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np.sum(np.cumsum(3.3020391588667524+array_x, axis=1), axis=1) |
np.square(9.903924958953844)*np.cos(2*np.pi*np.sum(array_x/3.4002804436283562, axis=1)) |
np.mean(8.803615605336374-np.square(np.round(array_x-10*(array_x))), axis=1)+np.sin(2*np.pi*np.mean(3.1626726739850897-np.square(np.round(array_x-10*(array_x))), axis=1)) |
np.amax(np.exp(np.round(3.498087889978326-np.square(array_x)+array_x*8.970933243518235)), axis=1) |
np.mean(np.exp(np.sin(2*np.pi*array_x))/9.909929291905916+array_x/1.3132379823109668-7.018371285394856*(np.dot(array_x, np.array([[0.49219509838389575, 0.03331812292745884, 0.2999335899535499, 0.8504641523808966, 0.26775722540913993, 0.7669900607278105, 0.1838528931244704, 0.3399260080361777, 0.4476653371276207, 0.34378886675200926], [0.39958765801868046, 0.01290235507692128, 0.23074042770842007, 0.4301188876527794, 0.1389236712731512, 0.4258334019322081, 0.46125391994179055, 0.18673437663088688, 0.17161571228865669, 0.18112327865488453], [0.20324296533398967, 0.6124777210924983, 0.16300274664063608, 0.5971548262409707, 0.44844367467397794, 0.53748746609915, 0.5124008873322939, 0.8581739526200638, 0.3985888913734933, 0.6783417328582545], [0.35776934335009636, 0.06551952350939061, 0.9582984017729586, 0.9588067217617747, 0.050072668741635296, 0.6912154779207506, 0.664585820762998, 0.5311941279631206, 0.259692666303713, 0.9922495702596764], [0.5490148256219471, 0.9681077974420806, 0.3241640696339475, 0.9344430573250512, 0.5662768946904787, 0.22011986636485048, 0.7193589149758799, 0.8448359054368747, 0.0697980480264041, 0.07904884717388627], [0.2802867338541166, 0.5554927389344929, 0.3047918813877335, 0.13124066236757592, 0.11987738595727959, 0.7754211367360591, 0.32262073266494995, 0.17339013310964624, 0.8564087159879629, 0.5496888625647572], [0.09907820633845876, 0.2974748461572204, 0.8080423165576266, 0.8627966232948422, 0.22635681954986142, 0.9984460126690307, 0.008421344309575307, 0.18883062106371562, 0.2328706028931471, 0.056879928252364986], [0.49791017919545033, 0.7816913500245161, 0.8866098927743623, 0.4646080026926165, 0.9668576772510582, 0.9365433149099515, 0.3456927709658312, 0.8257995071748278, 0.9712724789888318, 0.06691008268585363], [0.074952312908114, 0.5945653978612816, 0.5317662482152347, 0.6985689249778406, 0.8673909216289182, 0.19767750792648453, 0.07189438164144513, 0.05216126404881283, 0.7573546248321776, 0.2058483213343294], [0.3890549701016536, 0.824470309626539, 0.7374112446025602, 0.03505112992390269, 0.9926300189341388, 0.9076564999974248, 0.5979721675660349, 0.36751786787667373, 0.07050460750420284, 0.32350721732721854]])))/8.439543503740767*np.round(4.724661941619377), axis=1) |
np.mean(8.481172308587414-array_x/np.sin(2*np.pi*1.933002098362349+array_x)*array_x, axis=1) |
np.mean(-(4.677723491895431/6.303743306805377+array_x/6.173004432817823*5.03800633058034), axis=1)+10*(np.sin(2*np.pi*np.mean(-(2.3085012671293037/9.149632322835751+array_x/7.8725484661396345*9.982743631956414), axis=1))) |
np.prod(3.3599132878302456+array_x, axis=1)/np.cos(2*np.pi*np.sin(2*np.pi*5.375738572170046)) |
np.sum(np.exp(4.901990349978295-array_x), axis=1) |
np.mean(9.854133192819173/np.exp(3.293066173778312*array_x), axis=1)+np.sin(2*np.pi*np.mean(5.6012027706707705/np.exp(7.138338745027905*array_x), axis=1)) |
np.mean(np.exp(np.square(array_x)-5.770858273962505)+9.782982293016094+(np.dot(array_x, np.array([[0.4191027374713918, 0.22636750542270356, 0.21173460366397312, 0.25166143398105423, 0.552156560395505, 0.28162003684560566, 0.9907696130758, 0.09764863561798676, 0.12108819693550976, 0.13215216316727874], [0.6995945691422384, 0.533733202201171, 0.10382710031796805, 0.21506589851415836, 0.4189104959668901, 0.7165429931341867, 0.6421025269537887, 0.028122475825211213, 0.7390523102956359, 0.02164216920893891], [0.7199197610122221, 0.9176979849632576, 0.007469133887642254, 0.9156352544394134, 0.4209985419709489, 0.10117191477692067, 0.06231688433043936, 0.30838761059999653, 0.13228393865284827, 0.6399242748256562], [0.8721975579268358, 0.6429145399876124, 0.4902617036787803, 0.45131636007829046, 0.6839384861234992, 0.5023879519696329, 0.8741665086441218, 0.08291812200245285, 0.2613258676626319, 0.5962191246921549], [0.5166314801364615, 0.485933714351072, 0.5655979810957369, 0.6796340044193132, 0.4866274565588209, 0.8023686285718614, 0.5548545318195962, 0.2685913349738691, 0.9412990838526498, 0.4466697147055251], [0.9161243936838256, 0.17165441354670374, 0.9460686813096907, 0.14475413452898656, 0.8236402480743182, 0.8160704770967494, 0.9186205986044754, 0.857839529251203, 0.044064259398089, 0.13003538379581925], [0.23221701223024416, 0.12465591144761168, 0.7223162764932769, 0.34826199801714974, 0.713594826310417, 0.0870319693870748, 0.666574794966136, 0.02994829712306757, 0.4920949086190436, 0.46522070761917156], [0.4110829251936422, 0.2781014928126444, 0.26371728780228076, 0.6611678727678446, 0.8438245814364114, 0.8903577486095511, 0.04045770214257782, 0.8874104980195047, 0.045787322626112514, 0.8904578902476256], [0.4072850257959594, 0.9331832287009753, 0.9619211385398146, 0.31355842223608654, 0.9213715510698844, 0.3503896977778749, 0.6315789628303381, 0.32225003487502246, 0.49464014047271254, 0.7323930529003798], [0.2678240402970097, 0.8639978310888654, 0.7732598983699459, 0.3179420529166137, 0.7493510235935698, 0.6834748852136782, 0.9309910016698195, 0.6214736721396737, 0.006298177657981019, 0.913019437966309]])))*5.737877598176257+array_x, axis=1) |
1/(np.sqrt(abs(np.prod(array_x*7.529156887345826, axis=1)-1/(np.exp(5.334180396485211)))))+np.sin(2*np.pi*1/(np.sqrt(abs(np.prod(array_x*1.7477437767125523, axis=1)-1/(np.exp(7.570340535548954)))))) |
np.mean(array_x+7.632383901333431/7.052197662127348/np.log(abs(np.cos(2*np.pi*array_x+5.249141982887315))), axis=1)+10*(np.sin(2*np.pi*np.mean(array_x+2.8292878392889893/8.906847897484454/np.log(abs(np.cos(2*np.pi*array_x+8.076130495889675))), axis=1))) |
np.mean(array_x-9.027410828597082+3.0202126436259396-array_x*np.square(5.592591537796569), axis=1) |
np.mean(9.836392624774264*array_x*7.533091329697363+3.631659447470321, axis=1) |
np.mean(array_x-3.569520437300104+abs(np.square(np.round(8.733979290608817)))*np.cos(2*np.pi*7.055732533783772+array_x+3.009871491916445), axis=1) |
np.mean(np.exp(np.sqrt(abs(9.198849738830813)))*np.log(abs(6.308924457027132/np.cos(2*np.pi*np.sqrt(abs(array_x))))), axis=1) |
np.mean(10*(2.89063367953474-np.cos(2*np.pi*1/(np.log(abs(array_x))))), axis=1) |
1/(np.sqrt(abs(6.768829381438292)))/5.49398755303504-np.sum(np.sin(2*np.pi*6.516346038152674+array_x), axis=1)+7.349396188636382*array_x[:,0]+np.sin(2*np.pi*1/(np.sqrt(abs(5.1177214205669115)))/4.7641958455798825-np.sum(np.sin(2*np.pi*1.8162073783047497+array_x), axis=1)+8.520868976458338*array_x[:,0]) |
np.mean(np.square(np.round(array_x+np.sqrt(abs(5.833960999735595)))-np.cumsum(np.cos(2*np.pi*np.exp(8.069268249362032-array_x)), axis=1)), axis=1) |
9.23259081388416-np.prod(3.114365462806046+array_x, axis=1) |
np.mean(5.455916653686758/4.180081127204293-array_x*1.9625227521092863-10*(array_x), axis=1) |
np.sum(np.sqrt(abs(np.log(abs(1/(np.sqrt(abs(1.7385036627461463)))))-(np.dot(array_x, np.array([[0.8520024311202309, 0.6437428541782977, 0.42538058670959833, 0.9628891265827869, 0.7205853412203445, 0.04688110492329878, 0.14754019878287972, 0.10573371742371318, 0.27847564152256055, 0.5274880571192054], [0.020082452014557828, 0.04334774218490656, 0.2038761390330428, 0.5872659214444285, 0.9352536497345649, 0.37529170901723663, 0.050587049855995936, 0.9403393677648436, 0.4199185542348648, 0.6392506779031162], [0.6657030778498022, 0.24694704460736616, 0.9582313833333582, 0.6613356504353426, 0.564927975248587, 0.2896326436986588, 0.9318918623537655, 0.8458832293796879, 0.23720807976457836, 0.3653959437381279], [0.0660758115700748, 0.9453549955461512, 0.02607777527669808, 0.4885372432482863, 0.6860536136225727, 0.4971617603360654, 0.8266022710711931, 0.18158403718297522, 0.7241317327784291, 0.9725076249329759], [0.39059749731497473, 0.9741771405557997, 0.3681265910280701, 0.2707999688272168, 0.44530545023514123, 0.4941048427893807, 0.1377124450524364, 0.32839867127251277, 0.4729258605372446, 0.7343231581126034], [0.6999243942833918, 0.919836850765637, 0.4014643101177453, 0.44704711147159126, 0.6320758482998373, 0.5175687106967022, 0.24228424554355021, 0.7819739915312066, 0.02703024432069545, 0.40004812384486765], [0.2558820178122929, 0.9731427532433696, 0.3798669853540001, 0.1019854973886708, 0.32442426553883585, 0.824573375211157, 0.8321115616588816, 0.9076872747759942, 0.14150585113248604, 0.3762189721014255], [0.12317866573159575, 0.06659903873257689, 0.27225926940203526, 0.28035199533463884, 0.8195847611779856, 0.4339112143427525, 0.712069979459939, 0.39674120832229665, 0.513839553358484, 0.24937309065521718], [0.45221544000865876, 0.10318513434376575, 0.443376552647052, 0.426451171639064, 0.47114284341249113, 0.8195629340138091, 0.020481417822017733, 0.6455554096552775, 0.9003505071685883, 0.6469203760406678], [0.7895384246040217, 0.8390592930391065, 0.7713559652540238, 0.14052815971023913, 0.24773585625363925, 0.9495621050812951, 0.09014886379515796, 0.2816469347516123, 0.7231061038035131, 0.7741666034041845]]))))), axis=1) |
np.mean(9.362146175418383*array_x+np.cos(2*np.pi*array_x)-np.exp(1.0771561442897089)*(np.dot(array_x, np.array([[0.992084039040282, 0.7693128756046984, 0.9863337917955013, 0.37251560715163445, 0.5246317395548302, 0.9418155014439568, 0.5967117510193779, 0.4257455511292825, 0.6840081408226009, 0.050256919752953766], [0.7130403896445424, 0.726009706109431, 0.3951054872154034, 0.643311745155088, 0.2298528493553137, 0.6103702474038987, 0.14760329711346554, 0.051969357780805026, 0.02031204387915697, 0.9276093751458884], [0.06521920001722914, 0.2512514308900968, 0.3692944588303687, 0.026387066508531287, 0.7251807467167045, 0.5829051947166223, 0.1512557934857779, 0.5575817467361719, 0.5832183672831711, 0.4713167006735398], [0.5629425024038309, 0.6667561645715038, 0.7640674841362639, 0.3872574020832996, 0.44210288781942353, 0.95242130979131, 0.01727633954548813, 0.7332576548433513, 0.9421644392615337, 0.35138806307487025], [0.946973082151875, 0.5917301164102801, 0.6720763292474113, 0.3882381016565898, 0.6885757724330589, 0.8744128585369563, 0.7201774220719563, 0.22923231946831923, 0.5559966789497071, 0.1763940822566169], [0.035826716760737454, 0.8951602929235035, 0.42537623369922406, 0.7349030384422626, 0.5226886577758066, 0.8964541684828274, 0.3002060360462151, 0.7171060671119622, 0.7075494339692631, 0.22731347843495509], [0.1063030764387094, 0.8681476910598233, 0.7023611852830857, 0.08408822183572162, 0.0066487200222875575, 0.9115494101646838, 0.34543559376812605, 0.21155569972833488, 0.035447320181378084, 0.5715435364605617], [0.20773821386579472, 0.8711711652377852, 0.11053369074007979, 0.8399468329593999, 0.2871829931735451, 0.5655178099458522, 0.6510497852224861, 0.7054228017893808, 0.41116338206643155, 0.5193846416393011], [0.031876647356989474, 0.9760187648811667, 0.19630263592510244, 0.6141812017621058, 0.6432142059976751, 0.746750636495534, 0.13030390390070634, 0.4821567081000038, 0.800186162288507, 0.7065127365214906], [0.13430655306225703, 0.46105416828351464, 0.609379067031142, 0.4022351764912543, 0.3339628026621332, 0.6542525420984951, 0.1195120899686134, 0.056002659331660265, 0.8732030857867559, 0.7140993659106042]]))), axis=1)+10*(np.sin(2*np.pi*np.mean(2.1934052982574213*array_x+np.cos(2*np.pi*array_x)-np.exp(3.180658286576595)*(np.dot(array_x, np.array([[0.31997525293944074, 0.45821615229393364, 0.8799810074836393, 0.8462757008607621, 0.9144579115603862, 0.9857975326291647, 0.6444640914508761, 0.16923747039287174, 0.038007099029904734, 0.42282893078790595], [0.8418033746396724, 0.6488373717747159, 0.7549495084930312, 0.9308703687127213, 0.5616789158956028, 0.035891137666757555, 0.7395537460154706, 0.5028044376516109, 0.7572626146164295, 0.2188900591593813], [0.11764357251185542, 0.3184205129451291, 0.5465312000977235, 0.750221885430352, 0.6783522085221624, 0.31656263968707443, 0.8647133055775097, 0.4501121470232582, 0.9621043452802961, 0.5037096311219632], [0.33546322954834673, 0.4825937619767674, 0.13654085936952165, 0.9294630763576415, 0.8902922889592135, 0.31145335608879476, 0.6710355978839034, 0.8772206495952715, 0.7711685260906143, 0.6620783824749626], [0.36684103754081576, 0.5384593508214931, 0.9222419258341972, 0.35533779569923585, 0.1080241107477603, 0.8333964202139192, 0.6526494025849436, 0.9373244513334293, 0.12127337508874292, 0.7208591637512747], [0.7003369764172117, 0.990883363276194, 0.8627972168840469, 0.7638454735867913, 0.12200211228498192, 0.5869003551781781, 0.5605767624058836, 0.4459978813260056, 0.6157352492525988, 0.24211513222814884], [0.9341506116148256, 0.7817901766335887, 0.1326967341104176, 0.9736873725609564, 0.8812358955128904, 0.21826100303452667, 0.18532575666225892, 0.6865603454080926, 0.591618396414665, 0.8925763209629128], [0.6790730796908931, 0.7121814451922296, 0.8399043539176246, 0.18503789370081847, 0.6944314572550159, 0.09984963891570608, 0.40860870366809654, 0.3294395081520156, 0.2213544367150555, 0.9970082299713484], [0.8416149464968916, 0.7400135021989624, 0.643285098944051, 0.2733044895368103, 0.10529234713784719, 0.010325179747078472, 0.8360269577058702, 0.9836053427316362, 0.8562864999310672, 0.8737186457326644], [0.7477655263733216, 0.3101720272339473, 0.2443922462868724, 0.6316175976510268, 0.2589921652132682, 0.5362727568929163, 0.650442019918584, 0.16218503881204194, 0.7167686568453886, 0.49088628394213285]]))), axis=1))) |
np.mean(np.exp(array_x+(np.array(range(1, array_x.shape[1]+1)))/5.217257266538393+6.549129985087228), axis=1) |
np.mean(8.483108186153213+(np.dot(array_x, np.array([[0.9268667508303039, 0.5563498684191126, 0.6662984978056699, 0.9179424046710715, 0.9579399594359151, 0.23475943793027465, 0.7658203146444001, 0.5821726924018913, 0.1325457297329723, 0.8641639197605427], [0.9712924677086544, 0.8663271678559079, 0.45248465478670974, 0.03096214182203627, 0.6121837000305113, 0.9734938484936366, 0.22198442395518603, 0.45212518681243563, 0.9311161233706726, 0.16055952158332898], [0.5734498176626207, 0.1499602922187142, 0.46493029699953903, 0.0325085549552403, 0.4962801895141207, 0.9311854208641728, 0.4736472696332893, 0.229168382066687, 0.5513825622023997, 0.06583121254867752], [0.9551565455374155, 0.1999486087686696, 0.3895274165343351, 0.2038971193909842, 0.03813528120989362, 0.4742596445230226, 0.16890254893361356, 0.8322181730601859, 0.7900591125814019, 0.03194638546571027], [0.9332632715364251, 0.28401026108192184, 0.24469167426794147, 0.5534572098952792, 0.22626824356474162, 0.7789612911222993, 0.5168652550924292, 0.38895916225037075, 0.13912198004823662, 0.5779002027018973], [0.6399749728567558, 0.729403636012326, 0.741124573644797, 0.61257014148902, 0.3775757048913203, 0.954187502393143, 0.7073196320866653, 0.1805815927164064, 0.3822545808640989, 0.29458965723715635], [0.7170272629198531, 0.4172854252288217, 0.3399551336515658, 0.6565955636734166, 0.8121281059860116, 0.2730729817721185, 0.30670692198086, 0.15859876102401138, 0.38757497907105287, 0.25557453591966306], [0.9910348412828623, 0.6440020670287007, 0.712796127629723, 0.8565143084305563, 0.0813508208081899, 0.13336838531629358, 0.3586090249905709, 0.5772775178529911, 0.12063987568598389, 0.1611437745018589], [0.08153107661280912, 0.530688982754052, 0.5180604616268435, 0.25099467915932416, 0.482028291707716, 0.39959134450943823, 0.6844526205963525, 0.5852162684504336, 0.1995728523116398, 0.6660356955332501], [0.024540889203203964, 0.25710381343851796, 0.3663944624629073, 0.8246364150104133, 0.9959853317807552, 0.6648037254067944, 0.44345373743318484, 0.7694357307894201, 0.4768755575397482, 0.6113726662013726]])))*7.098064058551325+9.201944525431129*array_x, axis=1) |
np.round(np.square(np.mean(np.square(8.708928478624212*array_x)+3.5040173869903417, axis=1))) |
np.round(np.mean(array_x-array_x*np.sqrt(abs(4.500292629250726))*np.square(8.494996686021102)-array_x-4.232722532469602*array_x-4.277777571576132+array_x, axis=1)) |
np.sin(2*np.pi*np.sum(np.cos(2*np.pi*np.square(abs(8.13716237535261))*9.249635116231534-array_x), axis=1))+10*(np.sin(2*np.pi*np.sin(2*np.pi*np.sum(np.cos(2*np.pi*np.square(abs(1.743407564202879))*8.430743201905942-array_x), axis=1)))) |
np.exp(np.sum(np.round(np.sqrt(abs(1.929368044643099)))-array_x, axis=1)) |
np.square(np.mean(array_x-(np.array(range(1, array_x.shape[1]+1))), axis=1))+np.sqrt(abs(np.sin(2*np.pi*9.36002629248441)))+np.sin(2*np.pi*np.square(np.mean(array_x-(np.array(range(1, array_x.shape[1]+1))), axis=1))+np.sqrt(abs(np.sin(2*np.pi*5.121068293938434)))) |
abs(10*(np.amax(7.803437264138106-2.4082159698932015*array_x, axis=1))-np.log(abs(9.988257638409445))+np.exp(2.8609161147540583)) |
np.sqrt(abs(np.square(np.square(abs(np.sum(3.858504702634457-array_x*np.exp(array_x), axis=1))))-np.prod(array_x, axis=1))) |
np.mean(-(np.sqrt(abs(array_x*np.log(abs(2.555041131316618))*np.sqrt(abs(np.sin(2*np.pi*1.0819671776780413)))-np.square(np.exp(5.721625766191547-array_x))))), axis=1)+10*(np.sin(2*np.pi*np.mean(-(np.sqrt(abs(array_x*np.log(abs(8.820364853813112))*np.sqrt(abs(np.sin(2*np.pi*5.9960472348548945)))-np.square(np.exp(7.370734763305403-array_x))))), axis=1))) |
np.round(np.mean(np.exp(2.785771738732762)*array_x-np.sqrt(abs(array_x))+1.4637563266163134+4.603814053697124, axis=1)) |
np.mean(abs(np.exp(9.854669253059345+np.square(array_x)-np.sqrt(abs(1.2703961085326396+2.315852348753414*array_x))/9.322871986594956+array_x+array_x)), axis=1) |
np.mean(10*(np.sqrt(abs(np.square(6.765744839085895)-10*(1.9567544225646154)-array_x+(np.dot(array_x, np.array([[0.07542425879374648, 0.5363501290651709, 0.2781276129472331, 0.21357044500322964, 0.9199392006298963, 0.31830576797298527, 0.4580898596816916, 0.7466164750789885, 0.4094621867817484, 0.961459443712162], [0.002162169427798677, 0.18383853184165877, 0.03867875273179511, 0.3174564342659393, 0.9668941712056035, 0.6323900721472365, 0.8213982472092147, 0.89356840013776, 0.31098685079412647, 0.1800178008526212], [0.36440804339085997, 0.6859788032914956, 0.4513584050653463, 0.2805273374864492, 0.1866787757551297, 0.25277274642211434, 0.8789268069439137, 0.47842759269401824, 0.8159094328178245, 0.4925980603999003], [0.16910118759914594, 0.8049435518306197, 0.9005566512328189, 0.42168738415564644, 0.0299145941710095, 0.4381915219280258, 0.4917425060995212, 0.5089908085753815, 0.6508136213370886, 0.13454479451095347], [0.22317183723425582, 0.5860427133288514, 0.5255300986170865, 0.8751784910531389, 0.5094229428918701, 0.204676662485058, 0.5687821167789925, 0.9853272786396713, 0.47704501479865824, 0.6480536221368064], [0.4902466630525243, 0.41661805377964023, 0.19514596952739482, 0.03018928448931002, 0.44311397707876954, 0.0793652913767785, 0.8571512112934445, 0.5463337734842094, 0.1231454666487608, 0.18217116375082543], [0.8921392995470285, 0.7649384035104541, 0.6946622458613587, 0.48479868098358836, 0.3993625240615949, 0.3731148376833403, 0.8488728411870963, 0.14154978906412874, 0.8833246727221191, 0.9084184014569505], [0.8738815247488319, 0.34495118119264556, 0.247531988297216, 0.5660419920633818, 0.4101952566978787, 0.8633232625837857, 0.1471148343680918, 0.3347227366103094, 0.6042482985020191, 0.5295242452035869], [0.8280811366716117, 0.682103739921193, 0.7217756345760841, 0.4737123957157985, 0.1804321531569606, 0.23643876631578897, 0.7192653843661819, 0.7227184398408869, 0.47937165125879233, 0.9775182794069955], [0.5992042577176022, 0.36732855347279925, 0.023994739553358735, 0.43591948194018004, 0.9897831251634105, 0.00775347931556758, 0.4073352413749146, 0.37913792349185915, 0.007331257442599992, 0.3270731727682781]])))*6.356255227206671))), axis=1) |
abs(1.630307236545881/2.7773345384741455+np.sqrt(abs(np.sum(np.exp(-(array_x)), axis=1))))+10*(np.sin(2*np.pi*abs(9.434665546676426/4.966759258335876+np.sqrt(abs(np.sum(np.exp(-(array_x)), axis=1)))))) |
np.mean(np.sqrt(abs(1.4658772365402974))-6.095999875366142*np.cos(2*np.pi*(np.array(range(1, array_x.shape[1]+1)))*array_x)+6.2652575036940386-5.790937412253301/np.sin(2*np.pi*np.exp(2.4161466039881243)-np.exp((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.mean(np.square(abs((np.dot(array_x, np.array([[0.030293377072460936, 0.5441973221489244, 0.9959212202564672, 0.7161092090903407, 0.5272629460481493, 0.7107298572634467, 0.22647068579454277, 0.6988818476568437, 0.6788661717967646, 0.8474368232267604], [0.5347097123640238, 0.12826967107146625, 0.8636749521856482, 0.12326677741187264, 0.3612786587362594, 0.5893026396037715, 0.6539543608632357, 0.01692806126746993, 0.25151901081956773, 0.6494705348635389], [0.6704510726339974, 0.8758185763066478, 0.5699163645523456, 0.7912757859577143, 0.09065773212048178, 0.4237842088277911, 0.8699845724951153, 0.6488677750695786, 0.5653449967604127, 0.8292118805736806], [0.8131558892056583, 0.3268020467263246, 0.08369157196464938, 0.1603635622760785, 0.7504397408354867, 0.07117758329853774, 0.5355932854726231, 0.7162574589753116, 0.5987384856573122, 0.025683652943752078], [0.06009972890276505, 0.7935440688312237, 0.01808434214582022, 0.34046027780176846, 0.549324159430334, 0.47253503131225094, 0.6905962261750519, 0.1497111346220502, 0.1273108065616978, 0.0655897951753388], [0.511873155096237, 0.6849032972281693, 0.36247978509867007, 0.6287607271233249, 0.8789975885675149, 0.21461878053372774, 0.8874116808318557, 0.8114729406133935, 0.2292205031297172, 0.5354426035213069], [0.5966269510538195, 0.7929955251692358, 0.6823109986305395, 0.0008791822388720671, 0.4700295166934888, 0.7994313003038265, 0.3812200907121981, 0.2676978772566586, 0.3127215604739011, 0.6449247172434894], [0.13745596625946943, 0.5398373662519337, 0.34052478867321045, 0.39694874631674815, 0.14060375049293594, 0.24120176041061836, 0.6745849096680354, 0.7443223662639079, 0.11946763490666013, 0.23436294848898964], [0.22526728918705652, 0.7459460434943016, 0.016094040365600693, 0.22911780975448537, 0.8593999277550796, 0.08231626883816479, 0.5732024951093221, 0.12222663066731831, 0.6817348608015044, 0.6542446953429406], [0.29980279472836757, 0.6199127602687419, 0.17820063397269592, 0.9886320217194312, 0.903797993730064, 0.8640556924456716, 0.08386219446402954, 0.4841522187149553, 0.047457639659365114, 0.6407330710264578]]))))*array_x*7.157750696641705-7.968169233853899)/9.109265803739778, axis=1) |
np.mean(1.2885359889339845*array_x-10*(np.round(np.square(8.283156513792996))), axis=1)+10*(np.sin(2*np.pi*np.mean(6.615207716846953*array_x-10*(np.round(np.square(5.417916811346438))), axis=1))) |
np.mean(7.274111471943936*(np.dot(array_x, np.array([[0.992632541289831, 0.18263394840245228, 0.33381574205365006, 0.2755453874265146, 0.16415588699647687, 0.2835497080550091, 0.41934440669313466, 0.7770064179230045, 0.16411575418715119, 0.7832695417249146], [0.16761122596369527, 0.7970043460821558, 0.22460157172534745, 0.14969116416286832, 0.18456306581192683, 0.911725156314403, 0.16144892343162986, 0.37592498468465996, 0.8678053255843948, 0.935337976675345], [0.538386566096717, 0.6376822851055512, 0.733071446186317, 0.07421006700972699, 0.6002290333846628, 0.7897604127187926, 0.3275601139626364, 0.8571470344289523, 0.4380002964849219, 0.6947968386063684], [0.9456357219278945, 0.12700666920032055, 0.4679295864271733, 0.42029222492444496, 0.6829892940660415, 0.6329618677952947, 0.9818034714781729, 0.6547754967161197, 0.6015293975385145, 0.2060153245741121], [0.19764440346994894, 0.9628165411627227, 0.6101633444359448, 0.98501643469001, 0.0008012463365919542, 0.4935339573529093, 0.7144086154753082, 0.6450585425157692, 0.6932075882454685, 0.15215803650988347], [0.044585627897457236, 0.15574270407888036, 0.8559468438681586, 0.9420551691108152, 0.46299163134705823, 0.680496191589527, 0.08773789444707236, 0.09131875714586457, 0.514310749217067, 0.06701940067797074], [0.33211738092446685, 0.08398586319952994, 0.03365419181042684, 0.8379679530608438, 0.9779599930148782, 0.16262274824435752, 0.21694210481892806, 0.20974668333152025, 0.6346646655381177, 0.3928880110710766], [0.8606348678695991, 0.9733900542949633, 0.9892386924728173, 0.4063301482563324, 0.8768768575078916, 0.35459446743763734, 0.6313265288155283, 0.024198870946130602, 0.20513971305975176, 0.7429078262751846], [0.7544737240565168, 0.7483011818985958, 0.5697738388053784, 0.17201193184709684, 0.5283149214891241, 0.5350029461709426, 0.9859537412342569, 0.5523334364370583, 0.24294814985191304, 0.8178669808791891], [0.02812752414566222, 0.4705746091464007, 0.05065540801584478, 0.9497159713379901, 0.1782545844570671, 0.4592579897898169, 0.5351974144365546, 0.9274315113747286, 0.3335070466747322, 0.07535096420776843]])))*array_x-1.5799488703190876*np.sin(2*np.pi*4.700927058466007+array_x)-abs(np.square(7.451835639394267+array_x))*8.68921598937531, axis=1) |
np.mean(10*(4.039028373290498+(np.dot(array_x, np.array([[0.06651271474166698, 0.8259712617060799, 0.10684910971039918, 0.4892270115435964, 0.03312249260620692, 0.5961091028367491, 0.6470823164428621, 0.803657623421419, 0.6251224499240202, 0.6701115293883849], [0.4509984133079922, 0.06543361619444332, 0.18616757588824018, 0.2758667357218385, 0.16673157326363874, 0.3052734652308433, 0.1462167043303808, 0.4237839969544066, 0.7540817470532931, 0.10146614894189077], [0.0003162436678249003, 0.6681084617715137, 0.6137467435877035, 0.965905922110258, 0.37869416500205755, 0.04131861420546168, 0.3672306865391215, 0.031455553964368055, 0.05232765966077191, 0.8981672228302896], [0.7852318594036755, 0.9386658555233045, 0.48139713401183426, 0.07483307430532937, 0.7294880948167369, 0.9703173231413941, 0.762908940862124, 0.7803863881675726, 0.43803542921299843, 0.35855256831018534], [0.5954773945779487, 0.5681235042907932, 0.978596389758617, 0.06470159329827285, 0.558459450430247, 0.7187287228503451, 0.7752259483803398, 0.15194772683100666, 0.10288316832074607, 0.8343461570732635], [0.8073384968585212, 0.6874942786539724, 0.4597203513484027, 0.2297894185724395, 0.5324980518696277, 0.7468754862698419, 0.28344549161170196, 0.3900160101685404, 0.050746102847867625, 0.7605791703970952], [0.5829503474719309, 0.1366120906459396, 0.6622855739861954, 0.8100291482419001, 0.19438470920018025, 0.32068787655193565, 0.25025683521321207, 0.825542209882113, 0.044435994589254735, 0.6313522338196492], [0.05931003227646581, 0.029029708669163545, 0.6506183025789505, 0.13923857796150396, 0.07463479612674151, 0.36917400534723854, 0.017081130931885458, 0.31634688005574985, 0.26138885282800417, 0.9899532412249433], [0.4056953417320802, 0.15675868102296941, 0.8828731823302028, 0.06623061629022498, 0.23544244763324584, 0.9119063086184986, 0.8558937961690158, 0.21178665846238232, 0.4509178850738085, 0.3769954802378852], [0.025398839523493866, 0.3519532860058233, 0.6910551958559519, 0.5555003872339112, 0.07168932425418639, 0.9076164276240948, 0.06203818054272303, 0.4523752719779601, 0.2764961288748722, 0.6215476444737603]])))-np.sqrt(abs(7.019692409584829))+np.exp(7.376148648516426)), axis=1) |
np.mean(np.square(7.133115268329712+np.square(array_x)+array_x/1.5709932598325116), axis=1) |
np.mean(3.823213735396564-(np.array(range(1, array_x.shape[1]+1)))+(np.dot(array_x, np.array([[0.9570210180666904, 0.6238932643072083, 0.18127674757844037, 0.9024384010044504, 0.014715463756307723, 0.7088269403036633, 0.9534548015338974, 0.48673454683746187, 0.7198357684966904, 0.5795726884922809], [0.4638030242361585, 0.89396156393083, 0.08522915219056715, 0.8849070756770964, 0.3975614146284595, 0.6434917854321799, 0.9526146603790083, 0.30064926290844396, 0.39309796333890945, 0.5155508379700385], [0.13048838637254123, 0.7721897083322651, 0.4453396609198452, 0.1884678407418463, 0.021588518637005727, 0.2128755831889172, 0.44648499006504727, 0.005482324024886798, 0.17113866845205894, 0.39966055702261116], [0.8910530512383769, 0.10137698981372345, 0.942673769658872, 0.6339625365467504, 0.6759832011613005, 0.6552578546477541, 0.35129716085296525, 0.7161728968633517, 0.30052918422936736, 0.12666608976232852], [0.7032255646303456, 0.06744436598141235, 0.10672690822938147, 0.15709199226875292, 0.5523511222909099, 0.26109813234217105, 0.7452405044773648, 0.834016374340012, 0.4527016868658472, 0.23754015083997304], [0.9679061906167529, 0.13373557015004522, 0.20356036523668608, 0.19406925967735522, 0.4331977273905283, 0.51856243366362, 0.8770886633903814, 0.2071420955776062, 0.7339942351413095, 0.700141269511083], [0.1116474573327112, 0.38686568096528506, 0.3925004261457038, 0.35005380372647, 0.9202351726189749, 0.5919372092479028, 0.5160990000025028, 0.17342228131312776, 0.8060559631506783, 0.20310245298793894], [0.1652530862899736, 0.24260055296148297, 0.10919571368407532, 0.33876893851657564, 0.644431818617343, 0.28303899906435126, 0.48150339334502046, 0.005219132906930102, 0.562894431206589, 0.7209236864898889], [0.3309933575545251, 0.7892457986150264, 0.7734248311323668, 0.11911474281342282, 0.16166424280856484, 0.8189535700088277, 0.255227995800022, 0.07296460203282307, 0.21916678889074404, 0.30568444837664144], [0.6045942400380743, 0.19290766530944392, 0.9445934245897132, 0.5197429387112003, 0.5385399730138299, 0.6277327041993006, 0.9218060346271062, 0.3442636631108613, 0.12255611060220883, 0.059949301677351574]])))*3.2510065625768605+array_x/8.770325611418743, axis=1) |
np.square(np.sqrt(abs(np.round(1.231625779132635)))*np.amax(array_x, axis=1))*np.square(np.mean(array_x+8.11749064181864, axis=1))+np.exp(3.8731930692654086) |
np.mean(np.cos(2*np.pi*6.664190923792261+array_x)+array_x-2.946261999574097+array_x, axis=1)+10*(np.sin(2*np.pi*np.mean(np.cos(2*np.pi*8.823912071574245+array_x)+array_x-7.69524339245821+array_x, axis=1))) |
np.mean(np.exp(np.round(np.cumsum(array_x, axis=1)+np.sin(2*np.pi*9.959161245569568))), axis=1) |
np.mean(8.44444657025982*np.exp(array_x*np.sqrt(abs(7.101172075374481))), axis=1) |
np.mean(array_x-np.round((np.array(range(1, array_x.shape[1]+1)))), axis=1)-np.sin(2*np.pi*1.6183319494901633)+10*(np.sin(2*np.pi*np.mean(array_x-np.round((np.array(range(1, array_x.shape[1]+1)))), axis=1)-np.sin(2*np.pi*5.150935347999366))) |
np.sum(1/(np.square(np.sin(2*np.pi*2.733891681910628+2.102716376108037*array_x))), axis=1) |
np.round(np.mean(-(np.exp(9.797254581548868-array_x*2.23880275161999)+8.286807684288892), axis=1)) |
10*(abs(np.mean(-(array_x), axis=1)))*np.mean(array_x+4.663944823612804, axis=1)+np.sin(2*np.pi*7.738126472716032) |
np.mean(5.150751916933174+(np.array(range(1, array_x.shape[1]+1)))*array_x*4.3140825724820715*np.square(7.541303272232461), axis=1) |
np.mean(5.242655551477634/4.138970526852633-array_x/np.log(abs(2.789640116518161)), axis=1)+10*(np.sin(2*np.pi*np.mean(9.227263359690044/3.0697923248418926-array_x/np.log(abs(5.850727131099993)), axis=1))) |
np.round(np.log(abs(np.prod(9.208505447098881+array_x*3.449333672108602-4.06219210953094-np.square((np.array(range(1, array_x.shape[1]+1)))+array_x), axis=1)))) |
np.mean(np.sin(2*np.pi*np.square(4.12429017382976))-10*(-(np.sin(2*np.pi*1.5630984269919472)))/2.1012853739926536+array_x+np.cos(2*np.pi*6.790054154189576), axis=1)+10*(np.sin(2*np.pi*np.mean(np.sin(2*np.pi*np.square(8.323959015461169))-10*(-(np.sin(2*np.pi*9.383623568559171)))/2.437666929257265+array_x+np.cos(2*np.pi*1.4487528892111206), axis=1))) |
np.square(1.292317270345905)*np.square(-(abs(np.sum(np.exp(array_x), axis=1)))) |
np.mean(8.486408006116818-np.square(np.cos(2*np.pi*np.cos(2*np.pi*array_x))*9.04878831120443), axis=1) |
np.sum(np.exp(np.sqrt(abs(np.round(np.log(abs(np.sqrt(abs(4.744614078973788))))))))+array_x/1.8703591539770448*5.109221240931659+array_x, axis=1) |
np.mean(np.round(1.0538481925098495-10*((np.dot(array_x, np.array([[0.17314793376547, 0.033972541360406616, 0.02032166710802008, 0.09209746285606246, 0.31351863044924644, 0.6025255212289201, 0.0004900114328764138, 0.3435855212588482, 0.39739257689646246, 0.316218284609709], [0.8128519632211021, 0.15576120520585102, 0.8969959977666371, 0.42280255987018567, 0.25101702166608997, 0.5727707655000306, 0.1502022683386931, 0.4273754544829197, 0.9093772837184749, 0.14857644958099392], [0.9507816612549228, 0.9516016124394551, 0.7095368971563624, 0.8653413276708731, 0.010833113352354373, 0.23281227248351133, 0.9047897892501159, 0.8167665762909375, 0.5678804940256186, 0.18244789701161812], [0.27703976653629026, 0.4498153704180975, 0.6175625043013819, 0.5203433380238344, 0.15456000536136527, 0.11629745559217586, 0.23135392417180833, 0.9152220711666197, 0.8736856959959454, 0.5446857580409796], [0.826096960156214, 0.6523309034054302, 0.3655961988233277, 0.22672125901183138, 0.7760658906566855, 0.7053644083330403, 0.766131616466546, 0.2215803035394609, 0.1523749053733814, 0.853382741640118], [0.924085416458142, 0.8715461965723347, 0.6394024244611872, 0.7168579755895937, 0.7048719492950268, 0.8454479742869655, 0.15996584878361975, 0.7605740269184786, 0.9751999348614085, 0.4752850080983987], [0.07215892429663195, 0.7828487064124785, 0.6813993166605491, 0.11957463431750481, 0.8530966454702664, 0.8135234637204195, 0.24102325572090855, 0.43273881240289647, 0.6112927984654735, 0.6335860678491436], [0.26794005724492764, 0.07779833669592418, 0.44062072986996637, 0.9257472529842353, 0.24627768885454993, 0.8159917769789888, 0.39197673573176073, 0.02417343149689788, 0.32991439427896785, 0.0009344657692427205], [0.4525985401461733, 0.19851587853213637, 0.5930289965074199, 0.9014550058935794, 0.7090757795109383, 0.565277452719634, 0.633810729746439, 0.06365920238670975, 0.8025904451555511, 0.0064402344446863324], [0.006373021647193777, 0.7247900019297554, 0.12337487716738849, 0.41796619109461, 0.5300407362051112, 0.10051988768870246, 0.32226521151400656, 0.19204205313631162, 0.9840538442594061, 0.018029195606472426]])))-4.966145825654914)), axis=1) |
np.mean(4.1173358957558985-10*(np.sqrt(abs(array_x)))-(np.array(range(1, array_x.shape[1]+1)))-np.exp(array_x+np.log(abs(7.287743052500628))/np.exp(np.cos(2*np.pi*array_x))), axis=1) |
abs(np.amax(1/(np.cos(2*np.pi*(np.array(range(1, array_x.shape[1]+1)))*array_x+5.187304530834615/8.813465647376912-(np.array(range(1, array_x.shape[1]+1)))*array_x*8.953989138886111)), axis=1)) |
np.mean(1/(np.cos(2*np.pi*9.536533264744257-(np.dot(array_x, np.array([[0.25004059245033494, 0.43222613204483395, 0.28636993509576536, 0.252894887853365, 0.4922582618513853, 0.3296463190687169, 0.1312260631972908, 0.23165850979966485, 0.4088898159368478, 0.183433526411649], [0.6342358734760098, 0.7377194278420929, 0.20275327026694412, 0.33731875209833206, 0.3113688260644104, 0.5418029456765684, 0.35290073455489623, 0.18015170582334084, 0.5019141201647159, 0.5866824434515652], [0.5425858869039006, 0.3628582833176821, 0.9680796169075179, 0.4276866783080506, 0.2637506223327072, 0.5661320850583408, 0.039463051462076626, 0.8633379402231323, 0.4536752783658612, 0.008287723209169928], [0.4580156533173255, 0.07484780420740411, 0.9963320079145208, 0.5504734654976491, 0.2884878036304094, 0.12394630895113345, 0.6507901111847878, 0.5293358609670289, 0.07239508443051956, 0.19195506952553432], [0.222251565037745, 0.8768999110475703, 0.4606385018053566, 0.22165212103256993, 0.8723626627489386, 0.025231967214008, 0.9151909797931189, 0.9044730167166689, 0.5079104275625842, 0.11875278049504201], [0.6163756745712962, 0.33480692933761236, 0.7575719488693348, 0.7396689637266879, 0.6514132370446137, 0.7551858843993934, 0.1790855486819639, 0.879734289545314, 0.1357607219464424, 0.38195464843134863], [0.8278909420333103, 0.9007394152584663, 0.1658536134104962, 0.30786499510608945, 0.8579852718821268, 0.6689686574415465, 0.9648392392343161, 0.9877846256161723, 0.4579963672917956, 0.7482917294184935], [0.8213889008362625, 0.9854432605948179, 0.03947814642477876, 0.8376720290251374, 0.6611769840664198, 0.9068811529933181, 0.8368882346753674, 0.4085280250283764, 0.6556355191413952, 0.46134779487785615], [0.880630305283167, 0.8189644692600453, 0.9671184996970212, 0.25180974507572806, 0.7020353947508098, 0.6606507439373579, 0.8636042857998959, 0.3774042656089077, 0.12765287415099613, 0.48818317143674317], [0.5695635114010127, 0.11641810560364596, 0.22717076497374422, 0.7618696068197158, 0.790466974561958, 0.23271726443726115, 0.0554667493135238, 0.13695928025935244, 0.5182802337443317, 0.5965028762151584]])))-array_x)), axis=1) |
np.mean(10*(9.284231638240787+1/(np.log(abs(3.554862873136163)))+np.exp(array_x+6.712924728595026)), axis=1) |
np.round(np.sum(np.sin(2*np.pi*array_x)-array_x-8.129918801016608, axis=1)-np.sqrt(abs(3.662524669193988))) |
np.round(np.sum(10*(-(np.exp(2.9811951813952073)))/np.sin(2*np.pi*4.091157987571362/10*(3.6059015080262573)/9.120207945960974+array_x), axis=1)) |
np.mean(1.6925109310473148+np.square(array_x)*np.square(np.square(np.square(np.exp(1.6504571705421087)))), axis=1) |
np.mean(np.square(np.exp(np.square(array_x)*4.318592255562964*np.log(abs(1.3272899318135833)))), axis=1)+np.sin(2*np.pi*np.mean(np.square(np.exp(np.square(array_x)*4.918344215278338*np.log(abs(5.910336932981084)))), axis=1)) |
np.sum(array_x+np.cos(2*np.pi*8.998596061725271-array_x*np.exp(array_x))/np.square(np.square(np.log(abs((np.array(range(1, array_x.shape[1]+1)))))-1/(6.957269447804758))), axis=1) |
np.mean(10*(np.round(np.square((np.dot(array_x, np.array([[0.0691432120278811, 0.2771466081791434, 0.23120684764266675, 0.36734200568081843, 0.815041532897457, 0.3428910079418793, 0.015137034945967076, 0.41386432772256254, 0.9359899808522524, 0.9155055710596405], [0.8934849159072741, 0.30176648433906117, 0.04791593450750342, 0.7064988294423856, 0.04843278793299577, 0.07001101318786318, 0.7562577831842466, 0.9697203477605953, 0.6052070685491574, 0.49632222376461743], [0.6620435787820681, 0.4172476284242608, 0.5830297892355153, 0.7421190171959892, 0.38858578224649154, 0.0018008096549021468, 0.2530492128529568, 0.0742224642402074, 0.7406804716375723, 0.1277407528612695], [0.6971582086960475, 0.3467652929736271, 0.6282743836915194, 0.344103707028625, 0.48419598509086115, 0.9261171043747445, 0.20069812949315124, 0.019424179133041286, 0.4906141075871554, 0.34284590523521985], [0.8795464864120015, 0.33186741604513903, 0.5474103490872102, 0.41159121331682713, 0.9931003735146163, 0.7231984648719921, 0.9433753901089946, 0.15734239447486087, 0.9305675354817209, 0.8112739686335396], [0.11054882099305485, 0.3060196078036673, 0.6446995899757623, 0.3731012818987377, 0.9011279111177594, 0.5086582287861157, 0.2274812887599048, 0.353093680566131, 0.9769131564155251, 0.8937573406169607], [0.2568816291749466, 0.5458040960175261, 0.5317957168310717, 0.05497987235313029, 0.17175966990673275, 0.07833157673138069, 0.9316120339663987, 0.7993473267347457, 0.9790773447933748, 0.20302023115074685], [0.3743449823304542, 0.34868285586922376, 0.381793398920215, 0.6235708813695493, 0.7002849669729028, 0.2799231007864178, 0.18861759867673855, 0.5129262008538716, 0.15259888623283124, 0.9274020608564494], [0.4759616911713388, 0.5691385816405713, 0.17727929939530185, 0.03550436431866755, 0.7822855034245719, 0.4168392704265519, 0.7818465428828207, 0.684515665482808, 0.20537527489459628, 0.8520343898132344], [0.5372952111888039, 0.5291805050791167, 0.664065971443088, 0.387693286204693, 0.6076283025426323, 0.15509424717171127, 0.9723396987491493, 0.2434385121862983, 0.6895326805457531, 0.7926614801695212]])))-3.393053647895398-6.337001116997369)-5.4094981339455055)/8.415225346126732-7.662819958900534*np.cos(2*np.pi*array_x)), axis=1) |
np.mean(np.log(abs(6.533503433267568))/np.sqrt(abs(2.4340015989636314-3.0947644327636454*array_x)), axis=1)+10*(np.sin(2*np.pi*np.mean(np.log(abs(8.574673428170248))/np.sqrt(abs(2.1241981448880107-6.947706114102606*array_x)), axis=1))) |
np.mean(np.round(np.sin(2*np.pi*array_x)+3.963040466477187+array_x+(np.array(range(1, array_x.shape[1]+1)))/np.sin(2*np.pi*8.943292967588949)-6.063127216837031+np.sin(2*np.pi*array_x)*(np.array(range(1, array_x.shape[1]+1)))-array_x+array_x*2.745761389180045), axis=1) |
np.mean(np.exp(6.497777971121742*array_x)*2.5816191344220676, axis=1) |
np.mean(8.166431644712043+array_x/6.35258706717094-np.square(8.142721199795677+array_x), axis=1) |
np.sum(np.sqrt(abs(np.sqrt(abs(np.exp((np.array(range(1, array_x.shape[1]+1)))*array_x))))), axis=1)-np.round(2.6896414353317724)*3.0874093256956336 |
np.mean(np.exp(np.cos(2*np.pi*9.62504715518095)*np.cos(2*np.pi*array_x)+9.548515345076918), axis=1) |
1.936464142932323-np.mean(10*(np.exp((np.dot(array_x, np.array([[0.48565771313381556, 0.5193351479843322, 0.3204800283140721, 0.5138967373235549, 0.8702648664241871, 0.19866239647392903, 0.10597855578076676, 0.2783349829374355, 0.9208530538280024, 0.0672931642036908], [0.28336835070716027, 0.9380048619856283, 0.22001761053705116, 0.34142063777012654, 0.16018267786723117, 0.2034249201697469, 0.1596415942859576, 0.1705849271826786, 0.7479615143973974, 0.2183762447001123], [0.750664106150057, 0.06269870992429061, 0.9023629346583283, 0.2937300418756843, 0.037578289375464036, 0.5153759649686985, 0.7230383942253051, 0.7704848666532828, 0.6146743093683437, 0.9481652058371268], [0.08768355854247545, 0.8047708271908284, 0.7519721119255351, 0.5960702812882291, 0.4968957490770284, 0.08723627974375947, 0.614545545427133, 0.26565556791795075, 0.554408123268088, 0.5961756117326904], [0.9802893928262368, 0.5393379025515784, 0.08480632634224083, 0.13180310302095888, 0.5990327754324758, 0.9379938223366072, 0.6842919036195126, 0.1692709562461202, 0.01446804820672154, 0.00898427499754173], [0.2586925421639733, 0.897763017901437, 0.8068854574105038, 0.8892851221262832, 0.37916278891597655, 0.13521363765458805, 0.3569092154247654, 0.9934570381098964, 0.8790758470589103, 0.5521987409178676], [0.5580682052152752, 0.4472108132781726, 0.6388070252077721, 0.550187787262985, 0.2523095444316781, 0.49521400781161384, 0.29863254084718716, 0.9328152725227096, 0.9418406036408105, 0.4152729443206049], [0.7522703807661119, 0.6893078868298848, 0.053063780766001045, 0.7912613652773545, 0.6112269642769661, 0.0031808546168565766, 0.010346935367887, 0.15290224699908284, 0.6631865561666331, 0.6082430683779765], [0.5572290218472867, 0.8308538460329954, 0.9351668841447845, 0.8663136360061706, 0.8578919982074609, 0.7787161393660661, 0.838205458550428, 0.724514440786722, 0.3367805483787778, 0.14038168417948693], [0.16085749853104891, 0.1917456831617208, 0.5670610551196374, 0.8459870073977795, 0.5074615330485146, 0.010332781965553095, 0.8233927995324277, 0.6782776978780005, 0.5198415872604641, 0.5716690215952378]])))+(np.dot(array_x, np.array([[0.7674512976546852, 0.1919468941961019, 0.4283985965889182, 0.5632326177150095, 0.48312721351975363, 0.035575087700304375, 0.6293360506540988, 0.3310573158690444, 0.26657673439993057, 0.37664844719740154], [0.08716924119912095, 0.5537772700530227, 0.4107905569308459, 0.09840630784366289, 0.5004812926767586, 0.37730650878452565, 0.7234905693820161, 0.9833844640943178, 0.6236129957008779, 0.38593951748778554], [0.1453722564037886, 0.4555482621716229, 0.27442586281804027, 0.6241473190242363, 0.06838772553390748, 0.8861520372941208, 0.1357402570883639, 0.9839328083938962, 0.4995821880868564, 0.12392782886658693], [0.1418863234042408, 0.3493184534490458, 0.779421544143175, 0.43108822449621054, 0.6830152511362941, 0.15216081373197232, 0.11646881525504993, 0.0909500828861779, 0.22250178663255837, 0.28998030902398964], [0.8617542246253588, 0.6059427257211532, 0.8380872725419295, 0.04450491773463949, 0.9578651221492737, 0.6210406332366178, 0.26494406429324, 0.30967202834391827, 0.1042049018796748, 0.016687716081885906], [0.13363590020769534, 0.6848101124302854, 0.6523827101408312, 0.7517309672678266, 0.9297333100406033, 0.42524733066493026, 0.6467908380695213, 0.18350238045523737, 0.8233689927659732, 0.45397177112178233], [0.4715427531858146, 0.800385345182199, 0.29268706647246057, 0.0785438428455636, 0.682584804322793, 0.3931382139409304, 0.9075681392242385, 0.3698933057062884, 0.27499810398095303, 0.18196740368214903], [0.6311624820021638, 0.6296237524761723, 0.3088865463761121, 0.04626318367788751, 0.7067774173604222, 0.8989532971130756, 0.15270168249238314, 0.43291314979473505, 0.9896686007374771, 0.2710513721075981], [0.5952454108369769, 0.25544905284527153, 0.5682689361144493, 0.34973106952867783, 0.9820401641110055, 0.11786954285456275, 0.6104040881908702, 0.2722417932671918, 0.2724364552552142, 0.8463747105666417], [0.7487266824317265, 0.7164813823417271, 0.282194993991546, 0.045633566067288855, 0.5026523061850405, 0.9582898954740502, 0.7732257169677236, 0.7733590627828566, 0.8263076437216546, 0.3814698246869276]]))))), axis=1) |
np.mean(1.8389514094508597-6.397228026173432*np.exp((np.array(range(1, array_x.shape[1]+1)))*array_x), axis=1) |
np.mean(8.563820889120088*3.028630787117159-np.exp(8.617983614886413)*array_x*array_x, axis=1) |
np.mean(8.999700199236475-(np.dot(array_x, np.array([[0.7862636976988073, 0.37498549878604526, 0.8956602451946359, 0.2803844068543807, 0.34288230318393587, 0.4877321681405792, 0.6685113389336174, 0.9435142605645793, 0.8025624852823132, 0.38381075167513345], [0.9010222396199359, 0.839113381005597, 0.2818481898626263, 0.5335365215243277, 0.1874532065078537, 0.5631953472840436, 0.9974228370772622, 0.9347013387599004, 0.48814768719712887, 0.05404437880288315], [0.6660195077201229, 0.7039165887730084, 0.11912806992080094, 0.6469538332542378, 0.016534329016246296, 0.9262155483393829, 0.1737969888865485, 0.7900086923125563, 0.2251219925323651, 0.9442502790666598], [0.2497056573967732, 0.3603661224303686, 0.3746502725376132, 0.9239705026001732, 0.2232031574728055, 0.8937156074914123, 0.5473917463210352, 0.8163910325651033, 0.14413829183700777, 0.9809902707440399], [0.238624637776519, 0.25923261770040873, 0.1235182254551801, 0.6691935544176175, 0.44837189927955345, 0.5929919612217782, 0.3073985726911329, 0.29971785449288535, 0.8269942678321461, 0.8602454780743954], [0.7510639693080475, 0.3674770037540285, 0.9477244704407553, 0.4456050417114772, 0.6847997345215739, 0.9861901576083089, 0.09980727434011227, 0.9563051879253366, 0.687264595532642, 0.7305652084415705], [0.9744384420296925, 0.019864975372186344, 0.06548764826723308, 0.5788630517291153, 0.9738274617504711, 0.8123838664685719, 0.4470701926744367, 0.5872948074248238, 0.9309135660879846, 0.640311995835869], [0.8751321370057116, 0.22869259598567648, 0.22626950748250718, 0.9495080172326751, 0.9538513261379659, 0.41517418769585956, 0.5252569870339373, 0.36090661302780336, 0.20180184064812623, 0.5518347371192325], [0.33591642130081434, 0.3860113141479399, 0.6848605844402137, 0.90860266085775, 0.7366512969122013, 0.09697382881177319, 0.9646680187328824, 0.3289122986749051, 0.5981801735083275, 0.9305374313052257], [0.5111946464088818, 0.7287183613255062, 0.5585489162011228, 0.6135708752994327, 0.22352979663289807, 0.578200083286865, 0.10207161516361962, 0.1881660881049636, 0.18805934740713526, 0.3745368289638443]])))*5.490745741926156*array_x+array_x, axis=1) |
np.sqrt(abs(np.sum(np.exp(6.856596908701253+np.sqrt(abs(7.133360953137073*array_x))), axis=1))) |
np.mean(np.square(np.sin(2*np.pi*np.sqrt(abs(9.506235906257618)))+array_x+9.263203641018059), axis=1)+np.sin(2*np.pi*np.mean(np.square(np.sin(2*np.pi*np.sqrt(abs(5.027197983605063)))+array_x+1.5109408416956032), axis=1)) |
np.mean(np.square(abs(9.579421411776803-abs((np.dot(array_x, np.array([[0.11581117827410503, 0.8655249354114766, 0.15920516061505907, 0.03940191662720738, 0.8550813511851337, 0.49578283546692103, 0.8284436352794872, 0.5282375321456922, 0.4149370875625309, 0.19007908917901772], [0.8527515116462292, 0.22844770938145187, 0.6071764644422855, 0.28359780289229297, 3.9951338239752054e-05, 0.10317588266177946, 0.9522353446217229, 0.27777003333307637, 0.05592362004605589, 0.2784501396370166], [0.7300240384422938, 0.3973008264391096, 0.3151270386089958, 0.06993747151738805, 0.8543543422450397, 0.45506651043463753, 0.5465247427884318, 0.6298702697596118, 0.3054688240299541, 0.8049605269313532], [0.5638452532168281, 0.8804969455315985, 0.0429277915907611, 0.6785555238960982, 0.7607373344920757, 0.15984570153084476, 0.5375513035337594, 0.579767749308983, 0.06556068668103521, 0.31754675923253106], [0.765619460984296, 0.5424688843899456, 0.5718065912876995, 0.7952602792896319, 0.8202647201986424, 0.3465246846341903, 0.33347100784130723, 0.020296047112726145, 0.4448743442719515, 0.7230448864015337], [0.6147331714324121, 0.5133211152722047, 0.6776664418966175, 0.02479582300007377, 0.6588086536778027, 0.8623344772670383, 0.9023717152261975, 0.24807805925752002, 0.039249339301956065, 0.4169382271662445], [0.8080822693331944, 0.9401466388858827, 0.6413444547514151, 0.24478675565234553, 0.366418627709155, 0.23266710813250868, 0.2624920545983366, 0.4312896768524228, 0.6912083100580199, 0.30708935420336714], [0.2814971851409206, 0.8969221232497708, 0.9515547836178913, 0.8192149925788037, 0.368361709312666, 0.3706035635373951, 0.163003944075221, 0.9284920460838871, 0.4445703909709786, 0.9395952821934498], [0.24112581082785578, 0.40937700094433915, 0.6422575130680118, 0.8481052990867307, 0.1169902016843154, 0.19460102372366028, 0.7244008371052596, 0.14962893931247467, 0.15913705504246634, 0.15707610451396214], [0.055080642933649226, 0.8197014696694593, 0.6103822001908922, 0.25947953344954955, 0.7280833004332857, 0.990147321929574, 0.11239977041309979, 0.4553011080428605, 0.031130364708809588, 0.6198176649418964]])))))), axis=1) |
np.mean(np.cos(2*np.pi*array_x-5.331679467443381)*6.485882785727758+3.607149792919613, axis=1) |
np.round(np.mean(abs(np.square(3.5124041047923016-array_x/np.log(abs(1.4384184166565492)))), axis=1)) |
np.mean(np.square(2.050827413885628-(np.array(range(1, array_x.shape[1]+1)))*array_x*7.600592106393529), axis=1)/9.186899690503338 |
abs(np.sqrt(abs(3.953716364241136))+10*(np.sum((np.array(range(1, array_x.shape[1]+1)))*array_x, axis=1))+5.328822494924354) |
np.mean(np.sin(2*np.pi*np.log(abs(5.800827783389601+np.square(np.cumsum(np.cos(2*np.pi*9.518956186047946-array_x), axis=1)))))*7.337808518230449+array_x*9.461122936426126+array_x, axis=1)+np.sin(2*np.pi*np.mean(np.sin(2*np.pi*np.log(abs(2.6974817482105866+np.square(np.cumsum(np.cos(2*np.pi*8.338717209098755-array_x), axis=1)))))*1.3515687410667505+array_x*9.200162836247275+array_x, axis=1)) |
np.mean(-(array_x)-10*(1.7911782417837259)+abs(2.7385309424048048), axis=1)+10*(np.sin(2*np.pi*np.mean(-(array_x)-10*(2.3600496353263947)+abs(9.25203937196602), axis=1))) |
np.mean(np.log(abs(np.log(abs(5.226168257932093))))+np.cos(2*np.pi*5.984928016786023*(np.dot(array_x, np.array([[0.22729108070615212, 0.10024182395059766, 0.49327752163749206, 0.6736965594570505, 0.4994718256559192, 0.5295652600858514, 0.2830454633355508, 0.2351616358879174, 0.9232539370601838, 0.2669086398756], [0.2958785775961984, 0.2254711065919084, 0.6329110668162903, 0.9823194510975772, 0.3957693882353106, 0.565513683411279, 0.7786067794362775, 0.18585535046387658, 0.15071088402136357, 0.34562391081556787], [0.5970622769311715, 0.730971734133948, 0.26374493992596204, 0.3265956062717479, 0.9115757957402012, 0.6398497473460274, 0.13580115007695204, 0.6936916069047789, 0.5905309053148518, 0.4585397370919866], [0.7817157933164718, 0.18851804885183276, 0.37689850074878106, 0.8400378970104474, 0.20730113002340322, 0.6291095811002438, 0.6254007049575427, 0.35919408334393854, 0.2061254297326267, 0.6720145809385996], [0.8301181671189694, 0.09748714230441369, 0.9882269182679015, 0.8289602042946669, 0.5996567500214419, 0.9304030494071948, 0.8614453263472802, 0.9409396499459948, 0.13561517986952742, 0.23687108231441456], [0.13880103223385354, 0.18773793928357196, 0.8643948649482597, 0.22163036404984138, 0.19826894895146185, 0.9081155345191694, 0.12165606233660853, 0.6110621811524316, 0.7367467108708838, 0.6549318304310996], [0.600966158980262, 0.35717665386414166, 0.5045427230391114, 0.5294696300193636, 0.47796413072975896, 0.4069232299646114, 0.960855726898321, 0.34757978356597996, 0.8967461905700651, 0.805653369022597], [0.12892343070128465, 0.43922779932085554, 0.1665602105318298, 0.04505312468386535, 0.16982097767677862, 0.6743848968545625, 0.9980927385743239, 0.7441706378779959, 0.17455596110487204, 0.7609758248854189], [0.9287598569174693, 0.8301874444081561, 0.39138527958471014, 0.7011790858357851, 0.6091764747063947, 0.3463281496558339, 0.18902236470435696, 0.9789895907752136, 0.29654431152310723, 0.3889010853867009], [0.8100204568939741, 0.13724492468754879, 0.8335696347016156, 0.1370844727751056, 0.10907450877961689, 0.08711401347276115, 0.6328319475281564, 0.1976755449497023, 0.19812277472318562, 0.899264582263213]]))))/8.66544822414241+np.exp((np.dot(array_x, np.array([[0.783282807078101, 0.0590583838614549, 0.7947255182523932, 0.8109760479135096, 0.5296862943898412, 0.3024688550313812, 0.711837593933081, 0.8702355569563114, 0.7054233534794102, 0.07039446920866232], [0.7652542079272059, 0.09982365975365248, 0.5935022098742497, 0.9013909049196882, 0.6959447360016207, 0.07140330109588222, 0.07082003868255837, 0.20399922314140406, 0.39815659475779375, 0.5250448144698239], [0.8202200134414837, 0.7713612008600506, 0.5767807931777927, 0.36482563564314385, 0.6977079702376076, 0.29514831213463644, 0.7069922839205411, 0.7002059107042958, 0.8617236282930436, 0.7654272748753681], [0.2834901563734157, 0.9713735123848085, 0.2609360736875421, 0.10760335985415603, 0.6996570999013902, 0.2077339842104733, 0.7866478730160027, 0.7055509590367905, 0.04246447264642128, 0.8705478943707602], [0.44498436420581444, 0.21411449089321632, 0.41466994309753524, 0.792851550131121, 0.3449496327710052, 0.6507192885453343, 0.5677776851598889, 0.7531902949068376, 0.22268277288806726, 0.8104780326101072], [0.6827422943775135, 0.6280416264893718, 0.9758277563246904, 0.9267747822628396, 0.8139529359546319, 0.42924025832486934, 0.20445887257100592, 0.38070745771658143, 0.5629422431013321, 0.09652236800014424], [0.666759938829933, 0.18868799516572476, 0.347039157235857, 0.4641853036588194, 0.4064756897214068, 0.06027931509791795, 0.37359576884203005, 0.0818856524865188, 0.45178939569793863, 0.672316023259297], [0.5526909598367727, 0.6565517543476457, 0.43233025708455775, 0.5237625902314569, 0.28686920149951844, 0.5005685792154361, 0.2453456370447069, 0.8693854362361753, 0.43223826083832306, 0.535939820689602], [0.10330066306559516, 0.7767498479691017, 0.18565337925766356, 0.1018022673779736, 0.10242623146581065, 0.20758222885106947, 0.7834419791351499, 0.8101358133379164, 0.3771342932988886, 0.08936729978667923], [0.9679648190719855, 0.3708521983195664, 0.2218616109660997, 0.7576197372852389, 0.46266978277184245, 0.409779071452784, 0.5295271694287048, 0.4062924050697706, 0.6543683479671323, 0.9865447998857182]])))), axis=1) |
np.mean(-(3.180778454356764*np.cos(2*np.pi*(np.dot(array_x, np.array([[0.22646087153295713, 0.16352103963841758, 0.10099925272643384, 0.6952586950900548, 0.36831303079400923, 0.43504596530983775, 0.5698827723302045, 0.23559997917761555, 0.9006801997787393, 0.9159275046984959], [0.3130083502985156, 0.6515966906417405, 0.3444877314746191, 0.4465420537088226, 0.10440273700869251, 0.7046251588000502, 0.2519882300329128, 0.18083501783423994, 0.8136345687162975, 0.13816288288051748], [0.9822271911343103, 0.463608689534034, 0.7457846215055948, 0.5387226483970702, 0.867309499810358, 0.9500263247012322, 0.2623557762293962, 0.688499008764239, 0.7393676364468744, 0.562205797127497], [0.30398714867580634, 0.6230575384659689, 0.5852647839432104, 0.4878348537750573, 0.10579896593408378, 0.8765846218611854, 0.6192614286872345, 0.818431907699026, 0.43692193184030526, 0.08838582488848767], [0.40626351539388805, 0.02965569885210595, 0.846584208431794, 0.4746222669691935, 0.2573415009881881, 0.7652281236832967, 0.4151699227304918, 0.9248825234198573, 0.46757500939999286, 0.6568996325336511], [0.06292323526459076, 0.7756496532279508, 0.6353967617756847, 0.3798732602759426, 0.8067500603399715, 0.6538677565535328, 0.9321010512031614, 0.2648277053324196, 0.7732723163137085, 0.03262251834855834], [0.9734242539468797, 0.3972398924828455, 0.985509988780526, 0.46842679869281345, 0.5559084155579002, 0.06409644475424292, 0.0036966876780416547, 0.614436354434948, 0.4873820214077943, 0.9636621285325876], [0.8481239446322412, 0.35008618430933847, 0.03508357471297063, 0.5363289270001154, 0.036969749738490654, 0.7097035565191725, 0.21606592868430585, 0.2977849638115483, 0.45036346541857697, 0.10988771848323853], [0.5173297175692182, 0.3647445062646758, 0.6537628934219173, 0.8546301535335875, 0.40274632534325283, 0.5262944205149553, 0.19598923889914643, 0.5299846945362867, 0.5129400584069699, 0.24652215912750897], [0.006667037578703683, 0.7237764184904536, 0.8443562774577156, 0.9398637756346695, 0.6490986245975597, 0.6761595810681269, 0.24068122858691754, 0.6390727695291233, 0.45852347912717695, 0.9786721537786254]]))))*1.4163426695077526)*4.229658498345051+np.sqrt(abs(np.sin(2*np.pi*np.sin(2*np.pi*np.square(array_x)+4.634814408933438)))), axis=1) |
np.sum((np.dot(array_x, np.array([[0.6179094980553327, 0.05061589650542064, 0.24510946249095178, 0.01370386684498548, 0.7673323995361422, 0.305299909135342, 0.9740768135914085, 0.19144313016813552, 0.8347271887890558, 0.6843083009458767], [0.0780009732907383, 0.79905241019959, 0.3983483897449307, 0.14410775250833563, 0.6184623336654009, 0.08242806897315968, 0.7249589688912628, 0.824894659371604, 0.9664570283640768, 0.20206876982712374], [0.5095655774345453, 0.5578179808668313, 0.6552247118282074, 0.6109891205706212, 0.29024329383504166, 0.717881340686211, 0.24021317278481025, 0.022908121798745684, 0.3675381049728714, 0.7209011511491745], [0.5542260329867293, 0.6833051658966356, 0.3156120673105818, 0.8397619807419345, 0.5112841371513039, 0.6546141366851397, 0.6355669559513316, 0.1981459871239163, 0.9473557405294495, 0.5137530029392294], [0.9276194595308769, 0.4639680837446092, 0.36109362567881254, 0.24881964073944363, 0.7539613152235751, 0.40537616129715837, 0.9748662386983419, 0.16021564499485907, 0.21555391993981887, 0.8321687344402552], [0.2430376379693182, 0.815894277211137, 0.8851070333805348, 0.15358905198925643, 0.8997418059399704, 0.7911826321331752, 0.35835847220188943, 0.37133578460965533, 0.6147006879351742, 0.589970226362589], [0.8087837806790182, 0.9537638205018258, 0.6378310352256551, 0.5529831426413016, 0.6971310754819189, 0.5322818006165522, 0.3872504753594985, 0.4936940992907328, 0.09502901079244097, 0.6503082838517967], [0.8112689517099572, 0.4999091357306985, 0.7030573361692737, 0.8308403617222659, 0.605527482409662, 0.0837242877583314, 0.4332984714310606, 0.9999709952667362, 0.8744011253645102, 0.18381298443942118], [0.9750310364474646, 0.024250887251796915, 0.4322421169129501, 0.07226688225616251, 0.761186448112302, 0.8640501845437287, 0.5931306984423315, 0.898757543234606, 0.2600530572451851, 0.1405200636299735], [0.8084696816429091, 0.26380144143283835, 0.3768584087053338, 0.24143273829038037, 0.5835396816577149, 0.35514795879103755, 0.22068428621594138, 0.7555717058131933, 0.8318527231581964, 0.7534617135406646]])))+np.exp(8.315604276859162)*2.4670924339698947-np.round(6.100728393449405), axis=1) |
np.mean(10*(np.square(array_x-3.888902383934067)), axis=1) |
np.mean(10*(9.88381228942903-np.exp((np.array(range(1, array_x.shape[1]+1)))*array_x)), axis=1) |
array_x[:,0]/8.895935412549363*np.prod(array_x+(np.array(range(1, array_x.shape[1]+1))), axis=1)-2.797043422870936 |
np.amax(10*(np.sin(2*np.pi*array_x-2.8520233833321362)), axis=1) |
np.mean(np.square(2.0972418655002882+array_x-(np.dot(array_x, np.array([[0.8531412148416105, 0.713772273697274, 0.352879297550439, 0.3142643761131255, 0.25279249984044727, 0.9090041692456536, 0.17766766510495413, 0.15952006060125024, 0.8718294706618331, 0.15359359810612294], [0.5835001876334945, 0.5893255224932048, 0.2833250660039379, 0.886186277009785, 0.10501490969937477, 0.068821145915829, 0.9246417544858483, 0.0014778825648895655, 0.5744565729336933, 0.7901830032888745], [0.1505894351400624, 0.4313011763435469, 0.5424148734829121, 0.8973763943527716, 0.524274518784462, 0.04710755609802808, 0.879127628414111, 0.15695442376436763, 0.9869687386861594, 0.7402061766355174], [0.6955174748346699, 0.21478963511484273, 0.2375385799313653, 0.7446952781764609, 0.6636158017028221, 0.9468108063385007, 0.49973651336511893, 0.7222129553288331, 0.5290584665092919, 0.8539554981488795], [0.24465898125035568, 0.8272326266532228, 0.6755960747870587, 0.07297486775403828, 0.8697875189629224, 0.5240638381622461, 0.523267993286765, 0.1894780827989483, 0.9028444472246833, 0.7965709279612965], [0.2902104200646207, 0.1952265161276442, 0.8161478904003309, 0.16929034432464485, 0.5474113530651655, 0.4584366902273702, 0.9240577757112414, 0.3752200228664201, 0.7269180168210346, 0.6880782065437135], [0.7782387213545098, 0.17641823071360274, 0.12253576520149445, 0.9277987465706097, 0.3435777168953016, 0.7577168075886688, 0.16130257577407014, 0.06636559990355861, 0.8580330327822083, 0.7081984252633259], [0.8580494010174052, 0.43318577673694847, 0.3479900431851418, 0.5089574709316798, 0.8731559661696816, 0.8774360760250637, 0.39948939605318545, 0.057332610481342194, 0.21707996838123145, 0.32789466617349083], [0.032688969355562536, 0.23285097125831355, 0.94281155673926, 0.9442057972543855, 0.4802036781470992, 0.6543583385507796, 0.3823749543645002, 0.11526525585833869, 0.0934082867905246, 0.6976522889497848], [0.05289620587720323, 0.6807327712305643, 0.5163590272355254, 0.9691087906445033, 0.2312393821460068, 0.855317410590987, 0.7442505646871682, 0.20168382953730246, 0.8961283418823434, 0.32984628111380543]])))-np.cumsum(np.round(array_x), axis=1)), axis=1)+np.sin(2*np.pi*np.mean(np.square(9.47789869753424+array_x-(np.dot(array_x, np.array([[0.5893839886648989, 0.2067549919159638, 0.8543969209596631, 0.816695289070698, 0.6243766350646663, 0.39840170662242935, 0.8722908358149332, 0.9765688538283201, 0.1659718529455324, 0.6497247659129568], [0.8660819352010993, 0.806658706071391, 0.007998776742098368, 0.3914113922134991, 0.5881580314392442, 0.03522854693348043, 0.6631826761820083, 0.24551446827674972, 0.7326557957357824, 0.062096610074202196], [0.4890217981144268, 0.09167894857274617, 0.5915055907921074, 0.6782921968351923, 0.4161004231587806, 0.24350818136824504, 0.43509588673467103, 0.8371710988100102, 0.22068334364130882, 0.34718359127971354], [0.5081802979192058, 0.8291812620548382, 0.11464871395165843, 0.3636129630064153, 0.03676609933235919, 0.7523702606705477, 0.9371605934118832, 0.10419372223257517, 0.9296952592772748, 0.29724212348793266], [0.14339307031522053, 0.7324172608512344, 0.24771398687763202, 0.6817837445470392, 0.9755957126539799, 0.7899141893479841, 0.18222470676447378, 0.6151584795963345, 0.14856119058769324, 0.33210563632961443], [0.07839300307914088, 0.5569207013941747, 0.24179266744268757, 0.9422631944691617, 0.6283702895324856, 0.1837087236628503, 0.5166769142865247, 0.2301843107259871, 0.9223879044145595, 0.7945251106512679], [0.9254764263928437, 0.896938216637443, 0.891551316667768, 0.4926465787671942, 0.07885420982012747, 0.42968087016447465, 0.47859404858071697, 0.2685853491736654, 0.06024878635242936, 0.6262540223052799], [0.11736854818646592, 0.009988305353825555, 0.5460663881376158, 0.4783126293963258, 0.24367594397464165, 0.48434132960025045, 0.6689536247914996, 0.6446896754284911, 0.23704650599651034, 0.15983195188863986], [0.26306529529126466, 0.607532682244668, 0.5892554463851525, 0.3480019032753702, 0.529596289088903, 0.13883001919842042, 0.5800373167996764, 0.42640001102739, 0.6840969209167657, 0.9392631781032924], [0.08925789672665352, 0.7646820841861308, 0.06237256867436247, 0.8092989155030703, 0.4217805415752274, 0.34578786886711577, 0.3314763869406302, 0.12666188475393314, 0.7603052262981488, 0.7313064374459344]])))-np.cumsum(np.round(array_x), axis=1)), axis=1)) |
np.mean(array_x*7.1605495497850775+7.1028594496398405*10*(5.611540446278784-array_x+5.60182119431045)-np.round(array_x+4.598350274079122)/2.0205957974679514-(np.dot(array_x, np.array([[0.7120608528131298, 0.7586404563368405, 0.4757427842712212, 0.3749175427146615, 0.5048804440732265, 0.015112462216593792, 0.0610627501905151, 0.4220793134921669, 0.10854148530814889, 0.5140015959259647], [0.754271050601452, 0.8609465796164966, 0.9282282903323652, 0.9942373376047103, 0.8522872829816324, 0.7130604983632695, 0.1749521021560584, 0.6574359937886186, 0.8989784858080986, 0.977536663053211], [0.9747513273779711, 0.2392803317465474, 0.6855992180488762, 0.5138049439634952, 0.42989913463563756, 0.4005841741693371, 0.49260515732425947, 0.6397644769028147, 0.5575643153316884, 0.8819646278741708], [0.5727830742338187, 0.18846665875987434, 0.254470463752406, 0.7690289046201926, 0.6285025546720269, 0.6788723542389805, 0.0500252321015463, 0.6475986449033471, 0.07196004275853407, 0.9326275357436868], [0.6365033836570149, 0.7228035262311241, 0.06607654054580447, 0.9969076834868789, 0.07443352603653253, 0.14148534613417285, 0.6246826124298566, 0.6377974368291194, 0.710500585454235, 0.44444466900356694], [0.7140962654317312, 0.3728165734830211, 0.4281059678699529, 0.4267273257436629, 0.4300250383015727, 0.2402952420747516, 0.527006864574748, 0.562240438451545, 0.4854115267622494, 0.5320680870855119], [0.6439439868117163, 0.6553511550942098, 0.9492480620763162, 0.6850450662242219, 0.6872935096874133, 0.4916214342272065, 0.9820655385137101, 0.6711483540543677, 0.4899938819760712, 0.7276363273934238], [0.6632371169426767, 0.3587243230799554, 0.885169527991546, 0.9465561837056888, 0.18721506030279933, 0.11948266853945622, 0.9892405737330077, 0.21395557580097446, 0.10584762619547639, 0.4640093337290647], [0.7002085298306124, 0.4385278723138333, 0.12310959052163828, 0.25845048668893644, 0.5780109172779443, 0.2201679826979155, 0.6054525760696434, 0.6923198610060379, 0.7745257151315319, 0.5919783595750323], [0.17466089901195359, 0.27621829065206915, 0.8243423068746478, 0.6863688963994085, 0.4849068660680894, 0.027897753250398116, 0.6911928665928099, 0.9560251479601565, 0.8152261892510665, 0.38775071363747726]]))), axis=1) |
np.mean(np.exp(3.2159188181379403-array_x*8.737434170222937/3.2923463861139353*(np.array(range(1, array_x.shape[1]+1)))+4.049750063476968-abs(4.434182377995796)), axis=1) |