How do I synchronize the selection in the 2 charts below? Also, how do I get the bounds of the box selection?
import holoviews as hv
import hvplot.pandas
from bokeh.sampledata.autompg import autompg
hv.extension('bokeh')
hv.Layout([autompg.hvplot.scatter(x='mpg', y='yr', tools=['box_select']), autompg.hvplot.scatter(x='mpg', y='yr', tools=['box_select'])]).cols(1)
The linked selection is easy:
import holoviews as hv
import hvplot.pandas
from bokeh.sampledata.autompg import autompg
hv.extension('bokeh')
from holoviews.plotting.links import DataLink
a = autompg.hvplot.scatter(x='mpg', y='yr', tools=['box_select'])
b = autompg.hvplot.scatter(x='mpg', y='yr', tools=['box_select'])
DataLink(a, b)
hv.Layout([a, b]).cols(1)
Documentation: https://www.holoviews.org/user_guide/Linking_Plots.html
Now for retrieving the bounds. You can use BoundsXY for that:
import numpy as np
import holoviews as hv
from holoviews.streams import BoundsXY
data = np.random.multivariate_normal((0, 0), [[1, 0.1], [0.1, 1]], (1000,))
points = hv.Points(data).opts(tools=['box_select'])
sel = BoundsXY(source=points)
def cog(bounds):
'Center of gravity'
if bounds is None:
bounds=(0, 0, 0, 0)
index = points.dframe().x.between(*bounds[::2]) & points.dframe().y.between(*bounds[1::2])
x = points.dframe().loc[index, 'x'].mean() if index.any() else []
y = points.dframe().loc[index, 'y'].mean() if index.any() else []
return hv.Points((x, y)).opts(size=10)
mean_sel = hv.DynamicMap(cog, kdims=[], streams=[sel])
points * mean_sel
(modelled on http://holoviews.org/reference/apps/bokeh/selection_stream.html)