:jAddlZddlZddlZddlmZddlmZmZddl m Z m Z m Z ddl mZddlmZmZddlmZddlmZdd lmZmZdd lmZmZdd lmZe d \ZZeedZeddeddcZ Z!ejDjGdedfeddgfeddfedddgfedfedfeddgfgdZ$ejDjGdedfedddfedddfeddddgfeddfeddfedddgfgejDjGdd dgdZ%ejDjGdgddZ&ejDjGddd gd!Z'ejDjGdd dgd"Z(ejDjGdd dgejDjGddd gd#Z)ejDjGd$ee e!d%dd&ifee e!d'd&d(d)feeed*ddifgd+Z*ejDjGdd dgd,Z+ejDjGdd dgd-Z,ejDjGdedd.dfedd.d fedfgd/Z-d0Z.ejDjGdgd1d2Z/d3Z0ejDjGd4edd5d6fedd5d6fedd5d6fedd7d6fedd7d8fedd7d8feedd9d:feedd9d:feedd9d:fedd5d6fedd7d6fedd5d6fedd7d6feddd5d6fed;dd7d6fgd<Z1y)=N)clone)DBSCANKMeans) load_irismake_classificationmake_multilabel_classification)IsolationForest)LinearRegressionLogisticRegression)ClassifierChain)scale)DecisionTreeClassifierDecisionTreeRegressor)_get_response_values_get_response_values_binary)assert_allcloseT) return_X_yF)copydzestimator, response_method predict_probadecision_function) n_clusterspredictscorecLtjjdjddtjddgdz}}t |j ||}d}tjt|5t|||d d d y #1swYy xYw) z;Check the error message with not supported response method.r rz%has none of the following attributes:matchresponse_methodN) nprandom RandomStaterandnarrayrfitpytestraisesAttributeErrorr) estimatorr#Xyerr_msgs v/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/sklearn/utils/tests/test_response.py#test_estimator_unsupported_responser2s 99  # ) )"a 0"((Aq6A:2FqAi $$Q*I5G ~W 5   +    s BB#)r random_stater3return_response_method_usedctjjdjddtjddgdz}}t |j ||}t||||}t|tr|dn|}t||}t|d|||dJ|r |d|k(sJyy)z.Check the behaviour of `_get_response_values`.rrrrrr#r5N) r$r%r&r'r(rr)r isinstancelistgetattrr)r-r#r5r.r/resultschosen_response_methodprediction_methods r1"test_estimator_get_response_valuesr>4s" 99  # ) )"a 0"((Aq6A:2FqAi $$Q*I" '$? G)$?_ +ABGAJ 1! 45 1:  "qz3333#r#)rrrpredict_log_probactddd\}}tj||}d}tjt |5t |||dd d d y #1swYy xYw) zVCheck that `_get_response_values` raises the proper error message with classifier.rrr n_samples n_classesr3zDpos_label=whatever is not a valid label: It should be one of \[0 1\]r whateverr# pos_labelN)rr r)r*r+ ValueErrorr)r#r.r/ classifierr0s r15test_get_response_values_classifier_unknown_pos_labelrJWsj qq IDAq#%))!Q/JVG z 1   +     s A""A+r@ctddd\}}tj|}tj ||}d}t j t|5t|||dddy#1swYyxYw) zpCheck that `_get_response_values` will raise an error when `y_pred` has a single class with `predict_proba`.rrrrBzJGot predict_proba of shape \(10, 1\), but need classifier with two classesr r"N) rr$ zeros_likerr)r*r+rHr)r#r. y_two_classy_single_classrIr0s r1Htest_get_response_values_classifier_inconsistent_y_pred_for_binary_probarOlsy )2QRSNA{]];/N')--a@J   z 1MZOLMMMs A66A?ctddddgd\}}tj||}d}t|||d| }t |d|j ||d d k(sJ|r |ddk(sJt||||j d| }t |d|j |d z|d dk(sJ|r |ddk(sJyy) zaCheck the behaviour of `_get_response_values` with `decision_function` and binary classifier.rr333333?ffffff?rrCrDweightsr3rNr#rGr5r)rr r)rrrclasses_)r5r.r/rIr#r;s r1>r?z estimator, X, y, err_msg, paramsz.Expected 'estimator' to be a binary classifierautozCpos_label=unknown is not a valid label: It should be one of \[0 1\]unknownrFz.be a binary classifier. Got 3 classes instead.ct|j||}tjt|5t ||fi|dddy#1swYyxYw)zMCheck that we raise the proper error messages in _get_response_values_binary.r N)rr)r*r+rHr)r-r.r/r0paramss r1test_get_response_errorrcsM:i $$Q*I z 1<#Iq;F;<<(*=>$( *&FI FJ44X>q!tDE >> o -- -*>,o>$( *&FI FJ88BC >> 1 11 1r?)rrrctd\}}ttj||}t |||\}}|J|j |j k(sJ|dk(r-t j|dk\|dkjsJy|dk(r1|dkjdkDsJ|dkDjdkDsJyt j|dk(|dk(jsJy)Nrr4r"rrr) rr r r)rrmr$rnrosum logical_or)r#r.Yr-r\rGs r1-test_get_response_values_multilabel_indicatorrxas *q 9DAq 2 4599!Q?I,1oFI    <<177 "" "/)~~fk6Q;7;;=== / / !A%%% !A%%%}}Vq[&A+6::<< 50% of samples" warning should not be raised when calling `type_of_target(classes_)`. Non-regression test for issue #31583. rxrZerrorrr"N) r$r%r&r'repeataranger r)warningscatch_warnings simplefilter UserWarningr)r.r/clfs r19test_response_values_type_of_target_on_classes_no_warningrxs a &&sA.A "))B-#A   " "1a (C  "Fg{3S!_EFFFs )B99Cz7estimator, response_method, target_type, expected_shapebinary)r multiclass)rr| multilabel)rrr|cltjjdjdd}|dk(rtjddgdz}n(|dk(rgd}ntjddgddggdz}t |j ||}t||| \}}|j|k(sJy ) a Check that output shape corresponds to docstring description - for binary classification, it is a 1d array of shape `(n_samples,)`; - for multiclass classification - with response_method="predict", it is a 1d array of shape `(n_samples,)`; - otherwise, it is a 2d array of shape `(n_samples, n_classes)`; - for multilabel classification, it is a 2d array of shape `(n_samples, n_outputs)`; - for outlier detection, regression and clustering, it is a 1d array of shape `(n_samples,)`. rrrrrrr) rrrrZrrrrZrZrr"N) r$r%r&r'r(rr)rrm)r-r# target_typeexpected_shaper.r/r\r]s r1"test_response_values_output_shape_rsN a &&r1-Ah HHaVaZ   $ * HHq!fq!f%) *i $$Q*I$Y?SIFA <<> )) )r?)2rnumpyr$r* sklearn.basersklearn.clusterrrsklearn.datasetsrrrsklearn.ensembler sklearn.linear_modelr r sklearn.multioutputr sklearn.preprocessingr sklearn.treerrsklearn.utils._responserrsklearn.utils._testingrr.r/rerfmark parametrizer2r>rJrOrXr^rcrhrjrqrsrxrrr?r1rs  * -E/'FU2D!1 !%tWag(  /2  ?4G"HI 1 / 1 1DEF 9  O,  _g67        Y' 11 -y9 11 -w7 11 - 7/CD a ()4 a (*=> a (+> *JK 6u F4G 4,J  "*_>Q,RSMTM"6u F&1G&1R6u F*_>Q,RS&TG&R& " #   <  '   # $   R &Y ?   # $ <  0  4<54<6u F-G-66u F1G16 !! QR  23**"26H==(F*=  y(E:  %@  2HeD  y,>   gF  2L'J +- . <Q +- .wW .0 1      Ix7  I|U;  )Xu=  )\5A 1 y(E: 1 y,>)2*32*r?