hMhddlmZddlZddlZddlmZddlmZddlmZm Z m Z ddl m Z ddl m Z ddlZddlZddlZddlmZdd lmZmZdd lmZmZmZmZmZmZGd d Z Gd de Z!Gdde Z"Gdde Z#GddZ$GddeZ%ddZ&ddZ'dZ(dZ)d dZ*dS)!) annotationsNcopy) UserString)IterableSequenceMapping)Number)datetime)PlotData) QUAL_PALETTES color_palette)_check_argument_version_predates desaturatelocator_to_legend_entriesget_color_cycle remove_nacBeZdZUdZdZded<dZdZdZdZ dZ dZ dS) SemanticMappingz6Base class for mapping data values to plot attributes.Nz str | Nonemap_typec||_dSN)plotter)selfrs M/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/seaborn/_base.py__init__zSemanticMapping.__init__+s c@d}t|t|krjdd|dt|ddt|ddg}d t|tj|D}nst|t|krSdd |d t|ddt|d g}|d t|}|rt j|td|S)z/Input check when values are provided as a list. z The z list has fewer values ()z than needed (z) and will cycle, which mayz produce an uninterpretable plot.cg|]\}}|Sr$).0_xs r z6SemanticMapping._check_list_length..>sIIIDAqaIIIrThe z list has more values (z), which may not be intended.N stacklevel)lenjoinzip itertoolscyclewarningswarn UserWarning)rlevelsvaluesvariablemessages r_check_list_lengthz"SemanticMapping._check_list_length4s0 v;;V $ $hhIII3v;;IIIHF HHH2 G JIC 0G0G$H$HIIIFF [[3v;; & &hhFxFFF FFFJF JJJ GLS[[L)F  > M';1 = = = = rc|j|S)z)Apply the mapping to a single data value. lookup_table)rkeys r_lookup_singlezSemanticMapping._lookup_singleLs %%rct|ttjtjfrfd|DSj|gRiS)z-Get the attribute(s) values for the data key.c2g|]}j|gRiSr$)r>)r%kargskwargsrs rr(z,SemanticMapping.__call__..Ss7III'D';D;;;F;;IIIr) isinstancelistnpndarraypdSeriesr>)rr=rBrCs` ``r__call__zSemanticMapping.__call__Pse cD"*bi8 9 9 =IIIIIISIII I&4&srJr$rrrrsy@@  HFL0&&&=====rrcJeZdZdZdZdZdZ d fd ZdZdZ dZ dZ xZ S) HueMappingz9Mapping that sets artist colors according to data values.Nct||jdt jt }t|tj r,d}tj |d| }| r|d}tj |ddSdS||||j|jd}|dkr1t j|}||||\} } }} nP|d krdx} }||||\} } n+dx} }|t+|||\} } ||_||_| |_||_| |_||_| |_dS) zMap the levels of the `hue` variable to distinct colors. Parameters ---------- # TODO add generic parameters huedtypez|Numpy array is not a supported type for `palette`. Please convert your palette to a list. 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Parameters ---------- # TODO add generic parameters sizerUrXrYN)rZrr[r\rHrIr]notnarrarcrerfrErr5risizes size_ranger<) rrrrkrirlrr5r<rrns rrzSizeMapping.__init__/s[ !!! $$VRYU-C-C-CDD ::<<    ( -**eW.v6H 9$$9=9M9M%::6 dJJ ]**'+'?'?%(($ " (,'?'?JJu(($ " $DM DKDIDJ(DO ,D   Q( -( -rcR|d}n!t|ttfrd}n|}|S)NrXrY)rDr{rE)rrirr|rs rrazSizeMapping.infer_map_typegs6   HH d| , , $HHHrc |j|}nz#t$rm||}tj|r tj}|jd|tj|jzz}YnwxYw|S)Nr) r<rprirFrqrrrsrptp)rr=rvrws rr>zSizeMapping._lookup_singlers J%c*EE J J JYYs^^Fuv&& OA&"&2I2I)IIEEE  J  s A4BBct||}t|trWt|t|z }t |rd|}t ||}nt|tr5|||d}tt||}nt|tr%t|dkrd}t |n"|d|}t ||j j }tjg|t|Rddd}tt||}||fS)Nz(Missing sizes for the following levels: r'A `sizes` tuple must have only 2 values"Value for `sizes` not understood: )rrDr{rrrrrEr9r/rr-r_default_size_rangerFlinspace)rrlrrkr5rrxr<s rrfzSizeMapping.categorical_mapping}sl"4// eT " "2 4&kkCJJ.G7|| &JJJ oo% ::<"'$u++..//F,,..K[))3{+;+;;JJ "')DKKMM":":;;<u::??CC$S//)" "B5BB oo%"\=  <:''))DD e $ $ :'.DDD#*"677 KTKKCS// !::D {{}}  DLLLtF||  eT " " 4 LLFBb11EFE 2 233L|T:55rNNN) rKrLrMrNrirrar>rfrerrs@rrr*sBB D596-6-6-6-6-6-p      8$8$8$tM6M6M6M6M6M6M6rrc6eZdZdZdZdfd ZddZdZxZS) StyleMappingz8Mapping that sets artist style according to data values.rYNc t||jdt jt }|rt|dkrt|}t||}| ||tt|d}| ||tt|d}i}g}|D]\} } t#| t$jjst$j| } | | || <|| t|r t5|sd} t7| i} |D]>} i| | <|r"|| | | d<|| | | d<|r|| | | d<?||_| |_d Sd S) zMap the levels of the `style` variable to distinct values. Parameters ---------- # TODO add generic parameters stylerUr markersdashesz+Filled and line art markers cannot be mixedmarkerpathN)rZrr[r\rHrIr]rr variable_typerEr_map_attributesunique_markersr- unique_dashesitemsrDrr MarkerStyleget_path transformed get_transformappend is_filledr`rr5r<)rrrrrkrlr5pathsfilled_markersrAmrxr<r=rns rrzStyleMapping.__init__ s> !!! $$Wbie.D.D.DEE ::<<    , -T""j00Dzz'tU33F**F !"" &3~+>+> &C oo%L > >$& S!;29#,L%h/05c L%f->28+L%h/ DK ,D   Y, -, -rcL||j|}n|j||}|S)z(Get attribute(s) for a given data point.r;)rr=attrrvs rr>zStyleMapping._lookup_singleGs- <%c*EE%c*40E rc|durtt||}nt|tr;t|t|z }|rd|d|}t ||}net|t r5||||}tt||}n|rd|d|}t |i}|S)z5Handle the specification for a given style attribute.TzThese `z` levels are missing values: zThis `z` argument was not understood: )r{r/rDrrrr9)rargr5defaultsrr<rrxs rrzStyleMapping._map_attributesOs $;;FH 5 566LL T " " &kkCHH,G &LLL7LL oo%LL X & & ))&#t<rrrs@rrrsnBBH8-8-8-8-8-8-trrc eZdZdZdddddZdddZdZdifd Zed Z ed Z difd Z d"d Z d#dZ d$dZd$dZ d"dddddddZedZdZ d%dZdZd&dZ d$dZdZdZdZd Zd%d!ZdS)' VectorPlotterz2Base class for objects underlying *plot functions.@index@values@columns)r'yrTrr'r)rRrNci|_ddd|_|||dD]!}||vrt|d|"dS)NFrrTrrmap_) _var_levels _var_orderedassign_variablesgetattr)rrl variablesvars rrzVectorPlotter.__init__rsw #(e44 dI... , . .Ci+lSll++--- . .rcNtddht|jzS)z.Return True at least one of x or y is defined.r'r)boolrr)rs r has_xy_datazVectorPlotter.has_xy_datas%S#JT^!4!44555rcp|jD](}t|d|ddx}|j|j|<)|jS)a4Property interface to ordered list of variables levels. Each time it's accessed, it updates the var_levels dictionary with the list of levels in the current semantic mappers. But it also allows the dictionary to persist, so it can be used to set levels by a key. 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Parameters ---------- data : flat vector or collection of vectors Data can be a vector or mapping that is coerceable to a Series or a sequence- or mapping-based collection of such vectors, or a rectangular numpy array, or a Pandas DataFrame. kwargs : variable -> data mappings Behavior with keyword arguments is currently undefined. Returns ------- plot_data : :class:`pandas.DataFrame` Long-form data object mapping seaborn variables (x, y, hue, ...) to data vectors. variables : dict Keys are defined seaborn variables; values are names inferred from the inputs (or None when no name can be determined). cg|] \}}|| Srr$r%rArs rr(z.sBBB$!QAMAMMMrrRsr zThe following variablez) cannot be assigned with wide-form data: z, c3"K|] }d|dV dS)`Nr$r%rs r z;VectorPlotter._assign_variables_wideform..s*88!XXXX888888rNrUc3zK|]6}t|tot|ttf V7dSr)rDrstrbytesrs rrz;VectorPlotter._assign_variables_wideform..sV   q( # # GJq3,,G,G(G      r)rrrnamec>i|]\}}|tj|Sr$)rHrI)r%r=vals rrz.s&IIISRYs^^IIIrTrc>g|]\}}t|dk|SrXrrs rr(z.s5a=3C3Cy3P3P3P3P3Prrr)var_name value_namerid_varsFr$)!rrr-r.rrDr{r6rF atleast_1drobjectrH DataFramerIrrindexflat_structurerr enumerater wide_structurecolumns categoriesorderedadd_categoriesAttributeError to_seriesmelt CategoricalrE)rrlrCassignedrrxemptyr6flatr[r flat_datarrr data_dictir= wide_data numeric_colsmelt_kws use_indexorig_categories orig_orderedcategory_columnsobjs rrz(VectorPlotter._assign_variables_wideformsr.CB&,,..BBB x== "8}}q((bAW1WWWC 49988x88888 8CS// ! -CII  dD ! ! C[[]]FF]2:d&#A#A#ABBF         _ 3 III Y 3  $,,..I$>#/.E II! E E$---.s3D%,YQRR%A%AIcN%*4+>s+C%DIcN Y//II$)) ! 'oo44FAs!#vq11C&(Ys^^IcNN $(( JIIDJJLLIII  T555I'oo//L",/I%/iHHH D$7$>$>$@$@@I B&.#,&/&7&BO#,#4#ddh}||t jt |z zfd|D}|rj}nj}|r| }j } |rddht |zD]} j | j d} j| dkr\j| r| | | | | <Wt#j|| | | <| j} | | | | | | <|r&||d d d } g}|D]0}| |}||gn|1t3j|}|rt7t|}|D]}t9|d krt;t<d r|dn|} | |}n#t@$r|j!g}YnwxYw|j"r|srtGtI||}|| fVdSi| fVdS) aGenerator for getting subsets of data defined by semantic variables. Also injects "col" and "row" into grouping semantics. Parameters ---------- grouping_vars : string or list of strings Semantic variables that define the subsets of data. reverse : bool If True, reverse the order of iteration. from_comp_data : bool If True, use self.comp_data rather than self.plot_data by_facet : bool If True, add faceting variables to the set of grouping variables. allow_empty : bool If True, yield an empty dataframe when no observations exist for combinations of grouping variables. dropna : bool If True, remove rows with missing data. Yields ------ sub_vars : dict Keys are semantic names, values are the level of that semantic. sub_data : :class:`pandas.DataFrame` Subset of ``plot_data`` for this combination of semantic values. Ncolrowc&g|] }|jv |Sr$)r)r%rrs rr(z+VectorPlotter.iter_data..s%OOO9N9N9N9N9Nrr'rrrYF)ras_indexobservedrRz2.2.0)%rDrrrEextendrr comp_datar[rrr convertersilocrcr convert_unitsrFrrr transformgroupbyr\rr0productreversedr-rrH get_grouprplocrr{r/)r grouping_varsr)r*r+r,r facet_varsrlr5axis converterr8 grouped_data grouping_keysrr= iter_keyspd_key data_subsetsub_varss` r iter_datazVectorPlotter.iter_dataQsnF  MM  s + + 0*OMM  u - - 0 //M  J  S003}3E3EEE    POOO OOO  ">DD>D  !;;==D%%''  Tc S%7%77 T T OD16q9 >$'=88(. D (1'>'>vd|'L'Lt (*wtDz/@/@/B/B'C'Ct ) 7 7 9 9 CI#,9Y-D-DVD\-R-R#S#SF4LL & "<<EEE(LM$ A Ajjoo$$3;RRC@@@@!)=9I 6$T)__55   3 3"#hh!mm0A"g0N0NmCFFTW/"."8"8"@"@KK/// #'(2,KKK /$[M3 7 788 0 0 2 222222' 3 3.diikk/ ! ! ! ! !s&I<<JJc >t|ds|jSt|ds|jdddgdd }d D]}||jvr g}|j||j|d }|D](\}}||tj tj gtj }| }||j vr&|||j |}tj||t$}|j}|tj|||j|j *|rtj|} ntjt$| } |d|| ||_|jS)zFDataframe with numeric x and y, after unit conversion and log scaling.ax _comp_dataF)deepr'rrRignore)r@errorsyxrr)rVrr)hasattrr[rdroprr9r5maskisinrFinfrsrrrHrdr7astyper]rr8rrIrrconcatinsertrK) rr4rpartsgroupedrAorigcompr8comp_cols rr4zVectorPlotter.comp_datastT"" " > !t\** (5!!sCjq::   3 3dn,,.-55doc6JQV5WW'. Y YOIt99TYY/@%A%A26JJD;;==Ddo-- $DIIdoc.B$C$CD=)@)@)F)FGGNNuUUD ) 7 7 9 9 CILL99T??DJTY!W!W!WXXXX@!y//HH!yu3???H  C2222'DOrc|dd}|dd}|||jj||fS||jj|S||jj|S|j |jjS|jS)z>Return an Axes object based on existence of row/col variables.r/Nr.)r\facets axes_dictrJ)rrGr/r.s r _get_axeszVectorPlotter._get_axessll5$''ll5$'' ?s;(#s4 4 _;(- - _;(- - W_;> !7Nrcddlm}t||rTd|_||_|j}|j|j|jd<|j |j |jd<n||_d|_|g}td |j }|gd}nt|tr|g}|D].}|j|}||vrd|d |d |d } t| /ddd } i|_|D]}d dd |} t#j|jj|t*} t-|jd|d} | dus | | | kr$t-|d|d| jdd<n| durP|D]:\}}||}t-||d| j|j<;nwt-|j| d}t5|D]O\}}| dkr|dfnd|f}t-|jj||d}|| j|j| |k<P| |j|<|j||j|d}|D]X\} }|j|dkr-|j|r|j|}nd}t;||}| |Y|dx}}n[ |\}}nT#t$rG|jddkr|nd}|jd dkr|nd}YnwxYwtAd||fD]@\}}|r9|D]6}t-|d|d}|dur|dd(|d|d7A|jd ddkr|D]}|j!"ddSdS)aAssociate the plotter with an Axes manager and initialize its units. Parameters ---------- obj : :class:`matplotlib.axes.Axes` or :class:'FacetGrid` Structural object that we will eventually plot onto. allowed_types : str or list of str If provided, raise when either the x or y variable does not have one of the declared seaborn types. log_scale : bool, number, or pair of bools or numbers If not False, set the axes to use log scaling, with the given base or defaulting to 10. If a tuple, interpreted as separate arguments for the x and y axes. rR) FacetGridNr.r/rrXr rYr)z variable is z , but one of z is requiredrrr')rrrV_shareTrr@F_namesrPrYrXset_scalelogrT) nonpositive)baserk)#axisgridrdrDrJr`axesflatten col_namesr row_namesr intersectionrrrcrtr5rHrIr[rrrr=rHrbrr9rr update_unitsr\r/yaxis set_inverted)rr allowed_types log_scalerdax_listaxis_variablesrr|rx facet_dim other_varrA share_state axes_vars axes_datarJrrlevelidxr@r[ seed_datarkscalexscaleyri set_scales r_attachzVectorPlotter._attachs* (''''' c9 % % DGDKh&&((G}(),&}(),&DGDKeGT//??  BBBMM  s + + ,*OM! % %C~c*H},,3333X33$333 nn$ - e,, !, 2, 2C!,,S1I (<3fUUUI!$+~~~tDDK d""kYy5I&I&I#*71:#|||#D#D aaa  %''040@0@SS, 9!^^I669@\\\9R9R io66S$DKK1G1G1GHHE$-e$4$4SS5(3u(<(#&-77(-% $ 4 $ 1)U C CI&&y1111 2  # #FVV V!* V V V&*n&8&8&=&=&J&JPU&*n&8&8&=&=&J&JPU V tff%566 I IKD% I!IIB ',>4,>,>,> ? ?I}}! %V<<<<<! %eHHHHH >  c4 ( (M 9 9 , ,%%d++++ : 9 , ,s)K//AM?Mcv|jhfd|jjjD}d|D}t |dkrd}t ||d}n*t|jd}|j| jfS)zDReturn a function implementing the scale transform (or its inverse).Nc6g|]}t|dS)r@)r)r%rJr@s rr(z7VectorPlotter._get_scale_transforms..s)TTT]]]33TTTrc6h|]}|Sr$) get_scale)r%r@s r z6VectorPlotter._get_scale_transforms..s"===4dnn&&===rrRz=Cannot determine transform with mixed scales on faceted axes.rr@) rJr`rnrr- RuntimeErrorrrr8inverted)rr@ axis_listscalesrx transform_objs ` r_get_scale_transformsz#VectorPlotter._get_scale_transformss 7?TTTTdk>N>STTTI==9===F6{{QV"3'''%aL6688MM$DG]]];;IIKKM& (>(>(@(@(JJJrr c|s[td|D}||jd|||s]td|D}||jd||dSdS)zCAdd axis labels if not present, set visibility to match ticklabels.c3>K|]}|VdSr get_visibler%ts rrz1VectorPlotter._add_axis_labels..*JJAMMOOJJJJJJrr')visiblec3>K|]}|VdSrrrs rrz1VectorPlotter._add_axis_labels..rrrN) get_xlabelrget_xticklabels set_xlabelrr\ get_ylabelget_yticklabels set_ylabel)rrJ default_x default_y x_visible y_visibles r_add_axis_labelszVectorPlotter._add_axis_labelss }} QJJR5G5G5I5IJJJJJI MM$.,,S)<Add labeled artists to represent the different plot semantics.)autobrieffullz7`legend` must be 'auto', 'brief', 'full', or a boolean.TrNch|]}||Srr$)r%titles rrz0VectorPlotter.add_legend_data..s(        rc3NK|]}j|dV dSr)rr\)r%rrs rrz0VectorPlotter.add_legend_data..s5 K KQT^  4 ( ( K K K K K KrrrRr Fwr)rcolorr linewidthrrc||f}|vr|jdi|dS|tdi||<dS)Nr$)updaterr{)rval_namekwsr=keys legend_kwss rrz-VectorPlotter.add_legend_data..updatesdH$Cj  & 3&------- C   "&++++ 3rrrrcg|] }|D]}| Sr$r$)r% var_attrsrs rr(z1VectorPlotter.add_legend_data..s%TTT9)TT$$TTTTrlabelz.2z3.5.0r$)legendrDrrrr-popr{r_update_legend_datar\_legend_attributesr6rrlinesLine2Dadd_linepatchesPatch add_patch collections Collectionadd_collection add_artistr legend_title legend_data legend_order)rrJfunc common_kwsattrs semantic_kws verbosityrxtitlesr title_kwsrrrrrr=r&rr level_kws use_attrsrartistrrs` @@radd_legend_datazVectorPlotter.add_legend_datas_K i % % );T*T*TKCS// ! $  I %-RR:??3D3D )1rr|7H7H7J7J   K K K K2J K K K    &kkQ&&FJJLLQr"    . . . . . . =#k3-?$OOE++--  JC  $ $Yy%AQAQRUAVAV       >>'5 ) ) 1 NN7 # # # % %CHAuS/CI(UT (;(;(=(=TTTI " 0 03;;&)$iIdOTTTT'4)S:)S)STTF g.. &fci&677.KK'''' (9::.LL(((((BCC.%%f--- f%%%%K     $ $ $ $!&(rcd}t|d|dd} | dS| jdko#|dkp|dkot| j|k} | rt | jt jjr!t j |} n t j | } t| jt| jf} t| | |j|j\} }n| jgx} }n | jx} }|s=|j|d"||j|d f|j|fi||in|}t)| |D]\}}| t |t*rfd |Dn||ifd |D||j||fidS) z1Generate legend tick values and formatted labels.r*r&rNrXrr)numticks)nbinsrci|]}|Sr$r$)r%rrs rrz5VectorPlotter._update_legend_data../s>>>4D$>>>rc0i|]\}}|v ||Sr$r$)r%rArrs rrz5VectorPlotter._update_legend_data..2s)WWWTQEUVJJQ%JJJr)rrr-r5rDrirrLogNormticker LogLocator MaxNLocatorrrrr[ infer_objectsrVrr\r/rErr)rrrrrr attr_names other_props brief_ticksmapperrlocatorlimitsr5formatted_levelsformatted_levelrrs @@rrz!VectorPlotter._update_legend_datasg }3}}}d33 > F9,   JV#HFM(:(:[(H   6&+sz'9:: D*///EE*00{0CC''V]););;F'@!4!B!B!D!D!J(( $F$$] "(* *F%%(. 5F% U++C66B FDN3'14>#3F T T) T T T'/bb[ &)&2B&C&C E E "E? ve}}j$//.>>>>:>>>DD+&-D WWWW[5F5F5H5HWWWXXXt~c*ODDtDDD E ErctrNotImplementedErrorrr@rBrCs r scale_nativezVectorPlotter.scale_native:s "!rctrrrs r scale_numericzVectorPlotter.scale_numeric@ "!rctrrrs rscale_datetimezVectorPlotter.scale_datetimeGrrctdddg|||jvrd|j|<d|j|<d|j|<|j|dkr!|j|d |_|j|}|dup|jjd k|j|<tj t||| }|+| |}| |}n4| t}| t}||j|<d|j|<||j|<|S) a Enforce categorical (fixed-scale) rules for the data on given axis. Parameters ---------- axis : "x" or "y" Axis of the plot to operate on. order : list Order that unique values should appear in. formatter : callable Function mapping values to a string representation. Returns ------- self r@r'rNrYr rX mergesort)kindcategoryrQ)rrrcr[ sort_valuesrrVrrrHIndexrmaprWrr)rr@rk formattercat_datas rscale_categoricalzVectorPlotter.scale_categoricalNsWT c D111 t~ % %#'DN4 #0DN4 #%DN4  >$ 9 , ,!^77;7OODN>$'..00 #(t"3"Xx~7Jj7X$*8U;;$GGG  ||I..HIIi((EEs++HLL%%E!& -t (t rrrr)NN)r r )rKrLrMrNrrrrpropertyrrrrr"r%r(rHr4rbrrrrrrrrrr$rrrrhs+<<Ij:N$)44N B...."66X6  X "%)B:L$L$L$L$\    !!!!"""" !u"e5u"u"u"u"u"n**X*X   $ G,G,G,G,VKKK, Q Q Q QCGP)P)P)P)d/E/E/El""" """"""[[[[[[rrc,eZdZdZdZfdZdZxZS) VariableTypez Prevent comparisons elsewhere in the library from using the wrong name. Errors are simple assertions because users should not be able to trigger them. If that changes, they should be more verbose. recp||jvs J|t|dSr)allowedrZr)rrlrns rrzVariableType.__init__s<t|###T### rc>||jvs J||j|kSr)rrl)rothers r__eq__zVariableType.__eq__s* $$$e$$$yE!!r)rKrLrMrNrrrrrs@rrrsX3G"""""""rrrXctj|}t|jtjrt dStj|rt dS|}tj 5tj dttf tj|ddgrt |cdddSn#t $rYnwxYwdddn #1swxYwYtjj|rt dStjj|rt dSd }||rt dSd }||rt dSt dS) a+ Determine whether a vector contains numeric, categorical, or datetime data. This function differs from the pandas typing API in two ways: - Python sequences or object-typed PyData objects are considered numeric if all of their entries are numeric. - String or mixed-type data are considered categorical even if not explicitly represented as a :class:`pandas.api.types.CategoricalDtype`. Parameters ---------- vector : :func:`pandas.Series`, :func:`numpy.ndarray`, or Python sequence Input data to test. boolean_type : 'numeric' or 'categorical' Type to use for vectors containing only 0s and 1s (and NAs). Returns ------- var_type : 'numeric', 'categorical', or 'datetime' Name identifying the type of data in the vector. rYrXrM)actionrrrRNr c@|D]}t|tsdSdSNFT)rDr r'x_is r all_numericz"variable_type..all_numerics4  Cc6** uu trcX|D]&}t|ttjfsdS'dSr)rDr rF datetime64rs r all_datetimez#variable_type..all_datetimes;  CcHbm#<== uu tr)rHrIrDrVCategoricalDtyperr_r`rr2catch_warnings simplefilter FutureWarningDeprecationWarningrFrUrtapitypesis_numeric_dtypeis_datetime64_dtype)vectorrrr s rrrsG.Yv  F&, 344+M*** wv'I&&&]]__F  " "  }6H&I     wv1v&&**,, 2#L11          2    D                 v|$$V,,'I&&& v|''//(J'''  {6'I&&& |F(J'''  & &&s6#D$7DD$ DD$DD$$D(+D(Tc`|dnt|}|dnt|}d}d}|wt|dr(tj|dd|r)|dkr#t |ddd S|wt|d r(tj|dd |r)|dkr#t |dd dSt|d s|d kr-|r)|dkr#t |ddd St|ds|dkr-|r)|dkr#t |dd dS|"d t|d }t||d kr|d krdS|dkr|dkrd S|dkr|dkrdS|rd||fvrd}t |d S)aaDetermine how the plot should be oriented based on the data. For historical reasons, the convention is to call a plot "horizontally" or "vertically" oriented based on the axis representing its dependent variable. Practically, this is used when determining the axis for numerical aggregation. Parameters ---------- x, y : Vector data or None Positional data vectors for the plot. orient : string or None Specified orientation. If not None, can be "x" or "y", or otherwise must start with "v" or "h". require_numeric : bool If set, raise when the implied dependent variable is not numeric. Returns ------- orient : "x" or "y" Raises ------ ValueError: When `orient` is an unknown string. TypeError: When dependent variable is not numeric, with `require_numeric` Nz.{} orientation requires numeric `{}` variable.z0{} orientation ignored with only `{}` specified.h HorizontalrrXVerticalr'rz5`orient` must start with 'v' or 'h' or be None, but `z ` was passed.rYz7Neither the `x` nor `y` variable appears to be numeric.) rr startswithr2r3rrtreprr) r'rorientrequire_numericx_typey_typenonnumeric_dv_errorsingle_var_warningrxs r infer_orientr"s:YTTM!$4$4FYTTM!$4$4FJKy v;; ! !# & & H M,33L#FF G G G  Iv22/66z3GGHH Hs  v;; ! !# & & F M,33JDD E E E  Kv22/66|SIIJJ Js V   $ $#  Iv22/66z3GGHH Hs V   $ $#  Kv22/66|SIIJJ Js   0LL 0 0 0 oo = V}%<%<s 9  9!4!4s 9  9!4!4s Yvv.>>>Gnnsrcgd}d}t||krtjddg|}tjddg|}tjt t |dddddt |dd}|D]M}t |ttjfd|D}||N|dz }t||k|d|S) aBuild an arbitrarily long list of unique dash styles for lines. Parameters ---------- n : int Number of unique dash specs to generate. Returns ------- dashes : list of strings or tuples Valid arguments for the ``dashes`` parameter on :class:`matplotlib.lines.Line2D`. The first spec is a solid line (``""``), the remainder are sequences of long and short dashes. )r )rW?)rRrR)?r$r&)rRrRrRr%r&rWrRrNc3 K|]}|fV dSrr$)r%seggaps rrz unique_dashes..s'*J*J#C:*J*J*J*J*J*Jr) r-r0combinations_with_replacementchainr/rErrr) nrpab segment_listsegmentsspecr*s @rrros#$F A f++//  3QIq A A  3QFA > >! GGAbDM$$B$  GGAbDM) )  %  Hh--C*J*J*J*J*J*J*JKLLD MM$     Q% f++//( "1":rcgd}d}t||krNd|dzz dz }||dzd|f|dzd|f|ddf|ddfg|dz }t||kN|d|S)aWBuild an arbitrarily long list of unique marker styles for points. Parameters ---------- n : int Number of unique marker specs to generate. Returns ------- markers : list of string or tuples Values for defining :class:`matplotlib.markers.MarkerStyle` objects. All markers will be filled. ) oX)rWr-P)rWrr)rWrRr^)rWrRr7rr'ihrRrrN)r-r3)r-rrr/s rrrs   G A g,,   1q5MA  UAqM UAqM 1I 1I     Q g,,   2A2;rcl|t|dr|j}nr |jj}nd#ttf$rPt j|}t|dkrtj |}YnwxYwtt j |}t|S)aReturn a list of unique data values. Determine an ordered list of levels in ``values``. Parameters ---------- vector : list, array, Categorical, or Series Vector of "categorical" values order : list-like, optional Desired order of category levels to override the order determined from the ``values`` object. Returns ------- order : list Ordered list of category levels not including null values. Nr rX)rRr catrtr rHrIrrrFrfilternotnullrE)rrks rrrs& } 6< ( ( +%EE + -~. + + + &))0022 ((I55GENNE  +rz5)) ;;s )AB  B r)NNNTr)+ __future__rr2r0rrrcollections.abcrrr numbersr r numpyrFpandasrH matplotlibrseaborn._core.datar seaborn.palettesr r seaborn.utilsrrrrrrrrQrrrrrr"rrrr$rrrGs""""""""""""7777777777''''''8=8=8=8=8=8=8=8=vO0O0O0O0O0O0O0O0dZ6Z6Z6Z6Z6/Z6Z6Z6z[[[[[?[[[BA A A A A A A A H""""":"""(Y'Y'Y'Y'xPPPPf000f+++\!!!!!!r