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np.square(np.sqrt(abs(np.mean(array_x, axis=1)-7.7758818973578965))-np.exp(4.254256669331493)) |
np.mean(9.611253555724765*array_x+9.714663270135375, axis=1) |
np.sum(np.round(np.square(6.8327270663949875-np.cos(2*np.pi*np.sqrt(abs((np.dot(array_x, np.array([[0.7258860041900306, 0.5066629171355118, 0.5431407577814328, 0.5659023963408412, 0.14278558574123967], [0.5541716250194286, 0.45533094429930476, 0.17158356034049682, 0.11020022534793594, 0.7733652255715091], [0.8203370498373951, 0.21511567789303765, 0.063889806998642, 0.5055259255410078, 0.6263103083588375], [0.4475522389590032, 0.4457202973692357, 0.5450327988410298, 0.6615248296890688, 0.0326822364880075], [0.21918689811744707, 0.5352061054712793, 0.22571801450605555, 0.7921435655779065, 0.6605779585449175]])))-4.481977360980263+np.sqrt(abs(array_x))+array_x-2.086169631029971))))), axis=1) |
np.mean(5.646971177862586-array_x+10*(array_x), axis=1) |
np.mean(array_x-5.936383167548877*(np.dot(array_x, np.array([[0.5875644556151876, 0.9668379970905803, 0.7418507024299851, 0.08723352916801874, 0.7596856417712707], [0.7553779382357984, 0.43339081579569394, 0.20877262174027367, 0.2792375799744622, 0.7336238443994669], [0.37419837656323274, 0.5223921887924651, 0.884763338836382, 0.37624051237195144, 0.6273556407828809], [0.5050255132651914, 0.11038947970052038, 0.08399383105867875, 0.20147168038913987, 0.13166775979779932], [0.3691896931464591, 0.20734016518443188, 0.7299397333609372, 0.209055729924562, 0.8958899201432884]])))-array_x+6.115123906611898, axis=1) |
np.mean(np.square(10*(1/(array_x+np.sin(2*np.pi*4.644533987520969))-np.sin(2*np.pi*9.91615999276384))), axis=1)+np.sin(2*np.pi*np.mean(np.square(10*(1/(array_x+np.sin(2*np.pi*4.981842755550588))-np.sin(2*np.pi*1.563775653449552))), axis=1)) |
np.mean(np.round(np.square(5.6317011041219365-array_x)), axis=1) |
np.mean(array_x, axis=1)*array_x[:,0]+7.62037197324785/3.8272608908150563+10*(np.sin(2*np.pi*np.mean(array_x, axis=1)*array_x[:,0]+5.184913389734258/7.956735013581934)) |
np.mean(np.square(8.88362953393118)+array_x*4.490064804691428*5.736718176196972*5.339031560129119-(np.dot(array_x, np.array([[0.9367433489779347, 0.7557384077938992, 0.8414507925129702, 0.06735603626872988, 0.1876512440520065], [0.34790861615746405, 0.9127919908178783, 0.4935514292054597, 0.902058646487161, 0.577072129301452], [0.18752259477930489, 0.1539127711044579, 0.8000484727227937, 0.13828717905650778, 0.4936343521158708], [0.2498778260101291, 0.5455590326173383, 0.6142241533670273, 0.25107168654543066, 0.00759195845135352], [0.15307588994784416, 0.6013777714064038, 0.502651604724272, 0.6333563754689127, 0.33853712645276657]])))-np.sqrt(abs(np.log(abs(2.81065002612073)))), axis=1) |
np.sum(np.sqrt(abs(array_x))-7.25791386808386, axis=1)-np.mean(np.exp(array_x+9.45827474576004), axis=1)*4.499611587454828 |
np.sum(np.exp(np.cumsum(np.sqrt(abs(-(5.694285976346156)))-np.sqrt(abs(array_x)), axis=1)), axis=1) |
np.sum(np.exp(7.138725478889687+array_x+7.617428637822276), axis=1)-np.square(3.190512597094878)-np.cos(2*np.pi*np.sum(array_x/2.3371324647295633, axis=1)) |
np.mean(np.square(array_x-7.681315460582773)/np.cos(2*np.pi*7.493515786616554)+1.6070122498099482+array_x-array_x+np.exp(1.1840982338094692), axis=1) |
np.mean(np.round(np.sqrt(abs(6.356973329242103))+np.exp(abs(np.round(array_x)-5.7152236938871255))), axis=1) |
np.mean(abs(np.cumsum(3.3097794719034686+np.cumsum(array_x, axis=1), axis=1)), axis=1) |
9.634706429202014*np.exp(5.389451454081977+np.sum(array_x, axis=1)*1.644822439866128) |
10*(np.prod(10*(np.exp(array_x))-np.round((np.dot(array_x, np.array([[0.5812709621225463, 0.2733507156586126, 0.9151375341631863, 0.8936404295319679, 0.776230005646782], [0.8371987992738936, 0.24400720607413595, 0.4837920386335419, 0.6090125816222619, 0.8560219317134609], [0.39984389142206644, 0.6179323123899653, 0.3921372565680359, 0.3264569339770921, 0.5322878209622135], [0.47320250626074367, 0.9309350119157673, 0.8868219927238123, 0.6282714448442522, 0.31922485734655837], [0.7555226512762444, 0.173754084638453, 0.9259380824237615, 0.31364237606268963, 0.3170722366946801]])))), axis=1)) |
np.square(np.sum(array_x*1.8688172436876211, axis=1)-np.cos(2*np.pi*7.113869734777577))+np.sin(2*np.pi*np.square(np.sum(array_x*8.836556206626616, axis=1)-np.cos(2*np.pi*6.926004212746599))) |
np.mean(array_x*array_x*8.88249021219064+6.188034944784679-array_x*1.6245664624539529, axis=1)+10*(np.sin(2*np.pi*np.mean(array_x*array_x*3.6025433943884786+7.662024347464813-array_x*8.980110153316716, axis=1))) |
np.mean(np.square(1/(np.round(6.701896690351917)+6.415460783373609/(np.dot(array_x, np.array([[0.6532626513854995, 0.2548238111998057, 0.9716563094872377, 0.40546197156304975, 0.43264239324514076], [0.07660134558948384, 0.30286273002710573, 0.9863903304644687, 0.7326721576389813, 0.6306681673487712], [0.30189752136488046, 0.22404729822601233, 0.6217292988237073, 0.020817289451781185, 0.0663901639556187], [0.6362687208463814, 0.4285718458251949, 0.34430183839799045, 0.21836589548137597, 0.3472819715701586], [0.731983316838058, 0.26794844437201804, 0.9665579239604093, 0.741830148507589, 0.7301233818352416]])))-9.68816285340409)+np.exp(array_x)/6.174828338006034)+8.32693304950642/(np.array(range(1, array_x.shape[1]+1)))+1.8949542459025972+array_x, axis=1) |
np.sqrt(abs(np.exp(9.185869759378892+10*(np.amax(6.370399716506536/10*(array_x), axis=1)))))+10*(np.sin(2*np.pi*np.sqrt(abs(np.exp(7.840817983117978+10*(np.amax(6.605570988749092/10*(array_x), axis=1))))))) |
np.mean(np.sqrt(abs(np.cos(2*np.pi*np.sin(2*np.pi*np.cos(2*np.pi*9.2682479183992))-np.round(array_x)))), axis=1)+10*(np.sin(2*np.pi*np.mean(np.sqrt(abs(np.cos(2*np.pi*np.sin(2*np.pi*np.cos(2*np.pi*6.466118993002715))-np.round(array_x)))), axis=1))) |
np.mean(abs(np.sin(2*np.pi*np.round(np.sqrt(abs(2.537376736370107)))*abs(np.log(abs(5.353061040657484))*9.084403340918096+array_x))), axis=1)+10*(np.sin(2*np.pi*np.mean(abs(np.sin(2*np.pi*np.round(np.sqrt(abs(3.2010114937709417)))*abs(np.log(abs(8.424469744080492))*2.8702114010640596+array_x))), axis=1))) |
np.mean(10*(8.820131205245701+array_x-(np.dot(array_x, np.array([[0.02309329834986329, 0.30494433588361314, 0.8138002531744539, 0.7419148725736923, 0.0661777921436747], [0.5989836801745808, 0.45192769387421117, 0.5749099189951369, 0.1658550033448658, 0.9052304170025766], [0.8893217087448806, 0.748204210475343, 0.9998577131613823, 0.10914536237089245, 0.3889627216731961], [0.3988219815367948, 0.6628197855637946, 0.4314105951307322, 0.9054046112914633, 0.6331235906218123], [0.2117372347361448, 0.6077909593673532, 0.9817999910038818, 0.29098175437245255, 0.2570724517897778]])))*8.746958770274604/2.2531047006172216+np.sin(2*np.pi*array_x)-6.857098561758352), axis=1) |
np.sum(np.cos(2*np.pi*array_x/4.676170153582154)*9.647473725171574, axis=1)-4.5480115097041605 |
10*(np.sin(2*np.pi*-(np.cos(2*np.pi*np.sqrt(abs(5.935677815952265))*np.prod(array_x-array_x*2.5524990636787304, axis=1)+np.cos(2*np.pi*np.cos(2*np.pi*6.7309047813487295))))))-np.cos(2*np.pi*np.sqrt(abs(1.0099723381647412))*np.prod(array_x-array_x*5.094163239687496, axis=1)+np.cos(2*np.pi*np.cos(2*np.pi*8.42580376000799))) |
np.mean(array_x-3.3703757837086523+np.cumsum(np.square((np.dot(array_x, np.array([[0.8113563889026021, 0.5581331916883197, 0.10923366571023496, 0.9547764629028214, 0.016339585656854227], [0.17032062558004224, 0.11109653985128387, 0.3927691946994156, 0.9092230795617028, 0.22191295954617218], [0.6244356335221573, 0.6053553938705143, 0.8161490476144007, 0.7125196351515882, 0.35426010066565117], [0.8637506770775444, 0.48393009829649825, 0.5185359512327571, 0.19553909186971985, 0.2113773056854661], [0.8332280946311788, 0.7620581618496143, 0.45788562094410323, 0.8902475090085256, 0.34602077913934093]]))))*array_x-(np.dot(array_x, np.array([[0.5137025728738953, 0.7315528952711826, 0.13742079570637433, 0.6908558333937329, 0.38096092615450505], [0.6674995688821082, 0.8423630120922952, 0.8968408261476699, 0.8698249197884628, 0.31725278977373006], [0.5012990010788188, 0.48623358100210834, 0.47630132323673213, 0.9906566509948028, 0.13286699946642044], [0.8068847257843159, 0.31994068701099887, 0.13655060123539842, 0.9471140816652959, 0.5499938530020064], [0.7397364765564582, 0.41042198582730083, 0.6943438573940546, 0.019074364693125734, 0.4632362616569482]])))-6.854206721233035*3.259878729439101, axis=1), axis=1) |
np.mean(7.655443210241482-np.sin(2*np.pi*(np.array(range(1, array_x.shape[1]+1)))*array_x)*4.014044055592631-4.721241319577406, axis=1) |
np.exp(np.square(array_x[:,0])/5.298675053225745)-8.694803491864757*np.sin(2*np.pi*np.square(np.mean(array_x, axis=1)))+np.sin(2*np.pi*np.exp(np.square(array_x[:,0])/3.4536427824066354)-5.743227866222507*np.sin(2*np.pi*np.square(np.mean(array_x, axis=1)))) |
np.mean(array_x+array_x*5.554948761584568+np.sqrt(abs(np.sqrt(abs(8.144217574909163)))), axis=1)+10*(np.sin(2*np.pi*np.mean(array_x+array_x*8.795962883237895+np.sqrt(abs(np.sqrt(abs(9.562152512028614)))), axis=1))) |
np.mean(np.sin(2*np.pi*9.439248277983388-(np.array(range(1, array_x.shape[1]+1)))*array_x)+np.square(5.456930192572481)+np.exp(np.square(2.4918121362354975))*np.cumsum((np.array(range(1, array_x.shape[1]+1)))*array_x, axis=1), axis=1) |
np.square(-(5.816085108908313/np.exp(np.mean(array_x, axis=1)))-2.470584028999782) |
np.square(np.mean(array_x-array_x+array_x, axis=1)-8.011422010084397) |
np.mean(np.exp(-(9.921095921653919)/1/(3.5415582128236087)-array_x-array_x+5.10085621055137), axis=1) |
np.sum(np.sqrt(abs(np.exp(5.339658254257038*array_x)))+np.sin(2*np.pi*np.square(9.073993271668067)), axis=1) |
np.mean(10*(abs((np.array(range(1, array_x.shape[1]+1)))*array_x))-1.6221233220621043*np.square(np.sqrt(abs(7.471666330638229))/np.sqrt(abs((np.array(range(1, array_x.shape[1]+1))))))+abs(1.1310679331958746), axis=1) |
np.mean(np.exp(array_x/7.991928103516018+5.697077580265251-np.cos(2*np.pi*3.5163367594764257))-5.136754595626632, axis=1) |
np.mean(np.square(4.311021560615656+(np.array(range(1, array_x.shape[1]+1)))*array_x+10*((np.array(range(1, array_x.shape[1]+1)))*array_x-3.263307610672653)), axis=1) |
np.mean(abs(7.632156497716917)*np.cos(2*np.pi*array_x-1.639844355708448), axis=1) |
np.mean(1.3516291865858074+1/(array_x-5.981878723279144-(np.array(range(1, array_x.shape[1]+1))))+np.round(array_x)/1.3788027252156398-array_x, axis=1)+10*(np.sin(2*np.pi*np.mean(6.521678981886964+1/(array_x-5.627971675961048-(np.array(range(1, array_x.shape[1]+1))))+np.round(array_x)/2.1943754155086004-array_x, axis=1))) |
np.mean(1/(np.sin(2*np.pi*np.sin(2*np.pi*6.45592310688417-array_x))+array_x/1.5818043590551814-1.7543633058373547/9.595306093944211), axis=1)+np.sin(2*np.pi*np.mean(1/(np.sin(2*np.pi*np.sin(2*np.pi*3.1946333907353903-array_x))+array_x/9.717085047100635-1.0256593372859837/9.857923176586196), axis=1)) |
np.mean(np.round(3.7309730514337702*np.exp((np.array(range(1, array_x.shape[1]+1)))*array_x)-5.121549139984804/(np.array(range(1, array_x.shape[1]+1)))*array_x), axis=1) |
np.log(abs(np.sum(-(np.exp(4.032679138288037+np.sin(2*np.pi*array_x)*4.896342426506468)), axis=1)-np.amax(array_x+4.360720043643849+np.sqrt(abs((np.array(range(1, array_x.shape[1]+1)))))/np.log(abs(np.log(abs(6.307005742111784)))), axis=1))) |
np.mean(np.sin(2*np.pi*np.cos(2*np.pi*9.53257886202569+(np.dot(array_x, np.array([[0.40820623568165226, 0.2935621179878416, 0.45095367067381364, 0.6832119040013925, 0.1402753088806421], [0.012338549326513792, 0.040172828154617535, 0.48041821536452844, 0.7289046927786588, 0.6850714944074558], [0.8952182171941704, 0.6674962909974467, 0.7368314665399953, 0.5004075283818914, 0.46728749292869864], [0.47266257624107366, 0.4575320981407074, 0.4693123986735255, 0.561923925416352, 0.7421160658693796], [0.22705459203446343, 0.30525660817044387, 0.15665945577898754, 0.16198080386383196, 0.978888511412184]])))))*8.015401433573476, axis=1) |
np.mean(5.232184529448835--(array_x)*array_x, axis=1)+10*(np.sin(2*np.pi*np.mean(3.7161553739637103--(array_x)*array_x, axis=1))) |
np.mean(1.5837613204923517*5.087904625024717+7.758508083963575*array_x, axis=1) |
np.mean(6.469637005164126/np.cos(2*np.pi*np.sqrt(abs(array_x-3.74729333584224))), axis=1) |
np.mean(abs(abs(10*(array_x))+1.785262168924981), axis=1) |
np.square(abs(10*(np.sum(array_x, axis=1))+4.059951644543247*np.square(6.784107532062633))) |
np.mean(np.exp(np.square(2.381000322039032)+1/(np.cumsum(6.8858413186314085/array_x, axis=1))), axis=1) |
np.mean(np.square((np.array(range(1, array_x.shape[1]+1)))*array_x/9.063803238545052+(np.array(range(1, array_x.shape[1]+1)))+(np.array(range(1, array_x.shape[1]+1)))*array_x/np.cos(2*np.pi*1.587243626393238)), axis=1) |
np.sum(6.3268208337615155+array_x*9.250467025168522, axis=1) |
np.mean(np.square(np.sin(2*np.pi*np.square(1.384318809446373))-array_x-9.643576631199988)-10*(-(abs(9.473720011377718-array_x))), axis=1)+np.sin(2*np.pi*np.mean(np.square(np.sin(2*np.pi*np.square(6.891153287485171))-array_x-7.409445496776718)-10*(-(abs(3.831522289747019-array_x))), axis=1)) |
np.mean(np.square(1/(np.log(abs(np.cumsum(np.log(abs(2.2244701045113677-np.cos(2*np.pi*np.cos(2*np.pi*8.6079348548937*array_x-(np.dot(array_x, np.array([[0.7355254572944836, 0.5885894787351715, 0.35889124502412906, 0.22106594430048898, 0.8527052436686383], [0.36566678962762134, 0.5162159742305166, 0.2758763936980537, 0.15625805096805245, 0.8817665464587945], [0.970055692899916, 0.1999832297430273, 0.42647690662899596, 0.5624794291936448, 0.8280332701775985], [0.6895393911182695, 0.518848737487684, 0.9704982288196612, 0.29734424617964794, 0.4509217397804074], [0.831718744817007, 0.4409178199263838, 0.5619085580584867, 0.46605069825103507, 0.11822536592360788]])))*array_x)))), axis=1))))), axis=1) |
np.round(7.434448646835305)+np.sum(abs(array_x-3.32306648342113/np.log(abs(array_x))), axis=1) |
np.mean(1/(np.sin(2*np.pi*abs(8.266201201900637))-np.sqrt(abs(np.log(abs(6.890948698382773))-np.sqrt(abs((np.dot(array_x, np.array([[0.49246161436592184, 0.4373058816445713, 0.4590272464306919, 0.003420571050488097, 0.9480140892733866], [0.4136811445774915, 0.5284600712227983, 0.9978489240397623, 0.36917217224825827, 0.7197001992531185], [0.6832849522313962, 0.3118935573888838, 0.08553176249403327, 0.7075844799929862, 0.948533613961846], [0.9295172330861826, 0.8508923553851845, 0.725365263074581, 0.8798293304245353, 0.21819171857833952], [0.6179017729503978, 0.7156044133666661, 0.5583511272230637, 0.8477426857230841, 0.5492839591842202]])))))))), axis=1) |
np.sqrt(abs(np.sum(array_x, axis=1)))+10*(np.mean(np.exp(9.497578810409438-np.square(array_x)), axis=1))-3.197007877824654 |
np.mean(5.044102029234573+array_x-6.580146360250451+7.8195524991240495, axis=1)+10*(np.sin(2*np.pi*np.mean(1.2348760802596446+array_x-3.5690824184425933+8.735302878508161, axis=1))) |
np.mean(np.sqrt(abs(np.sqrt(abs(-(np.sqrt(abs(3.7619369175538693))-np.exp(abs(array_x))*8.21333896091118-np.cos(2*np.pi*array_x)))))), axis=1)+10*(np.sin(2*np.pi*np.mean(np.sqrt(abs(np.sqrt(abs(-(np.sqrt(abs(6.099463461730249))-np.exp(abs(array_x))*7.510041743958528-np.cos(2*np.pi*array_x)))))), axis=1))) |
np.mean(np.sin(2*np.pi*7.483951280211484*array_x/np.square(np.cos(2*np.pi*np.sqrt(abs(array_x))/2.310711128472467))-7.228043798286356), axis=1)+10*(np.sin(2*np.pi*np.mean(np.sin(2*np.pi*4.404254073554946*array_x/np.square(np.cos(2*np.pi*np.sqrt(abs(array_x))/6.448836144592529))-1.0277843688307162), axis=1))) |
np.mean(-((np.dot(array_x, np.array([[0.748485495867258, 0.7818233390171181, 0.7707826283933437, 0.12321399754187423, 0.03792443406181345], [0.774150026165773, 0.74068969274056, 0.557626545949143, 0.32394441039406585, 0.6682865724052658], [0.911195266994022, 0.060761076165469774, 0.6109025625340866, 0.7558381112610575, 0.45426687622032713], [0.5124479929480753, 0.8035626876874623, 0.14549873530927893, 0.5845689138377307, 0.5984560435962178], [0.7928826245108981, 0.7981466442328401, 0.877452434122, 0.9817595770226202, 0.6701609895759734]])))*8.476012125193105+1.156265354263541*(np.dot(array_x, np.array([[0.35094980518822827, 0.6056110982521007, 0.0538590332844453, 0.03290554527708767, 0.2027897347648666], [0.4735599623139717, 0.9891144323219899, 0.40841497285601924, 0.45989323540782123, 0.9366590270004881], [0.37907823091127557, 0.6456162040216009, 0.9716888835961679, 0.8399710006352176, 0.476188355733127], [0.8869972691686907, 0.5151075594100173, 0.9873527385814369, 0.8430310303929153, 0.033209913263239854], [0.21326730556035578, 0.9090391043435007, 0.6531745104617631, 0.5059858936472499, 0.4454873335076869]])))-(np.dot(array_x, np.array([[0.5191885030260015, 0.13267848421285589, 0.300856266565125, 0.8211329421997583, 0.33715855402172434], [0.8722900098843562, 0.43206182049358244, 0.3574539651116687, 0.862690194660858, 0.5612705919329068], [0.9688083890645097, 0.1695027478560901, 0.01806032666912416, 0.3060625669732322, 0.6251881301455061], [0.385146480837403, 0.2458603327230401, 0.23742900048050897, 0.8048813279104936, 0.832900101053703], [0.46997488867441106, 0.48183365520132926, 0.42523884359014297, 0.2506499106934075, 0.16129552804511849]])))-5.196179081535442), axis=1) |
np.mean(np.square(np.square(8.005543471068147*array_x))+6.468809315898333, axis=1) |
np.sum(np.square(array_x-(np.array(range(1, array_x.shape[1]+1)))*2.1492138686980606)-3.9191976722961517-np.sqrt(abs(array_x))+np.square(array_x)*1.7537952998224011, axis=1) |
np.prod(np.log(abs(-(np.sin(2*np.pi*7.038442042668822+array_x)*5.735834257932109*7.316136760673379+7.026817421648493))), axis=1)+np.sin(2*np.pi*np.prod(np.log(abs(-(np.sin(2*np.pi*1.6096031269855973+array_x)*5.230518901949414*8.478578659399185+4.683040568302681))), axis=1)) |
np.mean(np.log(abs(np.square(10*(10*(-(abs(10*(array_x/1.137705556253489+np.sin(2*np.pi*3.6852067923841116)))))-7.5633624034296565)))), axis=1)+10*(np.sin(2*np.pi*np.mean(np.log(abs(np.square(10*(10*(-(abs(10*(array_x/3.1632494394300448+np.sin(2*np.pi*4.422323469006841)))))-7.019915697581285)))), axis=1))) |
np.mean(10*(abs(6.167873318353254)*np.exp(array_x/7.8228098689978784)), axis=1) |
10*(np.sin(2*np.pi*np.mean(np.sin(2*np.pi*np.sqrt(abs(10*(np.square(np.sin(2*np.pi*6.60178377239877+array_x/np.square(5.912106271888061)+array_x)-array_x*array_x/5.772517163269467))))), axis=1))) |
np.mean(np.sin(2*np.pi*4.327005070789082)+np.square(np.square(array_x+6.563984088573997))+np.log(abs(10*(4.367985603492201))), axis=1)+np.sin(2*np.pi*np.mean(np.sin(2*np.pi*3.4480623652698803)+np.square(np.square(array_x+4.611668034437235))+np.log(abs(10*(8.317610081682547))), axis=1)) |
np.mean(np.cos(2*np.pi*5.538779835864543)+(np.array(range(1, array_x.shape[1]+1)))*np.exp(7.534839758538833)+7.148038869131121*-(array_x)-array_x/2.8750164233683124, axis=1)+np.sin(2*np.pi*np.mean(np.cos(2*np.pi*4.228323117314487)+(np.array(range(1, array_x.shape[1]+1)))*np.exp(3.9499239288696995)+5.485685641243417*-(array_x)-array_x/6.980536802017994, axis=1)) |
np.prod(np.log(abs(5.369598053869928-array_x-10*(9.885074325556824))), axis=1) |
np.mean(10*(1/(3.5933958145821174-array_x)+array_x-2.2455042510077057)+10*(4.509153799882339)-np.square(np.sin(2*np.pi*array_x*3.9770606325883406)), axis=1)+np.sin(2*np.pi*np.mean(10*(1/(6.182133140923636-array_x)+array_x-9.49239557138209)+10*(2.9288189112028866)-np.square(np.sin(2*np.pi*array_x*6.919446804616658)), axis=1)) |
np.mean(np.sqrt(abs(7.538510314104348))/np.square(np.log(abs(np.cos(2*np.pi*array_x)))-np.square((np.array(range(1, array_x.shape[1]+1)))/4.1116422139619555)), axis=1) |
np.mean(np.exp(np.sqrt(abs(8.206129145236334+(np.dot(array_x, np.array([[0.015494683547859989, 0.11371804363321969, 0.3423925889407715, 0.9946299014440818, 0.7405609656867046], [0.27084866088058035, 0.422665244128721, 0.4695828816636791, 0.7036945248425958, 0.5846095430228695], [0.05566518944916066, 0.6312670909772222, 0.2894631812944205, 0.8679689734663886, 0.7122566576568328], [0.6152891127271638, 0.38500828322696834, 0.2348947047829164, 0.9396663021355812, 0.024076227351599533], [0.31083911264920216, 0.5257033618168878, 0.25553056869155133, 0.4628466321967125, 0.12277788431882597]]))))))*4.085517519807173-7.89062328347868-array_x, axis=1)+np.sin(2*np.pi*np.mean(np.exp(np.sqrt(abs(2.942168556626528+(np.dot(array_x, np.array([[0.8869787803514906, 0.05540838463396425, 0.8208380679810879, 0.03692841256060708, 0.8354801364888461], [0.22140643081120404, 0.6800131982044146, 0.16769042089848307, 0.6906524617885553, 0.6070163556210145], [0.40549839899677076, 0.26966883941341957, 0.03545162329738383, 0.6432446590795254, 0.3608468237319321], [0.4119630534414386, 0.7713184481106051, 0.9002061209781224, 0.6244240651096606, 0.7506862518956455], [0.41396990624536123, 0.9064182443207237, 0.21941999434847137, 0.12481728268589043, 0.31125583179432026]]))))))*5.684121101200097-6.492598156605808-array_x, axis=1)) |
np.mean(10*(6.284898692076279-array_x), axis=1) |
np.mean(np.square(10*(array_x-6.269433666878299)*9.570749816955669), axis=1) |
np.mean(np.log(abs(np.sqrt(abs((np.dot(array_x, np.array([[0.4827252637863685, 0.7001886221442193, 0.4821680353170392, 0.30655365781487154, 0.33051919909590055], [0.37732601703037083, 0.4513435839916665, 0.7640748849164758, 0.8315004343230927, 0.2812616399234745], [0.6885241046015461, 0.4384068472611189, 0.1366523988701812, 0.18585133388515707, 0.04754537684899973], [0.11593517471264447, 0.9184521890006839, 0.6973569208673109, 0.44133716285300983, 0.37991833937060926], [0.43039139516045954, 0.5776268348078765, 0.9258777610880217, 0.09634921131056273, 0.5956447560549633]])))+(np.dot(array_x, np.array([[0.7021234442127858, 0.5153054438529798, 0.31235329753640584, 0.08082637521671776, 0.958367469385258], [0.5324454133359197, 0.19129876371322296, 0.9037563158493306, 0.45547544164100484, 0.7567527299739948], [0.055961481534234636, 0.6195539465903674, 0.6308948594267753, 0.3719183373300684, 0.8947337926092592], [0.9750612202023776, 0.7530345354527485, 0.15050970671741581, 0.022945171506289608, 0.03842463586408984], [0.05323683560179426, 0.2522041211346274, 0.8236883015740571, 0.8297574268487259, 0.2035837941866946]])))/2.9414399700301725-1.0371417618798384))))*7.57993368302583/np.exp((np.dot(array_x, np.array([[0.972435957914427, 0.11494248028124243, 0.8736229783634573, 0.6135722694441033, 0.5763028012183582], [0.9418243633882682, 0.4202273644485114, 0.45273285304517197, 0.6059658286467834, 0.3298856057261793], [0.30884645578244496, 0.946240478045399, 0.9682254356654532, 0.6972987605579762, 0.6878975583565791], [0.4316813848626194, 0.07701071068202725, 0.13384458321104153, 0.4410040922261197, 0.48107817397611596], [0.7303218659885417, 0.09967820044595221, 0.19976805344196913, 0.003190421168700386, 0.3704698170429811]]))))+10*(6.760316604103433), axis=1) |
np.mean(abs(np.sin(2*np.pi*array_x))-np.sqrt(abs((np.dot(array_x, np.array([[0.8096793098058002, 0.07969307814105764, 0.9641961708988049, 0.9849510648294758, 0.6042193288101715], [0.12193206011773183, 0.5857483145597252, 0.01822666398613826, 0.9893057854087111, 0.941039600661174], [0.22791618114180057, 0.6244780854404393, 0.7893171067153524, 0.42079094626803104, 0.24797303428306738], [0.12715909743462883, 0.9972463111941723, 0.7686886161470204, 0.8304617095272316, 0.24866387853811944], [0.6897805246744557, 0.2462426500761623, 0.9353044043307102, 0.013488391136044386, 0.4461041056809246]])))*np.sqrt(abs(array_x*2.582541800976468))+np.sin(2*np.pi*np.cos(2*np.pi*4.715221776454478)))), axis=1)+10*(np.sin(2*np.pi*np.mean(abs(np.sin(2*np.pi*array_x))-np.sqrt(abs((np.dot(array_x, np.array([[0.8568898036551339, 0.8977014644723013, 0.5100423188800552, 0.8228550801946768, 0.42293342201882955], [0.11308508504792647, 0.8846580132575523, 0.2833418826780584, 0.13892093183771415, 0.8982988273250295], [0.27479748313878016, 0.9434413282110116, 0.42714723488969464, 0.7494426223059713, 0.8146849064508783], [0.5958984894193377, 0.057917635430353775, 0.7536416086118574, 0.002495339101205807, 0.8587516231270435], [0.32045673772868066, 0.8494921160859158, 0.20841792208069965, 0.7984563308289577, 0.9907389375156629]])))*np.sqrt(abs(array_x*9.679104368812535))+np.sin(2*np.pi*np.cos(2*np.pi*3.5451814619761457)))), axis=1))) |
np.mean(np.square(6.025392551151339-9.009566856191427-array_x*7.331701733613326/1.6351249458014596), axis=1) |
np.mean(np.cos(2*np.pi*5.157420462004223)+(np.dot(array_x, np.array([[0.3853475030336645, 0.6034462462642053, 0.7813953965198582, 0.4960841302142446, 0.4232307047096079], [0.8569037192348191, 0.7022693860721441, 0.5734427390909126, 0.30707300688748607, 0.055057688972689256], [0.6372631071838644, 0.4486865491491372, 0.2715342573627959, 0.5228739208595997, 0.13801419370289547], [0.03678147127260212, 0.861807093308635, 0.1809502937025712, 0.20635604150463482, 0.17478778270941397], [0.13837836810423043, 0.45788509082181006, 0.8477349694909737, 0.8957037664107096, 0.4916717719892679]])))*5.227105813909837, axis=1) |
np.mean(np.round(4.502860456037194-np.sin(2*np.pi*np.square(5.249628810015334)*array_x*6.407921032305663)*6.598797237501435*array_x+4.051343730794185), axis=1) |
10*(np.cos(2*np.pi*np.exp(np.amax(7.1921918886198615-1/(array_x), axis=1))))+np.sin(2*np.pi*10*(np.cos(2*np.pi*np.exp(np.amax(1.887940640796106-1/(array_x), axis=1))))) |
np.mean(np.square(-(array_x+np.round(7.893221573110327))), axis=1) |
np.mean(8.409963906611083-10*(np.sqrt(abs(array_x))), axis=1) |
np.mean(np.square(np.round(np.exp(np.exp(array_x))+7.3441835731321925-3.473862140049911)+array_x/np.round(-(8.280726223814478))-7.896426859005614+2.6690330400365223), axis=1) |
np.mean(np.square(-(np.sqrt(abs(3.160493062985747))))+array_x/6.402396442193594+np.sin(2*np.pi*abs(9.09659863837618/np.sin(2*np.pi*np.exp(array_x)))), axis=1)+10*(np.sin(2*np.pi*np.mean(np.square(-(np.sqrt(abs(5.409971604220807))))+array_x/6.350410126613206+np.sin(2*np.pi*abs(5.766694484081386/np.sin(2*np.pi*np.exp(array_x)))), axis=1))) |
np.mean(5.439075485359868-array_x*1.5704518534100176*7.494696404234706, axis=1) |
np.mean(1/((np.array(range(1, array_x.shape[1]+1)))*array_x-2.8036955773152252+5.8027252405181935*(np.array(range(1, array_x.shape[1]+1)))*array_x+1.842492894960582), axis=1) |
np.mean(10*(7.007138180174674*(np.dot(array_x, np.array([[0.30933090688071807, 0.3643856703108376, 0.544920747107368, 0.9692490992033872, 0.4437306551642026], [0.23470001496334647, 0.6985633940797312, 0.33557736948965233, 0.4743672598129727, 0.2465350646475707], [0.47909302240389895, 0.014633040848220924, 0.9499356416746005, 0.951610293695254, 0.5727963103854014], [0.48077917087506805, 0.20370446303885892, 0.32060810756759894, 0.05776937940257232, 0.2430348184264396], [0.16996110428720346, 0.6442087659742446, 0.7959431203659031, 0.43588063323401305, 0.4140509206760372]])))-(np.array(range(1, array_x.shape[1]+1)))*4.988138691163185*(np.dot(array_x, np.array([[0.539722048884291, 0.3385111186303452, 0.5774240083319169, 0.09551366205179879, 0.2432770761402353], [0.4951867277857148, 0.30382343336545425, 0.9592406518009129, 0.7049187966892384, 0.4652623234685098], [0.42944613363349027, 0.1164325449079805, 0.37484899465325927, 0.5233723320273864, 0.08450274496595911], [0.26072109363829765, 0.32908105971846957, 0.32700396157801503, 0.15598815758751472, 0.9476516636716844], [0.5091850909952685, 0.9826912005461517, 0.40495312410722006, 0.4824672577946766, 0.09122505691598837]])))-np.cumsum(np.log(abs(array_x-(np.array(range(1, array_x.shape[1]+1)))-6.02548300092653)), axis=1)-8.221382401050516), axis=1) |
-(np.mean(np.square(np.exp((np.dot(array_x, np.array([[0.3706859241713537, 0.662699419666347, 0.43220629826872714, 0.4211127568181756, 0.3269868788479997], [0.26770546956877694, 0.082974959494313, 0.2384531233490499, 0.2997276439468187, 0.1230172762329047], [0.6838514689430379, 0.6894013869548491, 0.7066962155221554, 0.9562321139006507, 0.6698782709978307], [0.7343489848704724, 0.3233701598397378, 0.06365340421420873, 0.9910817251255227, 0.06833210827816427], [0.7340137235332254, 0.0065082333198215325, 0.2076891665653694, 0.3156090769556398, 0.9078212495239739]]))))*(np.dot(array_x, np.array([[0.4735379077122226, 0.8585783150541616, 0.03606748972840235, 0.3921543723806772, 0.7219875640337495], [0.23907896675839424, 0.037734782208862505, 0.7588571614392405, 0.8943759509693195, 0.9338107557785387], [0.29778745891436553, 0.49554639946567614, 0.43917980364640985, 0.8075872599936998, 0.1878841870053325], [0.1145333555893917, 0.7442405400798231, 0.028353871957724985, 0.8933166020243425, 0.37562103635208344], [0.4970187325809393, 0.8025669494427535, 0.1908773745906288, 0.5031423743672978, 0.7859389640506895]])))+4.260129956654086), axis=1)) |
np.mean(4.976761188546605+(np.dot(array_x, np.array([[0.4424538118168505, 0.9397219920025287, 0.9822777700144905, 0.9711921575156035, 0.5369649655369672], [0.5763404044487762, 0.43488206517503225, 0.08906013170002514, 0.790437919606869, 0.1339565043912052], [0.8432449912840643, 0.22818849081370352, 0.49057418063219227, 0.6300330078514679, 0.620240632068056], [0.3370262445550949, 0.2543328240593863, 0.4916088804252531, 0.0007584603123726996, 0.22293858739989592], [0.8276660557259251, 0.412485915780915, 0.4676816783442277, 0.25100778584992267, 0.346068613375899]])))*6.563807317291152-np.sqrt(abs(array_x-6.563593705491195)), axis=1) |
np.mean(10*(10*(np.sqrt(abs(array_x))))-5.350704612558122*np.square(np.square(array_x))-2.7375437404890994, axis=1) |
np.mean(5.199179405396836*np.square(3.3876721624329584)-array_x+10*(1.808431252686337+array_x), axis=1)+np.sin(2*np.pi*np.mean(5.4665359572102385*np.square(9.750620963905499)-array_x+10*(6.910423694306915+array_x), axis=1)) |
np.mean(5.633734587935141*array_x/3.362218828862244/6.370087068403427/np.exp(9.086423559041942)-np.exp(8.607193398078042-array_x), axis=1) |
np.sqrt(abs(np.exp(np.sum(1/(array_x+1.9331780419858895)+1.0227358671290656, axis=1)))) |
np.mean(np.square(3.1288065692373763)*abs(array_x+np.sqrt(abs(8.68653658137456))), axis=1) |
np.amax(np.square(5.023517406241957+np.sqrt(abs((np.dot(array_x, np.array([[0.7575112058302376, 0.0371920891782217, 0.7217534025115273, 0.048383996437294186, 0.5304832638280726], [0.42885809234194594, 0.1375254035021839, 0.3549407717325024, 0.01934093702032491, 0.7796169925418324], [0.7427548088092109, 0.6086304001527307, 0.2908600499999, 0.718628334127852, 0.8742695428173226], [0.4263384003406583, 0.7132916506820375, 0.784588923590287, 0.02225304746365786, 0.3136610291212465], [0.5533325745563444, 0.5013964601539326, 0.7192547579448559, 0.17361309083437038, 0.8919736801760632]])))))-np.sin(2*np.pi*7.197905358570742-array_x)), axis=1) |
np.mean(10*(array_x)-np.cos(2*np.pi*9.012204849343911)+8.544831900564716-np.square(array_x), axis=1) |
np.sin(2*np.pi*np.log(abs(np.mean(3.7990863022412906+np.cos(2*np.pi*(np.dot(array_x, np.array([[0.09921871598068532, 0.9919630640142528, 0.9255286928696596, 0.15301472031006036, 0.25278956865595936], [0.3524948981999956, 0.8436307185973019, 0.6456209119425664, 0.4541950088946155, 0.8801527475269937], [0.5040842590343186, 0.7140909003574288, 0.36079528755993295, 0.1613572342512396, 0.9370616877150508], [0.626557579530416, 0.7654769773446697, 0.9091551009500692, 0.5471717620412823, 0.3973898941633438], [0.17442235107218196, 0.21791826729097308, 0.6582127189421351, 0.2560941621680666, 0.996103521752083]])))), axis=1))))*np.square(10*(np.mean(np.cumsum(9.619437016569922-(np.dot(array_x, np.array([[0.9504735485844119, 0.11713738971290077, 0.6570739992695648, 0.10368563810402609, 0.6327580262596193], [0.1147299295992853, 0.17896665385200805, 0.6881819694541597, 0.6058086440976937, 0.9193220185925925], [0.31816034752913047, 0.5570917332808134, 0.015800148378180556, 0.22150136148345545, 0.9825630143811972], [0.17370081229305945, 0.14490015551137592, 0.7548628924500645, 0.7396857032282318, 0.7226240113073056], [0.6226891789369361, 0.10259916464982632, 0.1346785076203436, 0.027463112045209792, 0.28126863126177415]])))+7.745320304440859, axis=1), axis=1))) |
np.mean(np.sqrt(abs(np.sqrt(abs(10*(np.sqrt(abs(array_x+np.sqrt(abs(array_x+2.710466508411023)))))))*2.264598663235525))+9.326651340828331*array_x-3.8868685181216156, axis=1) |
np.cos(2*np.pi*abs(4.179945225884179)/np.log(abs(np.amax(array_x-5.319056558675404-(np.dot(array_x, np.array([[0.8039058589296667, 0.6334636254090028, 0.018051925374752198, 0.5187247491675823, 0.748554250803355], [0.7183708994714567, 0.5852017368808423, 0.23202846980832748, 0.0525155172417221, 0.13839173139181926], [0.13973209915239237, 0.5552511064957071, 0.034901228837666554, 0.12531969286454792, 0.30275511024747326], [0.12515885616114997, 0.365393548752016, 0.6048042935565768, 0.5117163402063977, 0.7811820030129231], [0.9695247262773328, 0.7550534406590774, 0.6042266881892724, 0.20628941730251604, 0.31150296215093176]]))), axis=1)))+10*(np.sqrt(abs(10*(3.5006631536452035)))))+10*(np.sin(2*np.pi*np.cos(2*np.pi*abs(7.00833220625513)/np.log(abs(np.amax(array_x-1.9133223995016695-(np.dot(array_x, np.array([[0.0028071339395217, 0.07388287466779908, 0.5150533953721792, 0.13486229078324719, 0.6647549028720495], [0.7631768639647104, 0.5280315512086539, 0.24685622904914073, 0.26933039680971904, 0.6811745004995764], [0.9650229964824119, 0.4664497223983146, 0.29822409053352217, 0.5596316957828983, 0.7334113954086487], [0.6792867696017999, 0.27010350966942087, 0.16272665235636508, 0.3690500979099105, 0.1824926160481044], [0.20737133368694716, 0.22191012275598143, 0.5262820099399671, 0.7862661718843613, 0.5081739433664492]]))), axis=1)))+10*(np.sqrt(abs(10*(3.185974597199631))))))) |