[yt-users] GADGET visualization

Sun Mar 2 17:07:32 PST 2014

On Sun, Mar 2, 2014 at 4:32 PM, Andrew Weis <aweis at astro.columbia.edu> wrote:
> Sorry for the delayed reply.  I had forgotten that step, as it turns out.
> Thank you for those links.  I activated the installation, and endeavored to
> follow the steps at
> http://nbviewer.ipython.org/url/hub.yt-project.org/notebooks/e209c55b6aaa4a9ab12c55422bb3afdc.ipynb
>
> Most of the steps appeared to work, but when I tried to display the
> projection plot with pw.show(), nothing appeared.

Were you running those steps inside of an IPython notebook?  If so,
what happens when you add '%matplotlib inline' to the top of the
notebook?

If you weren't running of a notebook, that is the expected behavior.
You can save the plot to disk using pw.save() instead.

> I think the issue may lie
> with the definition of center; is the definition on the website a general
> definition, or specific to one simulation?  I am referring to the lines:
>
> # This is where the halo appears to be centered, although the halo center on
> the Agora website is somewhat different
>
>
> center=np.array([29.754, 32.1, 28.29])
>
>
> What do these numbers mean?  It is possible they may be different for my
> simulations, I would think, but how do we know that a particular halo is
> centered there?  Thanks again,
>

My guess is that Matt chose those as the location of an interesting
halo in the dataset he was looking at.  You will need to supply a
different center if you are looking at a different dataset.

If you're looking at a cosmology simulation, you will need to run a
halo finder to get the positions of the halos you want to look at.

>
> Andrew Weis
>
>
>
> On Tue, Feb 25, 2014 at 3:16 PM, Nathan Goldbaum <nathan12343 at gmail.com>
> wrote:
>>
>> 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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