Ë ñÍtf’ ãó^—ddlmZddlmZddlZddlZddlZd de fd„Z d„Z d„Z d d„Z d d „Zy) é)Úformat_dense_tile)Ú tile_boundsNÚmax_zoomcóÀ—tj|«}|dj«}|dj«}|dj«}|dj«}||z }||z } t|| «} t j |d«5} | j dt|«dfdtj¬«} |jddg¬«j| d d || jd <|| jd <|| jd <|| jd <|| jd<| | jd<d d d «|jddg¬«S#1swYŒxYw)z³ Convert a csv file containing points to a numpy array of [[x,y]] values. Parameters: ----------- csv_file: string The filename of the data file ÚxÚyÚwÚvalueséÚgzip)Ú compressionÚdtype)ÚcolumnsNÚmin_xÚmax_xÚmin_yÚmax_yrÚ max_width) ÚpdÚread_csvÚminÚmaxÚh5pyÚFileÚcreate_datasetÚlenÚnpÚfloat32Úreindexr Úattrs) Úcsv_fileÚ output_filerÚdfrrrrÚwidthÚheightrÚf_outÚdatasets ú_/var/www/html/software/conda/envs/higlass/lib/python3.12/site-packages/clodius/tiles/density.pyÚ csv_to_pointsr) sF€ô ‰XÓ €Bà ˆs‰GK‰K‹M€EØ ˆs‰GK‰K‹M€EØ ˆs‰GK‰K‹M€EØ ˆs‰GK‰K‹M€Eà E‰M€EØ U‰]€FÜE˜6Ó"€Iä ‰; Ó $ð /¨Ø×&Ñ&Ø ”s˜2“w l°¼b¿j¹jð'ó ˆð—Z‘Z¨¨c¨ ZÓ3×:Ñ:ˆ‘ˆ à!&ˆ ‰ gÑØ!&ˆ ‰ gÑØ!&ˆ ‰ gÑØ!&ˆ ‰ gÑØ$,ˆ ‰ jÑ!Ø%.ˆ ‰ kÑ"÷ /ð :‰:˜s C˜jˆ:Ó )Ð)÷ /ð /ús ÂB*EÅEcó —tj|d«5}|dj}t|d«t|d«gt|d«t|d«gt|d«t |d«d d œcd d d «S#1swYy xYw) z& Calculate the extent, etc... Úrr rrrrrrÚfalse)Úmin_posÚmax_posrrÚ mirror_tilesN)rrr ÚfloatÚint)Ú points_fileÚf_inr s r(Ú tileset_infor4/s€ô ‰; Ó $ð  ¨ØX‘×$Ñ$ˆô˜e G™nÓ-¬u°U¸7±^Ó/DÐEܘe G™nÓ-¬u°U¸7±^Ó/DÐEܘu [Ñ1Ó2ܘE *Ñ-Ó.Ø#ñ  ÷  ÷  ò  ús —A#BÂB có–—||dd…df|dkD}||dd…df|dk}||dd…df|dkD}||dd…df|dk}|S)aI Filter points that are within the extent Parameters: ----------- data: [[]] A 2D numpy array containing x,y values extent: [x_start, x_end, y_start, y_end] The region we want to return points within Returns ------- data: [[]] A 2D numpy array containing x,y values Nrr éé©)ÚdataÚextents r(Ú filter_pointsr;?su€ð& ’Q˜T‘ ˜V A™YÑ&Ñ '€DØ ’Q˜T‘ ˜V A™YÑ&Ñ '€Dà ’Q˜T‘ ˜V A™YÑ&Ñ '€DØ ’Q˜T‘ ˜V A™YÑ&Ñ '€Dà €Kóc óö—g}tj|d«5}t|dddtt |«|||||««}t |«D]“} t |«D]ƒ} t|tt |«||| z|| z««} t j| dd…df| dd…dfd¬«dj} t j| | dk(<|||| z|| zf| fgz }Œ…Œ•|cddd«S#1swYyxYw) z Get a 2D histogram of the given region. If the height and width are specified, then we need to partition this into multiple returned tiles. r+r Nrr6é)Úbinsg) rrr;rr4ÚrangerÚ histogram2dÚTÚnan) r2Úzrrr$r%ÚreturnsÚfÚ all_pointsÚiÚjÚfiltered_pointsÚdts r(Ú density_tilesrL[s€ð €Gä ‰; Ó $ð¨ä"Ø ˆh‰K™ˆNÜ œ  [Ó1°1°a¸¸EÀ6Ó Jó ˆ ô u“ò 5ˆAܘ6“]ò 5ä"/ؤ ¬L¸Ó,EÀqÈ!ÈaÉ%ÐQRÐUVÑQVÓ Wó#ô—^‘^Ø#¢A q DÑ)¨?º1¸a¸4Ñ+@Àsôàñç‘Qðô!#§¡2˜‘9‘ à˜a  Q¡¨¨A©Ð.°Ð3Ð4Ñ4‘ñ 5ð 5ð÷+÷òús ™C C/Ã/C8c ó†—t||||||«Dcgc] \}}|t|j««f‘Œ"c}}Scc}}w)N)rLrÚflatten)r2rDrrr$r%Útile_posr9s r(ÚtilesrP{sH€ô!.¨k¸1¸aÀÀEÈ6Ó R÷ á ˆXtð Ô$ T§\¡\£^Ó4Ò5ó ðùó s”%=)é)r6r6)Úclodius.tiles.formatrÚclodius.tiles.utilsrÚpandasrÚnumpyrrr1r)r4r;rLrPr8r<r(úrVs6ðÝ2Ý+ÛãÛ ñ#*°3ó#*òL  ò ó8ô@r<