o Nrf @shddlmZddlmZddlZddlZddlZdde fddZ dd Z d d Z dd dZ dddZdS))format_dense_tile) tile_boundsNmax_zoomc Cst|}|d}|d}|d}|d}||}||} t|| } t|dA} | jdt|dfdtj d} |j ddgdj | d d <|| j d <|| j d <|| j d <|| j d <|| j d<| | j d<Wd n1stwY|j ddgdS)z Convert a csv file containing points to a numpy array of [[x,y]] values. Parameters: ----------- csv_file: string The filename of the data file xywvaluesgzip) compressionZdtype)columnsNmin_xmax_xmin_ymax_yr max_width) pdZread_csvminmaxh5pyFileZcreate_datasetlennpZfloat32Zreindexr attrs) Zcsv_fileZ output_filerdfrrrrwidthheightrZf_outZdatasetr^/var/www/html/software/conda/envs/catlas/lib/python3.10/site-packages/clodius/tiles/density.py csv_to_points s*            r cCst|d1}|dj}t|dt|dgt|dt|dgt|dt|dd d Wd S1s:wYd S) z& Calculate the extent, etc... rr rrrrrrfalse)Zmin_posZmax_posrrZ mirror_tilesN)rrrfloatint) points_fileZf_inrrrr tileset_info/s   $r&cCst||dddf|dk}||dddf|dk}||dddf|dk}||dddf|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 r)dataZextentrrr filter_points?s r*r'c Csg}t|dh}t|dddtt||||||}t|D]E} t|D]>} t|tt|||| || } tj| dddf| dddfdddj} tj | | dk<|||| || f| fg7}q'q!|WdS1sswYdS) 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 Nrr')Zbinsg) rrr*rr&rangerZ histogram2dTnan) r%zrrrrreturnsfZ all_pointsijZfiltered_pointsdtrrr density_tiles[s.   $r5cCsddt||||||DS)NcSs g|] \}}|t|fqSr)rflatten).0Ztile_posr)rrr |sztiles..)r5)r%r/rrrrrrrtiles{sr9)r)r'r')Zclodius.tiles.formatrZclodius.tiles.utilsrZpandasrnumpyrrr$r r&r*r5r9rrrrs &