|LeUddlmZddlZddlmZddlmZddlZddl m Z m Z m Z m Z ddl mZddlmZmZddlZddlmZmZdd lmZmZdd lmZ dd lmZm Z m!Z!m"Z"m#Z#m$Z$m%Z%m&Z&m'Z'm(Z(m)Z)m*Z*m+Z+n#e,$rd \ ZZ Z!Z"Z#Z$Z%Z&Z'Z(Z)Z*Z+YnwxYw ddl-Z-ddl.Z/n#e0$rdxZ-Z/YnwxYwd dl1m2Z2m3Z3m4Z4m5Z5m6Z6m7Z7m8Z8m9Z9m:Z:m;Z;mZ>m?Z?m@Z@GddeZAGddeZBGdde2ZCGddeCZDGddeCZEGddeEZFGddeFZGGddeGZHGdd eEZIGd!d"e2ZJGd#d$eJZKGd%d&eKZLGd'd(eLZMGd)d*eJZNGd+d,eKZOGd-d.eJZPGd/d0eJZQGd1d2eQZRGd3d4eQZSGd5d6eSZTGd7d8eQZUGd9d:eQZVGd;deNZXGd?d@eJZYGdAdBeJZZGdCdDeJZ[GdEdFeJZ\GdGdHe\Z]GdIdJe\Z^GdKdLeKZ_GdMdNe_Z`GdOdPe`ZaGdQdRe`ZbGdSdTe_ZcGdUdVe_ZdGdWdXeJZeGdYdZeQZfGd[d\e2ZgGd]d^eKZhGd_d`ehZiGdadbehZjGdcdde_ZkGdedfekZlGdgdhekZmeneodiepqDddgzZrdS)j) annotationsN)Enum)Version)dshape isnumericRecordOption) coretypes)concatunique)AntialiasCombinationAntialiasStage2)isminus1isnull)cuda) cuda_atomic_nanmincuda_atomic_nanmax cuda_argscuda_row_min_in_placecuda_nanmax_n_in_place_4dcuda_nanmax_n_in_place_3dcuda_nanmin_n_in_place_4dcuda_nanmin_n_in_place_3dcuda_row_max_n_in_place_4dcuda_row_max_n_in_place_3dcuda_row_min_n_in_place_4dcuda_row_min_n_in_place_3dcuda_shift_and_insert) NNNNNNNNNNNNN)Exprngjitnansum_missingnanmax_in_placenansum_in_placerow_min_in_placenanmax_n_in_place_4dnanmax_n_in_place_3dnanmin_n_in_place_4dnanmin_n_in_place_3drow_max_n_in_place_4drow_max_n_in_place_3drow_min_n_in_place_4drow_min_n_in_place_3dshift_and_insertceZdZdZdZdS) SpecialColumna Internally datashader identifies the columns required by the user's Reductions and extracts them from the supplied source (e.g. DataFrame) to pass through the dynamically-generated append function in compiler.py and end up as arguments to the Reduction._append* functions. Each column is a string name or a SpecialColumn. A column of None is used in Reduction classes to denote that no column is required. rN)__name__ __module__ __qualname____doc__RowIndex5lib/python3.11/site-packages/datashader/reductions.pyr0r0-sHHHr7r0ceZdZdZdZdZdZdS) UsesCudaMutexaY Enum that encapsulates the need for a Reduction to use a CUDA mutex to operate correctly on a GPU. Possible values: No: the Reduction append_cuda function is atomic and no mutex is required. Local: Reduction append_cuda needs wrapping in a mutex. Global: the overall compiled append function needs wrapping in a mutex. rrN)r1r2r3r4NoLocalGlobalr6r7r8r:r:9s) B E FFFr7r:cFeZdZdZddZedZedZdS) Preprocessz#Base clase for preprocessing steps.columnstr | SpecialColumn | Nonec||_dSNrAselfrAs r8__init__zPreprocess.__init__Is  r7c|jfSrDrErGs r8inputszPreprocess.inputsLs  ~r7cdSrDr6rJs r8nan_check_columnzPreprocess.nan_check_columnPstr7NrArB)r1r2r3r4rHpropertyrKrMr6r7r8r@r@Gsd--XXr7r@ceZdZdZdZdS)extractz=Extract a column from a dataframe as a numpy array of values.c|jtjurjd}t|tjr|j|}|jd}n3t|dd}t|p||d}t|}trt|tj r|jtjur$tj |||ztjS||jjjdkr tj}nd}t%tjt%dkr!||j|Stj||j| S|jtjurJ|r$tj |||ztjStj |||ztjSt|tjr]|rIt||jjtjstj||jS||jjS||jjS) N_datashader_row_offset_datashader_row_lengthattrsrdtypef22.02na_valuefillna)rAr0r5 isinstancexrDatasetrUgetattrlencudf DataFramecparangenpint64rWkindnanr __version__to_cupyarray to_gpu_arraydatandarrayasarrayvalues)rGdfr attr_name row_offset row_lengthrUnullvals r8applyz extract.applyWs ;-0 0 00I"bj)) %Xi0 X&>? GT22$U[b)Q??  WW  *Jr4>22 *{m444yZ*-DBHUUUU$+$)S00&t'((GG,<,<<<$+...@@@8Bt{O888HHII I [M2 2 2 VyZ*-DBHUUUUyZ*-DBHUUUU BJ ' ' * ,Jr$+';RZHH ,z"T[/222$+++dk?) )r7N)r1r2r3r4rxr6r7r8rQrQUs)GG!*!*!*!*!*r7rQc:eZdZdZedZdZdZdZdS)CategoryPreprocessz*Base class for categorizing preprocessors.c|jSz"Returns name of categorized columnrErJs r8 cat_columnzCategoryPreprocess.cat_column}s {r7c td)z7Returns list of categories corresponding to input shapezcategories not implementedNotImplementedErrorrG input_dshapes r8 categorieszCategoryPreprocess.categoriess!">???r7c td)zValidates input shapezvalidate not implementedrrG in_dshapes r8validatezCategoryPreprocess.validates!"<===r7c td)z3Applies preprocessor to DataFrame and returns arrayzapply not implementedrrGrsrs r8rxzCategoryPreprocess.applys!"9:::r7N) r1r2r3r4rOr}rrrxr6r7r8rzrz{sc44 X@@@>>>;;;;;r7rzc$eZdZdZdZdZdZdS)category_codesal Extract just the category codes from a categorical column. To create a new type of categorizer, derive a subclass from this class or one of its subclasses, implementing ``__init__``, ``_hashable_inputs``, ``categories``, ``validate``, and ``apply``. See the implementation of ``category_modulo`` in ``reductions.py`` for an example. c0|j|jjSrD)measurerArrs r8rzcategory_codes.categoriess#DK0;;r7c|j|jvrtdt|j|jt jstddS)Nspecified column not foundzinput must be categorical)rAdict ValueErrorr^rct Categoricalrs r8rzcategory_codes.validatesW ;in , ,9:: :)+DK8".II :899 9 : :r7cttrt|tjr|ttjtdkr)||jjjS||jjj S||jjjj SNrY) rcr^rdrrkrAcatcodesrlrnrrrs r8rxzcategory_codes.applys  4Jr4>22 4t'((GG,<,<<<$+*088:::dk?&,99;; ;dk?&,3 3r7N)r1r2r3r4rrrxr6r7r8rrsK  <<<::: 44444r7rc eZdZdZejejejejej ej ej ej ej h Zdfd ZfdZdZdZdZxZS) category_moduloz A variation on category_codes that assigns categories using an integer column, modulo a base. Category is computed as (column_value - offset)%modulo. rcft|||_||_dSrD)superrHoffsetmodulo)rGrArr __class__s r8rHzcategory_modulo.__init__s-      r7cbt|j|jfzSrD)r_hashable_inputsrrrGrs r8rz category_modulo._hashable_inputss'ww''))T[$+,FFFr7cDtt|jSrD)listrangerrs r8rzcategory_modulo.categoriessE$+&&'''r7c|j|jvrtd|j|j|jvrtddS)Nrzinput must be an integer column)rArrr IntegerTypesrs r8rzcategory_modulo.validatesP ;in , ,9:: :  T[ )1B B B>?? ? C Br7c0||j|jz |jz}trlt |tjrRt tjt dkr|S| S|j Sr) rArrrcr^Seriesrrkrlrnrr)rGrsrresults r8rxzcategory_modulo.applys~T[/DK/4;>  !Jr4;// !t'((GG,<,<<<~~'''&&(( (= r7)r)r1r2r3r4rbool_uint8uint16uint32uint64int8int16int32rhrrHrrrrx __classcell__rs@r8rrsHbh 29biRTRZHbh(L GGGGG(((@@@ !!!!!!!r7rc:eZdZdZdfd ZfdZdZdZxZS)category_binninga A variation on category_codes that assigns categories by binning a continuous-valued column. The number of categories returned is always nbins+1. The last category (nbin) is for NaNs in the data column, as well as for values under/over the binned interval (when include_under or include_over is False). Parameters ---------- column: column to use lower: lower bound of first bin upper: upper bound of last bin nbins: number of bins include_under: if True, values below bin 0 are assigned to category 0 include_over: if True, values above the last bin (nbins-1) are assigned to category nbin-1 Tct||dz||_||z t|z |_||_|rdn||_|r|dz n||_dSNrr)rrHbin0floatbinsizenbins bin_underbin_over)rGrAlowerupperr include_under include_overrs r8rHzcategory_binning.__init__sm +++  u5  +6$0;qe r7czt|j|j|j|jfzSrD)rrrrrrrs r8rz!category_binning._hashable_inputss1ww''))TY dnVZVc,dddr7c@|j|jvrtddS)Nr)rArrrs r8rzcategory_binning.validates( ;in , ,9:: : - ,r7ctrt|tjrttjtdkr,||jtj}n3tj ||j d}tj |}n3||j }tj |}||jz |jz }d||<|t"}|j||dk<|j|||jk<|j||<|S)NrYrZTr\r)rcr^rdrrkrArlrerjrmrnisnanto_numpyrgrrastypeintrrr)rGrsrrr nan_values index_floatindexs r8rxzcategory_binning.applys  *Jr4>22 *t'((GG,<,<<<DK00"&0AA"T[/">">d">"K"KLL&))JJ _--//F&))J )T\9 #$ J""3''>eai%)]etz!" Jj r7)TT) r1r2r3r4rHrrrxrrs@r8rrs <<<<<<eeeee;;;r7rc`eZdZdZfdZedZedZdZdZ dZ xZ S)category_valueszVExtract a category and a value column from a dataframe as (2,N) numpy array of values.cXt|||_dSrD)rrH categorizer)rGr value_columnrs r8rHzcategory_values.__init__s) &&&&r7c(|jj|jfSrDrrArJs r8rKzcategory_values.inputs s '55r7c|jjSr|rrJs r8r}zcategory_values.cat_columns&&r7c|jjSrD)rrrs r8rzcategory_values.categoriess**r7c6|j|SrD)rrrs r8rzcategory_values.validates((333r7c|j||}trQt|tjr6ddl}|jtjkrd}n*||jj j dkr tj }nd}| |}|jtjkr.ttj||}nttjtdkr"||j|}n3| ||j|}|||fdS|jtjkr.ttj||}n||jj}tj||fdS)NrrXrYrZaxis)rrxrcr^rdcupyrAr0r5rWrirgrjrqrQrrkrlr]stackrr)rGrsrarrwbs r8rxzcategory_values.applys   " "2t , ,  -Jr4>22 - KKK{m444DK&+s22& QA{m444M23399"dCC)**gg.>.>>>t{O++W+==LLDK!7!7!@!@AA::q!f2:.. .{m444M23399"dCCt{O*8QF,,, ,r7) r1r2r3r4rHrOrKr}rrrxrrs@r8rrs``'''''66X6''X'+++444-------r7rc>eZdZdZd!d"dZedZd#d Zd Zd Z ed Z d Z dZ dZ d$dZdZdZd%dZdZdZd%dZdZedZedZedZedZedZedZed ZdS)& Reductionz"Base class for per-bin reductions.NrArBc"||_d|_dSrD)rA_nan_check_columnrFs r8rHzReduction.__init__7s !%r7c<|jt|jSdSrD)rrQrJs r8rMzReduction.nan_check_column;s!  ! -4122 24r7returnr:ctjS)a1Return ``True`` if this Reduction needs to use a CUDA mutex to ensure that it is threadsafe across CUDA threads. 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Fr6rGr partitioneds r8uses_row_indexzReduction.uses_row_indexLs ur7c|jtjkrdS|j|jvrt dt |j|jst ddS)Nrzinput must be numeric)rAr0r5rrrrrs r8rzReduction.validate]sh ;-0 0 0 F ;in , ,9:: :*4;788 6455 5 6 6r7c,t|jfSrDrQrArJs r8rKzReduction.inputse $$&&r7cdS)z?Return ``True`` if this is or contains a categorical reduction.Fr6rJs r8is_categoricalzReduction.is_categoricalisur7cdS)z]Return ``True`` if this is a ``where`` reduction or directly wraps a where reduction.Fr6rJs r8is_wherezReduction.is_wherems ur7cdS)NFr6rJs r8_antialias_requires_2_stagesz&Reduction._antialias_requires_2_stagesrs ur7tuple[AntialiasStage2]c@tt|d)Nz"._antialias_stage_2 is not defined)rtyperGself_intersect array_modules r8_antialias_stage_2zReduction._antialias_stage_2xs!"T$ZZ"S"S"STTTr7c|fSrDr6rs r8 _build_baseszReduction._build_bases~s wr7cdSNr6r6rs r8_build_combine_tempszReduction._build_combine_tempss rr7FcdSrr6rGrs r8 _build_tempszReduction._build_tempss rr7ct|jdd}|Dt|jjdkr'|jjd}t |d}t |t rt |j}|t tj kr|j S|t tj kr|j S|t tj kr|jS|t tjkr|jS|t tjkr|jSt'dt)NfieldsrrzUnexpected dshape )rarrbrrr^r tyrr _create_boolfloat32_create_float32_nanfloat64_create_float64_nanrh _create_int64r_create_uint32r)rGrequired_dshaper first_fields r8 _build_createzReduction._build_creates$0(DAA  #o&=&D"E"E"I"I)18;K$[^44O ov . . 9$_%788O fRX.. . .$ $ rz 2 2 2 2+ + rz 2 2 2 2+ + rx 0 0 0 0% % ry 1 1 1 1& &%&C6&C&CDD Dr7c|r.|r|j|jS|r|jS|j|jS|jS|r|j|jS|r|jS|j|jS|jSrD) rA_append_no_field_antialias_cuda_append_antialias_cuda_append_no_field_cuda _append_cuda_append_no_field_antialias_append_antialias_append_no_field_appendrGrschemar antialiasrs r8 _build_appendzReduction._build_appends  $ )T[0;; )22$11(( $T[066 $--$,,|#r7c|jSrD)_combinerGrrrr categoricals r8_build_combinezReduction._build_combines }r7c|jSrD) _finalize)rGrs r8_build_finalizezReduction._build_finalizes ~r7c0||dS)NboolrVzerosshapers r8rzReduction._create_bools!!%v!666r7c<|||jdS)Nf4rVfullrjr)s r8rzReduction._create_float32_nan    (8 EEEr7c<|||jdSNf8rVr-r)s r8r zReduction._create_float64_nanr/r7c0||dSr1)emptyr)s r8_create_float64_emptyzReduction._create_float64_empty!!%t!444r7c0||dSr1r'r)s r8_create_float64_zerozReduction._create_float64_zeror6r7c2||ddS)Nri8rV)r.r)s r8r zReduction._create_int64s  $ 777r7c0||dS)Nu4rVr'r)s r8r zReduction._create_uint32r6r7rDrNrr:rrF)r1r2r3r4rHrOrMrrrrKrrrrrrrrrr!r$ staticmethodrrr r5r8r r r6r7r8rr5s,,&&&&&X     "666''X'  UUUU  EEE.$$$(77\7FF\FFF\F55\555\588\855\555r7rc\eZdZdZdfd ZedZfdZed dZ xZ S) OptionalFieldReductionzOBase class for things like ``count`` or ``any`` for which the field is optionalNcJt|dSrD)rrHrGrArs r8rHzOptionalFieldReduction.__init__s!      r7c>|jt|jfndSr)rArQrJs r8rKzOptionalFieldReduction.inputss!*.+*A $$&&rIr7c\|j#t|dSdSrD)rArrrGrrs r8rzOptionalFieldReduction.validates1 ; " GG  Y ' ' ' ' ' # "r7Fc 2tj|dfi|SNrr_ DataArraybasesrkwargss r8r#z OptionalFieldReduction._finalize|E!H/////r7rDr?) r1r2r3r4rHrOrKrr@r#rrs@r8rBrBsYY!!!!!!JJXJ(((((000\00000r7rBc>eZdZdZdfd ZdZfdZfdZxZS) &SelfIntersectingOptionalFieldReductionz Base class for optional field reductions for which self-intersecting geometry may or may not be desirable. Ignored if not using antialiasing. NTcXt|||_dSrDrrHrrGrArrs r8rHz/SelfIntersectingOptionalFieldReduction.__init__)    ,r7c|j SrDrrJs r8rzCSelfIntersectingOptionalFieldReduction._antialias_requires_2_stages&&&r7c|r.|s,|r|j|jS|jS|j|jS|jSt |||||SrD)rA2_append_no_field_antialias_cuda_not_self_intersect)_append_antialias_cuda_not_self_intersect-_append_no_field_antialias_not_self_intersect$_append_antialias_not_self_intersectrrrGrrrrrrs r8rz4SelfIntersectingOptionalFieldReduction._build_appendss  E^ E E;&RRII;&MMDDww$$VVT9nUUUr7cVt|jfzSrDrrrrs r8rz7SelfIntersectingOptionalFieldReduction._hashable_inputs &ww''))T-@,BBBr7NT r1r2r3r4rHrrrrrs@r8rQrQs ------'''VVVVV"CCCCCCCCCr7rQceZdZdZdZddZeedZeedZ eedZ eed Z eed Z eed Z eejd dZeejd dZeejd dZeejd dZeejd dZddZedZedZdS)countaCount elements in each bin, returning the result as a uint32, or a float32 if using antialiasing. Parameters ---------- column : str, optional If provided, only counts elements in ``column`` that are not ``NaN``. Otherwise, counts every element. cj|rttjnttjSrD)rrrrrGrrrrs r8 out_dshapezcount.out_dshapes&%.Evbj!!!F294E4EEr7rrc|r ttj|jfSttj|jfSrDrr SUM_1AGGrjSUM_2AGGrs r8rzcount._antialias_stage_2?  W#$8$Ar?)r1r2r3r4rhrr@r!rrr]rrr\rjitrrZrrrr!rrr6r7r8reresyFFFWWWW  U\   U\  U\  U\  U\  U\W[\W[\W[\ W[\W[\!!!! ,,\,\r7receZdZdZeffd ZdZddZedZ edZ dZ d Z ed Z d Zd Zed ZddZdZdZddZdZdZdZddZdZdZxZS)byazApply the provided reduction separately per category. Parameters ---------- cats: str or CategoryPreprocess instance Name of column to aggregate over, or a categorizer object that returns categories. Resulting aggregate has an outer dimension axis along the categories present. reduction : Reduction Per-category reduction function. cJtt|tr||_n9t|t rt ||_ntd|jj|_|jjf|_ t|ddx}|xj |dddz c_ n |xj t|ddfz c_ ||_ |j !t|j|j |_dS|j|_dS)NzEfirst argument must be a column name or a CategoryPreprocess instancecolumnsrrA)rrHr^rzrstrr TypeErrorrArra reduction val_columnr preprocess)rGr}rrrs r8rHz by.__init__s  j"4 5 5 e)D    C ( ( e-j99D  cdd d&- (/1 y)T:: :G G LLGDDbDM )LLL LLWY$??A ALL" ? &-d.>PPDOOO".DOOOr7ctt|||j|jfSrD)hashrrrrrJs r8__hash__z by.__hash__sET$ZZ!6!6!8!8$:J:[:[:]:]^%&& &r7Fcjtfdj|DS)Nc3BK|]}tj|VdSrDrr).0tmprGs r8 z"by._build_temps..s0\\3R(#..\\\\\\r7)tuplerrrs` r8rzby._build_tempss7\\\\$.:U:UVZ:[:[\\\\\\r7c|jdSrIrrJs r8r}z by.cat_column|Ar7c|jdSNrrrJs r8rz by.val_columnrr7cn|j||j|dSrD)rrrrs r8rz by.validates4   +++  *****r7c|j|}|j||||t t fd|DS)Ncg|]}|fSr6r6)rc red_shapes r8 z!by.out_dshape..s;;;q)n;;;r7)rrrrhrr)rGrrrrcatsrs @r8rhz by.out_dshapes_**<88N--lIt[YY f;;;;d;;;<<===r7c|jfSrD)rrJs r8rKz by.inputss !!r7cdSrbr6rJs r8rzby.is_categoricaltr7c4|jSrD)rrrJs r8rz by.is_wheres~&&(((r7c|jjSrD)rrMrJs r8rMzby.nan_check_columns ~..r7rr:c4|jSrD)rrrJs r8rzby.uses_cuda_mutexs~--///r7c8|j||SrD)rrrs r8rzby.uses_row_indexs~,,T;???r7c4|jSrD)rrrJs r8rzby._antialias_requires_2_stagess~::<<%(V[,/F,>,02224 4r7cHtjjfdS)NcTj|fz|SrD)rr)r*rn_catsr rGs r8z"by._build_create..s7,4>+G+G ,,"fY. ,>,>r7)rbrr)rGr rs``@r8rzby._build_creates;_,344>>>>>> >r7cj||}t|dkr |dur|Stfd|DS)Nrrc3BK|]}tj|VdSrDr)rbaserGs r8rz"by._build_bases..s0BBDR($//BBBBBBr7)rrrbr)rGrrrMs` r8rzby._build_basess_++D+>> u::??uQx4//LBBBBEBBBBBBr7c>|j|||||SrD)rrrs r8rzby._build_appends ~++FFD)^\\\r7c>|j||||dSrb)rr!rs r8r!zby._build_combines!~,,VYkSWXXXr7c8|j||SrD)rrrs r8rzby._build_combine_tempss~224EEEr7cjtjdfd }|S)NFctj|}|dxxjgz cc<|dj<j|fd|i|S)Ndimscoordsr)copydeepcopyr}rr$)rMrrNrrrGs r8finalizez$by._build_finalize..finalize sm]6**F 6NNNt/ /NNN04F8 T_ -94>11&99%UUdUfUU Ur7r?)rrr)rGrrrs`` @r8r$zby._build_finalizesZD$//7788 V V V V V V V Vr7r?r=r>)r1r2r3r4rerHrrrOr}rrrhrKrrrMrrrrrrrr!rr$rrs@r8rrs  .3UWW//////8&&&]]]]XX+++>>> ""X")))//X/0000@@@===4444>>> CCC ]]]YYYYFFF       r7rceZdZdZdZddZeedZeedZ eedZ eed Z eZ e Z dd Zed Zed ZdS)anyzWhether any elements in ``column`` map to each bin. Parameters ---------- column : str, optional If provided, any elements in ``column`` that are ``NaN`` are skipped. cj|rttjnttjSrD)rrrrrgs r8rhzany.out_dshapes&%.Dvbj!!!F284D4DDr7rrcBttj|jfSrDrr MAXrjrs r8rzany._antialias_stage_2 4 8,:JKKMMr7c6t|s d|||f<dSdS)NTrrrprqs r8rz any._append"s)e}} C1I1rr7ct|s.t|||fs||||fkr ||||f<dSdSrwrprxs r8rzany._append_antialias*r{r7cd|||f<dS)NTrr6r}s r8rzany._append_no_field3sAqD qr7cbt|||fs||||fkr ||||f<dSdSrwrprs r8rzany._append_no_field_antialias9rr7Fc"|r|jS|jSrDrrs r8r!zany._build_combineErr7c0|ddS)Nrr&rrrs r8rz any._combineKsxxQfx---r7c|d}tdt|D]}t||||Sr)rrbr#rs r8rzany._combine_antialiasOrr7Nr>r?)r1r2r3r4rhrr@r!rrrrrrr!rrr6r7r8rrs3EEENNNN  U\   U\  U\  U\L,!!!! ..\.\r7rceZdZdZdZed dZedZdZ ee dZ ee j d d Zed Zd S) _upsamplez+"Special internal class used for upsamplingcNtttjSrDrr rr rgs r8rhz_upsample.out_dshapeYfRZ(()))r7Fc 2tj|dfi|SrIrJrLs r8r#z_upsample._finalize\rOr7c,t|jfSrDrrJs r8rKz_upsample.inputs`rr7c|jSrD)r5rGr s r8rz_upsample._build_createds ))r7cdSrDr6rqs r8rz_upsample._appendi  r7TrcdSrDr6rqs r8rz_upsample._append_cudaorr7c.tj|dSNrrrgnanmaxrs r8rz_upsample._combineuyA&&&&r7Nr?)r1r2r3r4rhr@r#rOrKrr!rrrrrr6r7r8rrWs55***000\0''X'***     U\ W[  \ ''\'''r7rc0eZdZdZdZeddZdS)FloatingReductionzBBase classes for reductions that always have floating-point dtype.cNtttjSrDrrgs r8rhzFloatingReduction.out_dshape|rr7Fc 2tj|dfi|SrIrJrLs r8r#zFloatingReduction._finalizerOr7Nr?)r1r2r3r4rhr@r#r6r7r8rrzsILL***000\000r7rceZdZdZddZdZeedZeedZ eedZ ee j d d Z ed Zd S) _sum_zerozSum of all elements in ``column``. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be numeric. rrcr|rttjdfSttjdfSrI)rr rkrlrs r8rz_sum_zero._antialias_stage_2s9  H#$8$A1EEG G#$8$A1EEG Gr7c|jSrDr8rs r8rz_sum_zero._build_create ((r7cLt|s|||fxx|z cc<dSdSrwrprqs r8rz_sum_zero._appends6e}}  1III III1rr7cV||z}t|s|||fxx|z cc<dSdSrwrprrrsrtruryrs r8rz_sum_zero._append_antialiass?ie}}  1III III1rr7c\||z}t|s||||fkr ||||f<dSdSrwrprs r8r]z._sum_zero._append_antialias_not_self_intersectsDie}} QT!2!2C1I1rr7Trcnt|s%tj|||f|dSdSrwrrqs r8rz_sum_zero._append_cudas:e}}  N  sQFE 2 2 21rr7c0|ddS)Nrr2rrrs r8rz_sum_zero._combinerr7Nr>)r1r2r3r4rrr@r!rrr]rrrrr6r7r8rrsHHHH )))  U\  U\  U\W[\ ,,\,,,r7rc>eZdZdZdfd ZdZfdZfdZxZS) !SelfIntersectingFloatingReductionz Base class for floating reductions for which self-intersecting geometry may or may not be desirable. Ignored if not using antialiasing. NTcXt|||_dSrDrSrTs r8rHz*SelfIntersectingFloatingReduction.__init__rUr7c|j SrDrWrJs r8rz>SelfIntersectingFloatingReduction._antialias_requires_2_stagesrXr7c|r(|s&|rtd|j|jS|jSt |||||S)NrQ)rrAr\r]rrr^s r8rz/SelfIntersectingFloatingReduction._build_appendsf  E^ E E)*RSSS;&MMDDww$$VVT9nUUUr7cVt|jfzSrDr`rs r8rz2SelfIntersectingFloatingReduction._hashable_inputsrar7rbrcrs@r8rrs ------''' V V V V VCCCCCCCCCr7rceZdZdZd dZdZeedZeedZ eedZ ed Z edd Z d S)raSum of all elements in ``column``. Elements of resulting aggregate are nan if they are not updated. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be numeric. ``NaN`` values in the column are skipped. rrc|r ttj|jfSttj|jfSrDrjrs r8rzsum._antialias_stage_2rmr7c\|r(t|jt|jfS|fSrD)rrArrs r8rzsum._build_basess0  dk**C ,<,<= =7Nr7ct|s3t|||fr||||f<n|||fxx|z cc<dSdSrwrprqs r8rz sum._appends]e}} c!Q$i   #!AqD AqD U" 1rr7c||z}t|s3t|||fr||||f<n|||fxx|z cc<dSdSrwrprs r8rzsum._append_antialiassfie}} c!Q$i   #!AqD AqD U" 1rr7c||z}t|s.t|||fs||||fkr ||||f<dSdSrwrprs r8r]z(sum._append_antialias_not_self_intersects\ie}} c!Q$i   EC1I$5$5!AqD qrr7c$t|dSr)r"rs r8rz sum._combinesd++++r7Fc |r7|\}}tj||tj}tj|fi|Stj|dfi|SrI)rgwhererjr_rK)rMrrNsumsanysrrs r8r#z sum._finalizes\  4JD$tRV,,A<,,V,, ,<a33F33 3r7Nr>r?) r1r2r3r4rrr@r!rrr]rr#r6r7r8rrs  WWWW   U\  U\  U\,,\,444\444r7rceZdZdZddZfdZdZddZee d Z ee j d d Z ed ZxZS)m2a`Sum of square differences from the mean of all elements in ``column``. Intermediate value for computing ``var`` and ``std``, not intended to be used on its own. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be numeric. ``NaN`` values in the column are skipped. rr:ctjSrD)r:r>rJs r8rzm2.uses_cuda_mutex3s ##r7c\tt||||||SrD)rr$rr^s r8rzm2._build_append6s'R,,VVT9n]]]r7c|jSrDr rs r8rzm2._build_create9r r7FcRt|jt|jfSrDrrArers r8rzm2._build_temps<!$+&&dk(:(:;;r7ct|sW|dkrQtj||z }tj||z|dzz }|||fxx||z ||z zz cc<dSdSNrrrrrgr rrrsr$rurreu1us r8rz m2._append@z e}} qyyZ__u,JsU{++uqy91a4URZEAI66qrr7Trct|sW|dkrQtj||z }tj||z|dzz }|||fxx||z ||z zz cc<dSdSr,r-r.s r8rzm2._append_cudaNr1r7ctjdd5tj|d|dz }tj||||z |z dzzzdcdddS#1swxYwYdS)Nignoredivideinvalidrrr;)rgerrstatenansumr)Msr!nsmus r8rz m2._combine[s [( ; ; ; @ @4a(((266q6>>9B9R"d2glQ%6"66Q??? @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @sAA66A:=A:r=r?)r1r2r3r4rrrrr@r!rrrrrrrs@r8r$r$'s  $$$$^^^^^)))<<<<    U\ W[  \ @@\@@@@@r7r$ceZdZdZdZd dZeedZeedZ ee j d d Z ed Z d S)minzMinimum value of all elements in ``column``. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be numeric. ``NaN`` values in the column are skipped. cdSrbr6rJs r8rz min._antialias_requires_2_stageskrr7rrcBttj|jfSrDrr MINrjrs r8rzmin._antialias_stage_2nrr7ct|s.t|||fs|||f|kr ||||f<dSdSrwrprqs r8rz min._appendrRe}} &QT"3"3 s1a4y57H7HC1I1rr7c||z}t|s.t|||fs||||fkr ||||f<dSdSrwrprs r8rzmin._append_antialiasz[ie}} &QT"3"3 us1a4y7H7HC1I1rr7Trcxt|s*t|||f|}t|s||krdSdSrw)rrrrrsrtrurs r8rzmin._append_cudaGe}} $S1a&%88Cc{{ cEkkqrr7c.tj|dSr)rgnanminrs r8rz min._combinerr7Nr>)r1r2r3r4rrr@r!rrrrrrr6r7r8r>r>bsNNNN  U\   U\W[\''\'''r7r>ceZdZdZd dZeedZeedZee j dd Z ee j dd Z ed Z d S)maxzMaximum value of all elements in ``column``. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be numeric. ``NaN`` values in the column are skipped. rrcBttj|jfSrDrrs r8rzmax._antialias_stage_2rr7ct|s.t|||fs|||f|kr ||||f<dSdSrwrprqs r8rz max._appendrDr7c||z}t|s.t|||fs||||fkr ||||f<dSdSrwrprs r8rzmax._append_antialiasrFr7Trc||z}t|s*t|||f|}t|s||krdSdSrwrrs r8rzmax._append_antialias_cudarr7cxt|s*t|||f|}t|s||krdSdSrwrrHs r8rzmax._append_cudarIr7c.tj|dSrrrs r8rz max._combinerr7Nr>)r1r2r3r4rr@r!rrrrrrrr6r7r8rMrMsNNNN  U\   U\W[\W[\''\'''r7rMc"eZdZdZfdZxZS) count_cata]Count of all elements in ``column``, grouped by category. Alias for `by(...,count())`, for backwards compatibility. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be categorical. Resulting aggregate has a outer dimension axis along the categories present. crtt||tdSrD)rrUrHrerDs r8rHzcount_cat.__init__s- i''88888r7)r1r2r3r4rHrrs@r8rUrUsB  999999999r7rUc0eZdZdZdZeddZdS)meanzMean of all elements in ``column``. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be numeric. ``NaN`` values in the column are skipped. cRt|jt|jfSrDr)rs r8rzmean._build_basesr*r7Fc |\}}tjdd5tj|dk||z tj}dddn #1swxYwYt j|fi|SNr4r5rrgr8r rjr_rK)rMrrNr!countsrrs r8r#zmean._finalizes f [( ; ; ; : :!T&["&99A : : : : : : : : : : : : : : :|A(((((s(AAANr?r1r2r3r4rr@r#r6r7r8rXrXsM<<<)))\)))r7rXc0eZdZdZdZeddZdS)varzVariance of all elements in ``column``. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be numeric. ``NaN`` values in the column are skipped. cxt|jt|jt|jfSrDrrArer$rs r8rzvar._build_bases+$+&&dk(:(:Bt{OOLLr7Fc |\}}}tjdd5tj|dk||z tj}dddn #1swxYwYt j|fi|Sr[r\rMrrNr!r]m2srrs r8r#z var._finalizes!fc [( ; ; ; ; ;!S6\26::A ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;|A(((((s(AAANr?r^r6r7r8r`r`PMMM)))\)))r7r`c0eZdZdZdZeddZdS)stdzStandard Deviation of all elements in ``column``. Parameters ---------- column : str Name of the column to aggregate over. Column data type must be numeric. ``NaN`` values in the column are skipped. cxt|jt|jt|jfSrDrbrs r8rzstd._build_bases rcr7Fc |\}}}tjdd5tj|dktj||z tj}dddn #1swxYwYt j|fi|Sr[)rgr8r sqrtrjr_rKres r8r#z std._finalize s!fc [( ; ; ; D D!RWS6\%:%:BFCCA D D D D D D D D D D D D D D D|A(((((s:A##A'*A'Nr?r^r6r7r8ririrgr7richeZdZdZdZdZdZfdZedZ dZ ed d Z xZ S) _first_or_lastz6Abstract base class of first and last reductions. c4ttjSrDrrr rgs r8rhz_first_or_last.out_dshapebj!!!r7c |p|SrDr6rs r8rz_first_or_last.uses_row_index "{"r7cdSrbr6rJs r8rz+_first_or_last._antialias_requires_2_stagesrr7c|||rP|}t||j}|j|_||||fzSt ||SN)selector lookup_columnr_create_row_index_selectorr rArrrrGrrrow_index_selectorwrapperrs r8rz_first_or_last._build_bases    t[ 1 1 ;!%!@!@!B!B %7t{SSSG(, G %%224EE R R77''k:: :r7cVt|dkrtd|dSNrz6_combine should never be called with more than one aggrrb RuntimeErrorrs r8rz_first_or_last._combine*+ t99q==WXX XAwr7cdSrDr6rJs r8rzz)_first_or_last._create_row_index_selector2 r7Fc 2tj|dfi|SNrrJrLs r8r#z_first_or_last._finalize5 |E"I00000r7r?) r1r2r3r4rhrrrr@rrzr#rrs@r8rnrns"""###;;;;;\   111\11111r7rncleZdZdZd dZeedZeedZdZ dS) firstaFirst value encountered in ``column``. Useful for categorical data where an actual value must always be returned, not an average or other numerical calculation. Currently only supported for rasters, externally to this class. Parameters ---------- column : str Name of the column to aggregate over. If the data type is floating point, ``NaN`` values in the column are skipped. rrcBttj|jfSrDrr FIRSTrjrs r8rzfirst._antialias_stage_2Ks 4 :L r1r2r3r4rr@r!rrrzr6r7r8rr=s  PPPP  U\   U\     r7rcleZdZdZd dZeedZeedZdZ dS) lastaLast value encountered in ``column``. Useful for categorical data where an actual value must always be returned, not an average or other numerical calculation. Currently only supported for rasters, externally to this class. Parameters ---------- column : str Name of the column to aggregate over. If the data type is floating point, ``NaN`` values in the column are skipped. rrcBttj|jfSrDrr LASTrjrs r8rzlast._antialias_stage_2qs 4 9<;KLLNNr7c6t|s ||||f<dSdSrwrprqs r8rz last._appendts)e}} C1I1rr7c||z}t|s.t|||fs||||fkr ||||f<dSdSrwrprs r8rzlast._append_antialias|rFr7ctSrD)_max_row_indexrJs r8rzzlast._create_row_index_selectorrr7Nr>rr6r7r8rrcs  OOOO  U\   U\     r7rcFeZdZd fd ZdZdZfdZdZfdZxZ S) FloatingNReductionNrcht||dkr|nd|_dSr)rrHn)rGrArrs r8rHzFloatingNReduction.__init__s2    1ff!r7c4ttjSrDrprgs r8rhzFloatingNReduction.out_dshaperqr7c d}tj|j}tj|}|dxx|gz cc<||d|<|S)Nrrr)rgrfrrr)rGrNn_namen_valuess r8_add_finalize_kwargsz'FloatingNReduction._add_finalize_kwargssU9TV$$v&&v6("#+x  r7cfdS)Ncztt|jfz|SrD)rrrrr*rrr rGs r8rz2FloatingNReduction._build_create..sB,51CT+J+J+X+X ,,"dfY. ,>,>r7r6rGr rs``r8rz FloatingNReduction._build_creates(>>>>>> >r7cdfd }|S)NFc>jdi|}j|fd|i|S)Nrr6)rr#)rMrrNrGs r8rz4FloatingNReduction._build_finalize..finalizes:.T.8888F!4>%==d=f== =r7r?r6)rGrrs` r8r$z"FloatingNReduction._build_finalizes( > > > > > >r7cVt|jfzSrD)rrrrs r8rz#FloatingNReduction._hashable_inputss"ww''))TVI55r7r) r1r2r3rHrhrrr$rrrs@r8rrs$$$$$$"""   >>>>>666666666r7rcbeZdZdZdZdZfdZedZdZ ed dZ xZ S) _first_n_or_last_nz:Abstract base class of first_n and last_n reductions. c |p|SrDr6rs r8rz!_first_n_or_last_n.uses_row_indexrsr7cdSrbr6rJs r8rz/_first_n_or_last_n._antialias_requires_2_stagesrr7c|||rP|}t||j}|j|_||||fzSt ||Srvryr{s r8rz_first_n_or_last_n._build_basesr~r7cVt|dkrtd|dSrrrs r8rz_first_n_or_last_n._combinerr7cdSrDr6rJs r8rzz-_first_n_or_last_n._create_row_index_selectorrr7Fc 2tj|dfi|SrrJrLs r8r#z_first_n_or_last_n._finalizerr7r?) r1r2r3r4rrrr@rrzr#rrs@r8rrs###;;;;;\   111\11111r7rcheZdZddZeedZeedZdZdS) first_nrrcFttj|jdfSNTrrrs r8rzfirst_n._antialias_stage_2s" 4 :L r1r2r3rr@r!rrrzr6r7r8rrsbbbb  U\   U\"*****r7rcheZdZddZeedZeedZdZdS) last_nrrcFttj|jdfSrrrs r8rzlast_n._antialias_stage_2s" 4 9<;KY]^^^``r7cZt|st|||f|ddSdSrwrr.rqs r8rzlast_n._appends6e}}  SAYq 1 1 11rr7cd||z}t|st|||f|ddSdSrwrrs r8rzlast_n._append_antialiass?ie}}  SAYq 1 1 11rr7c,t|jSr)_max_n_row_indexrrJs r8rzz!last_n._create_row_index_selectorrr7Nr>rr6r7r8rrsaaaa  U\  U\*****r7rceZdZddZddZeedZeedZee j d d Z dd Z ed Z edZdS)max_nrr:ctjSrDr:r=rJs r8rzmax_n.uses_cuda_mutex ""r7rcFttj|jdfSrrrs r8rzmax_n._antialias_stage_2 " 4 8,:JX\]]]__r7ct|sc|jd}t|D]F}t||||fs|||||fkrt|||f|||cSGdSNr;rrr*rr.rs r8rz max_n._append$e}}  ! A1XX  #aAg,''53q!Qw<+?+?$SAYq999HHH,@rr7c||z}t|sc|jd}t|D]F}t||||fs|||||fkrt|||f|||cSGdSrrrs r8rzmax_n._append_antialias1ie}}  ! A1XX  #aAg,''53q!Qw<+?+?$SAYq999HHH,@rr7Trct|sc|jd}t|D]F}t||||fs|||||fkrt|||f|||cSGdSrrr*rrrs r8rzmax_n._append_cuda@e}}  ! A1XX  #aAg,''53q!Qw<+?+?)#ad)UA>>>HHH,@rr7Fc"|r|jS|jSrD _combine_cudarrs r8r!zmax_n._build_combineM  !% %= r7c|d}tdt|D]F}|jdkrt|d||*t |d||G|SNrr)rrbndimr'r&rs r8rzmax_n._combineSp1gq#d))$$ 7 7Ax1}}$T!Wd1g6666$T!Wd1g6666 r7c.|d}t|jdd}tdt|D]R}|jdkr#t ||d||0t ||d||S|SNrrrr)rr*rrbrrrrr kernel_argsrs r8rzmax_n._combine_cuda]1g #2#// q#d))$$ I IAx1}})+6tAwQHHHH)+6tAwQHHHH r7Nr=r>r?)r1r2r3rrr@r!rrrrrr!rrr6r7r8rrs ####````    U\     U\ W[  \ !!!! \\r7rceZdZddZdZddZeedZeedZ ee j d d Z dd Z edZedZdS)min_nrr:ctjSrDrrJs r8rzmin_n.uses_cuda_mutexjrr7cdSrbr6rJs r8rz"min_n._antialias_requires_2_stagesmrr7rcFttj|jdfSrrArs r8rzmin_n._antialias_stage_2prr7ct|sc|jd}t|D]F}t||||fs|||||fkrt|||f|||cSGdSrrrs r8rz min_n._appendtrr7c||z}t|sc|jd}t|D]F}t||||fs|||||fkrt|||f|||cSGdSrrrs r8rzmin_n._append_antialiasrr7Trct|sc|jd}t|D]F}t||||fs|||||fkrt|||f|||cSGdSrrrs r8rzmin_n._append_cudarr7Fc"|r|jS|jSrDrrs r8r!zmin_n._build_combinerr7c|d}tdt|D]F}|jdkrt|d||*t |d||G|Sr)rrbrr)r(rs r8rzmin_n._combinerr7c.|d}t|jdd}tdt|D]R}|jdkr#t ||d||0t ||d||S|Sr)rr*rrbrrrrs r8rzmin_n._combine_cudarr7Nr=r>r?)r1r2r3rrrr@r!rrrrrr!rrr6r7r8rris####````    U\     U\ W[  \ !!!! \\r7rcZeZdZdZdZedZedZedZdS)modeatMode (most common value) of all the values encountered in ``column``. Useful for categorical data where an actual value must always be returned, not an average or other numerical calculation. Currently only supported for rasters, externally to this class. Implementing it for other glyph types would be difficult due to potentially unbounded data storage requirements to store indefinite point or line data per pixel. Parameters ---------- column : str Name of the column to aggregate over. If the data type is floating point, ``NaN`` values in the column are skipped. cNtttjSrDrrgs r8rhzmode.out_dshaperr7c tdNz.mode is currently implemented only for rastersrr}s r8rz mode._append!"RSSSr7c tdrrrs r8rz mode._combinerr7c  tdrr)rMrNs r8r#zmode._finalizerr7N) r1r2r3r4rhr@rrr#r6r7r8rrs ***TT\TTT\TTT\TTTr7rc`eZdZdZd d!fd ZdZd Zd Zd"d ZdZ fdZ d#dZ e e dZe e dZe ejddZe ejddZdZfdZdZd$dZdZfdZdZxZS)%r a Returns values from a ``lookup_column`` corresponding to a ``selector`` reduction that is applied to some other column. If ``lookup_column`` is ``None`` then it uses the index of the row in the DataFrame instead of a named column. This is returned as an int64 aggregation with -1 used to denote no value. Examples -------- >>> canvas.line(df, 'x', 'y', agg=ds.where(ds.max("value"), "other")) # doctest: +SKIP This returns the values of the "other" column that correspond to the maximum of the "value" column in each bin. Parameters ---------- selector: Reduction Reduction used to select the values of the ``lookup_column`` which are returned by this ``where`` reduction. lookup_column : str | None Column containing values that are returned from this ``where`` reduction, or ``None`` to return row indexes instead. Nrwrrx str | Nonec Ft|ttttt t ttttf std| tj }t|||_|j|f|_dS)NzWselector can only be a first, first_n, last, last_n, max, max_n, min or min_n reduction)r^rrrrrMrr>r_max_or_min_row_index_max_n_or_min_n_row_indexrr0r5rrHrwrAr)rGrwrxrs r8rHzwhere.__init__s(UGT63sTY%:>(({;;$$T;778 8r7cF|j}t|t}|r|jn|j|j||rt nttfd}tfd}tfd}tfd} tj fd} tj fd} tj fd} tj fd} |r|r|r| n| S|r| n|S|r|r| n| S|r|n|S) Nc |dj\}}t|D]b}t|D]P}|d||f}|s3|||d|dkr|d||f|d||f<QcdSrr*r) r selector_aggsnynxrsrrrappendr7s r8combine_cpu_2dz/where._combine_callback..combine_cpu_2ds!W]FB2YY 6 6r66A)!,QT2E"75>>6ffQ=;KU.S.SWX.X.X(,Q1 Q1 6 6 6r7c R|dj\}}}t|D]}t|D]r}t|D]`}|d|||f} |sB |||ddddd|f|dkr|d|||f|d|||f<asdSrr) rrrrncatrsrrrrrr7s r8combine_cpu_3dz/where._combine_callback..combine_cpu_3ds7=LBD2YY D DrDDA$T{{DD -a 0As ;&wu~~D&&A}Q?OPQPQPQSTSTSTVYPY?Z9>3@3@CD3E3E15aAs1CDGAq#I. DD D Dr7c f|dj\}}}t|D]}t|D]|}t|D]j}|d|||f} |rnK |||d|} | dkrn/t|d||f|d|||f| k}dSrr*rr.) rrrrrrsrrrrrrr7s r8combine_cpu_n_3dz1where._combine_callback..combine_cpu_n_3dsQ IBA2YY X XrXXA"1XXXX -a 0Aq 9"75>>"!E'-vaM!4De'L'L '!++!E(aAQ1a8H,WWWWX X Xr7c|dj\}}}}t|D]}t|D]}t|D]}t|D]}} |d|||| f}  | rn] |||ddddd|ddf| } | dkrn1t|d|||f|d|||| f| ~dSrr#)rrrrr rrsrrrrrrrr7s r8combine_cpu_n_4dz1where._combine_callback..combine_cpu_n_4ds1"1gmOBD!2YY ; ;r ; ;A$T{{ ; ;!&q;;A$1!$4Q3\$BE&wu~~& %+16!Q a8HAAAsTUTUTU8VX]+^+^L+a// %,T!WQ3Y-?aAsTUAV-9;;;; ; ; ; ;r7c|dj\}}tjd\}}||krV||krR|d||f}|s9|||d|dkr#|d||f|d||f<dSdSdSdSdSNrr;rr*rgrid) rrrrrrrsrrr7s r8combine_cuda_2dz0where._combine_callback..combine_cuda_2ds!W]FB<??DAq2vv!b&&%a(A.wu~~2&&A}Q7G*O*OST*T*T$(GAqDMDGAqDMMMv&&22*T*Tr7cN|dj\}}}tjd\}}}||krl||krh||krd|d|||f} |sJ |||ddddd|f|dkr'|d|||f|d|||f<dSdSdSdSdSdSNrrrr)) rrrrr rrrsrrrr7s r8combine_cuda_3dz0where._combine_callback..combine_cuda_3ds7=LBD QIAq#2vv!b&&S4ZZ%a(As3wu~~<&&A}Q7G111c 7RTY*Z*Z^_*_*_)-aAs);DGAq#I&&&v&&ZZ<<*_*_r7cp|dj\}}}tjd\}}||kr||kr~t|D]p}|d|||f} |rdS |||d|} | dkrdSt |d||f|d|||f| mdSdSdSr(r*rr*rr) rrrrrrrrsrrrrr7s r8combine_cuda_n_3dz2where._combine_callback..combine_cuda_n_3dsQ IBA<??DAq2vv!b&&qYYA)!,Q1W5Ewu~~#)6!Q a0@%#H#HL#a'')$q'!Q$-aAq9I<XXXXv&&YYr7c |dj\}}}}tjd\}}}||kr||kr||krt|D]} |d|||| f}  | rdS |||ddddd|ddf| } | dkrdSt |d|||f|d|||| f| dSdSdSdSr-r0)rrrrr rrrrsrrrrrr7s r8combine_cuda_n_4dz2where._combine_callback..combine_cuda_n_4ds"1gmOBD! QIAq#2vv!b&&S4ZZqccA)!,Q3\:Ewu~~#)6!Q a0@AAAsAAA0NPU#V#VL#a'')$q'!Q)*SUabbbbv&&ZZccr7) rwr^rrrrrrr!rr)rGrrr rwis_n_reductionrr!r$r&r+r.r1r3rr7s @@r8_combine_callbackzwhere._combine_callbackps) =#H.@AA  &*FF%F#m::4MMY((SY  6 6 6 6 6  6  D D D D D  D  X X X X X  X  ; ; ; ; ;  ;  2 2 2 2 2  2  < < < < <  <  Y Y Y Y Y  Y  c c c c c  c  I M,7N((=NN+6L''.wrapped_combines4yyA~~ V4yyA~~~~!+DM;M!N!N.<OQ crc**$q'-) %(()$ >>>>q#d)),,VVAGT!Wd1g.q1A=QRCS0TUUUU7M!,, ,r7)r5)rGrrrrr r9r8s` ` @r8r!zwhere._build_combinesG(({KHH - - - - - - -r7c|jfSrD)rwrs r8rzwhere._build_combine_tempss  r7ctjtrfdStS)Nctt|jjfz|SrD)rr rrwrrs r8rz%where._build_create.. sF0!uUD/A/A/O/O0!0!!&$-/);!;\0K0Kr7)r^rwrrrrs``r8rzwhere._build_creates` dm%7 8 8 :KKKKKK K77((99 9r7cft|jtr |jjnddfd }|S)NFcHdi|}tj|dfi|S)Nrr6rJ)rMrrNadd_finalize_kwargss r8rz'where._build_finalize..finalizes;".,,66v66<b 44V44 4r7r?)r^rwrr)rGrrr?s @r8r$zwhere._build_finalizesQ dm%7 8 8 '"&-"D  "&  5 5 5 5 5 5 r7rD)rwrrxrr=r>r?)r1r2r3r4rHrrrhrrrrr@r!rrrrrrrrr5r!rrr$rrs@r8r r s2 8 8 8 8 8 8 8JJJ&&& ####AAA]]]]]  U\  U\W[\W[\ $ $ $88888(|I|I|I|&    : : : : :       r7r cFeZdZdZdZdZdZdZdZe dZ dS) summarya%A collection of named reductions. Computes all aggregates simultaneously, output is stored as a ``xarray.Dataset``. Examples -------- A reduction for computing the mean of column "a", and the sum of column "b" for each bin, all in a single pass. >>> import datashader as ds >>> red = ds.summary(mean_a=ds.mean('a'), sum_b=ds.sum('b')) Notes ----- A single pass of the source dataset using antialiased lines can either be performed using a single-stage aggregation (e.g. ``self_intersect=True``) or two stages (``self_intersect=False``). If a ``summary`` contains a ``count`` or ``sum`` reduction with ``self_intersect=False``, or any of ``first``, ``last`` or ``min``, then the antialiased line pass will be performed in two stages. c xtt|\}}||_||_dSrD)zipsorteditemskeysrr)rGrNksvss r8rHzsummary.__init__5s2fV\\^^,,-B  r7ctt|t|jt|jfSrD)rrrrFrrrJs r8rzsummary.__hash__:s1T$ZZty!1!153E3EFGGGr7cH|jD]}|rdSdSNTF)rrr)rGvs r8rzsummary.is_categorical=s8  A!! tt ur7cL|jD]}|||rdSdSrK)rrr)rGrrrLs r8rzsummary.uses_row_indexCs<  Ak22 tt ur7cZ|jD]}||g}|jD]M}t|tr|j}t|t r||jNttj |dkrtddS)NrzKUsing multiple FloatingNReductions with different n values is not supported) rrrr^r rwrrrrbrgr r)rGrrLrs r8rzsummary.validateIs % %A JJ| $ $ $ $ % %A!U## J!/00 %$$$ ry"" # #a ' ']__ _ ( 'r7crtttd|jDS)Nc3$K|] }|jV dSrD)rK)rrLs r8rz!summary.inputs..Zs$"A"A18"A"A"A"A"A"Ar7)rr r rrrJs r8rKzsummary.inputsXs1VF"A"AT["A"A"AAABBCCCr7N) r1r2r3r4rHrrrrrOrKr6r7r8rArAs, HHH  _ _ _DDXDDDr7rAc.eZdZdZfdZdZdZxZS)rz=Abstract base class of max and min row_index reductions. c`ttjdS)NrE)rrHr0r5rs r8rHz_max_or_min_row_index.__init__`s'  677777r7c4ttjSrDrrrhrgs r8rhz _max_or_min_row_index.out_dshapecbhr7cdSrbr6rs r8rz$_max_or_min_row_index.uses_row_indexfrr7)r1r2r3r4rHrhrrrs@r8rr]s`88888   r7rceZdZdZd dZeedZeedZee j dd Z ed Z d S) rzMax reduction operating on row index. This is a private class as it is not intended to be used explicitly in user code. It is primarily purpose is to support the use of ``last`` reductions using dask and/or CUDA. rrc8ttjdfSrrr rrs r8rz!_max_row_index._antialias_stage_2q 4 8"==??r7c4||||fkr ||||f<dSdSrwr6rqs r8rz_max_row_index._appendts. 3q!t9  C1I1rr7c4||||fkr ||||f<dSdSrwr6rxs r8rz _max_row_index._append_antialias}s. 3q!t9  C1I1rr7Trch|dkr+tj|||f|}||krdSdSNrr)rrrMrHs r8rz_max_row_index._append_cudas= B;;.$$S1a&%88CU{{qrr7c|d}tdt|D]}tj|||| |S)Nrr)out)rrbrgmaximumrs r8rz_max_row_index._combinesO1gq#d))$$ . .A JsDG - - - - - r7Nr>) r1r2r3r4rr@r!rrrrrrr6r7r8rrjs @@@@  U\  U\W[\\r7rceZdZdZdZddZddZeedZ eed Z ee j d d Z ddZedZedZdS)rzMin reduction operating on row index. This is a private class as it is not intended to be used explicitly in user code. It is primarily purpose is to support the use of ``first`` reductions using dask and/or CUDA. cdSrbr6rJs r8rz+_min_row_index._antialias_requires_2_stagesrr7rrc8ttjdfSrrr rBrs r8rz!_min_row_index._antialias_stage_2rZr7r:ctjSrDrrJs r8rz_min_row_index.uses_cuda_mutexrr7c\|dkr%|||fdks||||fkr ||||f<dSdSr^r6rqs r8rz_min_row_index._appendsF B;;C1IOOus1a4y/@/@C1I1rr7c\|dkr%|||fdks||||fkr ||||f<dSdSr^r6rxs r8rz _min_row_index._append_antialiasF B;;C1IOOus1a4y/@/@C1I1rr7Trc\|dkr%|||fdks||||fkr ||||f<dSdSr^r6rqs r8rz_min_row_index._append_cudarir7Fc"|r|jS|jSrDrrs r8r!z_min_row_index._build_combinerr7c|d}tdt|D]}t||||Sr)rrbr%rs r8rz_min_row_index._combinesH1gq#d))$$ + +A S$q' * * * * r7c&|d}t|dkru|jdkr d|D}t|jdd}t dt|D]$}t ||d||%|S)Nrrr;c8g|]}tj|dS)r;)re expand_dims)rrts r8rz0_min_row_index._combine_cuda..s$???3sA..???r7r)rbrrr*rrrs r8rz_min_row_index._combine_cudas1g t99q==x1}}??$???#CIbqbM22K1c$ii(( E E%k247DGDDDD r7Nr>r=r?)r1r2r3r4rrrr@r!rrrrrr!rrr6r7r8rrs" @@@@####  U\  U\W[\!!!! \  \   r7rc@eZdZdZd fd ZdZd dZdZd d ZxZ S)rzAAbstract base class of max_n and min_n row_index reductions. rc~ttj|dkr|nd|_dS)NrEr)rrHr0r5r)rGrrs r8rHz"_max_n_or_min_n_row_index.__init__s8  67771ff!r7c4ttjSrDrTrgs r8rhz$_max_n_or_min_n_row_index.out_dshaperUr7rr:ctjSrDrrJs r8rz)_max_n_or_min_n_row_index.uses_cuda_mutexrr7cdSrbr6rs r8rz(_max_n_or_min_n_row_index.uses_row_indexrr7Fc"|r|jS|jSrDrrs r8r!z(_max_n_or_min_n_row_index._build_combinerr7)rr=r?) r1r2r3r4rHrhrrr!rrs@r8rrs$$$$$$   ####!!!!!!!!r7rceZdZdZd dZeedZeedZee j dd Z ed Z ed Z d S)rzMax_n reduction operating on row index. This is a private class as it is not intended to be used explicitly in user code. It is primarily purpose is to support the use of ``last_n`` reductions using dask and/or CUDA. rrc<ttjddfSNrTrrYrs r8rz#_max_n_row_index._antialias_stage_2  4 8"$OOOQQr7c|dkrZ|jd}t|D]=}||||fdks|||||fkrt|||f|||cS>dSNrr;r#rs r8rz_max_n_row_index._append  B;; ! A1XX  q!Qw<2%%Q1W)=)=$SAYq999HHH*>rr7c|dkrt|jd}t|D]W}||||fdks|||||fkr7t|dz |dD]}||||dz f||||f<|||||f<|cSXdS)Nrr;rr)rrrsrtruryrrjs r8rz"_max_n_row_index._append_antialias s B;; ! A1XX  q!Qw<2%%Q1W)=)="1Q32..66'*1a19~Aq!G #(C1aLHHH *> rr7Trc|dkrZ|jd}t|D]=}||||fdks|||||fkrt|||f|||cS>dSr{r*rrrs r8rz_max_n_row_index._append_cuda* B;; ! A1XX  q!Qw<2%%Q1W)=)=)#ad)UA>>>HHH*>rr7c|d}t|dkrD|jdkrt|d|dnt|d|d|Sr)rbrr+r*rrs r8rz_max_n_row_index._combine9 ]1g t99q==x1}}%d1gtAw7777%d1gtAw777 r7c|d}t|dkrlt|jdd}|jdkr#t ||d|dn"t ||d|d|SNrrrr)rbrr*rrrrrrs r8rz_max_n_row_index._combine_cudaC s~1g t99q==#CIcrcN33Kx1}}*;7QaIIII*;7QaIII r7Nr>)r1r2r3r4rr@r!rrrrrrrr6r7r8rrs RRRR    U\   U\"W[  \ \\r7rceZdZdZdZddZeedZeedZ ee j d d Z ed Z ed Zd S)rzMin_n reduction operating on row index. This is a private class as it is not intended to be used explicitly in user code. It is primarily purpose is to support the use of ``first_n`` reductions using dask and/or CUDA. cdSrbr6rJs r8rz-_min_n_row_index._antialias_requires_2_stagesV rr7rrc<ttjddfSrxrers r8rz#_min_n_row_index._antialias_stage_2Y ryr7c|dkrZ|jd}t|D]=}||||fdks|||||fkrt|||f|||cS>dSr{r#rs r8rz_min_n_row_index._append\ r|r7c|dkrZ|jd}t|D]=}||||fdks|||||fkrt|||f|||cS>dSr{r#)rrrsrtruryrrs r8rz"_min_n_row_index._append_antialiasj s B;; ! 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