Hi Nick, Sure. When rockstar is run on a time series, it holds the halos from the previous snapshot in memory so that it can do the ancestor/descendent linking right then and there. I believe this calculation is the standard check for a certain fraction of particles in common. This is saved to the out_*.list files in the desc_id column. When you load these files with ytree, it is just this information that's used to construct the merger tree. If you run consistent-trees, it does some additional calculation that is described in the method paper <https://arxiv.org/abs/1110.4370>. The resulting tree_0_0_0.dat file can also be read in with ytree. In practice, the resulting merger trees are pretty similar, though not exactly the same. Britton On Tue, Nov 27, 2018 at 9:48 AM Nick Gnedin <ngnedin@gmail.com> wrote:
Britton,
Thank you very much for the instructions, Rockstar seems to work well with a time series dataset.
Could you briefly tell me what the difference is between the two methods for building merger trees: (1) using consistent-trees and (2) using ytree directrly with ytree.load("out_0.list")? What would ytree use for making a merger tree?
n
On 11/25/18 12:02 PM, Britton Smith wrote:
Hi Nick,
Sorry for the long delay. Lots of travel this past week.
After reading through this discussion, I have two comments that might help.
First, to get rockstar to run on multiple datasets, you need to create a time series object and pass that directly to the RockstarHaloFinder. For example,
import yt yt.enable_parallelism() from yt.extensions.astro_analysis.halo_finding.rockstar.api import \ RockstarHaloFinder ts = yt.DatasetSeries(LIST_OF_FILES) rh = RockstarHaloFinder(ts, num_readers=1, num_writers=1) rh.run()
Note, I'm using the yt_astro_analysis < https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_yt-2Dproject_yt-5Fastro-5Fanalysis&d=DwMFaQ&c=gRgGjJ3BkIsb5y6s49QqsA&r=7jSLZBQB_2gqGQ3elA922w&m=VCOGCUxD8zIs3t0HFBFdetwrsVzzIJzgtUBDeEttg5I&s=BYY0g4bFBZeqUNzHuGG96I5PZ1ySNDSw8E4l4Z8YkNg&e=> package,
where all these tools have now moved for future development. I think the installation docs are also a bit clearer there. The halo finding part of the documentation definitely needs improvement. I'll try to do this within yt_astro_analysis docs < https://urldefense.proofpoint.com/v2/url?u=https-3A__yt-2Dastro-2Danalysis.readthedocs.io_en_latest_&d=DwMFaQ&c=gRgGjJ3BkIsb5y6s49QqsA&r=7jSLZBQB_2gqGQ3elA922w&m=VCOGCUxD8zIs3t0HFBFdetwrsVzzIJzgtUBDeEttg5I&s=6F-7Ybkvz3NE9EhlNZmSkDl2EeD4BcBHn7hlmphAYXU&e= .
Second, if you've now got all of the rockstar catalogs and don't want to use consistent-trees, what you'll need are the out_*.list files that get made. There will be one for each snapshot. You should find these within the rockstar_halos directory. If you have those, you can feed the first one, usually out_0.list, straight to ytree and it will assemble the merger trees. import ytree a = ytree.load("out_0.list")
Britton
On Wed, Nov 21, 2018 at 11:43 AM Nick Gnedin <gnedin@fnal.gov <mailto:gnedin@fnal.gov>> wrote:
Britton,
I am still confused about making merger trees with yt. I ran rockstar on my snapshots, but the ytree doc page says it is only able to make trees from Gadget FoF/Subfind halo finders.
I could use Consistent Trees, but it needs halo catalogs in rockstar native format, not in h5 format that is produced by yt.
Nick
On 10/5/2018 12:06 PM, Britton Smith wrote: > HI Nick, > > Sadly, yt's FoF and HOP finders don't output member particle information > for the halos, so it might not be possible to use those catalogs to make > merger trees. ytree's merger-tree creation works with FoF catalogs > generated by the inline Gadget halo finder, for which yt supports > extracting member particle information. If you're looking to make > merger-trees, the best route currently is probably > Rockstar/consistent-trees, the outputs of which can be loaded by ytree. > > It is probably a week's worth of work to fix up yt's HOP/FoF finders to > output particle information and then to add support for loading that > into yt. > > Britton > > On Fri, Oct 5, 2018 at 6:07 AM Nick Gnedin <gnedin@fnal.gov <mailto:gnedin@fnal.gov> > <mailto:gnedin@fnal.gov <mailto:gnedin@fnal.gov>>> wrote: > > > Folks, > > I am confused about how to compute merger trees with yt. Documentation > ( https://yt-project.org/doc/analyzing/analysis_modules/halo_merger_tree.html?... < https://urldefense.proofpoint.com/v2/url?u=https-3A__yt-2Dproject.org_doc_analyzing_analysis-5Fmodules_halo-5Fmerger-5Ftree.html-3Fhighlight-3Dmerger-2520tree&d=DwMFaQ&c=gRgGjJ3BkIsb5y6s49QqsA&r=7jSLZBQB_2gqGQ3elA922w&m=VCOGCUxD8zIs3t0HFBFdetwrsVzzIJzgtUBDeEttg5I&s=46GdRUpxGU2O0bccp_ySM0KnbxeBA38Oe2eHkqLSMMI&e=
> < https://urldefense.proofpoint.com/v2/url?u=https-3A__yt-2Dproject.org_doc_analyzing_analysis-5Fmodules_halo-5Fmerger-5Ftree.html-3Fhighlight-3Dmerger-2520tree&d=DwMFaQ&c=gRgGjJ3BkIsb5y6s49QqsA&r=7jSLZBQB_2gqGQ3elA922w&m=zeRRll5QvyPrOQIZHiEPcx7nJk84AGxCHVY_xIV4OZ8&s=JcesVppFFSFwh2Hj4CdmDhGC6m2PJwj6igNfcC-vblA&e= ) > > refers to ytree package, but that package documentation seems to > indicate that only FoF or Subfind halo catalogs can be converted into a > merger tree, while the halo finder in yt is HOP. > > I have run HOP for several snapshots from a simulation. What would you > recommend to use to make a merger tree from such a data set? > > Thank you, > > Nick Gnedin > > _______________________________________________ > yt-users mailing list -- yt-users@python.org <mailto:yt-users@python.org> > <mailto:yt-users@python.org <mailto:yt-users@python.org>> > To unsubscribe send an email to yt-users-leave@python.org <mailto:yt-users-leave@python.org> > <mailto:yt-users-leave@python.org <mailto:yt-users-leave@python.org>> > > > < http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=emailclient < https://urldefense.proofpoint.com/v2/url?u=http-3A__www.avg.com_email-2Dsignature-3Futm-5Fmedium-3Demail-26utm-5Fsource-3Dlink-26utm-5Fcampaign-3Dsig-2Demail-26utm-5Fcontent-3Demailclient&d=DwMFaQ&c=gRgGjJ3BkIsb5y6s49QqsA&r=7jSLZBQB_2gqGQ3elA922w&m=VCOGCUxD8zIs3t0HFBFdetwrsVzzIJzgtUBDeEttg5I&s=O4EelBoBxjAvpqC7GLS2Y9rlC_soWJE4c4PI8x3m39I&e=
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