Linking behavior¶
It’s often useful to link plots to add connected interactivity between plots. This section shows an easy way to do this, using the bokeh.plotting interface.
Linked panning¶
It’s often desired to link pan or zooming actions across many plots. All that is
needed to enable this feature is to share range objects between figure()
calls.
from bokeh.io import output_file, show
from bokeh.layouts import gridplot
from bokeh.plotting import figure
output_file("panning.html")
x = list(range(11))
y0 = x
y1 = [10-xx for xx in x]
y2 = [abs(xx-5) for xx in x]
# create a new plot
s1 = figure(width=250, height=250, title=None)
s1.circle(x, y0, size=10, color="navy", alpha=0.5)
# create a new plot and share both ranges
s2 = figure(width=250, height=250, x_range=s1.x_range, y_range=s1.y_range, title=None)
s2.triangle(x, y1, size=10, color="firebrick", alpha=0.5)
# create a new plot and share only one range
s3 = figure(width=250, height=250, x_range=s1.x_range, title=None)
s3.square(x, y2, size=10, color="olive", alpha=0.5)
p = gridplot([[s1, s2, s3]], toolbar_location=None)
# show the results
show(p)
Now you have learned how to link panning between multiple plots with the bokeh.plotting interface.
Linked brushing¶
Linked brushing in Bokeh is expressed by sharing data sources between glyph renderers. This is all Bokeh needs to understand that selections acted on one glyph must pass to all other glyphs that share that same source. To see how linked selection extends to glyph renderers that plot only a subset of data from a data source, see Linked selection with filtered data.
The following code shows an example of linked brushing between circle glyphs on
two different figure() calls.
from bokeh.io import output_file, show
from bokeh.layouts import gridplot
from bokeh.models import ColumnDataSource
from bokeh.plotting import figure
output_file("brushing.html")
x = list(range(-20, 21))
y0 = [abs(xx) for xx in x]
y1 = [xx**2 for xx in x]
# create a column data source for the plots to share
source = ColumnDataSource(data=dict(x=x, y0=y0, y1=y1))
TOOLS = "box_select,lasso_select,help"
# create a new plot and add a renderer
left = figure(tools=TOOLS, width=300, height=300, title=None)
left.circle('x', 'y0', source=source)
# create another new plot and add a renderer
right = figure(tools=TOOLS, width=300, height=300, title=None)
right.circle('x', 'y1', source=source)
p = gridplot([[left, right]])
show(p)
Linked properties¶
It is also possible to link values of Bokeh model properties together so that
they remain synchronized, using the js_link method. The example below links
a circle glyph radius to the value of a Slider widget:
from bokeh.layouts import column
from bokeh.models import Slider
from bokeh.plotting import figure, show
plot = figure(width=400, height=400)
r = plot.circle([1,2,3,4,5,], [3,2,5,6,4], radius=0.2, alpha=0.5)
slider = Slider(start=0.1, end=2, step=0.01, value=0.2)
slider.js_link('value', r.glyph, 'radius')
show(column(plot, slider))
The linking is accomplished in JavaScript, so this method works in standalone Bokeh documents, or in Bokeh server applications.
See Adding widgets for more information about different widgets, and JavaScript callbacks for more information about creating arbitrary JavaScript callbacks.