I have multiple categorical heatmap plots that are in a single display that have identical shapes and x,y coordinates. When hovering on any of the subplots I would like the inspection on one plot to trigger a new inspection on all other plots in the grid and display multiple tooltips simultaneously.
I have researched this topic and found similar posts such as:
Bokeh: Synchronizing hover tooltips in linked plots
Takeaway from link above: There are 2 suggested answers to this question, which attempt to mimic hover tooltips with text glyphs, however these implementations are not successful when I copy and run the code on my own computer (the graphs display correctly but the hover text glyphs don't appear). I assume this could be because of Bokeh API updates, but I am unsure. My reputation doesn't allow comments or I'd address this issue there.
Coordinate tooltips across multiple plots #1547
Takeaway from link above: There is no reproducible data so I am not able to recreate the plot listed here, however bryevdv summarizes what I am trying to do quite efficiently which I'll quote below:
Link on geometry. You might want the geometry of the inspection on one plot to trigger a completely new inspection (using that same geometry) on another plot. So if the cursor is at (10.5, 7) on one plot, then the additional plots do a hit test at (10.5, 7) and if there are glyphs that have any hovers a that point, then a hover gets drawn there.
I have created some generalized data to illustrate my problem:
from bokeh.io import show, output_notebook
from bokeh.layouts import gridplot
from bokeh.models import LinearColorMapper, HoverTool
from bokeh.plotting import figure, show, output_file
from bokeh.transform import transform
import numpy as np
import pandas as pd
data1 = [['A','A',100], ['A','B',175], ['B','A',75], ['B','B',200]]
data2 = [['A','A',25], ['A','B',100], ['B','A',50], ['B','B',75]]
data3 = [['A','A',150], ['A','B',75], ['B','A',25], ['B','B',125]]
df1 = pd.DataFrame(data1, columns = ['Left','Right','Value'])
df2 = pd.DataFrame(data2, columns = ['Left','Right','Value'])
df3 = pd.DataFrame(data3, columns = ['Left','Right','Value'])
def heatmap(df, title):
letters = ['A','B']
mapper = LinearColorMapper(palette=['#225ea8', '#41b6c4', '#a1dab4', '#ffffcc'], low=0, high=200)
TOOLS = 'reset'
p = figure(plot_width=255, plot_height=250, title=title,
x_range=letters,
y_range=list(reversed(letters)), x_axis_location='above',
tools=TOOLS, toolbar_location='below')
p.grid.grid_line_color = None
p.grid.grid_line_width = 0.5
p.axis.axis_line_color = None
p.axis.major_tick_line_color = None
p.axis.major_label_text_font_size = '9pt'
p.axis.major_label_standoff = 0
p.xaxis.major_label_orientation = 0
hover = HoverTool()
p.rect(x='Right', y='Left', width=1, height=1, line_color=None, source=df,
fill_color={'field': 'Value', 'transform': mapper})
hover.tooltips = [('Group','@Left @Right'), ('Value','@Value')]
p.tools.append(hover)
return p
output_notebook()
p1 = heatmap(df1, 'Plot 1')
p2 = heatmap(df2, 'Plot 2')
p3 = heatmap(df3, 'Plot 3')
grid = gridplot([[p1,p2,p3]])
show(grid)
Output:
My goal is to be able to observe the values across multiple plots at one time without having to be directed to another page or source, so I am open to alternative ways of doing this that doesn't involve hover tooltips. Thanks!
