, _UIntType>& __x)
- {
- __is >> __x._M_b;
- return __is;
- }
- private:
- _RandomNumberEngine _M_b;
- };
- /**
- * @brief Compares two %independent_bits_engine random number generator
- * objects of the same type for inequality.
- *
- * @param __lhs A %independent_bits_engine random number generator
- * object.
- * @param __rhs Another %independent_bits_engine random number generator
- * object.
- *
- * @returns true if the infinite sequences of generated values
- * would be different, false otherwise.
- */
- template<typename _RandomNumberEngine, size_t __w, typename _UIntType>
- inline bool
- operator!=(const std::independent_bits_engine<_RandomNumberEngine, __w,
- _UIntType>& __lhs,
- const std::independent_bits_engine<_RandomNumberEngine, __w,
- _UIntType>& __rhs)
- { return !(__lhs == __rhs); }
- /**
- * @brief Inserts the current state of a %independent_bits_engine random
- * number generator engine @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %independent_bits_engine random number generator engine.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RandomNumberEngine, size_t __w, typename _UIntType,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::independent_bits_engine<_RandomNumberEngine,
- __w, _UIntType>& __x)
- {
- __os << __x.base();
- return __os;
- }
- /**
- * @brief Produces random numbers by reordering random numbers from some
- * base engine.
- *
- * The values from the base engine are stored in a sequence of size @p __k
- * and shuffled by an algorithm that depends on those values.
- */
- template<typename _RandomNumberEngine, size_t __k>
- class shuffle_order_engine
- {
- static_assert(1u <= __k, "template argument substituting "
- "__k out of bound");
- public:
- /** The type of the generated random value. */
- typedef typename _RandomNumberEngine::result_type result_type;
- template<typename _Sseq>
- using _If_seed_seq = typename enable_if<__detail::__is_seed_seq<
- _Sseq, shuffle_order_engine, result_type>::value>::type;
- static constexpr size_t table_size = __k;
- /**
- * @brief Constructs a default %shuffle_order_engine engine.
- *
- * The underlying engine is default constructed as well.
- */
- shuffle_order_engine()
- : _M_b()
- { _M_initialize(); }
- /**
- * @brief Copy constructs a %shuffle_order_engine engine.
- *
- * Copies an existing base class random number generator.
- * @param __rng An existing (base class) engine object.
- */
- explicit
- shuffle_order_engine(const _RandomNumberEngine& __rng)
- : _M_b(__rng)
- { _M_initialize(); }
- /**
- * @brief Move constructs a %shuffle_order_engine engine.
- *
- * Copies an existing base class random number generator.
- * @param __rng An existing (base class) engine object.
- */
- explicit
- shuffle_order_engine(_RandomNumberEngine&& __rng)
- : _M_b(std::move(__rng))
- { _M_initialize(); }
- /**
- * @brief Seed constructs a %shuffle_order_engine engine.
- *
- * Constructs the underlying generator engine seeded with @p __s.
- * @param __s A seed value for the base class engine.
- */
- explicit
- shuffle_order_engine(result_type __s)
- : _M_b(__s)
- { _M_initialize(); }
- /**
- * @brief Generator construct a %shuffle_order_engine engine.
- *
- * @param __q A seed sequence.
- */
- template<typename _Sseq, typename = _If_seed_seq<_Sseq>>
- explicit
- shuffle_order_engine(_Sseq& __q)
- : _M_b(__q)
- { _M_initialize(); }
- /**
- * @brief Reseeds the %shuffle_order_engine object with the default seed
- for the underlying base class generator engine.
- */
- void
- seed()
- {
- _M_b.seed();
- _M_initialize();
- }
- /**
- * @brief Reseeds the %shuffle_order_engine object with the default seed
- * for the underlying base class generator engine.
- */
- void
- seed(result_type __s)
- {
- _M_b.seed(__s);
- _M_initialize();
- }
- /**
- * @brief Reseeds the %shuffle_order_engine object with the given seed
- * sequence.
- * @param __q A seed generator function.
- */
- template<typename _Sseq>
- _If_seed_seq<_Sseq>
- seed(_Sseq& __q)
- {
- _M_b.seed(__q);
- _M_initialize();
- }
- /**
- * Gets a const reference to the underlying generator engine object.
- */
- const _RandomNumberEngine&
- base() const noexcept
- { return _M_b; }
- /**
- * Gets the minimum value in the generated random number range.
- */
- static constexpr result_type
- min()
- { return _RandomNumberEngine::min(); }
- /**
- * Gets the maximum value in the generated random number range.
- */
- static constexpr result_type
- max()
- { return _RandomNumberEngine::max(); }
- /**
- * Discard a sequence of random numbers.
- */
- void
- discard(unsigned long long __z)
- {
- for (; __z != 0ULL; --__z)
- (*this)();
- }
- /**
- * Gets the next value in the generated random number sequence.
- */
- result_type
- operator()();
- /**
- * Compares two %shuffle_order_engine random number generator objects
- * of the same type for equality.
- *
- * @param __lhs A %shuffle_order_engine random number generator object.
- * @param __rhs Another %shuffle_order_engine random number generator
- * object.
- *
- * @returns true if the infinite sequences of generated values
- * would be equal, false otherwise.
- */
- friend bool
- operator==(const shuffle_order_engine& __lhs,
- const shuffle_order_engine& __rhs)
- { return (__lhs._M_b == __rhs._M_b
- && std::equal(__lhs._M_v, __lhs._M_v + __k, __rhs._M_v)
- && __lhs._M_y == __rhs._M_y); }
- /**
- * @brief Inserts the current state of a %shuffle_order_engine random
- * number generator engine @p __x into the output stream
- @p __os.
- *
- * @param __os An output stream.
- * @param __x A %shuffle_order_engine random number generator engine.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RandomNumberEngine1, size_t __k1,
- typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::shuffle_order_engine<_RandomNumberEngine1,
- __k1>& __x);
- /**
- * @brief Extracts the current state of a % subtract_with_carry_engine
- * random number generator engine @p __x from the input stream
- * @p __is.
- *
- * @param __is An input stream.
- * @param __x A %shuffle_order_engine random number generator engine.
- *
- * @returns The input stream with the state of @p __x extracted or in
- * an error state.
- */
- template<typename _RandomNumberEngine1, size_t __k1,
- typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::shuffle_order_engine<_RandomNumberEngine1, __k1>& __x);
- private:
- void _M_initialize()
- {
- for (size_t __i = 0; __i < __k; ++__i)
- _M_v[__i] = _M_b();
- _M_y = _M_b();
- }
- _RandomNumberEngine _M_b;
- result_type _M_v[__k];
- result_type _M_y;
- };
- /**
- * Compares two %shuffle_order_engine random number generator objects
- * of the same type for inequality.
- *
- * @param __lhs A %shuffle_order_engine random number generator object.
- * @param __rhs Another %shuffle_order_engine random number generator
- * object.
- *
- * @returns true if the infinite sequences of generated values
- * would be different, false otherwise.
- */
- template<typename _RandomNumberEngine, size_t __k>
- inline bool
- operator!=(const std::shuffle_order_engine<_RandomNumberEngine,
- __k>& __lhs,
- const std::shuffle_order_engine<_RandomNumberEngine,
- __k>& __rhs)
- { return !(__lhs == __rhs); }
- /**
- * The classic Minimum Standard rand0 of Lewis, Goodman, and Miller.
- */
- typedef linear_congruential_engine<uint_fast32_t, 16807UL, 0UL, 2147483647UL>
- minstd_rand0;
- /**
- * An alternative LCR (Lehmer Generator function).
- */
- typedef linear_congruential_engine<uint_fast32_t, 48271UL, 0UL, 2147483647UL>
- minstd_rand;
- /**
- * The classic Mersenne Twister.
- *
- * Reference:
- * M. Matsumoto and T. Nishimura, Mersenne Twister: A 623-Dimensionally
- * Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions
- * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30.
- */
- typedef mersenne_twister_engine<
- uint_fast32_t,
- 32, 624, 397, 31,
- 0x9908b0dfUL, 11,
- 0xffffffffUL, 7,
- 0x9d2c5680UL, 15,
- 0xefc60000UL, 18, 1812433253UL> mt19937;
- /**
- * An alternative Mersenne Twister.
- */
- typedef mersenne_twister_engine<
- uint_fast64_t,
- 64, 312, 156, 31,
- 0xb5026f5aa96619e9ULL, 29,
- 0x5555555555555555ULL, 17,
- 0x71d67fffeda60000ULL, 37,
- 0xfff7eee000000000ULL, 43,
- 6364136223846793005ULL> mt19937_64;
- typedef subtract_with_carry_engine<uint_fast32_t, 24, 10, 24>
- ranlux24_base;
- typedef subtract_with_carry_engine<uint_fast64_t, 48, 5, 12>
- ranlux48_base;
- typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24;
- typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48;
- typedef shuffle_order_engine<minstd_rand0, 256> knuth_b;
- typedef minstd_rand0 default_random_engine;
- /**
- * A standard interface to a platform-specific non-deterministic
- * random number generator (if any are available).
- */
- class random_device
- {
- public:
- /** The type of the generated random value. */
- typedef unsigned int result_type;
- // constructors, destructors and member functions
- random_device() { _M_init("default"); }
- explicit
- random_device(const std::string& __token) { _M_init(__token); }
- #if defined _GLIBCXX_USE_DEV_RANDOM
- ~random_device()
- { _M_fini(); }
- #endif
- static constexpr result_type
- min()
- { return std::numeric_limits<result_type>::min(); }
- static constexpr result_type
- max()
- { return std::numeric_limits<result_type>::max(); }
- double
- entropy() const noexcept
- {
- #ifdef _GLIBCXX_USE_DEV_RANDOM
- return this->_M_getentropy();
- #else
- return 0.0;
- #endif
- }
- result_type
- operator()()
- { return this->_M_getval(); }
- // No copy functions.
- random_device(const random_device&) = delete;
- void operator=(const random_device&) = delete;
- private:
- void _M_init(const std::string& __token);
- void _M_init_pretr1(const std::string& __token);
- void _M_fini();
- result_type _M_getval();
- result_type _M_getval_pretr1();
- double _M_getentropy() const noexcept;
- void _M_init(const char*, size_t); // not exported from the shared library
- __extension__ union
- {
- struct
- {
- void* _M_file;
- result_type (*_M_func)(void*);
- int _M_fd;
- };
- mt19937 _M_mt;
- };
- };
- /// @} group random_generators
- /**
- * @addtogroup random_distributions Random Number Distributions
- * @ingroup random
- * @{
- */
- /**
- * @addtogroup random_distributions_uniform Uniform Distributions
- * @ingroup random_distributions
- * @{
- */
- // std::uniform_int_distribution is defined in <bits/uniform_int_dist.h>
- /**
- * @brief Return true if two uniform integer distributions have
- * different parameters.
- */
- template<typename _IntType>
- inline bool
- operator!=(const std::uniform_int_distribution<_IntType>& __d1,
- const std::uniform_int_distribution<_IntType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief Inserts a %uniform_int_distribution random number
- * distribution @p __x into the output stream @p os.
- *
- * @param __os An output stream.
- * @param __x A %uniform_int_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::uniform_int_distribution<_IntType>&);
- /**
- * @brief Extracts a %uniform_int_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %uniform_int_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _IntType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::uniform_int_distribution<_IntType>&);
- /**
- * @brief Uniform continuous distribution for random numbers.
- *
- * A continuous random distribution on the range [min, max) with equal
- * probability throughout the range. The URNG should be real-valued and
- * deliver number in the range [0, 1).
- */
- template<typename _RealType = double>
- class uniform_real_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef uniform_real_distribution<_RealType> distribution_type;
- param_type() : param_type(0) { }
- explicit
- param_type(_RealType __a, _RealType __b = _RealType(1))
- : _M_a(__a), _M_b(__b)
- {
- __glibcxx_assert(_M_a <= _M_b);
- }
- result_type
- a() const
- { return _M_a; }
- result_type
- b() const
- { return _M_b; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_a;
- _RealType _M_b;
- };
- public:
- /**
- * @brief Constructs a uniform_real_distribution object.
- *
- * The lower bound is set to 0.0 and the upper bound to 1.0
- */
- uniform_real_distribution() : uniform_real_distribution(0.0) { }
- /**
- * @brief Constructs a uniform_real_distribution object.
- *
- * @param __a [IN] The lower bound of the distribution.
- * @param __b [IN] The upper bound of the distribution.
- */
- explicit
- uniform_real_distribution(_RealType __a, _RealType __b = _RealType(1))
- : _M_param(__a, __b)
- { }
- explicit
- uniform_real_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- *
- * Does nothing for the uniform real distribution.
- */
- void
- reset() { }
- result_type
- a() const
- { return _M_param.a(); }
- result_type
- b() const
- { return _M_param.b(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the inclusive lower bound of the distribution range.
- */
- result_type
- min() const
- { return this->a(); }
- /**
- * @brief Returns the inclusive upper bound of the distribution range.
- */
- result_type
- max() const
- { return this->b(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- return (__aurng() * (__p.b() - __p.a())) + __p.a();
- }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two uniform real distributions have
- * the same parameters.
- */
- friend bool
- operator==(const uniform_real_distribution& __d1,
- const uniform_real_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two uniform real distributions have
- * different parameters.
- */
- template<typename _IntType>
- inline bool
- operator!=(const std::uniform_real_distribution<_IntType>& __d1,
- const std::uniform_real_distribution<_IntType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief Inserts a %uniform_real_distribution random number
- * distribution @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %uniform_real_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>&,
- const std::uniform_real_distribution<_RealType>&);
- /**
- * @brief Extracts a %uniform_real_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %uniform_real_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>&,
- std::uniform_real_distribution<_RealType>&);
- /// @} group random_distributions_uniform
- /**
- * @addtogroup random_distributions_normal Normal Distributions
- * @ingroup random_distributions
- * @{
- */
- /**
- * @brief A normal continuous distribution for random numbers.
- *
- * The formula for the normal probability density function is
- * @f[
- * p(x|\mu,\sigma) = \frac{1}{\sigma \sqrt{2 \pi}}
- * e^{- \frac{{x - \mu}^ {2}}{2 \sigma ^ {2}} }
- * @f]
- */
- template<typename _RealType = double>
- class normal_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef normal_distribution<_RealType> distribution_type;
- param_type() : param_type(0.0) { }
- explicit
- param_type(_RealType __mean, _RealType __stddev = _RealType(1))
- : _M_mean(__mean), _M_stddev(__stddev)
- {
- __glibcxx_assert(_M_stddev > _RealType(0));
- }
- _RealType
- mean() const
- { return _M_mean; }
- _RealType
- stddev() const
- { return _M_stddev; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return (__p1._M_mean == __p2._M_mean
- && __p1._M_stddev == __p2._M_stddev); }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_mean;
- _RealType _M_stddev;
- };
- public:
- normal_distribution() : normal_distribution(0.0) { }
- /**
- * Constructs a normal distribution with parameters @f$mean@f$ and
- * standard deviation.
- */
- explicit
- normal_distribution(result_type __mean,
- result_type __stddev = result_type(1))
- : _M_param(__mean, __stddev)
- { }
- explicit
- normal_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { _M_saved_available = false; }
- /**
- * @brief Returns the mean of the distribution.
- */
- _RealType
- mean() const
- { return _M_param.mean(); }
- /**
- * @brief Returns the standard deviation of the distribution.
- */
- _RealType
- stddev() const
- { return _M_param.stddev(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return std::numeric_limits<result_type>::lowest(); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two normal distributions have
- * the same parameters and the sequences that would
- * be generated are equal.
- */
- template<typename _RealType1>
- friend bool
- operator==(const std::normal_distribution<_RealType1>& __d1,
- const std::normal_distribution<_RealType1>& __d2);
- /**
- * @brief Inserts a %normal_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %normal_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::normal_distribution<_RealType1>& __x);
- /**
- * @brief Extracts a %normal_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %normal_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error
- * state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::normal_distribution<_RealType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- result_type _M_saved = 0;
- bool _M_saved_available = false;
- };
- /**
- * @brief Return true if two normal distributions are different.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::normal_distribution<_RealType>& __d1,
- const std::normal_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief A lognormal_distribution random number distribution.
- *
- * The formula for the normal probability mass function is
- * @f[
- * p(x|m,s) = \frac{1}{sx\sqrt{2\pi}}
- * \exp{-\frac{(\ln{x} - m)^2}{2s^2}}
- * @f]
- */
- template<typename _RealType = double>
- class lognormal_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef lognormal_distribution<_RealType> distribution_type;
- param_type() : param_type(0.0) { }
- explicit
- param_type(_RealType __m, _RealType __s = _RealType(1))
- : _M_m(__m), _M_s(__s)
- { }
- _RealType
- m() const
- { return _M_m; }
- _RealType
- s() const
- { return _M_s; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_m == __p2._M_m && __p1._M_s == __p2._M_s; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_m;
- _RealType _M_s;
- };
- lognormal_distribution() : lognormal_distribution(0.0) { }
- explicit
- lognormal_distribution(_RealType __m, _RealType __s = _RealType(1))
- : _M_param(__m, __s), _M_nd()
- { }
- explicit
- lognormal_distribution(const param_type& __p)
- : _M_param(__p), _M_nd()
- { }
- /**
- * Resets the distribution state.
- */
- void
- reset()
- { _M_nd.reset(); }
- /**
- *
- */
- _RealType
- m() const
- { return _M_param.m(); }
- _RealType
- s() const
- { return _M_param.s(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return result_type(0); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { return std::exp(__p.s() * _M_nd(__urng) + __p.m()); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two lognormal distributions have
- * the same parameters and the sequences that would
- * be generated are equal.
- */
- friend bool
- operator==(const lognormal_distribution& __d1,
- const lognormal_distribution& __d2)
- { return (__d1._M_param == __d2._M_param
- && __d1._M_nd == __d2._M_nd); }
- /**
- * @brief Inserts a %lognormal_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %lognormal_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::lognormal_distribution<_RealType1>& __x);
- /**
- * @brief Extracts a %lognormal_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %lognormal_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::lognormal_distribution<_RealType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- std::normal_distribution<result_type> _M_nd;
- };
- /**
- * @brief Return true if two lognormal distributions are different.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::lognormal_distribution<_RealType>& __d1,
- const std::lognormal_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief A gamma continuous distribution for random numbers.
- *
- * The formula for the gamma probability density function is:
- * @f[
- * p(x|\alpha,\beta) = \frac{1}{\beta\Gamma(\alpha)}
- * (x/\beta)^{\alpha - 1} e^{-x/\beta}
- * @f]
- */
- template<typename _RealType = double>
- class gamma_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef gamma_distribution<_RealType> distribution_type;
- friend class gamma_distribution<_RealType>;
- param_type() : param_type(1.0) { }
- explicit
- param_type(_RealType __alpha_val, _RealType __beta_val = _RealType(1))
- : _M_alpha(__alpha_val), _M_beta(__beta_val)
- {
- __glibcxx_assert(_M_alpha > _RealType(0));
- _M_initialize();
- }
- _RealType
- alpha() const
- { return _M_alpha; }
- _RealType
- beta() const
- { return _M_beta; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return (__p1._M_alpha == __p2._M_alpha
- && __p1._M_beta == __p2._M_beta); }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- void
- _M_initialize();
- _RealType _M_alpha;
- _RealType _M_beta;
- _RealType _M_malpha, _M_a2;
- };
- public:
- /**
- * @brief Constructs a gamma distribution with parameters 1 and 1.
- */
- gamma_distribution() : gamma_distribution(1.0) { }
- /**
- * @brief Constructs a gamma distribution with parameters
- * @f$\alpha@f$ and @f$\beta@f$.
- */
- explicit
- gamma_distribution(_RealType __alpha_val,
- _RealType __beta_val = _RealType(1))
- : _M_param(__alpha_val, __beta_val), _M_nd()
- { }
- explicit
- gamma_distribution(const param_type& __p)
- : _M_param(__p), _M_nd()
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { _M_nd.reset(); }
- /**
- * @brief Returns the @f$\alpha@f$ of the distribution.
- */
- _RealType
- alpha() const
- { return _M_param.alpha(); }
- /**
- * @brief Returns the @f$\beta@f$ of the distribution.
- */
- _RealType
- beta() const
- { return _M_param.beta(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return result_type(0); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two gamma distributions have the same
- * parameters and the sequences that would be generated
- * are equal.
- */
- friend bool
- operator==(const gamma_distribution& __d1,
- const gamma_distribution& __d2)
- { return (__d1._M_param == __d2._M_param
- && __d1._M_nd == __d2._M_nd); }
- /**
- * @brief Inserts a %gamma_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %gamma_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::gamma_distribution<_RealType1>& __x);
- /**
- * @brief Extracts a %gamma_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %gamma_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::gamma_distribution<_RealType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- std::normal_distribution<result_type> _M_nd;
- };
- /**
- * @brief Return true if two gamma distributions are different.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::gamma_distribution<_RealType>& __d1,
- const std::gamma_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief A chi_squared_distribution random number distribution.
- *
- * The formula for the normal probability mass function is
- * @f$p(x|n) = \frac{x^{(n/2) - 1}e^{-x/2}}{\Gamma(n/2) 2^{n/2}}@f$
- */
- template<typename _RealType = double>
- class chi_squared_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef chi_squared_distribution<_RealType> distribution_type;
- param_type() : param_type(1) { }
- explicit
- param_type(_RealType __n)
- : _M_n(__n)
- { }
- _RealType
- n() const
- { return _M_n; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_n == __p2._M_n; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_n;
- };
- chi_squared_distribution() : chi_squared_distribution(1) { }
- explicit
- chi_squared_distribution(_RealType __n)
- : _M_param(__n), _M_gd(__n / 2)
- { }
- explicit
- chi_squared_distribution(const param_type& __p)
- : _M_param(__p), _M_gd(__p.n() / 2)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { _M_gd.reset(); }
- /**
- *
- */
- _RealType
- n() const
- { return _M_param.n(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- {
- _M_param = __param;
- typedef typename std::gamma_distribution<result_type>::param_type
- param_type;
- _M_gd.param(param_type{__param.n() / 2});
- }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return result_type(0); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return 2 * _M_gd(__urng); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- typedef typename std::gamma_distribution<result_type>::param_type
- param_type;
- return 2 * _M_gd(__urng, param_type(__p.n() / 2));
- }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate_impl(__f, __t, __urng); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { typename std::gamma_distribution<result_type>::param_type
- __p2(__p.n() / 2);
- this->__generate_impl(__f, __t, __urng, __p2); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate_impl(__f, __t, __urng); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { typename std::gamma_distribution<result_type>::param_type
- __p2(__p.n() / 2);
- this->__generate_impl(__f, __t, __urng, __p2); }
- /**
- * @brief Return true if two Chi-squared distributions have
- * the same parameters and the sequences that would be
- * generated are equal.
- */
- friend bool
- operator==(const chi_squared_distribution& __d1,
- const chi_squared_distribution& __d2)
- { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; }
- /**
- * @brief Inserts a %chi_squared_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %chi_squared_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::chi_squared_distribution<_RealType1>& __x);
- /**
- * @brief Extracts a %chi_squared_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %chi_squared_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::chi_squared_distribution<_RealType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const typename
- std::gamma_distribution<result_type>::param_type& __p);
- param_type _M_param;
- std::gamma_distribution<result_type> _M_gd;
- };
- /**
- * @brief Return true if two Chi-squared distributions are different.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::chi_squared_distribution<_RealType>& __d1,
- const std::chi_squared_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief A cauchy_distribution random number distribution.
- *
- * The formula for the normal probability mass function is
- * @f$p(x|a,b) = (\pi b (1 + (\frac{x-a}{b})^2))^{-1}@f$
- */
- template<typename _RealType = double>
- class cauchy_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef cauchy_distribution<_RealType> distribution_type;
- param_type() : param_type(0) { }
- explicit
- param_type(_RealType __a, _RealType __b = _RealType(1))
- : _M_a(__a), _M_b(__b)
- { }
- _RealType
- a() const
- { return _M_a; }
- _RealType
- b() const
- { return _M_b; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_a;
- _RealType _M_b;
- };
- cauchy_distribution() : cauchy_distribution(0.0) { }
- explicit
- cauchy_distribution(_RealType __a, _RealType __b = 1.0)
- : _M_param(__a, __b)
- { }
- explicit
- cauchy_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { }
- /**
- *
- */
- _RealType
- a() const
- { return _M_param.a(); }
- _RealType
- b() const
- { return _M_param.b(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return std::numeric_limits<result_type>::lowest(); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two Cauchy distributions have
- * the same parameters.
- */
- friend bool
- operator==(const cauchy_distribution& __d1,
- const cauchy_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two Cauchy distributions have
- * different parameters.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::cauchy_distribution<_RealType>& __d1,
- const std::cauchy_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief Inserts a %cauchy_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %cauchy_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::cauchy_distribution<_RealType>& __x);
- /**
- * @brief Extracts a %cauchy_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %cauchy_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::cauchy_distribution<_RealType>& __x);
- /**
- * @brief A fisher_f_distribution random number distribution.
- *
- * The formula for the normal probability mass function is
- * @f[
- * p(x|m,n) = \frac{\Gamma((m+n)/2)}{\Gamma(m/2)\Gamma(n/2)}
- * (\frac{m}{n})^{m/2} x^{(m/2)-1}
- * (1 + \frac{mx}{n})^{-(m+n)/2}
- * @f]
- */
- template<typename _RealType = double>
- class fisher_f_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef fisher_f_distribution<_RealType> distribution_type;
- param_type() : param_type(1) { }
- explicit
- param_type(_RealType __m, _RealType __n = _RealType(1))
- : _M_m(__m), _M_n(__n)
- { }
- _RealType
- m() const
- { return _M_m; }
- _RealType
- n() const
- { return _M_n; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_m == __p2._M_m && __p1._M_n == __p2._M_n; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_m;
- _RealType _M_n;
- };
- fisher_f_distribution() : fisher_f_distribution(1.0) { }
- explicit
- fisher_f_distribution(_RealType __m,
- _RealType __n = _RealType(1))
- : _M_param(__m, __n), _M_gd_x(__m / 2), _M_gd_y(__n / 2)
- { }
- explicit
- fisher_f_distribution(const param_type& __p)
- : _M_param(__p), _M_gd_x(__p.m() / 2), _M_gd_y(__p.n() / 2)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- {
- _M_gd_x.reset();
- _M_gd_y.reset();
- }
- /**
- *
- */
- _RealType
- m() const
- { return _M_param.m(); }
- _RealType
- n() const
- { return _M_param.n(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return result_type(0); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return (_M_gd_x(__urng) * n()) / (_M_gd_y(__urng) * m()); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- typedef typename std::gamma_distribution<result_type>::param_type
- param_type;
- return ((_M_gd_x(__urng, param_type(__p.m() / 2)) * n())
- / (_M_gd_y(__urng, param_type(__p.n() / 2)) * m()));
- }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate_impl(__f, __t, __urng); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate_impl(__f, __t, __urng); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two Fisher f distributions have
- * the same parameters and the sequences that would
- * be generated are equal.
- */
- friend bool
- operator==(const fisher_f_distribution& __d1,
- const fisher_f_distribution& __d2)
- { return (__d1._M_param == __d2._M_param
- && __d1._M_gd_x == __d2._M_gd_x
- && __d1._M_gd_y == __d2._M_gd_y); }
- /**
- * @brief Inserts a %fisher_f_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %fisher_f_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::fisher_f_distribution<_RealType1>& __x);
- /**
- * @brief Extracts a %fisher_f_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %fisher_f_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::fisher_f_distribution<_RealType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- std::gamma_distribution<result_type> _M_gd_x, _M_gd_y;
- };
- /**
- * @brief Return true if two Fisher f distributions are different.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::fisher_f_distribution<_RealType>& __d1,
- const std::fisher_f_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief A student_t_distribution random number distribution.
- *
- * The formula for the normal probability mass function is:
- * @f[
- * p(x|n) = \frac{1}{\sqrt(n\pi)} \frac{\Gamma((n+1)/2)}{\Gamma(n/2)}
- * (1 + \frac{x^2}{n}) ^{-(n+1)/2}
- * @f]
- */
- template<typename _RealType = double>
- class student_t_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef student_t_distribution<_RealType> distribution_type;
- param_type() : param_type(1) { }
- explicit
- param_type(_RealType __n)
- : _M_n(__n)
- { }
- _RealType
- n() const
- { return _M_n; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_n == __p2._M_n; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_n;
- };
- student_t_distribution() : student_t_distribution(1.0) { }
- explicit
- student_t_distribution(_RealType __n)
- : _M_param(__n), _M_nd(), _M_gd(__n / 2, 2)
- { }
- explicit
- student_t_distribution(const param_type& __p)
- : _M_param(__p), _M_nd(), _M_gd(__p.n() / 2, 2)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- {
- _M_nd.reset();
- _M_gd.reset();
- }
- /**
- *
- */
- _RealType
- n() const
- { return _M_param.n(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return std::numeric_limits<result_type>::lowest(); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return _M_nd(__urng) * std::sqrt(n() / _M_gd(__urng)); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- typedef typename std::gamma_distribution<result_type>::param_type
- param_type;
-
- const result_type __g = _M_gd(__urng, param_type(__p.n() / 2, 2));
- return _M_nd(__urng) * std::sqrt(__p.n() / __g);
- }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate_impl(__f, __t, __urng); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate_impl(__f, __t, __urng); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two Student t distributions have
- * the same parameters and the sequences that would
- * be generated are equal.
- */
- friend bool
- operator==(const student_t_distribution& __d1,
- const student_t_distribution& __d2)
- { return (__d1._M_param == __d2._M_param
- && __d1._M_nd == __d2._M_nd && __d1._M_gd == __d2._M_gd); }
- /**
- * @brief Inserts a %student_t_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %student_t_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::student_t_distribution<_RealType1>& __x);
- /**
- * @brief Extracts a %student_t_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %student_t_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::student_t_distribution<_RealType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- std::normal_distribution<result_type> _M_nd;
- std::gamma_distribution<result_type> _M_gd;
- };
- /**
- * @brief Return true if two Student t distributions are different.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::student_t_distribution<_RealType>& __d1,
- const std::student_t_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /// @} group random_distributions_normal
- /**
- * @addtogroup random_distributions_bernoulli Bernoulli Distributions
- * @ingroup random_distributions
- * @{
- */
- /**
- * @brief A Bernoulli random number distribution.
- *
- * Generates a sequence of true and false values with likelihood @f$p@f$
- * that true will come up and @f$(1 - p)@f$ that false will appear.
- */
- class bernoulli_distribution
- {
- public:
- /** The type of the range of the distribution. */
- typedef bool result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef bernoulli_distribution distribution_type;
- param_type() : param_type(0.5) { }
- explicit
- param_type(double __p)
- : _M_p(__p)
- {
- __glibcxx_assert((_M_p >= 0.0) && (_M_p <= 1.0));
- }
- double
- p() const
- { return _M_p; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_p == __p2._M_p; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- double _M_p;
- };
- public:
- /**
- * @brief Constructs a Bernoulli distribution with likelihood 0.5.
- */
- bernoulli_distribution() : bernoulli_distribution(0.5) { }
- /**
- * @brief Constructs a Bernoulli distribution with likelihood @p p.
- *
- * @param __p [IN] The likelihood of a true result being returned.
- * Must be in the interval @f$[0, 1]@f$.
- */
- explicit
- bernoulli_distribution(double __p)
- : _M_param(__p)
- { }
- explicit
- bernoulli_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- *
- * Does nothing for a Bernoulli distribution.
- */
- void
- reset() { }
- /**
- * @brief Returns the @p p parameter of the distribution.
- */
- double
- p() const
- { return _M_param.p(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return std::numeric_limits<result_type>::min(); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, double>
- __aurng(__urng);
- if ((__aurng() - __aurng.min())
- < __p.p() * (__aurng.max() - __aurng.min()))
- return true;
- return false;
- }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng, const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two Bernoulli distributions have
- * the same parameters.
- */
- friend bool
- operator==(const bernoulli_distribution& __d1,
- const bernoulli_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two Bernoulli distributions have
- * different parameters.
- */
- inline bool
- operator!=(const std::bernoulli_distribution& __d1,
- const std::bernoulli_distribution& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief Inserts a %bernoulli_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %bernoulli_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::bernoulli_distribution& __x);
- /**
- * @brief Extracts a %bernoulli_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %bernoulli_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _CharT, typename _Traits>
- inline std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::bernoulli_distribution& __x)
- {
- double __p;
- if (__is >> __p)
- __x.param(bernoulli_distribution::param_type(__p));
- return __is;
- }
- /**
- * @brief A discrete binomial random number distribution.
- *
- * The formula for the binomial probability density function is
- * @f$p(i|t,p) = \binom{t}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$
- * and @f$p@f$ are the parameters of the distribution.
- */
- template<typename _IntType = int>
- class binomial_distribution
- {
- static_assert(std::is_integral<_IntType>::value,
- "result_type must be an integral type");
- public:
- /** The type of the range of the distribution. */
- typedef _IntType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef binomial_distribution<_IntType> distribution_type;
- friend class binomial_distribution<_IntType>;
- param_type() : param_type(1) { }
- explicit
- param_type(_IntType __t, double __p = 0.5)
- : _M_t(__t), _M_p(__p)
- {
- __glibcxx_assert((_M_t >= _IntType(0))
- && (_M_p >= 0.0)
- && (_M_p <= 1.0));
- _M_initialize();
- }
- _IntType
- t() const
- { return _M_t; }
- double
- p() const
- { return _M_p; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_t == __p2._M_t && __p1._M_p == __p2._M_p; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- void
- _M_initialize();
- _IntType _M_t;
- double _M_p;
- double _M_q;
- #if _GLIBCXX_USE_C99_MATH_TR1
- double _M_d1, _M_d2, _M_s1, _M_s2, _M_c,
- _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p;
- #endif
- bool _M_easy;
- };
- // constructors and member functions
- binomial_distribution() : binomial_distribution(1) { }
- explicit
- binomial_distribution(_IntType __t, double __p = 0.5)
- : _M_param(__t, __p), _M_nd()
- { }
- explicit
- binomial_distribution(const param_type& __p)
- : _M_param(__p), _M_nd()
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { _M_nd.reset(); }
- /**
- * @brief Returns the distribution @p t parameter.
- */
- _IntType
- t() const
- { return _M_param.t(); }
- /**
- * @brief Returns the distribution @p p parameter.
- */
- double
- p() const
- { return _M_param.p(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return 0; }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return _M_param.t(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two binomial distributions have
- * the same parameters and the sequences that would
- * be generated are equal.
- */
- friend bool
- operator==(const binomial_distribution& __d1,
- const binomial_distribution& __d2)
- #ifdef _GLIBCXX_USE_C99_MATH_TR1
- { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; }
- #else
- { return __d1._M_param == __d2._M_param; }
- #endif
- /**
- * @brief Inserts a %binomial_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %binomial_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _IntType1,
- typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::binomial_distribution<_IntType1>& __x);
- /**
- * @brief Extracts a %binomial_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %binomial_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error
- * state.
- */
- template<typename _IntType1,
- typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::binomial_distribution<_IntType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _UniformRandomNumberGenerator>
- result_type
- _M_waiting(_UniformRandomNumberGenerator& __urng,
- _IntType __t, double __q);
- param_type _M_param;
- // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined.
- std::normal_distribution<double> _M_nd;
- };
- /**
- * @brief Return true if two binomial distributions are different.
- */
- template<typename _IntType>
- inline bool
- operator!=(const std::binomial_distribution<_IntType>& __d1,
- const std::binomial_distribution<_IntType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief A discrete geometric random number distribution.
- *
- * The formula for the geometric probability density function is
- * @f$p(i|p) = p(1 - p)^{i}@f$ where @f$p@f$ is the parameter of the
- * distribution.
- */
- template<typename _IntType = int>
- class geometric_distribution
- {
- static_assert(std::is_integral<_IntType>::value,
- "result_type must be an integral type");
- public:
- /** The type of the range of the distribution. */
- typedef _IntType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef geometric_distribution<_IntType> distribution_type;
- friend class geometric_distribution<_IntType>;
- param_type() : param_type(0.5) { }
- explicit
- param_type(double __p)
- : _M_p(__p)
- {
- __glibcxx_assert((_M_p > 0.0) && (_M_p < 1.0));
- _M_initialize();
- }
- double
- p() const
- { return _M_p; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_p == __p2._M_p; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- void
- _M_initialize()
- { _M_log_1_p = std::log(1.0 - _M_p); }
- double _M_p;
- double _M_log_1_p;
- };
- // constructors and member functions
- geometric_distribution() : geometric_distribution(0.5) { }
- explicit
- geometric_distribution(double __p)
- : _M_param(__p)
- { }
- explicit
- geometric_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- *
- * Does nothing for the geometric distribution.
- */
- void
- reset() { }
- /**
- * @brief Returns the distribution parameter @p p.
- */
- double
- p() const
- { return _M_param.p(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return 0; }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two geometric distributions have
- * the same parameters.
- */
- friend bool
- operator==(const geometric_distribution& __d1,
- const geometric_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two geometric distributions have
- * different parameters.
- */
- template<typename _IntType>
- inline bool
- operator!=(const std::geometric_distribution<_IntType>& __d1,
- const std::geometric_distribution<_IntType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief Inserts a %geometric_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %geometric_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _IntType,
- typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::geometric_distribution<_IntType>& __x);
- /**
- * @brief Extracts a %geometric_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %geometric_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _IntType,
- typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::geometric_distribution<_IntType>& __x);
- /**
- * @brief A negative_binomial_distribution random number distribution.
- *
- * The formula for the negative binomial probability mass function is
- * @f$p(i) = \binom{n}{i} p^i (1 - p)^{t - i}@f$ where @f$t@f$
- * and @f$p@f$ are the parameters of the distribution.
- */
- template<typename _IntType = int>
- class negative_binomial_distribution
- {
- static_assert(std::is_integral<_IntType>::value,
- "result_type must be an integral type");
- public:
- /** The type of the range of the distribution. */
- typedef _IntType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef negative_binomial_distribution<_IntType> distribution_type;
- param_type() : param_type(1) { }
- explicit
- param_type(_IntType __k, double __p = 0.5)
- : _M_k(__k), _M_p(__p)
- {
- __glibcxx_assert((_M_k > 0) && (_M_p > 0.0) && (_M_p <= 1.0));
- }
- _IntType
- k() const
- { return _M_k; }
- double
- p() const
- { return _M_p; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_k == __p2._M_k && __p1._M_p == __p2._M_p; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _IntType _M_k;
- double _M_p;
- };
- negative_binomial_distribution() : negative_binomial_distribution(1) { }
- explicit
- negative_binomial_distribution(_IntType __k, double __p = 0.5)
- : _M_param(__k, __p), _M_gd(__k, (1.0 - __p) / __p)
- { }
- explicit
- negative_binomial_distribution(const param_type& __p)
- : _M_param(__p), _M_gd(__p.k(), (1.0 - __p.p()) / __p.p())
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { _M_gd.reset(); }
- /**
- * @brief Return the @f$k@f$ parameter of the distribution.
- */
- _IntType
- k() const
- { return _M_param.k(); }
- /**
- * @brief Return the @f$p@f$ parameter of the distribution.
- */
- double
- p() const
- { return _M_param.p(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return result_type(0); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng);
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate_impl(__f, __t, __urng); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate_impl(__f, __t, __urng); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two negative binomial distributions have
- * the same parameters and the sequences that would be
- * generated are equal.
- */
- friend bool
- operator==(const negative_binomial_distribution& __d1,
- const negative_binomial_distribution& __d2)
- { return __d1._M_param == __d2._M_param && __d1._M_gd == __d2._M_gd; }
- /**
- * @brief Inserts a %negative_binomial_distribution random
- * number distribution @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %negative_binomial_distribution random number
- * distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _IntType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::negative_binomial_distribution<_IntType1>& __x);
- /**
- * @brief Extracts a %negative_binomial_distribution random number
- * distribution @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %negative_binomial_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _IntType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::negative_binomial_distribution<_IntType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- std::gamma_distribution<double> _M_gd;
- };
- /**
- * @brief Return true if two negative binomial distributions are different.
- */
- template<typename _IntType>
- inline bool
- operator!=(const std::negative_binomial_distribution<_IntType>& __d1,
- const std::negative_binomial_distribution<_IntType>& __d2)
- { return !(__d1 == __d2); }
- /// @} group random_distributions_bernoulli
- /**
- * @addtogroup random_distributions_poisson Poisson Distributions
- * @ingroup random_distributions
- * @{
- */
- /**
- * @brief A discrete Poisson random number distribution.
- *
- * The formula for the Poisson probability density function is
- * @f$p(i|\mu) = \frac{\mu^i}{i!} e^{-\mu}@f$ where @f$\mu@f$ is the
- * parameter of the distribution.
- */
- template<typename _IntType = int>
- class poisson_distribution
- {
- static_assert(std::is_integral<_IntType>::value,
- "result_type must be an integral type");
- public:
- /** The type of the range of the distribution. */
- typedef _IntType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef poisson_distribution<_IntType> distribution_type;
- friend class poisson_distribution<_IntType>;
- param_type() : param_type(1.0) { }
- explicit
- param_type(double __mean)
- : _M_mean(__mean)
- {
- __glibcxx_assert(_M_mean > 0.0);
- _M_initialize();
- }
- double
- mean() const
- { return _M_mean; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_mean == __p2._M_mean; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- // Hosts either log(mean) or the threshold of the simple method.
- void
- _M_initialize();
- double _M_mean;
- double _M_lm_thr;
- #if _GLIBCXX_USE_C99_MATH_TR1
- double _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb;
- #endif
- };
- // constructors and member functions
- poisson_distribution() : poisson_distribution(1.0) { }
- explicit
- poisson_distribution(double __mean)
- : _M_param(__mean), _M_nd()
- { }
- explicit
- poisson_distribution(const param_type& __p)
- : _M_param(__p), _M_nd()
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { _M_nd.reset(); }
- /**
- * @brief Returns the distribution parameter @p mean.
- */
- double
- mean() const
- { return _M_param.mean(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return 0; }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two Poisson distributions have the same
- * parameters and the sequences that would be generated
- * are equal.
- */
- friend bool
- operator==(const poisson_distribution& __d1,
- const poisson_distribution& __d2)
- #ifdef _GLIBCXX_USE_C99_MATH_TR1
- { return __d1._M_param == __d2._M_param && __d1._M_nd == __d2._M_nd; }
- #else
- { return __d1._M_param == __d2._M_param; }
- #endif
- /**
- * @brief Inserts a %poisson_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %poisson_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _IntType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::poisson_distribution<_IntType1>& __x);
- /**
- * @brief Extracts a %poisson_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %poisson_distribution random number generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error
- * state.
- */
- template<typename _IntType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::poisson_distribution<_IntType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined.
- std::normal_distribution<double> _M_nd;
- };
- /**
- * @brief Return true if two Poisson distributions are different.
- */
- template<typename _IntType>
- inline bool
- operator!=(const std::poisson_distribution<_IntType>& __d1,
- const std::poisson_distribution<_IntType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief An exponential continuous distribution for random numbers.
- *
- * The formula for the exponential probability density function is
- * @f$p(x|\lambda) = \lambda e^{-\lambda x}@f$.
- *
- * <table border=1 cellpadding=10 cellspacing=0>
- * <caption align=top>Distribution Statistics</caption>
- * <tr><td>Mean</td><td>@f$\frac{1}{\lambda}@f$</td></tr>
- * <tr><td>Median</td><td>@f$\frac{\ln 2}{\lambda}@f$</td></tr>
- * <tr><td>Mode</td><td>@f$zero@f$</td></tr>
- * <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr>
- * <tr><td>Standard Deviation</td><td>@f$\frac{1}{\lambda}@f$</td></tr>
- * </table>
- */
- template<typename _RealType = double>
- class exponential_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef exponential_distribution<_RealType> distribution_type;
- param_type() : param_type(1.0) { }
- explicit
- param_type(_RealType __lambda)
- : _M_lambda(__lambda)
- {
- __glibcxx_assert(_M_lambda > _RealType(0));
- }
- _RealType
- lambda() const
- { return _M_lambda; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_lambda == __p2._M_lambda; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_lambda;
- };
- public:
- /**
- * @brief Constructs an exponential distribution with inverse scale
- * parameter 1.0
- */
- exponential_distribution() : exponential_distribution(1.0) { }
- /**
- * @brief Constructs an exponential distribution with inverse scale
- * parameter @f$\lambda@f$.
- */
- explicit
- exponential_distribution(_RealType __lambda)
- : _M_param(__lambda)
- { }
- explicit
- exponential_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- *
- * Has no effect on exponential distributions.
- */
- void
- reset() { }
- /**
- * @brief Returns the inverse scale parameter of the distribution.
- */
- _RealType
- lambda() const
- { return _M_param.lambda(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return result_type(0); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- {
- __detail::_Adaptor<_UniformRandomNumberGenerator, result_type>
- __aurng(__urng);
- return -std::log(result_type(1) - __aurng()) / __p.lambda();
- }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two exponential distributions have the same
- * parameters.
- */
- friend bool
- operator==(const exponential_distribution& __d1,
- const exponential_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two exponential distributions have different
- * parameters.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::exponential_distribution<_RealType>& __d1,
- const std::exponential_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief Inserts a %exponential_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %exponential_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::exponential_distribution<_RealType>& __x);
- /**
- * @brief Extracts a %exponential_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %exponential_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::exponential_distribution<_RealType>& __x);
- /**
- * @brief A weibull_distribution random number distribution.
- *
- * The formula for the normal probability density function is:
- * @f[
- * p(x|\alpha,\beta) = \frac{\alpha}{\beta} (\frac{x}{\beta})^{\alpha-1}
- * \exp{(-(\frac{x}{\beta})^\alpha)}
- * @f]
- */
- template<typename _RealType = double>
- class weibull_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef weibull_distribution<_RealType> distribution_type;
- param_type() : param_type(1.0) { }
- explicit
- param_type(_RealType __a, _RealType __b = _RealType(1.0))
- : _M_a(__a), _M_b(__b)
- { }
- _RealType
- a() const
- { return _M_a; }
- _RealType
- b() const
- { return _M_b; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_a;
- _RealType _M_b;
- };
- weibull_distribution() : weibull_distribution(1.0) { }
- explicit
- weibull_distribution(_RealType __a, _RealType __b = _RealType(1))
- : _M_param(__a, __b)
- { }
- explicit
- weibull_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { }
- /**
- * @brief Return the @f$a@f$ parameter of the distribution.
- */
- _RealType
- a() const
- { return _M_param.a(); }
- /**
- * @brief Return the @f$b@f$ parameter of the distribution.
- */
- _RealType
- b() const
- { return _M_param.b(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return result_type(0); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two Weibull distributions have the same
- * parameters.
- */
- friend bool
- operator==(const weibull_distribution& __d1,
- const weibull_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two Weibull distributions have different
- * parameters.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::weibull_distribution<_RealType>& __d1,
- const std::weibull_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief Inserts a %weibull_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %weibull_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::weibull_distribution<_RealType>& __x);
- /**
- * @brief Extracts a %weibull_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %weibull_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::weibull_distribution<_RealType>& __x);
- /**
- * @brief A extreme_value_distribution random number distribution.
- *
- * The formula for the normal probability mass function is
- * @f[
- * p(x|a,b) = \frac{1}{b}
- * \exp( \frac{a-x}{b} - \exp(\frac{a-x}{b}))
- * @f]
- */
- template<typename _RealType = double>
- class extreme_value_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef extreme_value_distribution<_RealType> distribution_type;
- param_type() : param_type(0.0) { }
- explicit
- param_type(_RealType __a, _RealType __b = _RealType(1.0))
- : _M_a(__a), _M_b(__b)
- { }
- _RealType
- a() const
- { return _M_a; }
- _RealType
- b() const
- { return _M_b; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_a == __p2._M_a && __p1._M_b == __p2._M_b; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- _RealType _M_a;
- _RealType _M_b;
- };
- extreme_value_distribution() : extreme_value_distribution(0.0) { }
- explicit
- extreme_value_distribution(_RealType __a, _RealType __b = _RealType(1))
- : _M_param(__a, __b)
- { }
- explicit
- extreme_value_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { }
- /**
- * @brief Return the @f$a@f$ parameter of the distribution.
- */
- _RealType
- a() const
- { return _M_param.a(); }
- /**
- * @brief Return the @f$b@f$ parameter of the distribution.
- */
- _RealType
- b() const
- { return _M_param.b(); }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return std::numeric_limits<result_type>::lowest(); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- { return std::numeric_limits<result_type>::max(); }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two extreme value distributions have the same
- * parameters.
- */
- friend bool
- operator==(const extreme_value_distribution& __d1,
- const extreme_value_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two extreme value distributions have different
- * parameters.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::extreme_value_distribution<_RealType>& __d1,
- const std::extreme_value_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief Inserts a %extreme_value_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %extreme_value_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::extreme_value_distribution<_RealType>& __x);
- /**
- * @brief Extracts a %extreme_value_distribution random number
- * distribution @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %extreme_value_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error state.
- */
- template<typename _RealType, typename _CharT, typename _Traits>
- std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::extreme_value_distribution<_RealType>& __x);
- /**
- * @brief A discrete_distribution random number distribution.
- *
- * The formula for the discrete probability mass function is
- *
- */
- template<typename _IntType = int>
- class discrete_distribution
- {
- static_assert(std::is_integral<_IntType>::value,
- "result_type must be an integral type");
- public:
- /** The type of the range of the distribution. */
- typedef _IntType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef discrete_distribution<_IntType> distribution_type;
- friend class discrete_distribution<_IntType>;
- param_type()
- : _M_prob(), _M_cp()
- { }
- template<typename _InputIterator>
- param_type(_InputIterator __wbegin,
- _InputIterator __wend)
- : _M_prob(__wbegin, __wend), _M_cp()
- { _M_initialize(); }
- param_type(initializer_list<double> __wil)
- : _M_prob(__wil.begin(), __wil.end()), _M_cp()
- { _M_initialize(); }
- template<typename _Func>
- param_type(size_t __nw, double __xmin, double __xmax,
- _Func __fw);
- // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/
- param_type(const param_type&) = default;
- param_type& operator=(const param_type&) = default;
- std::vector<double>
- probabilities() const
- { return _M_prob.empty() ? std::vector<double>(1, 1.0) : _M_prob; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_prob == __p2._M_prob; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- void
- _M_initialize();
- std::vector<double> _M_prob;
- std::vector<double> _M_cp;
- };
- discrete_distribution()
- : _M_param()
- { }
- template<typename _InputIterator>
- discrete_distribution(_InputIterator __wbegin,
- _InputIterator __wend)
- : _M_param(__wbegin, __wend)
- { }
- discrete_distribution(initializer_list<double> __wl)
- : _M_param(__wl)
- { }
- template<typename _Func>
- discrete_distribution(size_t __nw, double __xmin, double __xmax,
- _Func __fw)
- : _M_param(__nw, __xmin, __xmax, __fw)
- { }
- explicit
- discrete_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { }
- /**
- * @brief Returns the probabilities of the distribution.
- */
- std::vector<double>
- probabilities() const
- {
- return _M_param._M_prob.empty()
- ? std::vector<double>(1, 1.0) : _M_param._M_prob;
- }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- { return result_type(0); }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- {
- return _M_param._M_prob.empty()
- ? result_type(0) : result_type(_M_param._M_prob.size() - 1);
- }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two discrete distributions have the same
- * parameters.
- */
- friend bool
- operator==(const discrete_distribution& __d1,
- const discrete_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- /**
- * @brief Inserts a %discrete_distribution random number distribution
- * @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %discrete_distribution random number distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _IntType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::discrete_distribution<_IntType1>& __x);
- /**
- * @brief Extracts a %discrete_distribution random number distribution
- * @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %discrete_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error
- * state.
- */
- template<typename _IntType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::discrete_distribution<_IntType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two discrete distributions have different
- * parameters.
- */
- template<typename _IntType>
- inline bool
- operator!=(const std::discrete_distribution<_IntType>& __d1,
- const std::discrete_distribution<_IntType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief A piecewise_constant_distribution random number distribution.
- *
- * The formula for the piecewise constant probability mass function is
- *
- */
- template<typename _RealType = double>
- class piecewise_constant_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef piecewise_constant_distribution<_RealType> distribution_type;
- friend class piecewise_constant_distribution<_RealType>;
- param_type()
- : _M_int(), _M_den(), _M_cp()
- { }
- template<typename _InputIteratorB, typename _InputIteratorW>
- param_type(_InputIteratorB __bfirst,
- _InputIteratorB __bend,
- _InputIteratorW __wbegin);
- template<typename _Func>
- param_type(initializer_list<_RealType> __bi, _Func __fw);
- template<typename _Func>
- param_type(size_t __nw, _RealType __xmin, _RealType __xmax,
- _Func __fw);
- // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/
- param_type(const param_type&) = default;
- param_type& operator=(const param_type&) = default;
- std::vector<_RealType>
- intervals() const
- {
- if (_M_int.empty())
- {
- std::vector<_RealType> __tmp(2);
- __tmp[1] = _RealType(1);
- return __tmp;
- }
- else
- return _M_int;
- }
- std::vector<double>
- densities() const
- { return _M_den.empty() ? std::vector<double>(1, 1.0) : _M_den; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- void
- _M_initialize();
- std::vector<_RealType> _M_int;
- std::vector<double> _M_den;
- std::vector<double> _M_cp;
- };
- piecewise_constant_distribution()
- : _M_param()
- { }
- template<typename _InputIteratorB, typename _InputIteratorW>
- piecewise_constant_distribution(_InputIteratorB __bfirst,
- _InputIteratorB __bend,
- _InputIteratorW __wbegin)
- : _M_param(__bfirst, __bend, __wbegin)
- { }
- template<typename _Func>
- piecewise_constant_distribution(initializer_list<_RealType> __bl,
- _Func __fw)
- : _M_param(__bl, __fw)
- { }
- template<typename _Func>
- piecewise_constant_distribution(size_t __nw,
- _RealType __xmin, _RealType __xmax,
- _Func __fw)
- : _M_param(__nw, __xmin, __xmax, __fw)
- { }
- explicit
- piecewise_constant_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * @brief Resets the distribution state.
- */
- void
- reset()
- { }
- /**
- * @brief Returns a vector of the intervals.
- */
- std::vector<_RealType>
- intervals() const
- {
- if (_M_param._M_int.empty())
- {
- std::vector<_RealType> __tmp(2);
- __tmp[1] = _RealType(1);
- return __tmp;
- }
- else
- return _M_param._M_int;
- }
- /**
- * @brief Returns a vector of the probability densities.
- */
- std::vector<double>
- densities() const
- {
- return _M_param._M_den.empty()
- ? std::vector<double>(1, 1.0) : _M_param._M_den;
- }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- {
- return _M_param._M_int.empty()
- ? result_type(0) : _M_param._M_int.front();
- }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- {
- return _M_param._M_int.empty()
- ? result_type(1) : _M_param._M_int.back();
- }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two piecewise constant distributions have the
- * same parameters.
- */
- friend bool
- operator==(const piecewise_constant_distribution& __d1,
- const piecewise_constant_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- /**
- * @brief Inserts a %piecewise_constant_distribution random
- * number distribution @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %piecewise_constant_distribution random number
- * distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::piecewise_constant_distribution<_RealType1>& __x);
- /**
- * @brief Extracts a %piecewise_constant_distribution random
- * number distribution @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %piecewise_constant_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error
- * state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::piecewise_constant_distribution<_RealType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two piecewise constant distributions have
- * different parameters.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::piecewise_constant_distribution<_RealType>& __d1,
- const std::piecewise_constant_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /**
- * @brief A piecewise_linear_distribution random number distribution.
- *
- * The formula for the piecewise linear probability mass function is
- *
- */
- template<typename _RealType = double>
- class piecewise_linear_distribution
- {
- static_assert(std::is_floating_point<_RealType>::value,
- "result_type must be a floating point type");
- public:
- /** The type of the range of the distribution. */
- typedef _RealType result_type;
- /** Parameter type. */
- struct param_type
- {
- typedef piecewise_linear_distribution<_RealType> distribution_type;
- friend class piecewise_linear_distribution<_RealType>;
- param_type()
- : _M_int(), _M_den(), _M_cp(), _M_m()
- { }
- template<typename _InputIteratorB, typename _InputIteratorW>
- param_type(_InputIteratorB __bfirst,
- _InputIteratorB __bend,
- _InputIteratorW __wbegin);
- template<typename _Func>
- param_type(initializer_list<_RealType> __bl, _Func __fw);
- template<typename _Func>
- param_type(size_t __nw, _RealType __xmin, _RealType __xmax,
- _Func __fw);
- // See: http://cpp-next.com/archive/2010/10/implicit-move-must-go/
- param_type(const param_type&) = default;
- param_type& operator=(const param_type&) = default;
- std::vector<_RealType>
- intervals() const
- {
- if (_M_int.empty())
- {
- std::vector<_RealType> __tmp(2);
- __tmp[1] = _RealType(1);
- return __tmp;
- }
- else
- return _M_int;
- }
- std::vector<double>
- densities() const
- { return _M_den.empty() ? std::vector<double>(2, 1.0) : _M_den; }
- friend bool
- operator==(const param_type& __p1, const param_type& __p2)
- { return __p1._M_int == __p2._M_int && __p1._M_den == __p2._M_den; }
- friend bool
- operator!=(const param_type& __p1, const param_type& __p2)
- { return !(__p1 == __p2); }
- private:
- void
- _M_initialize();
- std::vector<_RealType> _M_int;
- std::vector<double> _M_den;
- std::vector<double> _M_cp;
- std::vector<double> _M_m;
- };
- piecewise_linear_distribution()
- : _M_param()
- { }
- template<typename _InputIteratorB, typename _InputIteratorW>
- piecewise_linear_distribution(_InputIteratorB __bfirst,
- _InputIteratorB __bend,
- _InputIteratorW __wbegin)
- : _M_param(__bfirst, __bend, __wbegin)
- { }
- template<typename _Func>
- piecewise_linear_distribution(initializer_list<_RealType> __bl,
- _Func __fw)
- : _M_param(__bl, __fw)
- { }
- template<typename _Func>
- piecewise_linear_distribution(size_t __nw,
- _RealType __xmin, _RealType __xmax,
- _Func __fw)
- : _M_param(__nw, __xmin, __xmax, __fw)
- { }
- explicit
- piecewise_linear_distribution(const param_type& __p)
- : _M_param(__p)
- { }
- /**
- * Resets the distribution state.
- */
- void
- reset()
- { }
- /**
- * @brief Return the intervals of the distribution.
- */
- std::vector<_RealType>
- intervals() const
- {
- if (_M_param._M_int.empty())
- {
- std::vector<_RealType> __tmp(2);
- __tmp[1] = _RealType(1);
- return __tmp;
- }
- else
- return _M_param._M_int;
- }
- /**
- * @brief Return a vector of the probability densities of the
- * distribution.
- */
- std::vector<double>
- densities() const
- {
- return _M_param._M_den.empty()
- ? std::vector<double>(2, 1.0) : _M_param._M_den;
- }
- /**
- * @brief Returns the parameter set of the distribution.
- */
- param_type
- param() const
- { return _M_param; }
- /**
- * @brief Sets the parameter set of the distribution.
- * @param __param The new parameter set of the distribution.
- */
- void
- param(const param_type& __param)
- { _M_param = __param; }
- /**
- * @brief Returns the greatest lower bound value of the distribution.
- */
- result_type
- min() const
- {
- return _M_param._M_int.empty()
- ? result_type(0) : _M_param._M_int.front();
- }
- /**
- * @brief Returns the least upper bound value of the distribution.
- */
- result_type
- max() const
- {
- return _M_param._M_int.empty()
- ? result_type(1) : _M_param._M_int.back();
- }
- /**
- * @brief Generating functions.
- */
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng)
- { return this->operator()(__urng, _M_param); }
- template<typename _UniformRandomNumberGenerator>
- result_type
- operator()(_UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng)
- { this->__generate(__f, __t, __urng, _M_param); }
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- template<typename _UniformRandomNumberGenerator>
- void
- __generate(result_type* __f, result_type* __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p)
- { this->__generate_impl(__f, __t, __urng, __p); }
- /**
- * @brief Return true if two piecewise linear distributions have the
- * same parameters.
- */
- friend bool
- operator==(const piecewise_linear_distribution& __d1,
- const piecewise_linear_distribution& __d2)
- { return __d1._M_param == __d2._M_param; }
- /**
- * @brief Inserts a %piecewise_linear_distribution random number
- * distribution @p __x into the output stream @p __os.
- *
- * @param __os An output stream.
- * @param __x A %piecewise_linear_distribution random number
- * distribution.
- *
- * @returns The output stream with the state of @p __x inserted or in
- * an error state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_ostream<_CharT, _Traits>&
- operator<<(std::basic_ostream<_CharT, _Traits>& __os,
- const std::piecewise_linear_distribution<_RealType1>& __x);
- /**
- * @brief Extracts a %piecewise_linear_distribution random number
- * distribution @p __x from the input stream @p __is.
- *
- * @param __is An input stream.
- * @param __x A %piecewise_linear_distribution random number
- * generator engine.
- *
- * @returns The input stream with @p __x extracted or in an error
- * state.
- */
- template<typename _RealType1, typename _CharT, typename _Traits>
- friend std::basic_istream<_CharT, _Traits>&
- operator>>(std::basic_istream<_CharT, _Traits>& __is,
- std::piecewise_linear_distribution<_RealType1>& __x);
- private:
- template<typename _ForwardIterator,
- typename _UniformRandomNumberGenerator>
- void
- __generate_impl(_ForwardIterator __f, _ForwardIterator __t,
- _UniformRandomNumberGenerator& __urng,
- const param_type& __p);
- param_type _M_param;
- };
- /**
- * @brief Return true if two piecewise linear distributions have
- * different parameters.
- */
- template<typename _RealType>
- inline bool
- operator!=(const std::piecewise_linear_distribution<_RealType>& __d1,
- const std::piecewise_linear_distribution<_RealType>& __d2)
- { return !(__d1 == __d2); }
- /// @} group random_distributions_poisson
- /// @} *group random_distributions
- /**
- * @addtogroup random_utilities Random Number Utilities
- * @ingroup random
- * @{
- */
- /**
- * @brief The seed_seq class generates sequences of seeds for random
- * number generators.
- */
- class seed_seq
- {
- public:
- /** The type of the seed vales. */
- typedef uint_least32_t result_type;
- /** Default constructor. */
- seed_seq() noexcept
- : _M_v()
- { }
- template<typename _IntType, typename = _Require<is_integral<_IntType>>>
- seed_seq(std::initializer_list<_IntType> __il);
- template<typename _InputIterator>
- seed_seq(_InputIterator __begin, _InputIterator __end);
- // generating functions
- template<typename _RandomAccessIterator>
- void
- generate(_RandomAccessIterator __begin, _RandomAccessIterator __end);
- // property functions
- size_t size() const noexcept
- { return _M_v.size(); }
- template<typename _OutputIterator>
- void
- param(_OutputIterator __dest) const
- { std::copy(_M_v.begin(), _M_v.end(), __dest); }
- // no copy functions
- seed_seq(const seed_seq&) = delete;
- seed_seq& operator=(const seed_seq&) = delete;
- private:
- std::vector<result_type> _M_v;
- };
- /// @} group random_utilities
- /// @} group random
- _GLIBCXX_END_NAMESPACE_VERSION
- } // namespace std
- #endif
|