8^j. dZddlZddlZddlZddlmZddlmZddl m Z ddl m Z ddl mZmZmZddl mZdd lmZdd lmZmZmZd Zej4ej6dd d j8Zej4gdj8Zej>eejAdkDe!Z"eejAZ#ejHe"jJe!Z&de&e#dk<de&e#dk\e#dkz<de&e#dkD<eddZ'ede'eddeddeddzgZ(e(Dcgc] }|e'k7s | c}Z)ejTjWde(dZ,dZ-ejTjWde)dZ.ejTjWde(dZ/ejTjWde(d Z0ejTjWde)d!Z1ejTjee3d"#ejTjWde)ejTjWd$ejhd%d&d'd(Z5d)Z6ejTjWde)d*Z7ejTjWde(d+Z8ejTjWde(d,Z9d-Z:ejTjWd.dedie;d/fgd0Zd3Z?ycc}w)4z+Testing for Gaussian process classificationN) approx_fprime)clone)ConvergenceWarning)GaussianProcessClassifier)RBFCompoundKernel WhiteKernel)ConstantKernel) MiniSeqKernel)assert_allcloseassert_almost_equalassert_array_equalc,tj|S)N)npsin)xs r/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/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@kernelct|jtt}t |j t|j tdddfdk\y)Nr&r?)rfitXyrpredict predict_probar&gpcs rtest_predict_consistentr17sF $6 2 6 6q! sbA $%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 $6 2 6 6q! z$test_lml_gradient..{s # n0M#s  r(T eval_gradientg& .>c(j|dS)NF)r>)r@gprs rz#test_lml_gradient..sc11%?r)epsilonrMd)rtolatol) rnext get_params set_paramsrr*r+r,r>r@rcopyr )r&r length_scale_param_name_rRrdlml_gradient_approxrbs @rtest_lml_gradientrpqs6]F"#**,#F@0,?@ $6 2 6 6q! r?r@finfofloat32eps) global_random_seed n_samples n_featuresrngr+r,r&last_lmlrugprQs rtest_random_startsrs/"Iz ))   2 3C )Z(1,q0A A A!2!2!2!: :a?A sK 3Vj({mj>X$FwH %a &!5+  #a) (()9)9:X 4 8 88888rcfd}t||}|jtt|j |j j |j |j k\sJy)Nc `tjj }|||d}}tdD]q}tj|j tj d|dddftjd|dddf}||d}||ksn||}}s||fS)NFr_rrr)rrwrxr} atleast_1duniformmaximumminimum) obj_func initial_thetarPr theta_optfunc_minrnr@rrs r optimizerz(test_custom_optimizer..optimizersii##$67  ]% 8 r /AMM BJJr6!Q$<8"**QqRSt :UVEe4A8|&+Q8  /(""r)r&r)rr*r+y_mcr>r?r@)r&rrr0s ` rtest_custom_optimizerrs` # $6Y GCGGAt  & &   $ $V\\ 2 33 3rct|}|jtt|j t }t |jdd|jt }ttj|d|y)Nr(r) rr*r+rr.X2r rzr-rrargmax)r&r0y_proby_preds rtest_multi_classrs` $6 2CGGAt   r "F 1 q) [[_Fryy+V4rc t|}|jttt|d}|jtt|j t }|j t }t ||y)Nr(r)r&n_jobs)rr*r+rr.rr )r&r0gpc_2ry_prob_2s rtest_multi_class_n_jobsrs` $6 2CGGAt %VA >E IIa   r "F""2&H)rc8tddg}t|}d}tjt|5|j t tdddtddgtdd gz}t|}tjd 5}tjd |j t tt|d k(sJt|djtsJ|djj ddk(sJt|djtsJ|djj ddk(sJ dddt#j$t d }tddgddg}t|}tjd 5}tjd |j |tt|d k(sJt|djtsJ|djj ddk(sJt|djtsJ|djj ddk(sJ dddy#1swY%xYw#1swY*xYw#1swYyxYw)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_boundsrs dD\ 2F #6 2C  ( @ 1 t = #JAJ(z:G   - h' Aq6{a&),,.@AAA 1I   " "1 %*1 1  1&),,.@AAA 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_shaper3sn $6 2CGGAqM$'#?#?#B K    -- -  QWWQZM 11 1rctt}|jttt j td5|jtdddy#1swYyxYw)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?sW #35 1CGGAt 6 ( $$Q' (((s A))A2cgd}tjgd}td}t|j ||}|j |y)Nr3r7rr8r()rr:r rr*rr;s r9test_latent_mean_and_variance_works_on_structured_kernelsrMsEA $%A g >F #6 2 6 6q! rs1  (1> OBMM+"++aR()++R]],-// BHHQqTZZ\A S)qTZZ\rxxs#R%Z$%bEkb4i !R$YA SSk:c;#3KPP   +2LV|5KVL7+J,J J#4567+,7+;,;#45 6   F#45RB)?@VA6  V*.#4536347+ 5, 57+ *, *F R!~a( )  /   7+2,2 ($sMs  L=L=