Mpj. bSrSSKrSSKrSSKrSSKJr SSKJr SSK J r SSK J r SSK JrJrJr SSK Jr SS KJr SS KJrJrJr S r\R4"\R6"SS S 55R8r\R4"/SQ5R8r\R>"\"\5RA5S:\!S9r"\"\5RA5r#\RH"\"RJ\!S9r&S\&\#S:'S\&\#S:\#S:-'S\&\#S:'\"SSS9r'\"SS9\'\"SSS9\"SS5\"SSS9-/r(\(Vs/sH o\':wdM UPM snr)\RTRWS\(5S5r,Sr-\RTRWS\)5S5r.\RTRWS\(5S5r/\RTRWS\(5S 5r0\RTRWS\)5S!5r1\RTRe\3S"S#9\RTRWS\)5\RTRWS$\Rh"S%S&S'55S(555r5S)r6\RTRWS\)5S*5r7\RTRWS\(5S+5r8\RTRWS\(5S,5r9S-r:\RTRWS.S\"S50\;S/4/5S05r<\RTRWS\(5S15r=S2r>S3r?gs snf)4z+Testing for Gaussian process classificationN) approx_fprime)clone)ConvergenceWarning)GaussianProcessClassifier)RBFCompoundKernel WhiteKernel)ConstantKernel) MiniSeqKernel)assert_allcloseassert_almost_equalassert_array_equalc.[R"U5$)N)npsin)xs c/var/www/html/pdf-tiff/venv/lib/python3.13/site-packages/sklearn/gaussian_process/tests/test_gpc.pyfrs 66!9 )@g@g@g@g@dtypegffffffֿgffffff??fixed length_scalelength_scale_boundsg?)r )MbP?@@g{Gz?Y@kernelc[US9R[[5n[ UR [5UR [5SS2S4S:5 g)Nr&r?)rfitXyrpredict predict_probar&gpcs rtest_predict_consistentr17sF $6 2 6 6q! s`A $%A g >F #6 2 6 6q r?r@r/s rtest_lml_precomputedrDPsI $6 2 6 6q! r )r&r0 input_thetas rtest_lml_without_cloning_kernelrKYsh $6 2 6 6q! r?r@rallabsbounds)r&r0lml lml_gradients rtest_converged_to_local_maximumrScs $6 2 6 6q! $test_lml_gradient..{s#, n0M,s( (r(T eval_gradientg& .>c(>TRUS5$)NF)r>)r@gprs r#test_lml_gradient..sc11%?r)epsilonrMd)rtolatol) rnext get_params set_paramsrr*r+r,r>r@rcopyr )r&r length_scale_param_name_rRrflml_gradient_approxrcs @rtest_lml_gradientrrqs6]F"#**,# @0?@ $6 2 6 6q! r?r@finfofloat32eps) global_random_seed n_samples n_featuresrngr+r,r&last_lmlrwgprQs rtest_random_startsrs""I ))   2 3C )(1,q0A A A!2!2!2!: :a?A sK 3Vj({mj>X$FwH %a &!5+  #a) (()9)9: 4 8 88888!)rc^U4Sjn[XS9nUR[[5 UR UR R 5UR UR 5:deg)Nc X>[RRT 5nUU"USS9pT[S5Hqn[R"UR [R "SUSS2S45[R"SUSS2S4555nU"USS9nX:dMoXxpTMs XE4$)NFr`rrr)rryrzr atleast_1duniformmaximumminimum) obj_func initial_thetarPr theta_optfunc_minrpr@rrs r optimizer(test_custom_optimizer..optimizersii##$67  ]% 8rAMM BJJr6!Q$<8"**QqRSt :UVEe4A|&+8 ""r)r&r)rr*r+y_mcr>r?r@)r&rrr0s ` rtest_custom_optimizerrs^ # $6 GCGGAt  & &   $ $V\\ 2 33 3rc[US9nUR[[5 UR [ 5n[ URS5S5 UR[ 5n[[R"US5U5 g)Nr(r) rr*r+rr.X2r r|r-rrargmax)r&r0y_proby_preds rtest_multi_classrs` $6 2CGGAt   r "F 1 q) [[_Fryy+V4rc[US9nUR[[5 [USS9nUR[[5 UR [ 5nUR [ 5n[ X45 g)Nr(r)r&n_jobs)rr*r+rr.rr )r&r0gpc_2ry_prob_2s rtest_multi_class_n_jobsrs^ $6 2CGGAt %VA >E IIa   r "F""2&H)rcZ[SS/S9n[US9nSn[R"[US9 UR [ [5 SSS5 [SS/S9[SS /S9-n[US9n[R"S S 9n[R"S 5 UR [ [5 [U5S :Xde[USR[5(deUSRR SS:Xde[USR[5(deUSRR SS:XdeSSS5 ["R$"[ S 5n[SS/SS/S9n[US9n[R"S S 9n[R"S 5 UR U[5 [U5S :Xde[USR[5(deUSRR SS:Xde[USR[5(deUSRR SS:XdeSSS5 g!,(df  GN4=f!,(df  GN;=f!,(df  g=f)Ngh㈵>r")r!r(zThe optimal value found for dimension 0 of parameter length_scale is close to the specified upper bound 0.001. Increasing the bound and calling fit again may find a better value.match)noise_level_boundsr#gj@T)recordalwaysrrzThe optimal value found for dimension 0 of parameter k1__noise_level is close to the specified upper bound 0.001. Increasing the bound and calling fit again may find a better value.rzThe optimal value found for dimension 0 of parameter k2__length_scale is close to the specified lower bound 1000.0. Decreasing the bound and calling fit again may find a better value.rrg$@r%rzThe optimal value found for dimension 0 of parameter length_scale is close to the specified upper bound 100.0. Increasing the bound and calling fit again may find a better value.zThe optimal value found for dimension 1 of parameter length_scale is close to the specified upper bound 100.0. Increasing the bound and calling fit again may find a better value.)rrpytestwarnsrr*r+r,r warningscatch_warnings simplefilterlen issubclasscategorymessageargsrtile) r&r0warning_message kernel_sumgpc_sumrX_tile kernel_dimsgpc_dimss rtest_warning_boundsrsy dD\ 2F #6 2C  ( @ 1  At = #JAJ(z:G   -h' Aq6{a&),,.@AAAA 1I   " "1 %*1 1  1&),,.@AAAA 1I   " "1 %*1 1  1% .4WWQ]FC:C:NK( Checks that the latent mean and variance have the right shape.r(rN)rr*r+r,latent_mean_and_variancerH)r&r0 latent_meanlatent_variances r'test_gpc_latent_mean_and_variance_shaper3sl $6 2CGGAqM$'#?#?#B K    -- -  QWWQZM 11 1rc[[5S9nUR[[5 [ R "[SS9 UR[5 SSS5 g!,(df  g=f)rr(zdReturning the mean and variance of the latent function f is only supported for binary classificationrN) rrr*r+rrrT ValueErrorr)r0s rAtest_gpc_latent_mean_and_variance_complain_on_more_than_2_classesr?sR #35 1CGGAt 6  $$Q'    s A$$ A2c/SQn[R"/SQ5n[SS9n[US9R X5nUR U5 g)Nr3r7rr8r()rr:r rr*rr;s r9test_latent_mean_and_variance_works_on_structured_kernelsrMsCA $%A g >F #6 2 6 6q rsx1  (1> OMM"++aR()++]],-//HHQqTZZ\A S)qTZZ\ xxs#R%Z$%bEkb4i !R$YA SSk:c;#3KPP   +2L'|5KV'L7+J,J J#4567+,7+;,;#45 6   F#45RB)?@VA6  V*.#4536347+ 5, 57+ *, *F R!~a( )  /   7+2,2 ($sMs 6 L,L,