:iZ!LSSKrSSKrSSKrSSKrSSKJr SSK J r S Sjr "SS5r Sr "SS \ 5rS rS r"S S 5rS!SjrSr"SS5r"SS\5r"SS\5r"SS\5rS!Sjr"SS5r"SS\5r"SS\5rSrg)"N)KMeans) SimpleImputerc [URS5Vs/sHn[U5PM nn[U[R 5(aUR nURn[[RSS9nURU5n[USSS9RU5nU(a[U5Hn[URS5Hn[RR!U5(a%USS2U4R#5R%5OUSS2U4n[R&"[R("XR*X74- 55n X U4UR*X74'M M [-UR*USS[R."UR05-5$s snf) a Summarize a dataset with k mean samples weighted by the number of data points they each represent. Parameters ---------- X : numpy.array or pandas.DataFrame or any scipy.sparse matrix Matrix of data samples to summarize (# samples x # features) k : int Number of means to use for approximation. round_values : bool For all i, round the ith dimension of each mean sample to match the nearest value from X[:,i]. This ensures discrete features always get a valid value. Returns ------- DenseData object. mean)missing_valuesstrategyr ) n_clusters random_staten_initNg?)rangeshapestr isinstancepd DataFramecolumnsvaluesrnpnan fit_transformrfitscipysparseissparsetoarrayflattenargminabscluster_centers_ DenseDatabincountlabels_) Xk round_valuesi group_namesimpkmeansjxjinds U/srv/projetos/modelo_ml_acdoc/venv/lib/python3.13/site-packages/shap/utils/_legacy.pyr+r+ sj*$)#45#4a3q6#4K5!R\\""ii HH rvv ?C !Aqq < @ @ CFqA1771:&38<<3H3H3K3KAadGOO%--/QRSTVWSWQXiir,C,CAD,I'I JK01q& ''- ' V,,k4r{{SYSaSaGbAb cc)6sF=c\rSrSrSrSrg)Instance6cXlX lgN)xgroup_display_values)selfr5r6s r/__init__Instance.__init__7s $8!)r6r5N__name__ __module__ __qualname____firstlineno__r8__static_attributes__r:r/r1r16s9r:r1cH[U[5(aU$[US5$r4)rr1vals r/convert_to_instancerE<s!#x   T""r:c \rSrSrSrSrSrg)InstanceWithIndexCcT[RXU5 X0lX@lX lgr4)r1r8 index_value index_name column_name)r7r5rLrJrKr6s r/r8InstanceWithIndex.__init__Ds$$#78&$&r:c[R"URUR/S9n[R"URUR S9n[R "X/SS9nURUR5nU$N)rr)axis)rrrJrKr5rLconcat set_index)r7indexdatadfs r/ convert_to_dfInstanceWithIndex.convert_to_dfJsb T--7HI||DFFD,<,<= YY}1 - \\$// * r:)rLrKrJNr<r=r>r?r8rVr@rAr:r/rGrGCs ' r:rGc[XX#S5$r4)rG)rDrLrJrKs r/convert_to_instance_with_indexrZRs S{ MMr:cz[U[5(d [S5e[U[5(aURcEUR Vs/sH(n[ U5S:XaURSUS4OSPM* snUl[ UR5[ UR 5:Xdeggs snf)Nz"instance must be of type Instance!rr)rr1 TypeErrorr"r6groupslenr5)instancerTgroups r/match_instance_to_datarbVs h ) )<==$ ""  ( ( 0PTP[P[-P[u3u:? 1eAh;'BP[-H )8001S5EEEE #-s/B8c\rSrSrSrSrg)ModelbcXlX lgr4f out_names)r7rhris r/r8Model.__init__cs "r:rgNr;rAr:r/rdrdbs#r:rdc[U[5(aUnO [US5nU(d`[URSS5nU(aB[ US5(a1[ R "U5nSURRlU$)acConvert a model to a Model object. Parameters ---------- val : function or Model object The model function or a Model object. keep_index : bool If True then the index values will be passed to the model function as the first argument. When this is False the feature names will be removed from the model object to avoid unnecessary warnings. N__self__feature_names_in_) rrdgetattrrhhasattrcopydeepcopyrlrm)rD keep_indexoutf_selfs r/convert_to_modelruhsl#uC  D1 gf&9::--$C/3CEENN , Jr:c[U[5(d [S5e[U[5(a UR UR 55nOUR UR 5nURc][UR5S:Xa S/Ul U$[URS5Vs/sHnS[U5-PM snUl U$![a [S5 ef=fs snf)Nzmodel must be of type Model!zDProvided model function fails when applied to the provided data set.rz output valuerz output value )rrdr]DenseDataWithIndexrhrVrT Exceptionprintrir_rrr)modelrTout_valr(s r/match_model_to_datar|s eU # #677 d. / /ggd0023Gggdii(G   w}}  "-.EO NBGw}}UVGWAXYAXAQ7AXYEO N  TU Zs4CC=C9C6c\rSrSrSrSrg)Datacgr4rAr7s r/r8 Data.__init__ r:rANr;rAr:r/r~r~ r:r~c\rSrSrSrSrg) SparseDatacURSn[R"U5UlU=R[R"UR5-slSUlSUlSUlURSUlXl g)NrFr) rronesweightssum transposedr^r) groups_sizerT)r7rTargs num_sampless r/r8SparseData.__init__sejjm ww{+  t||,,  ::a= r:rTr)r^rrrNr;rAr:r/rrsr:rc\rSrSrSrSrg)r"c[U5S:a USbUSO9[[U55Vs/sHn[R"U/5PM snUl[ SUR55nUR SnSnXQR S:waSnUR SnU(+=(a XQR S:H=(d U=(a XQR S:HnU(d [S5e[U5S:aUSO[R"U5Ul U=R[R "UR5-sl [UR5n U(+=(a XR S:H=(d U=(a XR S:HnU(d [S5eXpl X l Xl [UR5Ul gs snf)Nrc38# UHn[U5v M g7fr4)r_).0gs r/ %DenseData.__init__..s, 1A sFrTz"# of names must match data matrix!z$# of weights must match data matrix!)r_rrarrayr^rr ValueErrorrrrr)rTr) r7rTr)rr(r,rtvalidwls r/r8DenseData.__init__s}4y1}a)r?r staticmethodrhrr@rAr:r/rrs/r:rc>\rSrSrSr\SSj5r\S5rSrg) LogitLinkcg)NlogitrArs r/rLogitLink.__str__sr:cn[R"XSU- 5n[R"USU- - 5$Nr)rcliplog)r5epsilon x_clippeds r/rh LogitLink.fs.GGAG 4 vvi1y=122r:c<SS[R"U*5-- $r)rexprs r/rLogitLink.finv sAr N##r:rAN)gV瞯rs "()dX99 #  N F## <,   ,,<  *  4  $ $Ir: