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

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ipyvolume

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

Ipyvolume currenty 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

Ipyvolume will probably, but not yet:

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

Documentation

Documentation is generated at readthedocs: Documentation

Screencast demos

Animation

screencast

(see more at the documentation)

Volume rendering

screencast

Glyphs (quiver plots)

screencast quiver

Installation

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

Using pip

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/Anaconda

$ conda install -c conda-forge ipyvolume

Pre-notebook 5.3

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 nbextention list

If not enabled, enable them:

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

Pip as user: (but really, do not do this)

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

Developer installation

$ git clone https://github.com/maartenbreddels/ipyvolume.git
$ cd ipyvolume
$ pip install -e .
$ 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

Developer workflow

Jupyter notebook (classical)

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.

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

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