IPyvolume is a Python library to visualize 3d volumes and glyphs (e.g. 3d scatter plots), in the Jupyter notebook, with minimal configuration and effort. It is currently pre-1.0, so use at own risk. IPyvolume’s volshow is to 3d arrays what matplotlib’s imshow is to 2d arrays.

Other (more mature but possibly more difficult to use) related packages are yt, VTK and/or Mayavi.

Feedback and contributions are welcome: Github, Email or Twitter.

Quick intro


For quick resuls, use ipyvolume.widgets.quickvolshow. From a numpy array, we create two boxes, using slicing, and visualize it.

import numpy as np
import ipyvolume as ipv
V = np.zeros((128,128,128)) # our 3d array
# outer box
V[30:-30,30:-30,30:-30] = 0.75
V[35:-35,35:-35,35:-35] = 0.0
# inner box
V[50:-50,50:-50,50:-50] = 0.25
V[55:-55,55:-55,55:-55] = 0.0
ipv.quickvolshow(V, level=[0.25, 0.75], opacity=0.03, level_width=0.1, data_min=0, data_max=1)

Scatter plot

Simple scatter plots are also supported.

import ipyvolume as ipv
import numpy as np
x, y, z = np.random.random((3, 10000))
ipv.quickscatter(x, y, z, size=1, marker="sphere")

Quiver plot

Quiver plots are also supported, showing a vector at each point.

import ipyvolume as ipv
import numpy as np
x, y, z, u, v, w = np.random.random((6, 1000))*2-1
quiver = ipv.quickquiver(x, y, z, u, v, w, size=5)

Mesh plot

And surface/mesh plots, showing surfaces or wireframes.

import ipyvolume as ipv
x, y, z, u, v = ipv.examples.klein_bottle(draw=False)
m = ipv.plot_mesh(x, y, z, wireframe=False)

Built on Ipywidgets

For anything more sophisticed, use ipyvolume.pylab, ipyvolume’s copy of matplotlib’s 3d plotting (+ volume rendering).

Since ipyvolume is built on ipywidgets, we can link widget’s properties.

import ipyvolume as ipv
import numpy as np
x, y, z, u, v, w = np.random.random((6, 1000))*2-1
selected = np.random.randint(0, 1000, 100)
quiver = ipv.quiver(x, y, z, u, v, w, size=5, size_selected=8, selected=selected)

from ipywidgets import FloatSlider, ColorPicker, VBox, jslink
size = FloatSlider(min=0, max=30, step=0.1)
size_selected = FloatSlider(min=0, max=30, step=0.1)
color = ColorPicker()
color_selected = ColorPicker()
jslink((quiver, 'size'), (size, 'value'))
jslink((quiver, 'size_selected'), (size_selected, 'value'))
jslink((quiver, 'color'), (color, 'value'))
jslink((quiver, 'color_selected'), (color_selected, 'value'))
VBox([ipv.gcc(), size, size_selected, color, color_selected])

Try changing the slider to the change the size of the vectors, or the colors.

Quick installation

This will most likely work, otherwise read Installation

pip install ipyvolume
jupyter nbextension enable --py --sys-prefix ipyvolume
jupyter nbextension enable --py --sys-prefix widgetsnbextension

For conda/anaconda, use:

conda install -c conda-forge ipyvolume
pip install ipywidgets~=6.0.0b5 --user


Ipyvolume is an offspring project from vaex. Ipyvolume makes use of threejs, and excellent Javascript library for OpenGL/WebGL rendering.


  • 0.4
    • plotting
      • lines
      • wireframes
      • meshes/surfaces
      • isosurfaces
      • texture (animated) support, gif image and MediaStream (movie, camera, canvas)
    • camera control (angles from the python side), FoV
    • movie creation
    • eye separation for VR
    • better screenshot support (can be to a PIL Image), and higher resolution possible
    • mouse lasso (a bit rough), selections can be made from the Python side.
    • icon bar for common operations (fullscreen, stereo, screenshot, reset etc)
    • offline support for embedding/saving to html
    • Jupyter lab support
    • New contributors
      • Chris Sewell
      • Satrajit Ghosh
      • Sylvain Corlay
      • stonebig
      • Matt McCormick
      • Jean Michel Arbona
  • 0.3
    • new
      • axis with labels and ticklabels
      • styling
      • animation (credits also to https://github.com/jeammimi)
      • binary transfers
      • default camera control is trackball
    • changed
      • s and ss are now spelled out, size and size_selected

Indices and tables