reading Gadget-HDF5 format in yt-3.0
Hi, I noticed in the update log of yt-3.0 you can now read Gadget HDF5 format (for OWLS project), but it is possible for Rockstar to read the exact same formats? I have some HDF5 data and I'd like to run Rockstar on it through yt if it has this capability in 3.0. Are there any examples of carrying out such a process? Thanks. Thanks. Brendan
Hi Brendan, Thanks for writing. On Thu, Sep 26, 2013 at 9:41 PM, Brendan Griffen <brendan.f.griffen@gmail.com> wrote:
Hi,
I noticed in the update log of yt-3.0 you can now read Gadget HDF5 format (for OWLS project), but it is possible for Rockstar to read the exact same formats? I have some HDF5 data and I'd like to run Rockstar on it through yt if it has this capability in 3.0.
Good question! So there are a couple of things to address in this. The first is that of the HDF5 formats for reading data. I have issued a pull request, with Desika Narayanan's help, to add support for Gadget HDF5 data files, which are subtly different than the OWLS data files. I would *very* much appreciate it if you could help by testing this out. You can do so by doing: cd $YT_DEST/src/yt-hg # or wherever "yt instinfo" tells you, if you have run the install script hg pull -r d996eff https://bitbucket.org/MatthewTurk/yt-3.0 hg up -r d996eff python2.7 setup.py build_ext -i -f This will update you to that version of the code, and you should now be able to execute this command: from yt.mods import * ds = load("gadget_filename.hdf5") Things like projecting and analyzing particles and so on should now work. *Please* let us know if this works for your data, and if so, click on the "approve" button or leave a comment on the pull request: https://bitbucket.org/yt_analysis/yt-3.0/pull-request/99/implement-gadget-hd... I think we really only need one more external tester (Desika has tested it) and we can bring it in. The second thing is about Rockstar. I've been working on a pull request against my fork of Rockstar ( http://bitbucket.org/MatthewTurk/rockstar ) that enables deeper and better yt integration; these changes have been submitted upstream so hopefully I won't need a fork for much longer and we can all go back to tarballs of R*. I've been testing this in my bookmark "rockstar_work" (which I haven't merged with HDF5-gadget work, sorry!) and I am getting weird results. The process is working, but the halo masses are scaled incorrectly and I am going to be investigating units to figure out the problem. This is actually a regression, as it had previously well, and I will be investigating it in more detail. I hope to have some results shortly. Let me know if you get a chance to check the Gadget-HDF5, and hopefully by then I'll have the Rockstar stuff up and running! -Matt
Are there any examples of carrying out such a process? Thanks.
Thanks.
Brendan
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Hi Brendan, On Fri, Sep 27, 2013 at 4:22 PM, Matthew Turk <matthewturk@gmail.com> wrote:
Hi Brendan,
Thanks for writing.
On Thu, Sep 26, 2013 at 9:41 PM, Brendan Griffen <brendan.f.griffen@gmail.com> wrote:
Hi,
I noticed in the update log of yt-3.0 you can now read Gadget HDF5 format (for OWLS project), but it is possible for Rockstar to read the exact same formats? I have some HDF5 data and I'd like to run Rockstar on it through yt if it has this capability in 3.0.
Good question! So there are a couple of things to address in this.
The first is that of the HDF5 formats for reading data. I have issued a pull request, with Desika Narayanan's help, to add support for Gadget HDF5 data files, which are subtly different than the OWLS data files. I would *very* much appreciate it if you could help by testing this out. You can do so by doing:
cd $YT_DEST/src/yt-hg # or wherever "yt instinfo" tells you, if you have run the install script hg pull -r d996eff https://bitbucket.org/MatthewTurk/yt-3.0 hg up -r d996eff python2.7 setup.py build_ext -i -f
This will update you to that version of the code, and you should now be able to execute this command:
from yt.mods import * ds = load("gadget_filename.hdf5")
Things like projecting and analyzing particles and so on should now work. *Please* let us know if this works for your data, and if so, click on the "approve" button or leave a comment on the pull request:
https://bitbucket.org/yt_analysis/yt-3.0/pull-request/99/implement-gadget-hd...
I think we really only need one more external tester (Desika has tested it) and we can bring it in.
The second thing is about Rockstar. I've been working on a pull request against my fork of Rockstar ( http://bitbucket.org/MatthewTurk/rockstar ) that enables deeper and better yt integration; these changes have been submitted upstream so hopefully I won't need a fork for much longer and we can all go back to tarballs of R*.
I've been testing this in my bookmark "rockstar_work" (which I haven't merged with HDF5-gadget work, sorry!) and I am getting weird results. The process is working, but the halo masses are scaled incorrectly and I am going to be investigating units to figure out the problem. This is actually a regression, as it had previously well, and I will be investigating it in more detail. I hope to have some results shortly.
Let me know if you get a chance to check the Gadget-HDF5, and hopefully by then I'll have the Rockstar stuff up and running!
Okay, it turns out I was wrong and I was looking at unsorted halo masses and wondering why they were all so low-mass. Sorting fixed it. :) I've issued a pull request here, which hopefully we can get incorporated soon. There are still additional things on my Rockstar checklist, for what it's worth. https://bitbucket.org/yt_analysis/yt-3.0/pull-request/105/rockstar-updates/d... -Matt
-Matt
Are there any examples of carrying out such a process? Thanks.
Thanks.
Brendan
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participants (2)
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Brendan Griffen
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Matthew Turk