[yt-users] GADGET visualization

Nathan Goldbaum nathan12343 at gmail.com
Tue Feb 25 12:16:55 PST 2014


Did you 'activate' the yt installation?  The install script builds an
isolated environment using its own python interpreter.

More detail here:
http://yt-project.org/docs/dev/installing.html#activating-your-installation

The load function is in convenience.py:
https://bitbucket.org/yt_analysis/yt/src/61e6b84f875cc8fcf25b5b1e67ddd501a19daf68/yt/convenience.py?at=yt#cl-29

Cheers,

Nathan

On Tue, Feb 25, 2014 at 12:03 PM, Andrew Philip Weis
<apw2133 at columbia.edu> wrote:
> Thank you for the detailed response, Nathan.  To clarify, this is the YT
> method paper?
> http://iopscience.iop.org/0067-0049/192/1/9/pdf/0067-0049_192_1_9.pdf
>
> Does the fact that these simulations only contain dark matter affect what
> you say at all?
>
> I will probably have more questions in the near future; at the moment,
> though, I am confused about where in the source code to find certain
> functions.  For instance, the load function appears to be called after we
> do:
>
> from yt.mods import *
>
> but when I try this line in the terminal, I get an error that says there is
> "no module named yt.mods."  Why might this be?  I downloaded and installed
> the source code from:
> http://hg.yt-project.org/yt/raw/yt-3.0/doc/install_script.sh   but I cannot
> find yt.mods or yt/frontends.  Where would those be?  Is there further
> software I may need to install?  Thanks again,
>
> Andrew Weis
>
>
> On Mon, Feb 24, 2014 at 4:58 PM, Nathan Goldbaum <nathan12343 at gmail.com>
> wrote:
>>
>> Hi Andrew,
>>
>> Thanks for writing.  I'm responding since I've had some experience
>> working with yt's SPH frontends.  Matt and others might have more
>> information as well.
>>
>> Support for Gadget data is still not finished.  In the yt-3.0 branch
>> of the development repository, you'll should be able to load the data
>> and do some basic visualization and analysis tasks.  The data is
>> available both in its raw form as particles and also by depositing the
>> particle data onto an octree and then visualization and analyzing the
>> octree. The first notebook you linked to describes the basic of
>> loading, visualizating, and analyzing SPH data.
>>
>> If you want to work with a more stable codebase (although one that is
>> not being actively developed) you should be able to do many analysis
>> and viz tasks using the yt-3.0 branch of the main development
>> repository: https://bitbucket.org/yt_analysis/yt
>>
>> The 3.0 branch was a big refactoring of the underlying data selection
>> algorithms yt uses to load data off disk.  This made it possible to
>> present the same user interface for visualizing datasets from particle
>> codes like Gadget, octree AMR codes like Ramses, and patch-based AMR
>> codes like Enzo.
>>
>> Support for SPH smoothing is available in a separate repository.  In
>> this experimental development repository we've refactored the code to
>> use a symbolic units library to handle unit conversions and detect
>> code bugs using dimensional analysis.  We've also completely
>> refactored the way frontends are written and fields are set up and
>> detected.
>>
>> If you want to dive in to the code, I'd suggest starting with the
>> experimental version of yt.  This may be a bit more rocky at first -
>> there might be bugs - but will be more rewarding in the end as this is
>> the direction the codebase is going.  The work is ongoing in the
>> yt-3.0 branch on Matt Turk's fork of yt:
>> https://bitbucket.org/MatthewTurk/yt
>>
>> In both cases there is unfortunately not a lot of documentation at the
>> moment.  This is something that we're working on right now.  Mailing
>> list archives as well as the YTEP listing
>> (http://ytep.readthedocs.org/) might prove to be useful.
>>
>> As for your questions about yt internals, I've written some basic
>> description below.  I would also encourage you to read the yt method
>> paper and to take a look YTEP-0001 and YTEP-0005, which describe the
>> new geometry system.
>>
>> The basic data structure yt uses to represent an on-disk dataset is
>> the StaticOutput class.  The SPH frontend defines a GadgetStaticOutput
>> class as well as a GadgetHDF5StaticOutput subclass to represent HDF5
>> Gadget datasets.  You can create a new StaticOutput instance using the
>> 'load' function or by directly instantiating an instance of a
>> StaticOutput subclass defined in one of the frontends.  You'll need to
>> look at the parameters of the __init__ method to figure out exactly
>> how to load the data. For Gadget, the 'load' convenience function only
>> works with HDF5 datasets, so if you are have data written in Gadget's
>> binary format, you'll need to load your data by calling
>> GadgetStaticOutput directly.
>>
>> StaticOutput instances have as an attribute an instance of
>> GeometryHandler.  This class handles the indexing and selection of
>> data.  This is really the heart of yt's hard-core numerics, and is
>> written in a way that is very accessible at a high level.  If you want
>> to dive into the algorithms, I think it would help to look over the
>> GeometryHandler class as well as its subclass the
>> ParticleGeometryHandler.  That said, yt's interface is more or less
>> agnostic to the underlying algorithm used to index the data.
>>
>> Do you have specific questions about how to load and visualize your
>> datasets?
>>
>> Hope that's helpful and not too much of a manifesto :)
>>
>> -Nathan
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