B &[¨_}=ã@sàddlmZddlmZddlmZmZddlZddl Z dd„Z dd„Z d d „Z d d „Zd#d d„Zd$dd„Zddddddddiiddddddddddddddfdd„Zeeeddgdddgddddgddgdd gd!d"e_dS)%é)Úbuild_dataframe)Úmake_docstring)Úchoropleth_mapboxÚscatter_mapboxNcCs0|tjd}t t |tjd¡¡}||fS)zU Projects lat and lon to WGS84, used to get regular hexagons on a mapbox map é´)ÚnpÚpiZarctanhÚsin)ÚlatÚlonÚxÚy©rúH/tmp/pip-install-l29rncou/plotly/plotly/figure_factory/_hexbin_mapbox.pyÚ_project_latlon_to_wgs84srcCs>|dtj}dt t |¡¡tjddtj}||fS)zU Projects WGS84 to lat and lon, used to get regular hexagons on a mapbox map ré)rrZarctanÚexp)r r r r rrrÚ_project_wgs84_to_latlons(rcCs”d}d|d|dœ}d}dd„}dd„} ||ƒ||ƒtj} ||} | d krX| d n| d } | |d |d | ƒ} | |d |d | ƒ}t| ||ƒS) zÁ Get the mapbox zoom level given bounds and a figure dimension Source: https://stackoverflow.com/questions/6048975/google-maps-v3-how-to-calculate-the-zoom-level-for-a-given-bounds ré)ÚheightÚwidthécSsHt |tjd¡}t d|d|¡d}tt|tjƒtj ƒdS)Nrér)rr rÚlogÚmaxÚmin)r r ZradX2rrrÚlatRad&sz#_getBoundsZoomLevel..latRadcSs dt |||¡t d¡S)Ngffffffî?r)rr)ZmapPxZworldPxÚfractionrrrÚzoom+sz!_getBoundsZoomLevel..zoomrihrr)rrr)Zlon_minZlon_maxZlat_minZlat_maxÚmapDimZscaleZ WORLD_DIMZZOOM_MAXrrZ latFractionZlngDiffZ lngFractionZlatZoomZlngZoomrrrÚ_getBoundsZoomLevelsr c/ Csò| ¡}| ¡} | ¡} | ¡} d| |} || 8}| | 7} | |} | | }| dkrf|dkrf||}n(| dkr†|dkr†tddƒ\}}n| |}|t d¡}t ||¡ t¡}| | ||| d8} |||}|| |}t |¡ t¡}t |¡ t¡}t  |¡ t¡}t  |¡ t¡}|d}|d}|}|}||||}||dd||d}||ddd||dd}||k}|dkr„t  ||f¡}t  ||f¡} d|k||k@d|k@||k@|@}!d|k||k@d|k@||k@|@}"tj   |||!||!fd¡tj   | ||"||"fd¡|dk r^tj |||k<tj | | |k<t | ¡|  ¡g¡}#t |#¡}$nl|dkr’d}tj||ftd }x2t|ƒD]&}%xt|ƒD]}&g||%|&f<q¼Wq®Wtj||ftd } x2t|ƒD]&}%xt|ƒD]}&g| |%|&f<qWqôWxÞtt|ƒƒD]Î}%||%ršd||%krV|krønn>d||%krv|krønn|||%||%f ||%¡n^d||%kr¶|kr,nn>d||%krÖ|kr,nn| ||%||%f ||%¡q,Wx`t|ƒD]T}%xLt|ƒD]@}&||%|&f}'t|'ƒ|krF||'ƒ||%|&f<ntj ||%|&f<qWqWx`t|ƒD]T}%xLt|ƒD]@}&| |%|&f}'t|'ƒ|kr¨||'ƒ| |%|&f<ntj | |%|&f<qxWqjWt | t¡ ¡|  t¡ ¡f¡}#t |#¡}$|#|$}(t  |dft¡})t t |¡|¡|)d||…df<t t |¡|¡|)d||…df<t t |¡d|¡|)||d…df<t t |¡|¡d|)||d…df<|)dd…df|9<|)dd…df|9<|)dd…df|7<|)dd…df| 7<|)|$})ddddd d g}*d t tjd ¡d t tjd ¡dt tjd ¡dt tjd ¡dt tjd ¡d t tjd ¡g}+t|)ƒ},t |*g|,¡|t |)dd…df¡}-t |+g|,¡|t d¡t |)dd…df¡}.|-|.|)|(fS) aQ Computes the aggregation at hexagonal bin level. Also defines the coordinates of the hexagons for plotting. The binning is inspired by matplotlib's implementation. Parameters ---------- x : np.ndarray Array of x values (shape N) y : np.ndarray Array of y values (shape N) x_range : np.ndarray Min and max x (shape 2) y_range : np.ndarray Min and max y (shape 2) color : np.ndarray Metric to aggregate at hexagon level (shape N) nx : int Number of hexagons horizontally agg_func : function Numpy compatible aggregator, this function must take a one-dimensional np.ndarray as input and output a scalar min_count : int Minimum number of points in the hexagon for the hexagon to be displayed Returns ------- np.ndarray X coordinates of each hexagon (shape M x 6) np.ndarray Y coordinates of each hexagon (shape M x 6) np.ndarray Centers of the hexagons (shape M x 2) np.ndarray Aggregated value in each hexagon (shape M) g•Ö&è .>rrérg@gà?N)Zdtypegà¿é) rrrrÚsqrtÚceilÚastypeÚintÚroundÚfloorÚzerosÚaddZatÚnanZ concatenateZravelÚisnanÚemptyÚobjectÚrangeÚlenÚappendZhstackÚfloatÚrepeatÚarangeZtileÚcosrÚtanÚarrayZvstack)/r r Úx_rangeÚy_rangeÚcolorÚnxÚagg_funcÚ min_countZxminZxmaxZyminZymaxÚpaddingZDxZDyZdxÚ_ZdyÚnyZix1Ziy1Zix2Ziy2Znx1Zny1Znx2Zny2ÚnZd1Zd2ÚbdistZlattice1Zlattice2Zc1Úc2ÚaccumZ good_idxsÚiÚjÚvalsÚagreggated_valueÚcentersÚhxZhyÚmÚhxsÚhysrrrÚ_compute_hexbin9sÀ&    $ $&   @ @$   ""&&*4rNc CsÊt||ƒ\}} |dkr,t | ¡| ¡g¡}|dkrJt | ¡| ¡g¡}t||ƒ\} } t|| | | ||||ƒ\} } }}t| | ƒ\}}| t¡}t   |dd…df¡dt   |dd…df¡}||||fS)a Computes the lat-lon aggregation at hexagonal bin level. Latitude and longitude need to be projected to WGS84 before aggregating in order to display regular hexagons on the map. Parameters ---------- lat : np.ndarray Array of latitudes (shape N) lon : np.ndarray Array of longitudes (shape N) lat_range : np.ndarray Min and max latitudes (shape 2) lon_range : np.ndarray Min and max longitudes (shape 2) color : np.ndarray Metric to aggregate at hexagon level (shape N) nx : int Number of hexagons horizontally agg_func : function Numpy compatible aggregator, this function must take a one-dimensional np.ndarray as input and output a scalar min_count : int Minimum number of points in the hexagon for the hexagon to be displayed Returns ------- np.ndarray Lat coordinates of each hexagon (shape M x 6) np.ndarray Lon coordinates of each hexagon (shape M x 6) pd.Series Unique id for each hexagon, to be used in the geojson data (shape M) np.ndarray Aggregated value in each hexagon (shape M) Nrú,r) rrr7rrrNrr%ÚstrÚpdZSeries)r r Ú lat_rangeÚ lon_ranger:r;r<r=r r r8r9rLrMrIrHÚ hexagons_latsÚ hexagons_lonsÚ hexagons_idsrrrÚ_compute_wgs84_hexbinás0 0rWc Cs‚g}|dkrt t|ƒ¡}xZt|||ƒD]J\}}}t ||g¡j ¡}| |d¡| td|td|gdd¡q(Wtd|dS) zc Creates a geojson of hexagonal features based on the outputs of _compute_wgs84_hexbin NrZFeatureZPolygon)ÚtypeZ coordinates)rXÚidZgeometryZFeatureCollection)rXÚfeatures) rr4r0Úzipr7ÚTÚtolistr1Údict)rTrUÚidsrZr r ÚidxZpointsrrrÚ_hexagons_to_geojson(sraéFc,Cs¾ttƒdd}|dkrtj}|d|d ddg¡j}|d|d ddg¡j}t|d|dj|d|dj||d|||d\}}}}t|||ƒ}|dkr0|dkrÄ|dkrÄtd d d } nL|dkrâ|dk râtd |d } n.|dk r|dkrt||d } n t||d } t |d |d |d |d | ƒ}|dkrNt| ¡| ¡d }|ddk rr|d  |d¡j }!nd |dj i}!g}"x’|!  ¡D]†\}#}$|dj|$}%t|%|dj|%|dj|||drÚ|%|djnd|||d\}&}&}}'|" tjtj||'fddgd¡qŽWtj|"d |! ¡djdd d¡}(t |(d¡|(d<| dkrn|(d ¡|(d ¡g} t|(|ddddddœ|ddk r”dnd||| | | | | |||||||d})|rºt|ddk râ|dj|ddn|d|d|d|dd}*d|*jd _d|*jd _||*jd _ |) !|*jd ¡|ddk rºxvt"t#|*j$ƒƒD]d}+d|*j$|+jd _d|*j$|+jd _||*j$|+jd _ |)j$|+jd |*j$|+jd g|)j$|+_qRW|)S)zP Returns a figure aggregating scattered points into connected hexagons N)ÚargsÚ constructorÚ data_framer rrr )r r rRrSr:r;r<r=iÂ)rrrr)r r Úanimation_framer:Ú locations)Úcolumns)ZaxisÚkeys)ÚframeÚindex)rkrjTF)r:rgrj)reÚgeojsonrgr:Z hover_datarfÚcolor_discrete_sequenceÚcolor_discrete_mapÚlabelsÚcolor_continuous_scaleÚ range_colorÚcolor_continuous_midpointÚopacityrÚcenterÚ mapbox_styleÚtitleÚtemplaterr)Zby)rer r rfÚskip)%rÚlocalsrZmeanZaggÚvaluesrWrar^r ÚgroupbyÚgroupsrkÚitemsÚlocr1rQZ DataFrameZc_ÚconcatriZ rename_axisZ reset_indexZ to_numericrrrrZ sort_valuesÚdataZ hoverinfoZ hovertemplateÚmarkerZ add_tracer/r0Úframes),rer r r:Ú nx_hexagonr<rfrmrnrorprqrrrsrrtrurvrwrrr=Úshow_original_dataÚoriginal_data_markerrcrRrSrTrUrVÚcountrlrr|Zagg_data_frame_listrjrkZdfr?Zaggregated_valueZagg_data_frameZfigZ original_figrErrrÚcreate_hexbin_mapbox=s¶         "     r‡r&z/Number of hexagons (horizontally) to be createdÚfunctionz8Numpy array aggregator, it must take as input a 1D arrayzand output a scalar value.z=Minimum number of points in a hexagon for it to be displayed.z3If None and color is not set, display all hexagons.zDIf None and color is set, only display hexagons that contain points.ÚboolzCWhether to show the original data on top of the hexbin aggregation.r^zScattermapbox marker options.)rƒr<r=r„r…)Z override_dict)NNNNNNNN)N)Zplotly.express._corerZplotly.express._docrZplotly.express._chart_typesrrZnumpyrZpandasrQrrr rNrWrar‡r^Ú__doc__rrrrÚsr    * ?