Ë WËh <ãóª—ddlZddlmZddlZddlmZddlmZddl m Z ddlmZddl mZdd lmZmZGd „d«Zd„Zd „Zd„Zd„Zd„Zd„Zd„Zy)éN)ÚMappingé)Úcheck_consistent_length)Úcheck_matplotlib_support)Ú_get_response_values_binary)Ú parse_version)Útype_of_target)Ú_check_pos_label_consistencyÚ_num_samplescó‚—eZdZdZdddœd„Zeddddœd„«Zeddddœd „«Zed „«Ze d„«Z e d„«Zy) Ú"_BinaryClassifierCurveDisplayMixinzØMixin class to be used in Displays requiring a binary classifier. The aim of this class is to centralize some validations regarding the estimator and the target and gather the response of the estimator. N)ÚaxÚnamec óÎ—t|jj›d«ddlm}|€|j«\}}|€t |dt |dd««}||j|fS)Nz.plotrÚestimator_namer)rÚ __class__Ú__name__Úmatplotlib.pyplotÚpyplotÚsubplotsÚgetattrÚfigure)ÚselfrrÚpltÚ_s úQ/var/www/html/jupyter_env/lib/python3.12/site-packages/sklearn/utils/_plotting.pyÚ_validate_plot_paramsz8_BinaryClassifierCurveDisplayMixin._validate_plot_paramssc€Ü D§N¡N×$;Ñ$;Ð#<¸EÐ!BÔCÝ'à ˆ:Ø—L‘L“N‰EˆAˆrðˆ<Ü˜4Ð!1´7¸4ÀÈÓ3NÓOˆDØ2—9‘9˜dÐ"Ð"óÚauto)Úresponse_methodÚ pos_labelrcó”—t|j›d«|€|jjn|}t||||¬«\}}|||fS)Nz.from_estimator)r r!)rrrr)ÚclsÚ estimatorÚXÚyr r!rÚy_preds rÚ!_validate_and_get_response_valueszD_BinaryClassifierCurveDisplayMixin._validate_and_get_response_values$sX€ô ! C§L¡L >°Ð!AÔBà/3¨|ˆy×"Ñ"×+Ò+Àˆä7ØØ Ø+Øô Ñˆ ðy $Ð&Ð&r)Ú sample_weightr!rcóÄ—t|j›d«t|«dk7rtdt|«›d«‚t |||«t||«}||nd}||fS)Nz.from_predictionsÚbinaryz The target y is not binary. Got ú type of target.Ú Classifier)rrr Ú ValueErrorrr )r#Úy_truer'r)r!rs rÚ!_validate_from_predictions_paramszD_BinaryClassifierCurveDisplayMixin._validate_from_predictions_params5sz€ô ! C§L¡L >Ð1BÐ!CÔDä˜&Ó! XÒ-ÜØ2´>À&Ó3IÐ2JðKðóð ô ¨° Ô>Ü0°¸FÓCˆ àÐ'‰t¨\ˆà˜$ˆÐrcó‡—t|j›d«ddh}tˆfd„|D««std|›d«‚t ‰ddd«t ‰dd d«}}t|«||zk7rtd ||z›dt|«›d«‚t |«d k7rtdt |«›d«‚t|||« t||«}|S#t$r)} tt| «jdd««‚d} ~ wwxYw)Nz.from_cv_resultsr$Úindicesc3ó&•K—|]}|‰v–—Œ yw)N©)Ú.0ÚkeyÚ cv_resultss €rú zV_BinaryClassifierCurveDisplayMixin._validate_from_cv_results_params..Usøèø€Ò>¨3˜*Ô$Ñ>ùsƒzB`cv_results` does not contain one of the following required keys: zr. Set explicitly the parameters `return_estimator=True` and `return_indices=True` to the function`cross_validate`.ÚtrainrÚtestz=`X` does not contain the correct number of samples. Expected z, got ú.r+z"The target `y` is not binary. Got r,r/r&)rrÚallr.Úlenrr rr ÚstrÚreplace) r#r7r%r&r)r!Ú required_keysÚ train_sizeÚ test_sizeÚes ` rÚ _validate_from_cv_results_paramszC_BinaryClassifierCurveDisplayMixin._validate_from_cv_results_paramsHsLø€ô ! C§L¡L >Ð1AÐ!BÔCà$ iÐ0ˆ ÜÓ>° Ô>Ô>ÜØTØ /ð"$ð$óð ô ˜9Ñ% gÑ.¨qÑ1Ó2Ü ˜9Ñ% fÑ-¨aÑ0Ó1ðˆ ô ˜‹?˜j¨9Ñ4Ò4ÜðØ&¨Ñ2Ð3°6¼,Àq»/Ð9JÈ!ðMóð ô ˜!Ó Ò(ÜØ4´^ÀAÓ5FÐ4GÐGWÐXóð ô 1 mÔ4ð <Ü4°YÀÓBˆIð Ðøô ò <äœS ›VŸ^™^¨H°cÓ:Ó;Ð;ûð <úsÃCÃ DÃ#$DÄDcóR—|||›d|›d|d›d}|S| |›d|d›}|S||}|Sd}|S)z;Helper to get legend label using `name` and `legend_metric`Nz (z = ú0.2fú)r4)Úcurve_legend_metricÚ curve_nameÚlegend_metric_nameÚlabels rÚ_get_legend_labelz4_BinaryClassifierCurveDisplayMixin._get_legend_labelvsz€ðÐ*¨zÐ/EØ!l "Ð%7Ð$8¸Ð`curve_kwargs` must be None, a dictionary or a list of length z. Got: r;rzfTo avoid labeling individual curves that have the same appearance, `curve_kwargs` should be a list of z‹ dictionaries. Alternatively, set `name` to `None` or a single string to label a single legend entry with mean ROC AUC score of all curves.Ngà?z--Úblue)ÚalphaÚ linestyleÚcolorÚmeanrÚstdéÿÿÿÿz +/- rFrGÚmetricrK)r.ÚwarningsÚwarnÚ FutureWarningÚ isinstanceÚlistr=r>rr rLÚextendÚzipÚappendÚ enumerateÚ_validate_style_kwargs)Ún_curvesrÚ legend_metricrJÚcurve_kwargsÚkwargsÚdefault_multi_curve_kwargsÚlabelsÚlabel_aggregaterHrIÚfold_idxrKÚ curve_kwargs_s rÚ_validate_curve_kwargsz9_BinaryClassifierCurveDisplayMixin._validate_curve_kwargsƒsw€ñJ™FÜð?óð ñ ÜM‰MðRäô ð "ˆLäl¤DÔ)¬c°,Ó.?À8Ò.KÜØPØ*˜G L >°ð4óð ô tœTÔ"ÜD“ ˜Q’Ü˜|¬TÔ2äð6Ø6>°Zð@OðOóð ôdœCÔ Ø6ˆDÜdœDÔ!¤c¨$£i°1¢nØ˜(‘?ˆDØ$( Lˆv˜Ò °dˆôl¤GÔ,Ø(˜>¨HÑ4ˆLà/2ÀÐPVÑ%WÐ"ØÐØ˜!Š|Ø :Ð;¸hÑF‘à "˜tàˆØ]Ñ"Ü@×RÑRØ˜fÑ% t¨A¡wÐ0BóˆOð ˜UÑ#Ð/à˜‘7Ð&à'¨¨Ð,°°}ÀUÑ7KÈDÐ6QÐQRÐ/SÑSñ$ð (¨E°-ÀÑ2FÀtÐ1LÐ*MÑMð$ð M‰M˜?Ð+¨t¨f¸À1¹Ñ.EÑEÕFä36°}ÀXÑ7NÐPTÓ3Uò Ñ/Ð# ZØ— ‘ Ü6×HÑHØ+¨ZÐ9Kóõð ô$-¨VÓ#4÷ á˜%ô # G¨UÐ#3°\À(Ñ5KÕLð ˆ ñ ðÐùó sÆ:G)rÚ __module__Ú__qualname__Ú__doc__rÚclassmethodr(r0rDÚstaticmethodrLrir4rrr r sˆ„ñð+/°Tô#ðà17À4Èdó'óð'ð à.2¸dÈóóðð$ñ+óð+ðZñ óð ðñvóñvrr có—||S|€|rdSdSt|«r|jn|}|r|jd«r|dd}nd|›}n|jd«rd|dd›}|jdd«}|j «S) aÁValidate the `score_name` parameter. If `score_name` is provided, we just return it as-is. If `score_name` is `None`, we use `Score` if `negate_score` is `False` and `Negative score` otherwise. If `score_name` is a string or a callable, we infer the name. We replace `_` by spaces and capitalize the first letter. We remove `neg_` and replace it by `"Negative"` if `negate_score` is `False` or just remove it otherwise. NzNegative scoreÚScoreÚneg_éz Negative rú )ÚcallablerÚ startswithr?Ú capitalize)Ú score_nameÚscoringÚnegate_scores rÚ_validate_score_namerzýs¡€ðÐØÐØ ˆÙ#/ÐÐ<°WÐ<ä)1°'Ô):W×%Ò%Àˆ ÙØ×$Ñ$ VÔ,Ø'¨¨˜^‘ à(¨¨Ð5‘ Ø × "Ñ " 6Ô *Ø$ Z°° ^Ð$4Ð5ˆJØ×'Ñ'¨¨SÓ1ˆ Ø×$Ñ$Ó&Ð&rcó”—tjtj|««}|j«|j «zS)aCompute the ratio between the largest and smallest inter-point distances. A value larger than 5 typically indicates that the parameter range would better be displayed with a log scale while a linear scale would be more suitable otherwise. )ÚnpÚdiffÚsortÚmaxÚmin)Údatar}s rÚ_interval_max_min_ratior‚s1€ô7‰7”2—7‘7˜4“=Ó!€DØ8‰8‹:˜Ÿ™› Ñ"Ð"rcób—idd“dd“dd“dd“d d “dd“d d“dd“dd“dd“dd“dd“dd“dd“dd“dd “d!d"“d#d$d%d&d'd(d)œ¥}|j«D] \}}||vsŒ||vsŒtd*|›d+|›d,«‚|j«}|j«D]}||vr|||||<Œ||||<Œ|S)-aÃCreate valid style kwargs by avoiding Matplotlib alias errors. Matplotlib raises an error when, for example, 'color' and 'c', or 'linestyle' and 'ls', are specified together. To avoid this, we automatically keep only the one specified by the user and raise an error if the user specifies both. Parameters ---------- default_style_kwargs : dict The Matplotlib style kwargs used by default in the scikit-learn display. user_style_kwargs : dict The user-defined Matplotlib style kwargs. Returns ------- valid_style_kwargs : dict The validated style kwargs taking into account both default and user-defined Matplotlib style kwargs. ÚlsrPÚcrQÚecÚ edgecolorÚfcÚ facecolorÚlwÚ linewidthÚmecÚmarkeredgecolorÚmfcaltÚmarkerfacecoloraltÚmsÚ markersizeÚmewÚmarkeredgewidthÚmfcÚmarkerfacecolorÚaaÚantialiasedÚdsÚ drawstyleÚfontÚfontpropertiesÚfamilyÚ fontfamilyrÚfontnameÚsizeÚfontsizeÚstretchÚfontstretchÚ fontstyleÚfontvariantÚ fontweightÚhorizontalalignmentÚverticalalignmentÚmultialignment)ÚstyleÚvariantÚweightÚhaÚvaÚmaz Got both ú and z", which are aliases of one another)ÚitemsÚ TypeErrorÚcopyÚkeys)Údefault_style_kwargsÚuser_style_kwargsÚinvalid_to_valid_kwÚinvalid_keyÚ valid_keyÚvalid_style_kwargsr6s rr_r_#s¤€ð*ØˆkðàˆWðð ˆkðð ˆkð ð ˆkðð Ð ð ð Ð&ðð ˆlðð Ð ðð Ð ðð ˆmðð ˆkðð Ð ðð ,ðð ðð ð!ð" =ð#ð$Ø ØØ#Ø!Øò/Ðð2#6×";Ñ";Ó"=òÑˆYØÐ+Ò+° Ð=NÒ0NÜØ˜K˜=¨¨i¨[ð9ðóð ðð.×2Ñ2Ó4Ðà ×%Ñ%Ó'ò=ˆØÐ%Ñ%Ø;LÈSÑ;QÐÐ2°3Ñ7Ò8à&7¸Ñ&<Ð˜sÒ#ð =ðÐrcóš—dD] }|j|jd«Œ"dD]!}|j|jdd«Œ#y)z—Remove the top and right spines of the plot. Parameters ---------- ax : matplotlib.axes.Axes The axes of the plot to despine. )ÚtopÚrightF)ÚbottomÚleftrrN)ÚspinesÚset_visibleÚ set_bounds)rÚss rÚ_despinerÃbsP€ðò(ˆØ ‰ !‰× Ñ Õ'ð(à ò&ˆØ ‰ !‰×Ñ 1Õ%ñ&rcóÐ—t|«}|j›d|jdz›}|dk7r7|rtd|›d|›d«‚t j d|›d|›dt«|S|S) z/Deprecate `estimator_name` in favour of `name`.r;éÚ deprecatedzSCannot provide both `estimator_name` and `name`. `estimator_name` is deprecated in z and will be removed in z. Use `name` only.z"`estimator_name` is deprecated in z. Use `name` instead.)rÚmajorÚminorr.rVrWrX)rrÚversionÚversion_removes rÚ_deprecate_estimator_namerËps•€ä˜GÓ$€GØŸ ™ a¨¯ © ¸Ñ(9Ð':Ð;€NØ˜Ò%ÙÜð$Ø$+ 9Ð,DÀ^ÐDTðU#ð#óð ô ‰ Ø0°° Ð9QØÐÐ3ð 5äô ð ÐØ€Krcó2—|€yt|t«r|S|gS)z3Convert parameters to a list, leaving `None` as is.N)rYrZ)Úparams rÚ_convert_to_list_leaving_nonerÎ„s €à€}ØÜ%œÔØˆØˆ7€Nrc óü—i}|j«D]\}}t|t«sŒ|||<Œi|¥|¥}t|j «Dchc] }t|«’Œc}«dkDr‰|j«Dcgc]}|‘Œ}}dj dj |dd«|dg«} d} d|vrd} dj d „|j«D««}t| ›d |›d| ›d|›«‚ycc}wcc}w) z>Check required and optional parameters are of the same length.rr¯z, NrTÚz'name' (or self.name)z (or `plot`)c3óBK—|]\}}|›dt|«›–—Œyw)z: N)r=)r5r6Úvalues rr8z'_check_param_lengths..s(èø€ò& Ù'1 s¨Eˆsˆe2”c˜%“j\Ô"ñ& ùs‚z from `z` initializationz/, should all be lists of the same length. Got: )r°rYrZr=Úvaluesr³Újoinr.)ÚrequiredÚoptionalÚ class_nameÚoptional_providedrrÍÚ all_paramsr6Ú param_keysÚparams_formattedÚor_plotÚlengths_formatteds rÚ_check_param_lengthsrÞs(€àÐØ—~‘~Ó'ò,‰ˆˆeÜeœTÕ"Ø&+Ð˜dÒ#ð,ð3HÐ2Ð 1Ð2€JÜ J×$5Ñ$5Ó$7Ö8˜5ŒCJÒ8Ó9¸AÒ=Ø%/§_¡_Ó%6Ö7˜c’cÐ7ˆ Ð7ð#Ÿ<™<¨¯©°:¸c¸r°?Ó)CÀZÐPRÁ^Ð(TÓUÐØˆØ" jÑ0Ø$ˆGØ ŸI™Iñ& Ø5?×5EÑ5EÓ5Gô& ó ÐôØÐ ¨ |Ð3CÀGÀ9ðM<ØùÒ8ùÚ7sÁC4Á< C9)rVÚcollections.abcrÚnumpyr|rÐrÚ_optional_dependenciesrÚ _responserÚfixesrÚ multiclassr Ú validationr rr rzr‚r_rÃrËrÎrÞr4rrúræsSðóÝ#ãå%Ý<Ý2Ý Ý&ßB÷jñjòZ'ò6#ò<ò~&òò(ó r