a Dfg@sVddlZddlmZddlmZddlZddlZddlm Z m Z m Z m Z m Z mZddlmZmZddlmZddlmZdd lmZdd lmZmZd d lmZd d lmZd dlm Z d dl!m"Z"d dlm#Z#m$Z$Gddde Z%Gdddee e%eZ&Gddde&Z'Gddde&Z(Gddde(Z)Gdddee e Z*Gdddee e Z+dS)N)deepcopy) itemgetter)Dataset Dimension Element2DOverlayconfigutil) BoundingBoxBoundingRegion)ImageInterface) DataErrordimension_name)SheetCoordinateSystemSlice)Curve)Selection2DExpr)TriMesh)Table)categorical_aggregate2dcompute_slice_boundscseZdZdZejededgddddZejdddZ ejed gd d d Z d"fdd Z ddZ d#fdd Z d$fdd Zd%ddZd&ddZeddZeddZddZd d!ZZS)'Rastera Raster is a basic 2D element type for presenting either numpy or dask arrays as two dimensional raster images. Arrays with a shape of (N,M) are valid inputs for Raster whereas subclasses of Raster (e.g. RGB) may also accept 3D arrays containing channel information. Raster does not support slicing like the Image or RGB subclasses and the extents are in matrix coordinates if not explicitly specified. xyrrTzk The label of the x- and y-dimension of the Raster in form of a string or dimension object.defaultboundsconstantdocrr!zrNB The dimension description of the data held in the matrix.rr r"Nc sj|dust|tr$|gkr$td}|durJ|jdd\}}dd||f}tj|f|||d|dS)Nrrrrkdimsvdimsextents) isinstancelistnpzerosshapesuper__init__)selfdatar*r+r,paramsd1Zd2 __class__e/nfs/NAS7/SABIOD/METHODE/ermites/ermites_venv/lib/python3.9/site-packages/holoviews/element/raster.pyr3.s   zRaster.__init__cCs||vr||St||}t|ts:|tdf}ndt|d|jkr`t dd|jn>t|dkr|d|j dj tdfvrt |j dj ddd|ddD}|j |ddddd}t|r|j|dd St|s|S|jtj||d d dd SdS) NrzCan only slice %d dimensionsrz' is the only selectable value dimensioncSsg|]}t|tqSr:r-slice).0slr:r:r; @z&Raster.__getitem__..)r,TZaxis) dimensionsdimension_valuesr Zprocess_ellipsesr-tupler?lendepthKeyErrorr+namer5 __getitem__allcloneanyr/Z expand_dimsindex)r4ZslicesZ slc_typesr5r:r:r;rL6s"  (zRaster.__getitem__cs||}|rr|dkrr||}|jjdkr8tjtjfSt|jt|j}}|s^||fSt |||j |j St |||S)Nrr) get_dimension_index get_dimensionr5sizer/nanZnanminZnanmaxr dimension_rangerangeZ soft_ranger2)r4dim data_rangerUidx dimensionlowerupperr8r:r;rVJs     z Raster.rangecs||}|s,|dkr,tt|jjdS|sN|dkrNtt|jjdS|dvrtjd|jjdd|jjdf|}|r|S|S|dkr|jj}|r|S|St |SdS)zL The set of samples available along a particular dimension. rrrrrN) rQr/arrayrVr5r1ZmgridflattenTr2rF)r4rWexpandedflatZdim_idxvaluesarrr8r:r;rFVs   *zRaster.dimension_valuesc s|dur g}t|tr(|\}}t||}tjjddjd}t|jksVt|rt|stddt fdd| DD}fdd|D}j |d <t |fi|St t| \}} t| trtd |durtd |d fd dtj D} ddtjD} s4ddndd} | | td| <| djd} jt| ddd}tdrdkr|ddd}tt| |}| |d <t|fi|SdS)a[ Sample the Raster along one or both of its dimensions, returning a reduced dimensionality type, which is either a ItemTable, Curve or Scatter. If two dimension samples and a new_xaxis is provided the sample will be the value of the sampled unit indexed by the value in the new_xaxis tuple. NTZ onlychangedr+cSs$g|]\}}t|tr|n|gqSr:)r-r.)r@_cr:r:r;rB{rCz!Raster.sample..csg|]\}}||fqSr:)rQr@kvr4r:r;rB|rCcs"g|]}|j|fqSr:)_zdata _coord2matrixr@rhrlr:r;rB~sr*zKRaster sampling requires coordinates not slices,use regular slicing syntax.z Dimension z not found during samplingcsg|]\}}|kr|qSr:r:)r@id) sample_indr:r;rBs cSsg|] }tdqSN)r?r@rpr:r:r;rBrCcSs|dfSNrr:rkr:r:r;rCzRaster.sample..cSsd|fSrur:rvr:r:r;rwrCrrFr=r )r-rGzipdictparamrcr+rHndimssorteditemsr*rnextiterr? ValueErrorrQ Exception enumeraterVrnabsrFrKrmhasattrr.r)r4Zsamplesr Z sample_valuesXYr6Z table_datarZZ sample_coordother_dimensionsampleZcoord_fnx_valsZydatar5r:)rrr4r;rhsL        $z Raster.samplec  s||||\}}t||jkrHt|tjr<|j|jddS||jSn|dfdd|jD}| |d}| |dj d}||j |d}|rt |dr|ddd}t||} tt|jjd d ||jd } | dd| d dt| fi| SdS) z Reduces the Raster using functions provided via the kwargs, where the keyword is the dimension to be reduced. Optionally a label_prefix can be provided to prepend to the result Element label. NrDrcsg|]}|jkr|qSr:)rKr@rqrZr:r;rBrCz!Raster.reduce..Fr r=Trer*r+r,)Z _reduce_maprHr{r-r/Zufuncreducer5r*rQrFrKrmrrxryrzrcr+popr) r4rEfunctionZ reduce_mapdimsrZoidxrZreducedr5r6r:rr;rs&     z Raster.reducecCs t|jSrs)rHr+rlr:r:r;rIsz Raster.depthcCs|jSrsr5rlr:r:r;rmsz Raster._zdatacCs tt|dtt|dfS)Nrr)introundr4Zcoordr:r:r;rnszRaster._coord2matrixcCst|jjSrs)r/prodrmr1rlr:r:r;__len__szRaster.__len__)NNN)TT)TT)NN)NN)__name__ __module__ __qualname____doc__rzListrr*Stringgroupr+r3rLrVrFrrpropertyrIrmrnr __classcell__r:r:r8r;rs(    5   rcseZdZdZejeeddZej gddZ ej dddZ ej e de d gd dd d Zej e d gdddZejdddZdZd%ddZddZd&fdd Zd'fdd Zd(ddZd)dd Zd*fd!d" Zd#d$ZZS)+Imagea< Image represents a regularly sampled 2D grid of an underlying continuous space of intensity values, which will be colormapped on plotting. The grid of intensity values may be specified as a NxM sized array of values along with a bounds, but it may also be defined through explicit and regularly spaced x/y-coordinate arrays of shape M and N respectively. The two most basic supported constructors of an Image therefore include: Image((X, Y, Z)) where X is a 1D array of shape M, Y is a 1D array of shape N and Z is a 2D array of shape NxM, or equivalently: Image(Z, bounds=(x0, y0, x1, y1)) where Z is a 2D array of shape NxM defining the intensity values and the bounds define the (left, bottom, top, right) edges of four corners of the grid. Other gridded formats which support declaring of explicit x/y-coordinate arrays such as xarray are also supported. Note that the interpretation of the orientation of the array changes depending on whether bounds or explicit coordinates are used. zF The bounding region in sheet coordinates containing the data.)class_rr")ZgridZxarrayimageZcubeZ dataframe dictionary)rTr#rrrzo The label of the x- and y-dimension of the Raster in the form of a string or dimension object.rr$r%r&r'Nz The tolerance used to enforce regular sampling for regular, gridded data where regular sampling is expected. Expressed as the maximal allowable sampling difference between sample locations.)rr"rc Ks*|} t|tr:|p|j}|p |j}|p*|j}|dur:|j}|rB|nd}|dusvt|ttfr`|rvt|tj r|j dkrt|tj r|j dkr|nt d}d}|sd}|sd}n4t|tj r|j |j krtdt|j|j |j f|dur|| d<n tj| d<tj||f|||d| |jjs@td t|j|jj|jj|d d dd\} } |dur|dd } t| ||j\}}}}|dd }t|||j\}}}}t||f||ffd }nNt|rt|d}n6t|tttj fr|\}}}}t||f||ffd }d}|jt ur@t|tj tfs@|j!}t"dd|!D}|rtdd }|r|t#|r||nd}|rt#|r|nd}nH|!\}}}}|r|nt$||| |j}|r|nt$||| |j}t%|||||rttj&tj&ftj&tj&ffd |_|'|| dS)N)NNNNrrr(rz/%s type expects %d-D array received %d-D array.rtolr)z{} type expects gridded data, {} is columnar. To display columnar data as gridded use the HeatMap element or aggregate the data (e.g. using rasterize or np.histogram2d).TgriddedF)Zpoints)Zradiuscss|]}t| VqdSrs)r isfinite)r@rkr:r:r; /rCz!Image.__init__..)r(r()(r-rr xdensityydensityrr.rGr/ndarrayrSndimr0_ndimrtyperr Z image_rtolrr3 interfacerrformatr1rFr Z bound_rangeZ _time_unitr isscalarr lbrtrMrZcompute_densityrrT _validate)r4r5r*r+r r,rrrr6supplied_boundsZdim2Zdim1xvalslrrgyvalsbt data_boundsZ non_finiter:r:r;r3sv       $             zImage.__init__csxtjdkr:jdtjkr:tdjtjftj}j\}}fddjD\}}g}|jdkr~|||jdkr|||rt|dkrdj t |n|d} t|d | d t |j } t |j } d } d} | s| r d |d nd|d|d} n| s0d |d} | rPj| j || j d|sZdS|durfddjD\\} }\}}djd}djd}t| t js| |||} }t|t js||||}}| |||f}n|}d}t|jD]^\}}t|t jr&t |}t|t jr>t |}t |rtj||j dsd}q|rttddS)Nr<rz8Input array has shape %r but %d value dimensions definedc3s|]}j|dddVqdS)F)rarbNrFrrlr:r;rFsz"Image._validate..rz {} and {}rz coordinates must be 1D arrays, z dimension(s) were found to have multiple dimensions. Either supply 1D arrays or use the QuadMesh element for curvilinear coordinates.z{clsname} dimension{dims} not evenly sampled to relative tolerance of {rtol}. Please use the QuadMesh element for irregularly sampled data or set a higher tolerance on hv.config.image_rtol or the rtol parameter in the {clsname} constructor. z is z(s) z and z arez is)clsnamerrc3s|]}j|jVqdSrs)rrVrKr@Zkdrlr:r;rirCg?g@F)rTzSupplied Image bounds do not match the coordinates defined in the data. Bounds only have to be declared if no coordinates are supplied, otherwise they must match the data. To change the displayed extents set the range on the x- and y-dimensions.)rHr1r+rrrr*rappendrrGr Zvalidate_regular_samplingrrzwarningrrr-Zdatetime_typesrxr rZ dt_to_intrr/isclose)r4rrrxdimydimrrinvalidrZxvalidZyvalidmsgx0x1y0y1ZxstepZystepr Z not_closerrhr:rlr;r=sl        $ &      zImage._validatecs^|dur>|dust|tr>t|j|j|jd}t|fi|}tj||||g|Ri|S)aK Returns a clone of the object with matching parameter values containing the specified args and kwargs. If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters. Nr rr) issubclassrryr rrr2rN)r4r5Z shared_datanew_typelinkargsZ overridesZ sheet_paramsr8r:r;rNs  z Image.clonec s<tj|||fi|}t|tr8t|jdkr8t|S|S)Nr)r2 aggregater-rrHr+r)r4rErZspreadfnkwargsZaggr8r:r;rszImage.aggregatec s|rtfdd|DsSfddDtfddjD}jjdd}tdd |Drt||d d }j\}}|\}} } } t|\} } }}|d | |d | } } t | | t ||fd}n4 |d |d \}}|d |d }||fd}t t jjgj}j}|st|rT|St|trn|jd }j|gt|dSj|j|j|dSd S)a Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object. c3s|]}|VqdSrs)matches)r@sprlr:r;rrCzImage.select..cs:i|]2\}}|jvr|jt|tr2t|n|qSr:)r*rRrKr-rGr?)r@rjselrlr:r; sz Image.select..c3s*|]"}|jvr|jntdVqdSrs)rKr?r) selectionr:r;rsTrcSsg|]}t|tqSr:r>r@elr:r:r;rBrCz Image.select..NrrrF)r*rdatatype)rrrr )rOr}rGr*rr1rrrr?sheet2matrixidxr.r Zunique_iteratorrZndlocr/rr-r{rNrrr)r4Zselection_specsrcoordsr1r rrrrrrrrrrZslicedrrrr5r:)rr4r;selectsD        z Image.selectc s*|dur g}|r|rtd|rg}g|D]\}}|t|rh|r\d|fn|dfnZt|trfdd|D}t|dt|fvrtdn t|r‡fddt ||D}q0nddgt t t|dkr|d}t|t rj |Sfd d|DSdS) z Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. NzDSpecify coordinate using as either a list keyword arguments not bothrcs g|]}rd|fn|dfqSrr:rorYr:r;rBrCz!Image.closest..zLength of samples must matchcs<g|]4\}}r$|td|fn||tdfqS)r)r)r@rhrrr:r;rBsrcsg|]}j|qSr:)closest_cell_centerr)getterr4r:r;rBrC)rr}rQr/rrr-r.rHrxrr|rGr)r4rrrjrkr:)rrYr4r;closests6        z Image.closestc sd||}||}|dvrP|rP|jdkrP|j\}}}} |rH|| fS||fSt|||SdS)Nr])NN)rQrRrVr rr2) r4rWrXrUrYrZrrrrr8r:r;rVs   z Image.rangecCs |j|Srs)rrr:r:r;rnszImage._coord2matrix)NNNNNNN)NTNT)NNN)N)N)TT)rrrrrz ClassSelectorr r r rrrrrr*r+Numberrrr3rrNrrrrVrnrr:r:r8r;rs,  @E 2 ' rcsHeZdZdZejddZejdddZdZ de iZ d fd d Z Z S) ImageStacka ImageStack expands the capabilities of Image to by supporting multiple layers of images. As there is many ways to represent multiple layers of images, the following options are supported: 1) A 3D Numpy array with the shape (y, x, level) 2) A list of 2D Numpy arrays with identical shape (y, x) 3) A dictionary where the keys will be set as the vdims and the values are 2D Numpy arrays with identical shapes (y, x). If the dictionary's keys matches the kdims of the element, they need to be 1D arrays. 4) A tuple containing (x, y, level_0, level_1, ...), where the level is a 2D Numpy array in the shape of (y, x). 5) An xarray DataArray or Dataset where its `coords` contain the kdims. If no kdims are supplied, x and y are used. If no vdims are supplied, and the naming can be inferred like with a dictionary the levels will be named level_0, level_1, etc. r&)r"Tr#r<rNc  s|p|jttrVtrVtdjd}tdjd}||gRnDttrtfdd D}t t \}} |vrt|jd|<| vrt|jd| <nttj r(j dkr(tjd}tjd}fddtjdD} ||g| Rnrttrtdkrtdtj rdj dkrfddtdjdD} ddg| R|durttrd d ttddD}n"ttrfd d D}tjf||d |dS) Nrrc3s|]\}}|vr|VqdSrsr:ri_kdimsr:r;r%rCz&ImageStack.__init__..r<c3s$|]}dddd|fVqdSrsr:r@nrr:r;r.rCrc3s(|] }ddddd|fVqdS)rNr:rrr:r;r4rCcSsg|]}td|qS)Zlevel_rrtr:r:r;rB9rCz'ImageStack.__init__..csg|]}|vrt|qSr:r)r@keyrr:r;rB;rCr)r*r-r.rHr/aranger1ryr~r}mapstrrrrVrGkeysr2r3) r4r5r*r+r6rrfirstrrrdr8)rr5r;r3sB         zImageStack.__init__)NN)rrrrrzrr+rrrr_vdim_reductionsr3rr:r:r8r;rs  rcseZdZdZejdddZejedddeddd Z ej ed dded dded ddgd ddZ dZ de iZeddZedddZdfdd ZZS)RGBak RGB represents a regularly spaced 2D grid of an underlying continuous space of RGB(A) (red, green, blue and alpha) color space values. The definition of the grid closely matches the semantics of an Image and in the simplest case the grid may be specified as a NxMx3 or NxMx4 array of values along with a bounds, but it may also be defined through explicit and regularly spaced x/y-coordinate arrays. The two most basic supported constructors of an RGB element therefore include: RGB((X, Y, R, G, B)) where X is a 1D array of shape M, Y is a 1D array of shape N and R/G/B are 2D array of shape NxM, or equivalently: RGB(Z, bounds=(x0, y0, x1, y1)) where Z is a 3D array of stacked R/G/B arrays with shape NxMx3/4 and the bounds define the (left, bottom, top, right) edges of the four corners of the grid. Other gridded formats which support declaring of explicit x/y-coordinate arrays such as xarray are also supported. Note that the interpretation of the orientation changes depending on whether bounds or explicit coordinates are used. Tr#Ar]rVFl The alpha dimension definition to add the value dimensions if an alpha channel is supplied.rrZ instantiater"RGBr<z The dimension description of the data held in the matrix. If an alpha channel is supplied, the defined alpha_dimension is automatically appended to this list.r'r<rcCs|S)z Returns the corresponding RGB element. Other than the updating parameter definitions, this is the only change needed to implemented an arbitrary colorspace as a subclass of RGB. r:rlr:r:r;rgbms zRGB.rgbNcKszddlm}Wnty,tddYn0t|d(}t||} | d} Wdn1sf0Y|rx| S| j\} } } |durt|| }| |d| |d} }| | | |f}|| fd|i|}|r|jddd |S) aCLoad an image from a file and return an RGB element or array Args: filename: Filename of the image to be loaded height: Determines the bounds of the image where the width is scaled relative to the aspect ratio of the image. array: Whether to return an array (rather than RGB default) bounds: Bounds for the returned RGB (overrides height) bare: Whether to hide the axes kwargs: Additional kwargs to the RGB constructor Returns: RGB element or array r)rz(RGB.load_image requires PIL (or Pillow).Nrbgo@rr )ZxaxisZyaxis) ZPILr ImportErroropenr/r^r1floatopts)clsfilenameheightr^r Zbarerrfr5hwrgZxoffsetZyoffsetrr:r:r; load_imagexs$  &  zRGB.load_imagec  st|tr|}tdd|Ds,tddd|DtfddDsXtddd|D}td d|Drtd d dt||D}t|}|durt |j }nt|t rt |n|g}|j }t |d r|jd dkrt|dksrt|trFt|d tjrF|d jdkrF|d jd dkrFt|dksrt|tr|tdd|D|jf|vr|||tj|f||d|dS)Ncss|]}t|tVqdSrs)r-rr@imr:r:r;rrCzRGB.__init__..z.Input overlay must only contain Image elementscSsg|] }|jjqSr:)r5r1rr:r:r;rBrCz RGB.__init__..c3s|]}|dkVqdS)rNr:)r@r1Zshapesr:r;rrCzFImages in the input overlays must contain data of the consistent shapecSsg|]}|jdjqSr)r+rVrr:r:r;rBrCcss|]}d|vVqdSrsr:)r@rr:r:r;rrCzDRanges must be defined on all the value dimensions of all the ImagescSs.g|]&\}}|j|d|d|dqSr]r)r@rr r:r:r;rBrCr1r=rr<css|]}t|VqdSrsr)r@vdr:r:r;rrCr)r-rrcrMrrOrxr/Zdstackrr+r.alpha_dimensionrr1rHrGrrryrKrr2r3) r4r5r*r+r6ZimagesrangesZarraysalphar8r r;r3sB   &   z RGB.__init__)rFNF)NN)rrrrrzrrrrr rr+rrrrr classmethodrr3rr:r:r8r;r?s$   %rc@seZdZdZejdddZejedddeddd Z ej ed ddd ed dded ddgdddZ e ejZeddZdS)HSVav HSV represents a regularly spaced 2D grid of an underlying continuous space of HSV (hue, saturation and value) color space values. The definition of the grid closely matches the semantics of an Image or RGB element and in the simplest case the grid may be specified as a NxMx3 or NxMx4 array of values along with a bounds, but it may also be defined through explicit and regularly spaced x/y-coordinate arrays. The two most basic supported constructors of an HSV element therefore include: HSV((X, Y, H, S, V)) where X is a 1D array of shape M, Y is a 1D array of shape N and H/S/V are 2D array of shape NxM, or equivalently: HSV(Z, bounds=(x0, y0, x1, y1)) where Z is a 3D array of stacked H/S/V arrays with shape NxMx3/4 and the bounds define the (left, bottom, top, right) edges of the four corners of the grid. Other gridded formats which support declaring of explicit x/y-coordinate arrays such as xarray are also supported. Note that the interpretation of the orientation changes depending on whether bounds or explicit coordinates are used. Tr#rr]rFrrH)rVZcyclicSVrz The dimension description of the data held in the array. If an alpha channel is supplied, the defined alpha_dimension is automatically appended to this list.r'cstfddjD}fddjD}j|dd}tjdkrZ||df7}t}|d=t||fjj j d |S) z- Conversion from HSV to RGB. c3s|]}j|ddVqdS)F)raNrrrlr:r;rszHSV.rgb..csg|]}j|ddqS)Frbrrrlr:r;rBszHSV.rgb..Nr<rr+r) rGr*r+ hsv_to_rgbrHr get_param_valuesrr rr)r4rr5Zhsvr6r:rlr;rs    zHSV.rgbN)rrrrrzrrrrr rr+r/Z vectorizecolorsysrrrr:r:r:r;rs    rcsleZdZdZejdddZejededgdddZ ejedgd d Z dZ dfd d Z ddZ ZS)QuadMeshak A QuadMesh represents 2D rectangular grid expressed as x- and y-coordinates defined as 1D or 2D arrays. Unlike the Image type a QuadMesh may be regularly or irregularly spaced and contain either bin edges or bin centers. If bin edges are supplied the shape of the x/y-coordinate arrays should be one greater than the shape of the value array. The default interface expects data to be specified in the form: QuadMesh((X, Y, Z)) where X and Y may be 1D or 2D arrays of the shape N(+1) and M(+1) respectively or N(+1)xM(+1) and the Z value array should be of shape NxM. Other gridded formats such as xarray are also supported if installed. The grid orientation follows the standard matrix convention: An array Z with shape (nrows, ncolumns) is plotted with the column number as X and the row number as Y. Tr#rrrrr r!r$r%)rr Nc sh|dust|tr*|gkr*ggtdf}tj|||fi||jjsdtd t |j |jj dS)Nr(z{} type expects gridded data, {} is columnar. To display columnar data as gridded use the HeatMap element or aggregate the data (e.g. using np.histogram2d).) r-r.r/r0r2r3rrrrrrr4r5r*r+r6r8r:r;r3szQuadMesh.__init__cCs,|jj|ddd}|jj|ddd}|jdkrt|dd|ddkrZ|ddd}t|dd|ddkr|ddd}t|ddtjft|jt|ddtjft|}}|j |j f}|j ddd j }|d}t t |}||}||d||}|d} |d|d||} | } | } | d} t|| g}t| | g}t| | g}|||f}|jD]$}| |}|t||gf}qt|}|d tjjdd|d <tj|t t|dffid d |D}t|f|ffid d |DS)z5 Converts a QuadMesh into a TriMesh. rT)edgesrNr=rFrr*cSsi|]\}}|dkr||qSrfr:rir:r:r;rPs z$QuadMesh.trimesh..cSsi|]\}}|dkr||qS)r*r:rir:r:r;rRs )rrrr/rMZtileZnewaxisrHr`r_rFr1rrZ concatenater+r rrZ node_typer*r})r4xsZysZverticesr1s0t1ZjsZt1sZt2sZt3sZt4sZt5sZt6st2t3tsr Zzsr6nodesr:r:r;trimesh(sD     zQuadMesh.trimesh)NN)rrrrrzrrrrr*r+_binnedr3r#rr:r:r8r;rs rcseZdZdZejdddZejededgdddZ ejedgddZ dfd d Z e d d Z e ddZdfdd ZZS)HeatMapa HeatMap represents a 2D grid of categorical coordinates which can be computed from a sparse tabular representation. A HeatMap does not automatically aggregate the supplied values, so if the data contains multiple entries for the same coordinate on the 2D grid it should be aggregated using the aggregate method before display. The HeatMap constructor will support any tabular or gridded data format with 2 coordinates and at least one value dimension. A simple example: HeatMap([(x1, y1, z1), (x2, y2, z2), ...]) However any tabular and gridded format, including pandas DataFrames, dictionaries of columns, xarray DataArrays and more are supported if the library is importable. Tr#rrrrr$Nc s$tj|f||d|d|_dS)Nr)r2r3_griddedrr8r:r;r3qszHeatMap.__init__cCs|jdurt||_|jSrs)r&rrlr:r:r;rus  zHeatMap.griddedcCs |jjdkS)z3 Reports if the Dataset is unique. z non-unique)rlabelrlr:r:r;_unique{szHeatMap._uniquecs||}||jvrzfzBd|j_|j|urFt|||WWd|j_S|j|||}Wntynd}Yn0Wd|j_n d|j_0|dur|St|||S)aReturn the lower and upper bounds of values along dimension. Args: dimension: The dimension to compute the range on. data_range (bool): Compute range from data values dimension_range (bool): Include Dimension ranges Whether to include Dimension range and soft_range in range calculation Returns: Tuple containing the lower and upper bound TFN)rRr*rr$r2rVr)r4rWrXrUZdranger8r:r;rVs     z HeatMap.range)NN)TT)rrrrrzrrrrr*r+r3rrr(rVrr:r:r8r;r%Ws  r%),rcopyroperatorrnumpyr/rzcorerrrrr r Zcore.boundingregionr r Z core.datar Zcore.data.interfacerZcore.dimensionrZcore.sheetcoordsrrZchartrZgeomrZgraphsrZtabularrrrrrrrrrr%r:r:r:r;s2          65B|CY