e=0ddlZddlZddlZddlZddlmZddlm Z ddl m Z m Z ddl mZddlmZddlmZmZmZmZmZmZd Zd Zd ZGd d eZdZddZdZdZdZ dS)N)Dataset) BoundingBox)PandasInterfacedefault_datatype) Operation)Slice)cartesian_productdatetime_types is_cyclicis_nan one_to_onesort_topologicallyc|ddd}|d}tjdgtjtj|ddzdgg}g}t j|}tt|dz D][}||dz}t|||dn|dz }|j |}t|r| |\|S)z^ Split a Path type containing a single NaN separated path into multiple subpaths. rN) splitdimension_valuesnp concatenatewhereisnanr as_dframerangelensliceilocappend) pathvaluessplitssubpathsdataiendslcsubpaths 6lib/python3.11/site-packages/holoviews/element/util.py split_pathr(s ::a  A D  " "1 % %F ^aS"(28F+;+;"<">)C. w<< % OOG $ $ $ Oc`|\}}|\}}|j\}}} } |j|j} } d| z } d| z }t |t r4t jtt| |j } t |t r4t jtt||j }t |tr<|j |nt||j }|j| nt| |j} t |tr<|j |nt||j }|j| nt| |j} t!||f| | ff}t#||}||\}}} } t |tst |t&t(fs|g}t+|dkr"| t-t+||z z} gg}}|D]Q}|||\}}||| dz z ||| dz zRt j|t j |} }nt |tst |t(t&fs|g}t+|dkr"| t-t+||z z} gg}}|D]Q}|||\}}|||dz z |||dz zRt j|t j |} }t!||f| | ffS)z Given a 2D selection consisting of slices/coordinates, a SheetCoordinateSystem and the shape of the array returns a new BoundingBox representing the sliced region. g?N)pointsrr)boundslbrtxdensityydensity isinstancer r timedelta64intround _time_unitrstartmaxstopminrr compute_boundslistsetrfloatclosest_cell_centerr)slicesscsshapexidxyidxysxslbrtr.r/xunityunitr,r%lsrsidxxc_bstsycs r'compute_slice_boundsrS)ss JD$ FB""JAq!Qs|hH [E [E!^$$Bs5<<00#.AA!^$$Bs5<<00#.AA$:#AAQ ););"AAAty(9(9$:#AAQ ););"AAAty(9(9 !Q!Q 0 1 1 1F   C##C((--//JAq!Q dE " "&$s ,,;dVd t99q==s4yy!1!1"!45HRB " "C++C33EB IIbqj ! ! ! IIbqj ! ! ! !vbzz26"::1 e $ $ &$d ,,;dVd t99q==s4yy!1!1"!45HRB " "C++As33EAr IIbqj ! ! ! IIbqj ! ! ! !vbzz26"::1 1v1v. / / //r)ct|tjr|jn|}|D]}t |s|cSt jS)z? Aggregation function to get the first non-zero value. )r0pdSeriesrr rnan)xrvs r' reduce_fnrZ]sR$Ary11 8QXXqF ayy HHH  6Mr)cdeZdZdZejddgdZedZdZ dZ d d Z d S) categorical_aggregate2da Generates a gridded Dataset of 2D aggregate arrays indexed by the first two dimensions of the passed Element, turning all remaining dimensions into value dimensions. The key dimensions of the gridded array are treated as categorical indices. Useful for data indexed by two independent categorical variables such as a table of population values indexed by country and year. Data that is indexed by continuous dimensions should be binned before aggregation. The aggregation will retain the global sorting order of both dimensions. >> table = Table([('USA', 2000, 282.2), ('UK', 2005, 58.89)], kdims=['Country', 'Year'], vdims=['Population']) >> categorical_aggregate2d(table) Dataset({'Country': ['USA', 'UK'], 'Year': [2000, 2005], 'Population': [[ 282.2 , np.nan], [np.nan, 58.89]]}, kdims=['Country', 'Year'], vdims=['Population']) xarraygridzO The grid interface types to use when constructing the gridded Dataset.)defaultdocc|ddd\}}||d}||d}|jjdvrt j|}|jjdvr|t j|fS||tt }i}d}|D]} | |d} t| dkr| d g|| d <n8tt| dz D]} | | | dz\} } | g|| <|r`| jjd vr+t j | d k }t jt j| | }|st||rt j|}nmt!|s^t#t%jt)|}t|t|kr|nt j|}t j|t j|fS) zi Get the coordinates of the 2D aggregate, maintaining the correct sorting order. TlabelNrFSUO)container_type group_typerr)r#f) dimensionsrdtypekindrsortgroupbydictrrrrdiffall array_equalrr r: itertoolschainrasarray)clsobjxdimydimxcoordsycoordsgrouped orderingsrkgroupvalsr#p1p2coordss r' _get_coordsz#categorical_aggregate2d._get_coordssI ^^$^//3 d&&tU33&&tU33 = U * *gg&&G = U * *BGG,,, ,++d4)02228&((   ? ?E))$66D4yyA~~&*1gY $q'""s4yy{++))A!!AaC%[FB%'DIbMM ?:?j00GDMM1,1133DD>"'$-->>D  R:i11 Rgg&&GG9%% R)/+=i+H+HIJJF #F s7|| ; ;ffAQAQGz'""BJw$7$777r)c||\}}|d}|dd}|dd\}}t|t|f}tj|} ||||i} t ||gd\} } || || i} |D]1}tj| }tj|dd<|| |j<2t}t| |j |j |g}|j ||g|}|||g|}|s|}t!j|}|||gd }||}|D]2}|||| |j<3|| ||g||jjS) zr Generates a gridded Dataset from a column-based dataset and lists of xcoords and ycoords TrbrN)copy)kdimsvdimsdatatyperFrk)rrhrrprodr emptyrWnamerrrr interfacerreindexrrrlfirst reset_indexclonerreshapepr)selfrurxry dim_labelsrrvrwr@nsamples grid_datarCrDr"vdimrri dense_data concat_data reindexedaggdfs r'_aggregate_datasetz*categorical_aggregate2d._aggregate_datasets  ++C00^^$^//   $^ dWs7||,75>>7D'2 "GW#5DAAABb$# % %DXh''FF111I$DOO T#)ugVVV m//S0AE/RR ''t e<<  C  &y 1 1 ZZt 5Z 1 1 7 7 9 9 E E G Goob!! M MD##7#=#=#E#Ee#L#LIdi yy4,e"&&/33 3r)cd|jD}|j||d}t |t |krdnd}||}tj ||j j }| |}t|}td|D} |jD]0} ||| jj| jfz }1|||jj|S) Ncg|] }|j S)r.0ds r' zEcategorical_aggregate2d._aggregate_dataset_pandas..s000af000r)Fruniquez non-unique)namesc30K|]}|jdVdS)rN)r@rs r' zDcategorical_aggregate2d._aggregate_dataset_pandas..s(//Qagaj//////r))rrc)rr" set_indexrlrrrrU MultiIndex from_productindexrrtuplerrrrTrrr) rru index_colsrrclevelsrrr"r@rs r'_aggregate_dataset_pandasz1categorical_aggregate2d._aggregate_dataset_pandass,00ci000 X   + + 3 3JU 3 K K Q Q S SGGs3xx//\!!#&& **6*HHJJu%% V}}//$/////I D DD Yty)088??AC CDDyyuyEEEr)Nc2t|tr|jjr|S|jdkrt dt |dkrt dt|dg}||S)z Generates a categorical 2D aggregate by inserting NaNs at all cross-product locations that do not already have a value assigned. Returns a 2D gridded Dataset object. rz)Cannot aggregate more than two dimensionszUMust have at two dimensions to aggregate overand one value dimension to aggregate on. dataframer) r0rrgriddedndims ValueErrorrrhr)rrukeys r'_processz categorical_aggregate2d._processs c7 # # I (= IJ Y]]HII I !! " "Q & &HII Ic[M222--c222r))N) __name__ __module__ __qualname____doc__paramListr classmethodrrrrrr)r'r\r\hs&uz8V"4;RSSSH$8$8[$8L!3!3!3F F F F333333r)r\ct|}|sgggfStj|z tj|zdz}tj|}tj|}|||fS)z7 Lay out nodes on a circle and add node index. r)rrpiarangecossin)nodesNcircrXys r'circular_layoutrsf E A B| 5729Q<<  !D t A t A q%=r)rr2cbtjdd|}|\}}|\}}|\} } |\} } d|z dz|zdd|z dzz|z| zzdd|z z|dzz| zz|dz|zz} d|z dz|zdd|z dzz|z| zzdd|z z|dzz| zz|dz|zz}tj| |gS)zd Compute quadratic bezier spline given start and end coordinate and two control points. rrrr)rlinspace column_stack)r5r$c0c1stepssxsyexeycx0cy0cx1cy1rDrCs r'quadratic_bezierrs K1e $ $E FB FBHCHC U7Q,r/A%!|,U236 6 QuW+eQh s " #%*AXb[ 1B U7Q,r/A%!|,U236 6 QuW+eQh s " #%*AXb[ 1B ?B8 $ $$r)c|}d|j_|}|j}|j\}}|jjdd\}}}t j|||jg|jg}||jd|jdi}t j|||jg|jg}||jd|jd i}| d dgd }gd } t|| j |jjd d } | S)z Given a Graph element containing abstract edges compute edge segments directly connecting the source and target nodes. This operation depends on pandas and is a lot faster than the pure NumPy equivalent. graph_edge_indexNrleft_onright_onsrc_xsrc_ycolumnsdst_xdst_yraxis)rrrrr)dframerrrrrrUmergerename sort_valuesdropr:rrsize) graphedgesrsrctgtrXrrMrcols edge_segmentss r'connect_edges_pdrsF LLNNE)EK     E K   E{HC !"1"%IAq# % chZ H H HB AFGQVW= > >B "echZ38* E E EB AFGQVW= > >B * + + 0 02D1EA 0 N NB / / /DD001EEFFM r)c|}d|j_|ddd}|j}d|j_|ddgdd}|j\}}}|jjdd \}}}tj |||jg|jg } | |jd |jd i } tj | ||jg|jg } | |jd|jdi } tj | ||jg|jg } | |jd|jdi } | ddgd} | gdS)z Given a TriMesh element containing abstract edges compute edge segments directly connecting the source and target nodes. This operation depends on pandas and is a lot faster than the pure NumPy equivalent. trimesh_edge_indexcolorignorer)errorsr node_indexzNrrx0y0rx1y1x2y2r)rrrrrr) rrrrrrrrrUrrr) trimeshrrv1v2v3rXrrMrs r'connect_tri_edges_pdr s NN   ! ! # #E+EK JJwxaJ 8 8 D D F FE M " " ' ' ) )E#EK JJ~hQJ ? ?EJBB #BQB'IAq# % SXJ G G GB AFD!&$7 8 8B "ebgY#( D D DB AFD!&$7 8 8B "ebgY#( D D DB AFD!&$7 8 8B , - - 2 24H3IPQ 2 R RB 222 33r)cg}||jD]\}}|jdddd|f}|jdddd|f}t|rt|st d||jdd}||jdd}|t j|d|dg|S)z Given a Graph element containing abstract edges compute edge segments directly connecting the source and target nodes. This operation just uses internal HoloViews operations and will be a lot slower than the pandas equivalent. Nz+Could not find node positions for all edgesrr)arrayrrrrrr)rpathsr5r$start_dsend_dss r' connect_edgesr :s Ekk%+..33 s;qqq!!!U{+QQQ3Y'8}} LCKK LJKK Kx~bqb122ll6<+,, RXuQxQ0112222 Lr))rrr)!rqnumpyrpandasrUrcorercore.boundingregionr core.datarrcore.operationrcore.sheetcoordsr core.utilr r r r rrr(rSrZr\rrrrr rr)r'rs ------99999999&&&&&&$$$$$$&101010h}3}3}3}3}3i}3}3}3@   %%%%"44444r)