ParaView and yt
@ Matthew Turk | Monday, Jun 13, 2011 | 3 minute read | Update at Monday, Jun 13, 2011

Thanks to some awesome work by developers at Kitware, yt can now be called from within ParaView!

This relies on a couple things, all of which are pretty exciting moving forward. The idea behind this is to leverage where the two codes have their own strengths and weaknesses, and identify places where they can work productively together. For instance, yt has been designed to provide astrophysical analysis; in this way, it can generate adaptive projections, spectral energy distributions and so on. By feeding data to yt (and not asking yt to read any on its own) these functions can be called from within ParaView, and images and results returned back to ParaView.

The strategy taken has, so far, been a light one. Almost all of the yt machinery has been left in place; what happens is a relatively simple process:

  • Load data into ParaView
  • Feed data into yt
  • Construct IO handlers that pass the contents of internal VTK structures to yt through a custom IOHandlerBase implementation.
  • Construct a hierarchy from the existing contents of the vtkHierarchicalBoxDataSet object, and its attendant child objects.
  • Execute analysis
  • Return processed data to paraview

We’re currently investigating how to streamline this process; currently, it utilizes a new frontend I wrote that was designed to stream data into yt from arbitrary locations. This can act as a proxy for datasets that are already loaded into yt, for datasets that are constructed ab initio in yt and for accepting data through in-memory transfer from ParaView! One of the fun applications of this will be using ParaView as a means for conducting Co-processing of data.

Thanks very much to Jorge, Berk, Charles and George at Kitware for all your hard work to make this happen. This is going to be a really fun way to explore new methods for analysis moving forward.

Not only is this exciting because it enables better cross-talk between yt and ParaView, but also because of the technology that is being developed on both sides. The stream handler in yt, in particular, is a great output from this: it can be used in the future to construct arbitrary datasets in memory, as well as to prototype new frontends for codebases. When yt gains the ability to write out datasets for various code types, this will be a valuable tool for constructing datasets from scratch.

For more information, see this post on the AMR mailing list at Kitware, which contains an example script. While this functionality will be in the 2.2 release, it will be highlighted in the 2.3 release as we streamline and work out bugs in a proper ParaView frontend.

yt extension modules

yt has many extension packages to help you in your scientific workflow! Check these out, or create your own.


ytini is set of tools and tutorials for using yt as a tool inside the 3D visual effects software Houdini or a data pre-processor externally to Houdini.


Trident is a full-featured tool that projects arbitrary sightlines through astrophysical hydrodynamics simulations for generating mock spectral observations of the IGM and CGM.


pyXSIM is a Python package for simulating X-ray observations from astrophysical sources.


Analyze merger tree data from multiple sources. It’s yt for merger trees!


yt_idv is a package for interactive volume rendering with yt! It provides interactive visualization using OpenGL for datasets loaded in yt. It is written to provide both scripting and interactive access.


widgyts is a jupyter widgets extension for yt, backed by rust/webassembly to allow for browser-based, interactive exploration of data from yt.


yt_astro_analysis is the yt extension package for astrophysical analysis.

Make your own!!

Finally, check out our development docs on writing your own yt extensions!

Contributing to the Blog

Are you interested in contributing to the yt blog?

Check out our post on contributing to the blog for a guide!

We welcome contributions from all members of the yt community. Feel free to reach out if you need any help.

the yt data hub

The yt hub at has a ton of resources to check out, whether you have yt installed or not.

The collections host all sorts of data that can be loaded with yt. Some have been used in publications, and others are used as sample frontend data for yt. Maybe there’s data from your simulation software?

The rafts host the yt quickstart notebooks, where you can interact with yt in the browser, without needing to install it locally. Check out some of the other rafts too, like the widgyts release notebooks – a demo of the widgyts yt extension pacakge; or the notebooks from the CCA workshop – a user’s workshop on using yt.

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