jVddlZddlmZddlmZddlZddlmZddl m Z m Z m Z m Z mZmZddlmZmZddlmZddlmZmZdd lmZmZdd lmZmZmZdd lm Z d6d Z!e"d fdZ#ee!dZ$d7dZ%dZ&Gdde'Z(Gdde e Z)Gdde e Z*Gdde e Z+Gdde e Z,Gdde,Z-Gdd e,Z.Gd!d"e,Z/Gd#d$ee Z0Gd%d&e Z1d8d'Z2Gd(d)eZ3Gd*d+eeZ4Gd,d-e4eZ5Gd.d/e e e Z6Gd0d1e e e Z7Gd2d3e e e Z8Gd4d5e ee Z9dS)9N) defaultdict)partial)assert_array_equal) BaseEstimatorClassifierMixinMetaEstimatorMixinRegressorMixinTransformerMixinclone)_Scorermean_squared_error)BaseCrossValidator) GroupKFoldGroupsConsumerMixin)METHODSSIMPLE_METHODS)MetadataRouter MethodMappingprocess_routing)_check_partial_fit_first_callTc gd}tj}dx}}t|D] \}}|jtdgzvr |j}n!||dzdD]}|jt|zvr|j}|p |dj}|p |dj}t |dst d|_|sd|D}|j|| |dS) zUtility function to store passed metadata to a method of obj. If record_default is False, kwargs whose values are "default" are skipped. This is so that checks on keyword arguments whose default was not changed are skipped. )cross_validatecross_val_scorecross_val_predictlearning_curvepermutation_test_scorevalidation_curveNconsuming_metric_recordsc*ttSN)rlist/Users/tedpeters/Documents/Projects/Claude Projects/Misc Tools/notename-sheets/.venv/lib/python3.11/site-packages/sklearn/tests/metadata_routing_common.pyz!record_metadata..@s;t+<+<r&cPi|]#\}}t|tr|dk ||$S)default isinstancestr).0keyvals r' z#record_metadata..BsG   Sc3'' -09,<,< ,<,<,W(:';; ; ;^F E <q1uww$$ >W';; ; ;^F  (uQx(F  (uQx(F 3 # #>"#<#<==    "LLNN    L ''/////r&c tt|dt|t|t}|sBJd|jjd|d|dd|jDd |D]}t| t| ks4Jd| d | |s~|D]\}} ||} ||vr,| *tj | |  sJ=t| tjrt| | h| | usJd| d | d |d S) aCheck whether the expected metadata is passed to the object's method. Parameters ---------- obj : estimator object sub-estimator to check routed params for method : str sub-estimator's method where metadata is routed to, or otherwise in the context of metadata routing referred to as 'callee' parent : str the parent method which should have called `method`, or otherwise in the context of metadata routing referred to as 'caller' split_params : tuple, default=empty specifies any parameters which are to be checked as being a subset of the original values **kwargs : dict passed metadata r!z1No overlapping records. Checked routing for obj `z` with callee: `z `, caller: `z*`; records exist for callee-caller pairs: c&g|]\}}|D]}||fSr%r%)r.k1dk2s r' z+check_recorded_metadata..cs-JJJAJJ"B8JJJJr&.z Expected z, got Nz vs z . Method: )getattrdictgetr$ __class____name__r!r7setkeysnpisinallr,ndarrayr) r9methodparent split_paramspreserves_metadatar;recordsrecordr/valuerecorded_values r'check_recorded_metadatar\Js*c:tvv..226466BBFFvtvvVVG  NCM}||vrt ||}d|jD}|rJ?dS)aCheck if a metadata request dict is empty. One can exclude a method or a list of methods from the check using the ``exclude`` parameter. If metadata_request is a MetadataRouter, then ``exclude`` can be of the form ``{"object" : [method, ...]}``. N)excludecFg|]\}}t|ts||Sr#r+)r.propaliass r'rGz+assert_request_is_empty..s@   e%%% */): ):):):r&)r,rassert_request_is_emptyrouterrrIrequestsr7)metadata_requestr^name route_mapping_excluderTmmrpropss r'rbrbs"N33#3 L L D-"tw"4= #M$8( K K K K KObbG   W   &//  "|1133    y  r&cD]"\}}t||}|j|ksJ#fdtD}|D]&}t t||jrJ'dS)Ncg|]}|v| Sr%r%)r.rT dictionarys r'rGz(assert_request_equal..s#UUUF*.s>>>A1;/>>>r&z).)rnrzs r'__repr__z_Registry.__repr__sD C3t99 C C>>>>> C C C r&N)rM __module__ __qualname__rwr{rr%r&r'rsrssA      r&rsc:eZdZdZd dZd dZd dZd dZd dZdS) ConsumingRegressoracA regressor consuming metadata. Parameters ---------- registry : list, default=None If a list, the estimator will append itself to the list in order to have a reference to the estimator later on. Since that reference is not required in all tests, registration can be skipped by leaving this value as None. Nc||_dSr#registryrurs r'__init__zConsumingRegressor.__init__   r&r*cl|j|j|t||||SN sample_weightmetadatarr8record_metadata_not_defaultruXyrrs r' partial_fitzConsumingRegressor.partial_fitE = $ M  & & &#       r&cl|j|j|t||||Srrrs r'fitzConsumingRegressor.fitrr&clt|||tjt|fS)Nrshape)rrPzerosrnrs r'predictzConsumingRegressor.predicts=#      xs1vvi((((r&c*t|||dSNrrrrs r'scorezConsumingRegressor.score'#      qr&r#r*r*Nr*r*) rMrr__doc__rrrrrr%r&r'rrs  !!!!)))) r&rc@eZdZdZd dZdZd dZdZdZd Z d Z dS) NonConsumingClassifier5A classifier which accepts no metadata on any method.c||_dSr#)alpha)rurs r'rzNonConsumingClassifier.__init__s  r&cjtj||_tj||_|Sr#)rPuniqueclasses_ ones_likecoef_rurrs r'rzNonConsumingClassifier.fits% !  \!__  r&Nc|Sr#r%)rurrclassess r'rz"NonConsumingClassifier.partial_fitrxr&c,||Sr#)rrurs r'decision_functionz(NonConsumingClassifier.decision_functions||Ar&ctjt|f}d|dt|dz<d|t|dzd<|S)Nrrr r)rPemptyrn)rury_preds r'rzNonConsumingClassifier.predictsQQ *** !}Q1} !s1vv{}} r&c6tjt|t|jftj}tjtjt|jt||dd<|S)Nrdtypersize)rPrrnrfloat32random dirichletones)rury_probas r' predict_probaz$NonConsumingClassifier.predict_probasr(#a&&#dm*<* NNXNNNr&rc(eZdZdZedZdS))ConsumingClassifierWithoutPredictLogProbazConsumingClassifier without a predict_log_proba method, but with predict_proba. Used to mimic dynamic method selection such as in `BaggingClassifier.predict_log_proba()`. c tdNz1This estimator does not support predict_log_probarrzs r'rz;ConsumingClassifierWithoutPredictLogProba.predict_log_proba~PQQQr&N)rMrrrrrr%r&r'rrws> RRXRRRr&rc>eZdZdZedZedZdS)"ConsumingClassifierWithOnlyPredictzConsumingClassifier with only a predict method. Used to mimic dynamic method selection such as in `BaggingClassifier.predict_log_proba()`. c tdrrrzs r'rz0ConsumingClassifierWithOnlyPredict.predict_probarr&c tdrrrzs r'rz4ConsumingClassifierWithOnlyPredict.predict_log_probarr&N)rMrrrrrrr%r&r'rrs\ NNXNRRXRRRr&rc:eZdZdZd dZd dZd dZd dZd dZdS) ConsumingTransformera~A transformer which accepts metadata on fit and transform. Parameters ---------- registry : list, default=None If a list, the estimator will append itself to the list in order to have a reference to the estimator later on. Since that reference is not required in all tests, registration can be skipped by leaving this value as None. Nc||_dSr#rrs r'rzConsumingTransformer.__init__rr&r*cz|j|j|t|||d|_|S)NrT)rr8rfitted_rs r'rzConsumingTransformer.fitsL = $ M  & & &#        r&c0t||||dzSrrrs r' transformzConsumingTransformer.transform+#      1u r&ct|||||||||||Sr)rrrrs r' fit_transformz"ConsumingTransformer.fit_transforms] $      xx1MHxMMWW ]XX   r&c0t||||dz Srrrs r'inverse_transformz&ConsumingTransformer.inverse_transformrr&r#rrNN) rMrrrrrrrrr%r&r'rrs  !!!!     r&rc*eZdZdZddZddZddZdS) "ConsumingNoFitTransformTransformerzA metadata consuming transformer that doesn't inherit from TransformerMixin, and thus doesn't implement `fit_transform`. Note that TransformerMixin's `fit_transform` doesn't route metadata to `transform`.Nc||_dSr#rrs r'rz+ConsumingNoFitTransformTransformer.__init__rr&cl|j|j|t||||Sr)rr8rArs r'rz&ConsumingNoFitTransformTransformer.fits: = $ M  & & &MHMMMM r&c*t||||Sr)rArs r'rz,ConsumingNoFitTransformTransformer.transformsMHMMMMr&r#NNNr)rMrrrrrrr%r&r'rrs\QQ!!!!r&rc ||nt}|||t|fi||dd}t |||S)Nrr)rr8rrKr )ry_truerscorerr;holderrs r'rrsi)VV/?F11&111JJ55M ffM J J JJr&c eZdZdfd ZxZS)ConsumingScorerNc||_tt||}t|diddS)N)rrrr) score_funcsignr;response_method)rrrsuperr)rurrrLs r'rzConsumingScorer.__init__sS  -NNN  !"i      r&r#)rMrrr __classcell__)rLs@r'rrs=          r&rc.eZdZddZddZd dZd dZdS) ConsumingSplitterNc||_dSr#rrs r'rzConsumingSplitter.__init__rr&r*c#:K|j|j|t|||t|dz}t t d|}t t |t|}||fV||fVdS)N)groupsrr r)rr8rrnr$range)rurrrr split_index train_indices test_indicess r'splitzConsumingSplitter.splits = $ M  & & &#D(KKKK!ffk U1k2233 E+s1vv6677 M))))\))))))r&cdS)Nr r%)rurrrrs r' get_n_splitszConsumingSplitter.get_n_splitssqr&c#Kt|dz}ttd|}tt|t|}|V|VdS)Nr r)rnr$r)rurrrrrrs r'_iter_test_indicesz$ConsumingSplitter._iter_test_indicessg!ffk U1k2233 E+s1vv6677 r&r#r)NNNNr)rMrrrrrrr%r&r'r r sd!!!! * * * *r&r ceZdZdZdS))ConsumingSplitterInheritingFromGroupKFoldz\Helper class that can be used to test TargetEncoder, that only takes specific splitters.N)rMrrrr%r&r'rr sr&rc$eZdZdZdZdZdZdS) MetaRegressorz(A meta-regressor which is only a router.c||_dSr#) estimator)rurs r'rzMetaRegressor.__init__s "r&c t|dfi|}t|jj||fi|jj|_dSNr)rr rr estimator_rurr fit_paramsparamss r'rzMetaRegressor.fitsK u;; ;;3%//3AqQQFr=rmethod_mapping)raddrrrurcs r'get_metadata_routingz"MetaRegressor.get_metadata_routingsMd+++//n(??..eE.JJ0   r&NrMrrrrrr-r%r&r'rrsJ22###RRRr&rc.eZdZdZddZddZdZdZdS)WeightedMetaRegressorz*A meta-regressor which is also a consumer.Nc"||_||_dSr#rrrurrs r'rzWeightedMetaRegressor.__init__$"  r&c |j|j|t||t|dfd|i|}t |jj||fi|jj|_|SNrrrrr8rArr rrr )rurrrr"r#s r'rzWeightedMetaRegressor.fit(s = $ M  & & &M:::: uXXMXZXX3%//3AqQQFr>CsQOO!!!!     r&r>c.eZdZdZdZddZddZdZdS)MetaTransformerzA simple meta-transformer.c||_dSr#) transformer)rurEs r'rzMetaTransformer.__init__bs&r&Nc t|dfi|}t|jj||fi|jj|_|Sr)rr rEr transformer_r!s r'rzMetaTransformer.fitesN u;; ;;7E$"23371WW@R@VWW r&c Xt|dfi|}|jj|fi|jjS)Nr)rrGrrE)rurrtransform_paramsr#s r'rzMetaTransformer.transformjs> {GG6FGG*t *1MM0B0LMMMr&ct||jtddddS)Nr&rr(r)rEr*)rr+rErrzs r'r-z$MetaTransformer.get_metadata_routingnsYD)))--((?? SeS , , S KS 8 8 .   r&r#)rMrrrrrrr-r%r&r'rCrC_sd$$''' NNNN     r&rC)Tr#r):r2 collectionsr functoolsrnumpyrP numpy.testingr sklearn.baserrrr r r sklearn.metrics._scorerr r sklearn.model_selectionrsklearn.model_selection._splitrr sklearn.utils._metadata_requestsrrsklearn.utils.metadata_routingrrrsklearn.utils.multiclassrrAtupler\rrbrqr$rsrrrrrrrrrrrr rrr0r>rCr%r&r'rWs######,,,,,,@???????666666JJJJJJJJ CBBBBB(0(0(0(0X',egg$////d&goeLLL::::        &++++++++\ % % % % %_m % % %F     NM   QQQQQ/=QQQh N N N N N-@ N N N R R R R R0C R R R R R R R R)< R R R /////+]///d* K K K K     g   +-?60A: & $. D/-8     (*:M     r&