ipyvolume & bqplot

This example shows how the selection from a ipyvolume quiver plot can be controlled with a bqplot scatter plot and it’s selection tools. We first get a small dataset from vaex

import numpy as np
import vaex
ds = vaex.example()
N = 2000 # for performance reasons we only do a subset
x, y, z, vx, vy, vz, Lz, E = [ds.columns[k][:N] for k in "x y z vx vy vz Lz E".split()]

bqplot scatter plot

And create a scatter plot with bqplot

import bqplot.pyplot as plt
plt.figure(1, title="E Lz space")
scatter = plt.scatter(Lz, E,
                selected_style={'opacity': 0.2, 'size':1, 'stroke': 'red'},
                unselected_style={'opacity': 0.2, 'size':1, 'stroke': 'blue'},

Ipyvolume quiver plot

And use ipyvolume to create a quiver plot

import ipyvolume.pylab as ipv
quiver = ipv.quiver(x, y, z, vx, vy, vz, size=2, size_selected=5, color_selected="blue")

Linking ipyvolume and bqplot

Using jslink, we link the selected properties of both widgets, and we display them next to eachother using a VBox.

from ipywidgets import jslink, VBox
jslink((scatter, 'selected'), (quiver, 'selected'))
Link(source=(Scatter(colors=['steelblue'], default_size=1, interactions={'hover': 'tooltip'}, scales={'x': Lin…
hbox = VBox([ipv.current.container, plt.figure(1)])
# TODO: cannot display the figure twice currently
# hbox


We embed the two widgets in an html file, creating a standlone plot.

import ipyvolume.embed
# if we don't do this, the bqplot will be really tiny in the standalone html
bqplot_layout = hbox.children[1].layout
bqplot_layout.min_width = "400px"
ipyvolume.embed.embed_html("bqplot.html", hbox, offline=True, devmode=True)
Downloading https://unpkg.com/@jupyter-widgets/html-manager@^0.20.0/dist/embed-amd.js: [==========] Finished
ERROR:root:No traceback has been produced, nothing to debug.
!open bqplot.html
/bin/sh: 1: open: not found