There’s a new feature in yt 4.1 that lets you load data using just functions, without it needing to be in memory or to have its own frontend defined.
Back in the long, long distant past, the Stream frontend was created to make it easy to bring data into yt without writing a full-on “frontend.” Originally this was to make it easy to share data between VTK and yt – and it worked!
Building on our ability to read data using just functions, we can now load data from raw HDF5 files with a minimum of metadata.
I’ve heard it said that HDF5 isn’t exactly a file-format. Sure, it describes how to write bits down (and does this extremely well and thoroughly), but I have always personally found it to be more immediately useful as a filesystem for data. And, it seems that people who write data to disk find it to be similarly useful – but there’s no single way that people organize the data they use HDF5 to write to disk, attempts at metadata notwithstanding.
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
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.
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 https://girder.hub.yt/ 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
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.