a Df !@sddlZddlZddlmZddlmZmZddlm Z m Z ddl m Z m Z ddlmZmZGd d d ee ZGd d d eeZGd ddeeZGdddeee ZGdddeZGdddeee ZdS)NDataset) Dimensionprocess_dimensions)Element Element2D)get_param_valuesunique_iterator)Selection1DExprSelection2DExprcsneZdZdZdZdZdfdd ZeddZdfd d Z dd d Z d dZ dfdd Z dddZ ZS)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 sttrTjjdkrT|t|p<dt|j}t fdd|D|t |gddt j fi||st dg|_n2t|dkrtt|jdntd|d |_dS) NZ dataframec3s|]}|VqdS)N)dimension_values.0ddatad/nfs/NAS7/SABIOD/METHODE/ermites/ermites_venv/lib/python3.9/site-packages/holoviews/element/stats.py z-StatisticsElement.__init__..F)kdimsvdims_validate_vdimsDensityr z expects at most one vdim.r) isinstancer interfacedatatypeupdater dimensionslenrtupledictsuper__init__rr ValueErrortype__name__r)selfrrrparams __class__rrr&s   zStatisticsElement.__init__cCsjddlm}|jdurBtt|j|j}||dddg|d}|St|j|sd||fddi|jS|jS)z? The Dataset that this object was created from r rN)datasetZpipelineZ transformsrrrF)rZ_datasetlistr rr)r*rrr.rrrr.'s    zStatisticsElement.datasetcs |||jv}t|||S)aReturn the lower and upper bounds of values along dimension. Args: dimension: The dimension to compute the range on. data_range (bool): Compute range from data values dimension_range (bool): Include Dimension ranges Whether to include Dimension range and soft_range in range calculation Returns: Tuple containing the lower and upper bound ) get_dimensionrr%range)r*dimZ data_rangeZdimension_rangeZiskdimr,rrr26s zStatisticsElement.rangecCs<|j|dd}||jvr*tt|tjS|j||||S)aReturn the values along the requested dimension. Args: dimension: The dimension to return values for expanded (bool, optional): Whether to expand values Whether to return the expanded values, behavior depends on the type of data: * Columnar: If false returns unique values * Geometry: If false returns scalar values per geometry * Gridded: If false returns 1D coordinates flat (bool, optional): Whether to flatten array Returns: NumPy array of values along the requested dimension Tstrict)r1rnpfullr"nanrvalues)r*r3expandedZflatrrrrFs z"StatisticsElement.dimension_valuescCsD||}|durdS|jdur&|jS||jvr6tjS|j||S)aBGet the type of the requested dimension. Type is determined by Dimension.type attribute or common type of the dimension values, otherwise None. Args: dimension: Dimension to look up by name or by index Returns: Declared type of values along the dimension N)r1r(rr6float64rZdimension_type)r*r3rrrget_dimension_type[s   z$StatisticsElement.get_dimension_typecsh|rfdd|D}nj}fdd|D}|rZtdtjddd|Dt|dS)aConvert dimension values to DataFrame. Returns a pandas dataframe of columns along each dimension, either completely flat or indexed by key dimensions. Args: dimensions: Dimensions to return as columns multi_index: Convert key dimensions to (multi-)index Returns: DataFrame of columns corresponding to each dimension csg|]}j|ddqSTr4r1rr*rr ~rz,StatisticsElement.dframe..csg|]}|jvr|qSrrrr?rrr@r^{} element does not hold data for value dimensions. Could not return data for {} dimension(s)., cSsg|] }|jqSrnamerrrrr@rF)rr'formatr(r)joinr%dframe)r*r!Z multi_indexrr,r?rrHps zStatisticsElement.dframecst|durj}nfdd|D}fdd|D}|r^tdtjddd|Dtfdd|DS) aConvert dimension values to a dictionary. Returns a dictionary of column arrays along each dimension of the element. Args: dimensions: Dimensions to return as columns Returns: Dictionary of arrays for each dimension Ncsg|]}j|ddqSr=r>rr?rrr@rz-StatisticsElement.columns..csg|]}|jvr|qSrrArr?rrr@rrBrCcSsg|] }|jqSrrDrrrrr@rcsg|]}|j|fqSr)rErrr?rrr@r)rr'rFr(r)rGr$)r*r!rrr?rcolumnss zStatisticsElement.columns)NN)TT)TT)NF)N)r) __module__ __qualname____doc__Z_StatisticsElement__abstractZ_auto_indexable_1dr&propertyr.r2rr<rHrI __classcell__rrr,rr s  rc@sLeZdZdZejdddZejededgddZ ejedgd dZ 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. TdefaultZconstantxyrrrQZboundsrrr N r)rJrKrLparamStringgroupListrrrrrrrrOs rOc@sFeZdZdZejdddZejedgddZ ejedgddZ d S) Distributionz Distribution elements provides a representation for a one-dimensional distribution which can be visualized as a kernel density estimate. The data should be supplied in a tabular format and will use the first column. TrPValuer r rUrrVNrWrrrrr\sr\c@sDeZdZdZejdddZejgddZeje dgddZ dZ dS) BoxWhiskerz BoxWhisker represent data as a distributions highlighting the median, mean and various percentiles. It may have a single value dimension and any number of key dimensions declaring the grouping of each violin. TrP)rNrUrSr^N) r)rJrKrLrXrYrZr[rrrZ_inverted_exprrrrrr_s r_c@seZdZdZejdddZdS)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)rJrKrLrXrYrZrrrrr`sr`c@s8eZdZdZejdddZejededgddZ 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. TrPrRrSrTrUN) r)rJrKrLrXrYrZr[rrrrrrras ra)numpyr6rXZ core.datarZcore.dimensionrrZ core.elementrrZ core.utilr r Z selectionr r rrOr\r_r`rarrrrs