Try out in mybinder:

3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL.

Ipyvolume currently can

• Do (multi) volume rendering.
• Create scatter plots (up to ~1 million glyphs).
• Create quiver plots (like scatter, but with an arrow pointing in a particular direction).
• Render isosurfaces.
• Do lasso mouse selections.
• Render in the Jupyter notebook, or create a standalone html page (or snippet to embed in your page).
• Render in stereo, for virtual reality with Google Cardboard.
• Animate in d3 style, for instance if the x coordinates or color of a scatter plots changes.
• Animations / sequences, all scatter/quiver plot properties can be a list of arrays, which can represent time snapshots.
• Stylable (although still basic)
• Integrates with
  • ipywidgets for adding gui controls (sliders, button etc), see an example at the documentation homepage
  • bokeh by linking the selection
  • bqplot by linking the selection

Ipyvolume will probably, but not yet:

• Render labels in latex.
• Show a custom popup on hovering over a glyph.

Documentation is generated at readthedocs:

(see more at the documentation)

If you want to use Jupyter Lab, please use version 3.0.

Advice: Make sure you use conda or virtualenv. If you are not a root user and want to use the --user argument for pip, you expose the installation to all python environments, which is a bad practice, make sure you know what you are doing.

$ pip install ipyvolume

$ conda install -c conda-forge ipyvolume

If you are still using an old notebook version, ipyvolume and its dependend extension (widgetsnbextension) need to be enabled manually. If unsure, check which extensions are enabled:

$ jupyter nbextension list

If not enabled, enable them:

$ jupyter nbextension enable --py --sys-prefix ipyvolume
$ jupyter nbextension enable --py --sys-prefix widgetsnbextension

You have been warned, do this only if you know what you are doing, this might hunt you in the future, and now is a good time to consider learning virtualenv or conda.

$ pip install ipyvolume --user
$ jupyter nbextension enable --py --user ipyvolume
$ jupyter nbextension enable --py --user widgetsnbextension

$ git clone https://github.com/maartenbreddels/ipyvolume.git
$ cd ipyvolume
$ pip install -e . notebook jupyterlab
$ (cd js; npm run build)
$ jupyter nbextension install --py --overwrite --symlink --sys-prefix ipyvolume
$ jupyter nbextension enable --py --sys-prefix ipyvolume
# for jupyterlab (>=3.0), symlink share/jupyter/labextensions/bqplot-image-gl
$ jupyter labextension develop . --overwrite

Note: There is never a need to restart the notebook server, nbextensions are picked up after a page reload.

Start this command:

$ (cd js; npm run watch)

It will

• Watch for changes in the sourcecode and run the typescript compiler for transpilation of the src dir to the lib dir.
• Watch the lib dir, and webpack will build (among other things), ROOT/ipyvolume/static/index.js.

Refresh the page.