a `K@sddlmZddlmZddlZddlZddlZddlZddl Z ddl m Z ddl m Z mZmZmZmZddl mZmZmZmZddlmZdd lmZdd lmZmZmZee jZ e d krdd l!m"Z"dd l#m$Z$zddl#m%Z%WnddZ%Yn0ddl&m'Z'm(Z(n$ddl)m*Z*ddl+m,Z'ddl-m(Z(dZ.ddZ/ddZ0ddZ1Gddde2Z3Gddde2Z4d'd"d#Z5d(d%d&Z6dS)))absolute_import) LooseVersionN)Document)CustomJSColumnDataSourceSquare HoverTool GlyphRenderer)PlotTextCircleRange1d)Figure)transfer_functions)VisibleDeprecationWarningdownsample_aggregatesummarize_aggregate_values0.12.9)Protocol)notebook_content) encode_utf8cCs|SN)srr3lib/python3.9/site-packages/datashader/bokeh_ext.py r) CommsHandle get_comms) notebook_div) _CommsHandle)rzF {plot_div} cCsPtdkr>t|j|j\}}}tj||d}t|}|jnt |j|j}|S)a" Generates an HTML div to embed in the notebook. Parameters ---------- image: InteractiveImage InteractiveImage instance with a plot Returns ------- div: str HTML string containing the bokeh plot to be displayed r)Z plot_scriptZplot_div) bokeh_versionrpref NOTEBOOK_DIVformatrdocZholdr )imageZjsZdiv_Zhtmlrrrbokeh_notebook_div/s r*cCstdkrLt|jj}|sdStdkr,t}ntd}|d|}g|j_|St|jj}|dd g|d<t dd |jj |d ggd S) a Generates a bokeh patch event message given an InteractiveImage instance. Uses the bokeh messaging protocol for bokeh>=0.12.10 and a custom patch for previous versions. Parameters ---------- image: InteractiveImage InteractiveImage instance with a plot Returns ------- msg: str JSON message containing patch events to update the plot rNz2.0.0z1.0z PATCH-DOCr(rdataZ ModelChanged)attrkindZmodelnew)events references) r"listr'Z _held_eventsrZcreatedictdsr+tolistjsondumpsr$)r(r/Zprotocolmsgr+rrr patch_eventHs&   r8cCsjtdkr\||j||j||j|jD]&\}}|t||j|gdq2n ||dS)a5 Sends a bokeh patch event message via the supplied comm, using binary buffers for bokeh versions >= 0.12.10. Parameters ---------- msg: str JSON message containing patch events to update the plot comm: Comm Jupyter comm used to send data to the notebook frontend r)buffersN)r"sendZ header_jsonZ metadata_jsonZ content_jsonr9r5r6)r7commheaderZpayloadrrr send_patchls    r=c@sXeZdZdZdZdZiZdddZd d Zd d Z dd dZ ddZ ddZ ddZ dS)InteractiveImagea3 Bokeh-based interactive image object that updates on pan/zoom events. Given a Bokeh plot and a callback function, calls the function whenever the pan or zoom changes the plot's extent, regenerating the image dynamically. Works in a Jupyter/IPython notebook cell, using the existing notebook kernel Python process (not a separate Bokeh server). Does not yet support usage outside the notebook, but could be extened to use Bokeh server in that case. Parameters ---------- bokeh_plot : plot or figure Bokeh plot the image will be drawn on callback : function Python callback function with the signature:: fn(x_range=(xmin, xmax), y_range=(ymin, ymax), w, h, **kwargs) and returning a PIL image object. delay : int Specifies the delay between the first received event and when events are actually processed. Useful to ignore events generated immediately after initiating zooming. timeout: int Determines the timeout after which the callback will process new events without the previous one having reported completion. Increase for very long running callbacks. **kwargs Any kwargs provided here will be passed to the callback function. a // Define a callback to capture errors on the Python side function callback(msg){{ if (msg.msg_type == "execute_result") {{ if (msg.content.data['text/plain'] === "'Complete'") {{ if (Bokeh._queued.length) {{ update_plot(); }} else {{ Bokeh._blocked = false; }} Bokeh._timeout = Date.now(); }} }} else {{ console.log("Python callback returned unexpected message:", msg) }} }} var callbacks = {{iopub: {{output: callback}}}}; function update_plot() {{ var range = Bokeh._queued; var cmd = "{cmd}(" + range + ")" // Execute the command on the Python kernel if (IPython.notebook.kernel !== undefined) {{ var kernel = IPython.notebook.kernel; kernel.execute(cmd, callbacks, {{silent : false}}); }} Bokeh._queued = []; }} var plot = x_range.plots[0]; // Generate a command to execute in Python var ranges = {{xmin: x_range.start, ymin: y_range.start, xmax: x_range.end, ymax: y_range.end, w: Math.floor(plot.width), h: Math.floor(plot.height)}} var range_str = JSON.stringify(ranges) if (!Bokeh._queued) {{ Bokeh._queued = []; Bokeh._blocked = false; Bokeh._timeout = Date.now(); }} var timeout = Bokeh._timeout + {timeout}; if (typeof _ === "undefined") {{ }} else if ((Bokeh._blocked && (Date.now() < timeout))) {{ Bokeh._queued = [range_str]; }} else {{ Bokeh._queued = [range_str]; setTimeout(update_plot(), {delay}); Bokeh._blocked = true; Bokeh._timeout = Date.now(); }} z Updates image with data returned by callback rmrnrorprrwhraN)rDrEr2r+r3rt)rQrsrOrPrerdr(Znew_datarrrrqAszInteractiveImage.update_imagecCs4t|_|jD] }d|_q|j|jt|Sr)rr'r#r0Z _documentZadd_rootr*)rQmrrr _repr_html_Ps zInteractiveImage._repr_html_)r?r@N)N)r^r] __qualname____doc__r_r\r[rRrNrLrtrrrqryrrrrr>s%9  r>c@sVeZdZdZddd Zed d Zejd d Zed dZejddZddZ dS) HoverLayeram Wrapper for adding a HoverTool instance to a plot tools which highlights values under the user's mouse location. Parameters ---------- field_name : str Field title which will appear in hover tooltip highlight_fill_color : str Fill color for glyph which appears on mouse over. highlight_line_color : str Line color for glyph which appears on mouse over. size : int Defined hover layer resolution in pixels (i.e. height/width of hover grid) extent : list ``[xmin, ymin, xmax, ymax]`` in data coordinates representing aggregate bounds agg : xarray Datashader aggregate object (e.g. result of Canvas.points()) how : str Downsample method for summarizing ordinal aggregates (default: mean). Options include: mean, sum, max, min, median, std, var, count. Value#79DCDEFNmeanc Cs|dvrtdttgggdd|_tdddd|d|_tdd|d|d |d |_g|_d } td |ji| d |_ t |_ |j|j _ |j|j _ |j|j _|j|j _t|j |j gdd|_||_||_||_||_|pd|_||_|jdur|jdur|dS)N)rsummaxminZmedianZstdvarcountzinvalid 'how' downsample method)rbrcvaluerfrbrc)rbrc fill_color line_colorsizeg?r)rbrcr fill_alpharZ line_alpharz#source.selected = cb_data['index'];rgrWZmouse)rDZ renderersmoder) ValueErrorrr2 hover_datarinvisible_squarevisible_squaretooltipsrZ _callbackr rMZ data_sourceZglyphZselection_glyphZnonselection_glyphrtoolextentis_categorical field_name_agg_sizehowaggcompute) rQrZhighlight_fill_colorZhighlight_line_colorrrrrrrYrrrrRwsJ      zHoverLayer.__init__cCs|jSr)rrurrrrszHoverLayer.sizecCs6||_||j_||j_|jdur2|jdur2|dSr)rrrrrrrrQrrrrrs cCs|jSr)rrurrrrszHoverLayer.aggcCs&||_|jdur"|jdur"|dSr)rrrrrrrrrsc CsHt|jd|jd|jjd|j}t|jd|jd|jjd|j}t||\}}||d}t|jj |j|j d|_ g}|j r|j|jj dj }t|D]H\}} |j dddd|f|t| <|t| dt| fqn|j |d<||jd f|jj|jj|||j_|j S) Nrr)rbrcrz@{}rz@value)npZlinspacerrshaperZmeshgridZflattenrvaluesrZ hover_aggrZdimsr4 enumeraterFappendr&rrr+clearrtrr) rQZsq_xsZsq_ysZagg_xsZagg_ysZnew_hover_datarZcatsierrrrs.  $  zHoverLayer.compute)r}r~r~rFNNr) r^r]rzr{rRpropertyrsetterrrrrrrr|Xs& 7    r|linearXc Cst||d\}}}tj|||d}|}|dks:|dks:Jt||fd|ddd|d} d | _d | _d | _d | _d | j_ d | j _ | j |j g|gd g||gd gdd| S)as Helper function to create a Bokeh ``Figure`` object with a color ramp corresponding to input aggregate and transfer function. Parameters ---------- agg : xarray Datashader aggregate object (e.g. result of Canvas.points()) cmap : list of colors or matplotlib.colors.Colormap, optional The colormap to use. Can be either a list of colors (in any of the formats described above), or a matplotlib colormap object. how : str Datashader transfer function name (either linear or log) width : int Width in pixels of resulting legend figure (default=600) r)cmaprrlog2N)r)rOrirhZ lod_thresholdtoolbar_locationrP x_axis_typer FrZscreen)r(rbrcrdreZdw_units)rtfZshadermin_border_topmin_border_bottommin_border_leftmin_border_rightZyaxisZvisibleZgridZgrid_line_alpharkr) rrrrlZvals_arrZmin_valZmax_valZimgrZ legend_figrrrcreate_ramp_legends4 rrc Cs|dt|}i}tddd|d<td|d|d<|d||d<d|d <d|d <d|d <d|d <d|d <d|d<d|d<tfi|}t|D]~\}\}}||d||d} |r||n|} |td| |d| gd|dd|td| |d||dddq|S)a Creates a bokeh plot object with circle legend swatches and text corresponding to the ``colormap`` key values or the optional aliases values. Parameters ---------- colormap : dict Dictionary of category value to color value aliases : dict Dictionary of category value to aliases name font_size: int Font size to use in the legend text rrr?)rArjrOrPrirhrrrrZoutline_line_widthNr(g333333?z{}ptz#666666)rbrctextZtext_font_sizeZ text_colorrg?)rbrcrrrr) lenr r ritemsZ add_glyphr r&r ) ZcolormapaliasesZ font_sizeZy_maxZ plot_optionsZlegendrcatZcolorZtext_yZtext_valrrrcreate_categorical_legends<   r)rr)Nr)7Z __future__rZdistutils.versionrrGr5rBZnumpyrZbokehZbokeh.documentrZ bokeh.modelsrrrrr r r r r Zbokeh.plottingrrrZutilsrrr __version__r"Zbokeh.protocolrZbokeh.embed.notebookrrZbokeh.io.notebookrrZ bokeh.embedr Zbokeh.ior!Zbokeh.util.notebookr%r*r8r=objectr>r|rrrrrrsD            $U 0