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np.mean(6.141325006436351/np.cos(2*np.pi*np.cumsum(5.959372869691795-array_x, axis=1)), axis=1)+np.sin(2*np.pi*np.mean(2.8505862275754277/np.cos(2*np.pi*np.cumsum(7.841553963933762-array_x, axis=1)), axis=1)) |
np.round(np.mean(10*(7.291283066687017+np.sin(2*np.pi*8.346290426892136*array_x*2.613758400472861)), axis=1)) |
np.mean(9.01179515912408+np.exp(array_x*3.630396983052388)+np.exp((np.dot(array_x, np.array([[0.5032442169885598, 0.5710285433917043, 0.7950984112577577, 0.1936044765752506, 0.39186023743762], [0.9368307834334404, 0.6686829486396115, 0.5450515126124742, 0.8105474216660654, 0.9589878567106711], [0.6095022719137345, 0.4159502282995867, 0.03501452526627946, 0.025139823232043113, 0.40921548328188884], [0.9263319614824725, 0.19758296490534188, 0.7671054869404527, 0.12575687442401184, 0.24355115805546224], [0.6578573593027495, 0.36173157094400843, 0.9290851348176001, 0.11550953366019157, 0.979893016364632]])))-6.056002390313995/6.640879281928672), axis=1) |
np.mean(9.374953875501781-6.094498683682906*10*(array_x), axis=1) |
np.mean(np.cumsum(array_x*np.round(6.222308008039745)-5.8201614479018495, axis=1)-np.cos(2*np.pi*np.log(abs(5.327934277722916))), axis=1) |
np.mean(np.square(array_x+6.457789290636143)+np.sin(2*np.pi*np.cos(2*np.pi*2.733515519243408)), axis=1) |
np.mean(1.625404299036794+7.649440872523637*array_x*array_x/1.1814065758630075+np.sqrt(abs(array_x+4.847166243691709/2.6858064693823165/4.9541503572895795)), axis=1)+np.sin(2*np.pi*np.mean(8.820363400671877+1.5758693939763373*array_x*array_x/2.2540834176719717+np.sqrt(abs(array_x+3.9040499853176787/4.550275653267091/2.667731078619595)), axis=1)) |
np.sum(np.sqrt(abs(2.358134809858786*array_x))+array_x+1.8279924796327818, axis=1)+5.0892569321992065 |
np.mean(array_x+np.sin(2*np.pi*8.054933614007112)+np.cos(2*np.pi*6.6423307701340395)-3.5848972106631583+array_x*5.425887354130739*6.634942137415307, axis=1) |
np.mean(7.937222396432082*10*(np.cos(2*np.pi*np.square(6.852011633086261-array_x))), axis=1) |
np.mean(np.exp(6.282480104136792)*array_x+3.176503793434388, axis=1) |
np.mean(np.exp(array_x)*5.730923691872769-array_x, axis=1)+10*(np.sin(2*np.pi*np.mean(np.exp(array_x)*7.70615638253712-array_x, axis=1))) |
np.mean(abs(6.12766129620975)+(np.dot(array_x, np.array([[0.5162262998871522, 0.6404750619905739, 0.1933030511004794, 0.8970067681427856, 0.23388064519339868], [0.4339498499556368, 0.9537205647670826, 0.9379041020094941, 0.30937642312900016, 0.7767399553571446], [0.7046996160793918, 0.46944673514036905, 0.669775950125039, 0.5971247031629842, 0.3609536646292719], [0.791493382577293, 0.6512729210119507, 0.5251194987528859, 0.6161224768999759, 0.18097133321147063], [0.41331156526436474, 0.47232979628208005, 0.4124052636910236, 0.7913399545431626, 0.4435212604503671]])))-10*(7.419359536146773-(np.array(range(1, array_x.shape[1]+1)))*array_x)+5.496786258074903-(np.array(range(1, array_x.shape[1]+1)))*array_x, axis=1) |
np.mean(6.481384221523922-10*(array_x), axis=1)+np.sin(2*np.pi*np.mean(7.089789898440225-10*(array_x), axis=1)) |
np.mean(10*(8.796312887178892-np.sin(2*np.pi*np.square(np.log(abs(6.691880613296815+(np.dot(array_x, np.array([[0.9940631959966784, 0.9089634466376726, 0.9498903533670696, 0.7797181898772378, 0.8272468608197042], [0.49755077227794375, 0.5638931847521269, 0.8486618773355156, 0.4461561436167021, 0.042308384638102714], [0.4448365756149908, 0.8130973684376859, 0.5873908153356608, 0.014419645962999161, 0.3262071850886863], [0.8353612941428304, 0.19126012936851045, 0.2742982477067277, 0.12244521307474643, 0.011796384689405803], [0.43033098278740867, 0.776584597952939, 0.15668773102184275, 0.5265783384150696, 0.980393494825006]])))-5.294054554192852))))), axis=1) |
np.mean(np.square(5.295775018735269-array_x), axis=1)+np.sin(2*np.pi*np.mean(np.square(8.629342111359872-array_x), axis=1)) |
np.mean(np.exp(7.993012157572714+np.square(array_x))-(np.array(range(1, array_x.shape[1]+1)))+6.861861863478746/1.566142804323838, axis=1) |
np.mean(abs(7.369944042861698-np.sin(2*np.pi*array_x))*4.330124375554931, axis=1) |
np.square(np.sum(np.round(2.8551217849449406-(np.array(range(1, array_x.shape[1]+1)))*array_x)/3.9055806537448126, axis=1)) |
np.mean(6.9397242478758185+1/(np.sin(2*np.pi*7.827760143928392+np.cos(2*np.pi*array_x))), axis=1)+np.sin(2*np.pi*np.mean(5.011955670564361+1/(np.sin(2*np.pi*5.207422148087309+np.cos(2*np.pi*array_x))), axis=1)) |
np.mean(3.5690522227432844-array_x*10*(7.258555137808178), axis=1) |
np.mean(8.703315380025611*array_x-7.71417763551093, axis=1) |
np.square(np.sum(7.8918194507291-(np.array(range(1, array_x.shape[1]+1)))*array_x, axis=1)*8.749147017549337) |
np.square(7.423196772393372-np.mean(5.231329891566572-(np.dot(array_x, np.array([[0.005895572827756879, 0.1585008798639297, 0.6478638574958615, 0.5678916670995661, 0.1258648481028054], [0.29719201905006354, 0.8337477304948967, 0.04285628227792171, 0.4654624725918959, 0.09537016408049714], [0.007963396260310174, 0.7217631132797889, 0.7202568009231259, 0.19160530528650543, 0.0688777919933542], [0.0994402134238157, 0.13331728826108946, 0.023640816536238396, 0.314206499693671, 0.3026864495821886], [0.4692247609299842, 0.5682981384262192, 0.17452005224384526, 0.4820543907689261, 0.14981861149785713]])))*6.2430224225320945, axis=1))+abs(2.368289943551715)*np.square(np.prod(array_x, axis=1)) |
np.mean(np.log(abs(abs(-(np.square(array_x)))+8.100959982953643))-np.sqrt(abs(1.4611796058155675))+10*((np.array(range(1, array_x.shape[1]+1))))*8.713979628223921+array_x, axis=1)+10*(np.sin(2*np.pi*np.mean(np.log(abs(abs(-(np.square(array_x)))+9.986798292042428))-np.sqrt(abs(5.779565893979761))+10*((np.array(range(1, array_x.shape[1]+1))))*9.535193116141734+array_x, axis=1))) |
np.mean(np.cumsum(array_x+6.674097997727511+array_x, axis=1)*abs(2.1466154037987333), axis=1) |
np.mean(abs(array_x*8.987861901906815+np.cos(2*np.pi*6.106451502687338)*np.cumsum((np.dot(array_x, np.array([[0.03417804586033779, 0.9322556720488472, 0.813925986483505, 0.08932581026990727, 0.3026130718647799], [0.8887273099701392, 0.5501178719928888, 0.8712513169969285, 0.7492323673755494, 0.07422912404029025], [0.5513107448954935, 0.8813954473183964, 0.45012031005983955, 0.9477497426763727, 0.9403265602704324], [0.41531919447886956, 0.8508678676444558, 0.8979816958201665, 0.633877376788566, 0.910010737232179], [0.6742859414380478, 0.8150579172244073, 0.18510352351840975, 0.26496061832791273, 0.959300664943906]])))-1.3268898681893018, axis=1)), axis=1) |
np.amax(array_x+4.9249453982322+2.8282658358820623, axis=1)+10*(np.sin(2*np.pi*np.amax(array_x+8.980943375251176+6.586607778583048, axis=1))) |
np.exp(np.sqrt(abs(1/(np.mean(np.cos(2*np.pi*array_x*np.sin(2*np.pi*3.173283067498593))-np.sqrt(abs(array_x)), axis=1))))) |
np.mean(np.sqrt(abs(np.sqrt(abs(-(np.sqrt(abs(np.exp(np.cos(2*np.pi*np.square((np.dot(array_x, np.array([[0.7714905426719516, 0.3954669205564725, 0.8463307226924777, 0.6712612871642266, 0.8134872026072312], [0.7126590774945684, 0.06684010333497603, 0.30323269959742827, 0.23932046198564283, 0.33582154548500776], [0.8681375655610996, 0.9398480767162927, 0.9905107920096256, 0.3153660701604024, 0.004034738492599832], [0.8116689714316773, 0.08853054630893387, 0.39147510020948917, 0.1354185834060052, 0.2213162459829231], [0.35852101359496746, 0.9776764802229613, 0.5907259626320621, 0.40485153725598355, 0.6476808663235404]])))))))))))))/np.log(abs(np.sin(2*np.pi*np.cos(2*np.pi*(np.dot(array_x, np.array([[0.5269358644808534, 0.9742879051325668, 0.05841815296798614, 0.010207064215119632, 0.504998717926], [0.7152989205305911, 0.34249940799055123, 0.44408813621527155, 0.7867838267960884, 0.8156519302249835], [0.5274136307194826, 0.3270473034453858, 0.8006846295581875, 0.7375696925172135, 0.8211922009462962], [0.6991158305854333, 0.29371730808942853, 0.7623223141047941, 0.30890845010540713, 0.6964830326552277], [0.0700732446337099, 0.6182203372723502, 0.3137258927179817, 0.34057811920331615, 0.5361720301298823]]))))))), axis=1) |
np.mean(9.345329742748737*np.square(array_x-3.289143425486733)-2.4761237737923-np.square(2.284947540056379), axis=1) |
np.mean(np.sqrt(abs(array_x*2.9383457411343183+array_x))-np.square(7.12765071679493-10*(array_x*5.65689029435409)), axis=1) |
np.round(np.mean(abs(np.round(2.106916137336853))*np.square(5.218274118600953+array_x), axis=1)) |
np.mean(10*(np.square(5.326257690080654-array_x-2.0744027796911917+array_x)+9.051925359988825*np.square(array_x)+6.929130110848001), axis=1) |
np.mean(np.cumsum(np.square((np.dot(array_x, np.array([[0.7991264031460908, 0.39204527860916083, 0.09758285592808336, 0.5044358319610285, 0.9705885930051196], [0.6662984976255528, 0.5032540811322193, 0.22358666449365105, 0.20189032222744463, 0.283550349648668], [0.7086836870831065, 0.5556346170170092, 0.8865817908044489, 0.35275582880259115, 0.8517815274399059], [0.27294999202479664, 0.5117463907085189, 0.743746570290976, 0.4016338904554154, 0.5485768588302484], [0.42755584650740963, 0.15020314855466754, 0.3485677506732662, 0.6565059769161146, 0.11827592583335622]])))), axis=1)-np.exp(8.277641059894687)/np.sin(2*np.pi*np.sqrt(abs(np.cos(2*np.pi*8.412235191500516+(np.dot(array_x, np.array([[0.0677277767778558, 0.05183107001558551, 0.3993365041600553, 0.905711358166176, 0.20114966822177804], [0.536374314565893, 0.24912934002574605, 0.6740747518020642, 0.5773612588784276, 0.03648899095079838], [0.4714887640836013, 0.21038562174018893, 0.12150633440924996, 0.7442633429280137, 0.8858672923503178], [0.43906424213308093, 0.4122876666363272, 0.578704161184761, 0.6425904172283168, 0.06734614432635055], [0.08398252850710519, 0.5560752417906157, 0.2928961799640394, 0.6967348089047316, 0.21441699053975616]])))*(np.dot(array_x, np.array([[0.2593500318641676, 0.09132571699532055, 0.4000077707081875, 0.6404233841236101, 0.570195855795951], [0.3087289856053259, 0.5394355248019336, 0.287007872003637, 0.12719780701720407, 0.12535930842440102], [0.6668381975339253, 0.14882677392324073, 0.8882042837336447, 0.8510528045597289, 0.763903450299401], [0.4412617088099502, 0.6460413559289733, 0.4229962717613366, 0.778909335474752, 0.40931436080986494], [0.08022235897435348, 0.9055689340601573, 0.8358514345804614, 0.48149512790950877, 0.3847653985022056]]))))))+4.895533149412296), axis=1) |
np.amax(5.075880476553818+array_x*np.square(5.870712425160965), axis=1) |
np.exp(np.sum(np.sin(2*np.pi*array_x*array_x/np.sin(2*np.pi*7.70756526781585)*7.327968516037343)-np.sin(2*np.pi*abs(6.572722118303094)), axis=1))+10*(np.sin(2*np.pi*np.exp(np.sum(np.sin(2*np.pi*array_x*array_x/np.sin(2*np.pi*4.496175314864166)*6.711618391346544)-np.sin(2*np.pi*abs(3.333274197284497)), axis=1)))) |
np.sum(np.square(6.802359048242179-array_x+(np.dot(array_x, np.array([[0.28974843173910014, 0.5391716874768057, 0.819196203444752, 0.4043839696127841, 0.22981078765199692], [0.17790991069338802, 0.007230756364600688, 0.505004391148344, 0.4455720477947177, 0.19984065581844834], [0.6378177813913849, 0.14014484091807322, 0.5927571240216789, 0.31765059115299754, 0.014316859856268738], [0.590516018953098, 0.5665269168788076, 0.8248087328851571, 0.46502881439136945, 0.6233541037131147], [0.7394623333277973, 0.14897598611521423, 0.2185576427149487, 0.7193684457575586, 0.1477533756406315]])))-8.246118072472765), axis=1) |
np.mean(np.square(np.round(10*(1.9272778775558113-np.square((np.dot(array_x, np.array([[0.3875596277192387, 0.6068170786569888, 0.8564728720836958, 0.4164209224257719, 0.49653911459340916], [0.37731395417969993, 0.09314811607682638, 0.30206878140352067, 0.8967371788255707, 0.15486498786558056], [0.9606549704285848, 0.5962978560848989, 0.1019338451445494, 0.699665623801217, 0.7294514933453604], [0.09756885520299796, 0.9016480212829033, 0.10315932478944867, 0.5656534493061074, 0.6389360682883409], [0.764318123320218, 0.9029978067745951, 0.5986888871842879, 0.3563540976556172, 0.546236364960806]]))))))), axis=1) |
np.mean(10*(np.log(abs(-(np.sin(2*np.pi*array_x+(np.array(range(1, array_x.shape[1]+1)))))))*8.036172338174806-10*(array_x)*7.994779486754968+np.sqrt(abs(np.sqrt(abs(6.223465088831934))))), axis=1)+10*(np.sin(2*np.pi*np.mean(10*(np.log(abs(-(np.sin(2*np.pi*array_x+(np.array(range(1, array_x.shape[1]+1)))))))*2.085411700762605-10*(array_x)*6.66360599222654+np.sqrt(abs(np.sqrt(abs(4.460183554031501))))), axis=1))) |
np.sum(1/(np.log(abs(array_x-7.743089522217886*8.573511796090475+array_x+np.sin(2*np.pi*9.885463261855898)))), axis=1)-np.prod(6.228002045959278+array_x+9.401209094254945, axis=1) |
np.mean(10*(np.sqrt(abs(4.873599652610223))-np.sin(2*np.pi*4.8232895312041375*abs(1.9992889388555066*array_x*7.599303967839389))), axis=1) |
np.mean(np.exp(4.5361243473338595-array_x*4.117155568928528), axis=1) |
np.mean(np.square(np.cumsum(array_x-2.5481827017083507, axis=1))/7.316480780990613, axis=1)+np.sin(2*np.pi*np.mean(np.square(np.cumsum(array_x-3.6591633305420608, axis=1))/1.0147073969793794, axis=1)) |
np.mean(10*(np.square(6.8679896607018085-array_x))*9.868926551029794, axis=1) |
np.round(np.mean(np.square(5.898639626666816-array_x+8.22787484711927*9.527707291091668)/np.square(1.7385297200031493), axis=1)) |
np.mean(np.cumsum(np.cos(2*np.pi*np.cos(2*np.pi*array_x*5.7892056373723815-np.sqrt(abs(7.5375904082562935)))), axis=1), axis=1) |
9.758030006784692+np.sin(2*np.pi*7.729547359526485)-np.sum(np.exp(array_x), axis=1)-np.sqrt(abs(-(np.log(abs(4.9331644485412465))))) |
np.mean(abs(8.646996186736768-array_x)*6.975073212223085, axis=1)+10*(np.sin(2*np.pi*np.mean(abs(7.6701672589428975-array_x)*1.2635599056798004, axis=1))) |
np.mean(np.log(abs(np.log(abs(6.274605391791287))+array_x+(np.array(range(1, array_x.shape[1]+1)))))*np.exp(6.239555496355651)-np.sin(2*np.pi*array_x), axis=1) |
np.prod(10*(np.square(np.cos(2*np.pi*8.731341541450195*6.423423229676467+np.cumsum(array_x, axis=1)))), axis=1) |
np.mean(np.cos(2*np.pi*3.9090152044182913)*array_x*-(array_x+2.771991121443519)-array_x*5.8578565433912555-5.840532535314541-array_x, axis=1)+10*(np.sin(2*np.pi*np.mean(np.cos(2*np.pi*2.714511346615952)*array_x*-(array_x+3.0351336236046516)-array_x*8.5115218637093-2.1393426131126274-array_x, axis=1))) |
np.mean(np.cos(2*np.pi*9.297395124945812)-array_x+1.7354479634007447-array_x, axis=1)+10*(np.sin(2*np.pi*np.mean(np.cos(2*np.pi*7.099222812954325)-array_x+1.2448608757894004-array_x, axis=1))) |
np.mean(np.log(abs(np.exp(array_x)*abs(7.8485557096814125)+3.6267139722934063))-10*(np.square(array_x)*6.008931954731504), axis=1) |
np.mean(1/(np.sqrt(abs(array_x))-1/(9.884107411674062)), axis=1) |
abs(1/(np.cos(2*np.pi*np.prod(8.469509253047878+(np.dot(array_x, np.array([[0.0005839387908220806, 0.01766234113056453, 0.03808143816727627, 0.6595386298743077, 0.3493755308805072], [0.927999427508624, 0.47061087550037817, 0.028014443925326704, 0.9522777409394924, 0.5789208075295565], [0.8604919487903855, 0.0073116430981102765, 0.656043565629391, 0.7523543603585906, 0.7728929174547358], [0.11328844094006407, 0.5363817950574334, 0.686517877493548, 0.46231803715674635, 0.16753855913410942], [0.1393776160957526, 0.5702820076062479, 0.5098063798846587, 0.8987561724957965, 0.9683748566664726]]))), axis=1)))) |
np.round(np.prod(np.log(abs(1/(9.98979079570662*array_x+5.07216972591014))), axis=1)/4.689300594611731) |
np.mean(np.exp(np.round(1.2711391458056656+(np.dot(array_x, np.array([[0.5514056941698948, 0.8075465229234303, 0.2070660861492063, 0.0008898297969858193, 0.2701758007528672], [0.27290924529598803, 0.6349384122244994, 0.9419242214695259, 0.660369541430426, 0.7059404799872127], [0.9600690115647941, 0.05787047711291815, 0.10912338735793548, 0.9328458724075949, 0.3671230106626825], [0.017960487184682128, 0.96310460065711, 0.35460157835821926, 0.89767507101742, 0.7151974017641637], [0.19129994437658515, 0.2185729519411337, 0.32885169359967936, 0.5361610318529806, 0.7801128054863291]]))))), axis=1) |
np.mean(np.square(abs(3.557496586340544*array_x*3.48114918938436))+np.square(8.528290032883348)-array_x*abs(8.12510722596311), axis=1) |
np.mean(abs(3.892081923695081-np.cos(2*np.pi*(np.array(range(1, array_x.shape[1]+1))))/np.cos(2*np.pi*np.cos(2*np.pi*1.3822829556333036-(np.array(range(1, array_x.shape[1]+1)))-array_x/5.910536126869419))), axis=1) |
np.mean(np.round(np.cumsum(2.5456135991037856+-(5.9581042675226605)*array_x+6.712693762334896*np.square(array_x*abs(4.245852694241955)), axis=1)), axis=1) |
np.mean((np.array(range(1, array_x.shape[1]+1)))+np.round(np.cumsum(array_x, axis=1))*np.square(array_x+(np.array(range(1, array_x.shape[1]+1)))*array_x), axis=1) |
np.mean(np.exp(5.650676289757757-array_x)/9.05358894646177-10*(3.86907104160095), axis=1) |
np.mean(1.2959259488963806*np.square(6.195202665278324+array_x), axis=1) |
np.mean(10*(abs(3.705398771752802)+array_x)*7.762357340738064+array_x, axis=1) |
np.mean(7.258892035589265*3.2946476229783492+np.round(array_x)*abs(np.exp(7.8949446890610515)), axis=1) |
np.mean(np.square(array_x+7.609098493143868)-array_x/np.exp(9.73854891424687), axis=1) |
6.442473585250998/np.log(abs(array_x[:,0]*1.4392300976120942))/9.363564047179281-array_x[:,0]-9.218765197440216-abs(np.sum(1.0001196150088438+array_x, axis=1)) |
np.mean(np.square(10*(abs(np.square(6.22148710149557))-array_x/6.217140512652172*6.828465781889695))+4.0969573941454875-np.sin(2*np.pi*3.3993434949048904)-(np.array(range(1, array_x.shape[1]+1)))+4.577643423694029*3.8465778097682635, axis=1) |
np.mean(1.9616736467905898*np.exp(6.726238694110977-array_x), axis=1) |
np.mean(np.square(5.604493392284872+np.square(3.94570917251841)-10*((np.array(range(1, array_x.shape[1]+1)))*array_x)/np.cos(2*np.pi*7.591847213110155/(np.array(range(1, array_x.shape[1]+1)))*array_x))+4.314950242513619+(np.array(range(1, array_x.shape[1]+1)))*array_x-(np.array(range(1, array_x.shape[1]+1)))*array_x, axis=1) |
np.square(abs(np.square(np.amax(2.9120592665915024+array_x, axis=1)))) |
np.mean(np.square((np.dot(array_x, np.array([[0.1968522838825133, 0.38051234542686097, 0.07102305867026137, 0.5079247362152279, 0.6181086971469516], [0.2969704263860393, 0.7520224734204284, 0.6941587948399843, 0.766002387523244, 0.3164083732392774], [0.3299160757784093, 0.6142764043521123, 0.7554619165233488, 0.3031158257699621, 0.23914219168661632], [0.36841644310246224, 0.4146230046656487, 0.25899243540629324, 0.09095808188335819, 0.5820667247356258], [0.7525364704869316, 0.7430338028155106, 0.4938034320089296, 0.9840779811951987, 0.8794081371601548]])))*6.914467798874538+(np.dot(array_x, np.array([[0.030091216363665185, 0.0931007144423206, 0.6291354843708742, 0.3797816077135261, 0.15290342562904324], [0.12279357001856173, 0.4871777838335877, 0.7129756352491918, 0.8529518021081587, 0.9820959313322205], [0.8339885156973125, 0.8514768207239811, 0.9387593721632459, 0.720292606619532, 0.15870250632381133], [0.25341759592606616, 0.8246222880010781, 0.0603550476847331, 0.709212657603089, 0.31592634751600357], [0.06631662146830264, 0.15655533903468943, 0.9818996546065146, 0.40296256343227543, 0.8865493772376692]])))/np.square(6.129151691593369)+2.2165052596417603), axis=1) |
np.sum(1/(np.log(abs(7.832373538795121*array_x)))+10*(8.843683289604236), axis=1) |
np.sin(2*np.pi*np.mean((np.dot(array_x, np.array([[0.7673516102122184, 0.03242265802113331, 0.18342105649814044, 0.6640931135884185, 0.92795113826573], [0.19833971925854743, 0.1490360618167874, 0.16635558763331004, 0.2802396541276866, 0.9557183563622842], [0.25907822724369045, 0.9358866838582988, 0.22218135286371776, 0.022796265876054544, 0.9697540338795523], [0.17321084888662985, 0.9981066149538952, 0.19116774205483844, 0.7025155999953275, 0.7093024483719726], [0.6492558123305746, 0.2808412672137385, 0.9040653548195297, 0.789366888337612, 0.9210739693014751]])))-2.495021884297577+array_x, axis=1))+8.35913907800186-array_x[:,0]+10*(np.sin(2*np.pi*np.sin(2*np.pi*np.mean((np.dot(array_x, np.array([[0.9049860381559874, 0.48229190472908945, 0.0770388599669467, 0.22622195063167672, 0.03063193351050375], [0.4116690884353109, 0.5274159270716737, 0.19939829090354844, 0.14736854002081756, 0.4984078131839992], [0.03879249537516194, 0.8430069175495096, 0.10488353252981464, 0.905583011891279, 0.9389139008038409], [0.7641889097721158, 0.3541708103665935, 0.2225369965547922, 0.025454823792171122, 0.9230013387955096], [0.3870590350063082, 0.8390256959753234, 0.60072362527655, 0.23245946821414787, 0.023083269277288654]])))-8.295536882989676+array_x, axis=1))+5.657770175137566-array_x[:,0])) |
np.mean(9.273843034558533*np.square(9.625903291309584+array_x+array_x), axis=1) |
np.mean(9.415039062284807-np.square(6.097192899271518-(np.array(range(1, array_x.shape[1]+1)))*array_x*np.square((np.array(range(1, array_x.shape[1]+1)))*array_x)), axis=1) |
7.450186571679105+np.sum(np.sin(2*np.pi*np.square(8.54401906302656+array_x)), axis=1) |
np.sum(abs(np.square(2.6499492596298526+(np.dot(array_x, np.array([[0.48460861007515155, 0.6442374018469273, 0.3676765888831609, 0.9405307162274865, 0.5019571007162962], [0.747887145078225, 0.09768753771770933, 0.9184647916842534, 0.6114727020806627, 0.5919176637517705], [0.09987446087530327, 0.12935392381429012, 0.5469785748464747, 0.7462170706922256, 0.6982503655916946], [0.853989360091817, 0.44686564156560127, 0.7755037047943526, 0.49932678122574004, 0.25022629952290576], [0.4663461782716811, 0.4974767822325007, 0.27015204430711237, 0.07041479738465961, 0.5848947072633777]])))-array_x/7.1081405615967395)), axis=1) |
np.mean(np.sin(2*np.pi*np.exp(7.103514477905139))-10*(np.sqrt(abs(array_x))), axis=1) |
np.mean(np.square(8.822466715216677-array_x-np.sin(2*np.pi*1.279172395530788)-array_x+array_x), axis=1) |
10*(np.log(abs(1.4415755889126727+np.prod(np.sqrt(abs(10*(array_x)+7.626601035603591)), axis=1)))) |
np.sum(np.square(array_x/10*((np.array(range(1, array_x.shape[1]+1)))))-array_x, axis=1)-np.exp(1.531217952530564)+10*(np.sin(2*np.pi*np.sum(np.square(array_x/10*((np.array(range(1, array_x.shape[1]+1)))))-array_x, axis=1)-np.exp(8.656368047709861))) |
np.prod(-(np.sqrt(abs(np.sqrt(abs(array_x-np.square(np.square(array_x))+2.161359182254494)))))-array_x, axis=1) |
np.mean(np.sin(2*np.pi*array_x)-np.exp(3.717586840722594)+array_x*10*(6.420978402563146), axis=1) |
np.mean(np.sqrt(abs(8.135233405017686))+array_x*8.567338775984194, axis=1)+np.sin(2*np.pi*np.mean(np.sqrt(abs(2.1875331999317544))+array_x*9.923477311589224, axis=1)) |
6.666371159169414-np.amax(np.square(9.304004707166271+array_x), axis=1) |
np.sum(np.square(9.708543907389537-np.cos(2*np.pi*9.332766955909424-array_x))+1/(1.8009558008110509), axis=1) |
np.round(5.788717525465783)-array_x[:,0]-np.amax((np.dot(array_x, np.array([[0.7611998556189734, 0.05011534075630464, 0.2337029223610716, 0.01904531334577042, 0.5572092193323837], [0.21969957275271224, 0.20494609263108476, 0.9077833461506487, 0.19629040631214267, 0.7516847957187512], [0.627604001444095, 0.7850893810982872, 0.3120498541266983, 0.6265943776010202, 0.520380177345692], [0.621284939028864, 0.11495871232123045, 0.14390343235388625, 0.5769185567090951, 0.5188612981076915], [0.48217840202462536, 0.9377945167884764, 0.18468755697479133, 0.03982687675662078, 0.49749453095616836]])))*(np.dot(array_x, np.array([[0.2799715770235819, 0.31701403910596326, 0.807861057666022, 0.5512074557720016, 0.3242141316218523], [0.7005231391882781, 0.13994941380538095, 0.7342277475525795, 0.3424336891669696, 0.4207875280100709], [0.7778810342844225, 0.677078849291788, 0.9639209248189463, 0.9484905427934335, 0.19225148808821946], [0.9063192689049285, 0.6807779369215847, 0.7434996977196154, 0.25363102494877343, 0.13197632090865452], [0.33486903607387564, 0.45440058250523463, 0.7398006343752074, 0.7899083140293781, 0.3153593768599354]]))), axis=1) |
np.mean(np.square(6.510493471117462-np.exp(array_x)-8.171012691820906), axis=1) |
np.mean(array_x-7.2867833348956745-3.692171520066249*array_x*6.655955760120852, axis=1) |
np.sum(np.sin(2*np.pi*array_x), axis=1)+np.sqrt(abs(np.sin(2*np.pi*4.475558469359327))) |
np.mean(np.square(array_x*2.3703702710645307+np.exp(np.square(np.cos(2*np.pi*10*(7.572225926407454))))), axis=1) |
np.mean(abs(np.cumsum((np.dot(array_x, np.array([[0.2489167191545526, 0.49331638161631586, 0.14590590486892463, 0.9592682925772258, 0.925846262511795], [0.15198290325935448, 0.5602634418741189, 0.1692273313603614, 0.8324720180313262, 0.5987495073100401], [0.0677298137987904, 0.8011175179837489, 0.6457164372562335, 0.7063162238680291, 0.6545425804747818], [0.5766916376706289, 0.7378367081860636, 0.7145845144883899, 0.7344253212877837, 0.2665156884570491], [0.24338804835757344, 0.44598016983456445, 0.4941057711361925, 0.5737523010806712, 0.2980992270135656]]))), axis=1))-7.9646714502422595+array_x+np.square(4.329108261193694)/6.2835368293338325+array_x, axis=1) |
np.mean(np.exp(np.sqrt(abs(2.1886740514822343-array_x)))*5.441449517477692-2.9361633897952446-array_x+np.exp(array_x)-array_x, axis=1)+10*(np.sin(2*np.pi*np.mean(np.exp(np.sqrt(abs(4.629515759977168-array_x)))*9.632142788962032-3.420295168878073-array_x+np.exp(array_x)-array_x, axis=1))) |
np.mean((np.dot(array_x, np.array([[0.9341780365218499, 0.9748087553846694, 0.5014361737501805, 0.697671117563205, 0.019856650921482144], [0.6401559608458217, 0.5131797186433755, 0.5795188058769815, 0.4369710198114757, 0.5846935289120413], [0.9471903028139798, 0.6238500634813603, 0.22748505190339297, 0.07046340703713616, 0.9929213141805877], [0.5667064941632226, 0.4576090468744214, 0.4742884343697701, 0.06498450795249833, 0.5343967701774988], [0.5814643709600861, 0.9801677130575472, 0.657464836493671, 0.2993537131357358, 0.22284817228045517]])))-6.231372722186921*np.square(5.506423875320813*array_x-np.exp(4.048976638564561)), axis=1)+np.sin(2*np.pi*np.mean((np.dot(array_x, np.array([[0.742721989636909, 0.395830266934459, 0.5661097412441853, 0.8588619787446135, 0.4176836268822611], [0.0578115674195554, 0.9822127753465252, 0.00385025991384802, 0.0008050295331952784, 0.541259535924238], [0.002118785856178751, 0.49792705204302723, 0.22490029056615501, 0.0009565123918523488, 0.40364265016247114], [0.008167310237889636, 0.5155980999133934, 0.7702805807275913, 0.9316732041380014, 0.4072929342622108], [0.2399493552182963, 0.127987959363974, 0.6138810100332325, 0.703895460521705, 0.13859620103577497]])))-3.8738672153058014*np.square(2.0370767082743355*array_x-np.exp(6.703114723698875)), axis=1)) |
np.round(np.square(np.sum(np.exp(array_x)-np.sqrt(abs(9.90024143041739)), axis=1)+np.log(abs(array_x[:,0]-7.7942214978271105)))) |
np.mean(7.960012356018626+5.175924411575452*array_x*array_x*2.633932305254673, axis=1)+np.sin(2*np.pi*np.mean(8.607827903029136+5.896541834394029*array_x*array_x*5.726402341634476, axis=1)) |
np.mean(5.618293652596123+10*(array_x/5.9690613493878875/np.cos(2*np.pi*array_x*np.square(2.5872359178453115))), axis=1) |
np.mean(np.sqrt(abs(9.870114860521074))*np.sqrt(abs(array_x))-5.237505788723523+6.855643586372608*array_x+np.sin(2*np.pi*3.2274284945446876), axis=1)+10*(np.sin(2*np.pi*np.mean(np.sqrt(abs(2.740660958946164))*np.sqrt(abs(array_x))-2.037616294874134+9.49278280164187*array_x+np.sin(2*np.pi*5.0167337555542755), axis=1))) |