0Ph!`dZddlZddlZddlmZddlmZddlmZhdZ d dZ dZ d Z d Z dS) z+Utilities to discover scikit-learn objects.N) import_module) itemgetter)Path>setuptestsconftest externals experimentalestimator_checksc&ddlmm}m}m}m}ddlm}dg}tttj j }|t5tj|gdD]\}} }| d } t!d | Dsd | vr9t#| } t%j| t$j} d | D} ||  d d d n #1swxYwYt-|}fd|D} fd| D} |t/|t0s|g}nt1|}g}||||d}|D]?\}||vr6|||fd| D@|} |r t7dt9|d t;t-| t=dS)a1Get a list of all estimators from `sklearn`. This function crawls the module and gets all classes that inherit from BaseEstimator. Classes that are defined in test-modules are not included. Parameters ---------- type_filter : {"classifier", "regressor", "cluster", "transformer"} or list of such str, default=None Which kind of estimators should be returned. If None, no filter is applied and all estimators are returned. Possible values are 'classifier', 'regressor', 'cluster' and 'transformer' to get estimators only of these specific types, or a list of these to get the estimators that fit at least one of the types. Returns ------- estimators : list of tuples List of (name, class), where ``name`` is the class name as string and ``class`` is the actual type of the class. Examples -------- >>> from sklearn.utils.discovery import all_estimators >>> estimators = all_estimators() >>> type(estimators) >>> type(estimators[0]) >>> estimators[:2] [('ARDRegression', ), ('AdaBoostClassifier', )] >>> classifiers = all_estimators(type_filter="classifier") >>> classifiers[:2] [('AdaBoostClassifier', ), ('BaggingClassifier', )] >>> regressors = all_estimators(type_filter="regressor") >>> regressors[:2] [('ARDRegression', ), ('AdaBoostRegressor', )] >>> both = all_estimators(type_filter=["classifier", "regressor"]) >>> both[:2] [('ARDRegression', ), ('AdaBoostClassifier', )] ) BaseEstimatorClassifierMixin ClusterMixinRegressorMixinTransformerMixinignore_warningscVt|dsdSt|jsdSdS)N__abstractmethods__FT)hasattrlenr)cs W/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/sklearn/utils/discovery.py is_abstractz#all_estimators..is_abstractSs7011 51()) 5tcategorysklearn.pathprefix.c3(K|] }|tvVdSN_MODULE_TO_IGNORE.0parts r z!all_estimators..b(GG$D--GGGGGGr._cFg|]\}}|d||fS_) startswith)r*nameest_clss r z"all_estimators..hsB$1D'DOOTWDXDXwrNcXg|]&}t|dr|ddk$|'S)rrr issubclass)r*rrs rr5z"all_estimators..psJ qt] + +12!0G0G 0G0G0Grc6g|]}|d|Sr)r*rrs rr5z"all_estimators..vs,AAA{{1Q4/@/@A!AAAr) classifier regressor transformerclusterc@g|]}t|d|Sr:r7)r*estmixins rr5z"all_estimators..s,LLLS*SVU2K2KLSLLLrz_Parameter type_filter must be 'classifier', 'regressor', 'transformer', 'cluster' or None, got rkey)baserrrrr_testingrstrr__file__parent FutureWarningpkgutil walk_packagessplitanyrinspect getmembersisclassextendset isinstancelistitemsremove ValueErrorreprsortedr) type_filterrrrrr all_classesrootr1 module_name module_partsmoduleclasses estimatorsfiltered_estimatorsfiltersr3rrrBs @@@rall_estimatorsres,h*)))))K tH~~$+ , ,D - 0 0 0((!(!6TF:!V!V!V ( ( A{A&,,S11LGG,GGGGG ;&&";//F(AAG5<G   w ' ' ' ' (((((((((((((((( k""KJ BAAAZAAAJ+t,, ,&-KK{++K )'+#    #==??  KD%{""""4(((#**LLLLJLLL)  )%%)))  #j//z!}} 5 5 55sB!DD D cRddlm}g}tttjj}|t 5tj|gdD]\}}}| d}td|Dsd|vr9t|}tj |tj}d |D}|| d d d n #1swxYwYt!t#|t%d  S) aGet a list of all displays from `sklearn`. Returns ------- displays : list of tuples List of (name, class), where ``name`` is the display class name as string and ``class`` is the actual type of the class. Examples -------- >>> from sklearn.utils.discovery import all_displays >>> displays = all_displays() >>> displays[0] ('CalibrationDisplay', ) rrrr r!r$c3(K|] }|tvVdSr&r'r)s rr,zall_displays..r-rr.cpg|]3\}}|d|d/||f4S)r1Display)r2endswith)r*r3 display_classs rr5z all_displays..sY'D-s++15 i0H0H}%rNrrC)rFrrGrrHrIrJrKrLrMrNrrOrPrQrRrZrSr)rr\r]r1r^r_r`ras r all_displaysrls"*)))))K tH~~$+ , ,D - 0 0 0((!(!6TF:!V!V!V ( ( A{A&,,S11LGG,GGGGG ;&&";//F(AAG+2G   w ' ' ' ' ((((((((((((((((" #k"" 1 6 6 66sB!C33C7:C7ctj|sdS|jdrdS|j}|dr|drdSdS)NFr1r r T)rO isfunction__name__r2 __module__rj)itemmods r_is_checked_functionrssp  d # #u }$$u /C >>* % %6H)I)Iu 4rcHddlm}g}tttjj}|t 5tj|gdD]\}}}| d}td|Dsd|vr9t|}tj |t}d |D}|| d d d n #1swxYwYt!t#|t%d  S) aGet a list of all functions from `sklearn`. Returns ------- functions : list of tuples List of (name, function), where ``name`` is the function name as string and ``function`` is the actual function. Examples -------- >>> from sklearn.utils.discovery import all_functions >>> functions = all_functions() >>> name, function = functions[0] >>> name 'accuracy_score' rrrr r!r$c3(K|] }|tvVdSr&r'r)s rr,z all_functions..r-rr.cPg|]#\}}|d|j|f$Sr0)r2ro)r*r3funcs rr5z!all_functions..sED$s++%rNrrC)rFrrGrrHrIrJrKrLrMrNrrOrPrsrRrZrSr)r all_functionsr]r1r^r_r` functionss rrxrxs$*)))))M tH~~$+ , ,D - 0 0 0,,!(!6TF:!V!V!V , , A{A&,,S11LGG,GGGGG ;&&";//F*63GHHI"+I   + + + + ,,,,,,,,,,,,,,,,* #m$$*Q-- 8 8 88sBC..C25C2r&)__doc__rOrK importlibroperatorrpathlibrr(rerlrsrxr;rrr~s11 ######@6@6@6@6F(7(7(7V   -9-9-9-9-9r