e !ddlZddlZddlmZddlmZmZddlm Z m Z ddl m Z m Z ddlmZmZGd d ee ZGd d eeZGd deeZGddeee ZGddeZGddeee ZdS)NDataset) Dimensionprocess_dimensions)Element Element2D)get_param_valuesunique_iterator)Selection1DExprSelection2DExprcpeZdZdZdZdZd fd ZedZd fd Z d dZ d Z dfd Z dd Z xZS)StatisticsElementa StatisticsElement provides a baseclass for Element types that compute statistics based on the input data, usually a density. The value dimension of such elements are therefore usually virtual and not computed until the element is plotted. TFNc ttr}jjdkrm|t |p-dt|j}tfd|D|t|gdtj fi||stdg|_dSt|dkr$tt!|jdt%d|d|_dS) N dataframec3BK|]}|VdSN)dimension_values).0ddatas 7lib/python3.11/site-packages/holoviews/element/stats.py z-StatisticsElement.__init__..s1AAa..q11AAAAAAF)kdimsvdims_validate_vdimsDensityr z expects at most one vdim.r) isinstancer interfacedatatypeupdater dimensionslenrtupledictsuper__init__rr ValueErrortype__name__r)selfrrrparams __class__s ` rr)zStatisticsElement.__init__s3 tW % % B';66 MM*400 1 1 1@T__../?DJ/?@EAAAA5AAAAAD db%HHHIII((((( B#I../DJJJ ZZ!^^T 3OOOPP P+D%88ADJJJrcddlm}|j|rfd|D}nj}fd|D}|rRtdtjdd|Dt |dS)aConvert dimension values to DataFrame. Returns a pandas dataframe of columns along each dimension, either completely flat or indexed by key dimensions. Args: dimensions: Dimensions to return as columns multi_index: Convert key dimensions to (multi-)index Returns: DataFrame of columns corresponding to each dimension c>g|]}|dSTr?r8rrr-s r z,StatisticsElement.dframe..~,QQQ$,,Qt,<<QQQrc&g|] }|jv |SrrOs rrPz,StatisticsElement.dframe.. :::q!tz/////r^{} element does not hold data for value dimensions. Could not return data for {} dimension(s)., cg|] }|j SrSnamerrs rrPz,StatisticsElement.dframe..SjSjSj_`TUTZSjSjSjrF)rr*formatr+r,joinr(dframe)r-r$ multi_indexrr/s` rr_zStatisticsElement.dframeps  $QQQQjQQQJJJ::::J:::  n--3VDJJ4GSjSjdiSjSjSjIkIk-l-lnn nww~~j%000rc .|j}nfd|D}fd|D}|rRtdtjdd|Dt fd|DS)aConvert dimension values to a dictionary. Returns a dictionary of column arrays along each dimension of the element. Args: dimensions: Dimensions to return as columns Returns: Dictionary of arrays for each dimension Nc>g|]}|dSrMrNrOs rrPz-StatisticsElement.columns..rQrc&g|] }|jv |SrSrTrOs rrPz-StatisticsElement.columns..rUrrVrWcg|] }|j SrSrYr[s rrPz-StatisticsElement.columns..r\rcHg|]}|j|fSrS)rZrrOs rrPz-StatisticsElement.columns..s.LLLAafd33A667LLLr)rr*r]r+r,r^r')r-r$rs` rcolumnszStatisticsElement.columnss  JJQQQQjQQQJ::::J:::  n--3VDJJ4GSjSjdiSjSjSjIkIk-l-lnn nLLLLLLLMMMr)NN)TT)NFr)r, __module__ __qualname____doc___StatisticsElement__abstract_auto_indexable_1dr)propertyr1r9rrJr_rf __classcell__)r/s@rrr sJ B B B B B B  X ;;;;;; @@@@*888*1111110NNNNNNNNrrceZdZdZejddZejededgdZ ejedgd Z d S) Bivariatez Bivariate elements are containers for two dimensional data, which is to be visualized as a kernel density estimate. The data should be supplied in a tabular format of x- and y-columns. Tdefaultconstantxyrrrqboundsrrr N r,rgrhriparamStringgroupListrrrrSrrroros ELt < < > >ENNNrrc6eZdZdZejddZdS)Violinz Violin elements represent data as 1D distributions visualized as a kernel-density estimate. It may have a single value dimension and any number of key dimensions declaring the grouping of each violin. TrpN)r,rgrhrirzr{r|rSrrrrs0 ELD 9 9 9EEErrceZdZdZejddZejededgdZ dS) HexTilesa HexTiles is a statistical element with a visual representation that renders a density map of the data values as a hexagonal grid. Before display the data is aggregated either by counting the values in each hexagonal bin or by computing aggregates. TrprsrtrurvN) r,rgrhrirzr{r|r}rrrSrrrrsb ELd ; ; ;E EJ # #?$ & & &EEErr)numpyrArz core.datarcore.dimensionrr core.elementrr core.utilr r selectionr rrrorrrrrSrrrs ::::::::--------9999999977777777RNRNRNRNRNRNRNRNj E E E E E!2 E E E F F F F F?$5 F F F'9":::::Z::: & & & & & & & & & &r