Mailman 3 August 2021 - yt-users

enzo-mrp-music/get_halo_initial_extent.py not working with yt 4.0.1
by C Bernhardt 02 Jun '23

02 Jun '23

Dear yt users, I just updated yt to 4.0.1 and now I get this error message when trying to run enzo-mrp-music.py from John Wise on https://github.com/jwise77/enzo-mrp-music. Traceback (most recent call last): File "enzo-mrp-music/enzo-mrp-music.py", line 264, in <module> params = find_lagrangian_region(params) File "enzo-mrp-music/enzo-mrp-music.py", line 177, in find_lagrangian_region get_center_and_extent(params["halo_info"], File "enzo-mrp-music/get_halo_initial_extent.py", line 147, in get_center_and_extent halo_indices, halo_com, shifted = get_halo_indices(my_halo, final_dataset, File "enzo-mrp-music/get_halo_initial_extent.py", line 119, in get_halo_indices get_halo_sphere_particles(my_halo, dataset, radius_factor=radius_factor) File "enzo-mrp-music/get_halo_initial_extent.py", line 73, in get_halo_sphere_particles my_sphere = pf.h.sphere(my_halo_data['center'], radius_factor * r_200) AttributeError: 'EnzoDataset' object has no attribute 'h' I am honestly not sure what the attribute 'h' does in this case, so I didn't know what to try to adjust. Any suggestions for getting around this? Or how can I go back to yt 3? Kind regards, -- Carla Bernhardt PhD Student Universität Heidelberg ZAH Institut für Theoretische Astrophysik

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Porting .ply files to Blender with colors?
by Jill P. Naiman 14 Aug '22

14 Aug '22

Hi All, I was curious if anyone has had any luck porting .ply files generated with yt into Blender with colors? It seems to port in the surfaces just fine, but they are a uniform color. From what I can gather, Blender imports .ply files with face color instead of vertex so I tried the surf.export_ply routine with "face" instead of "vertex" for sample_type, but no luck ("vertex" doesn't work either). Let me know if I can provide any more useful info. Thanks for any help, -J

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Clump Finding for Gadget2 format
by 201s408s＠stu.kobe-u.ac.jp 21 Feb '22

21 Feb '22

Dear all, For my master's research, I installed yt and I want to load my research data converted to gadget2 format with yt. The function I want to use is the clump function, and I want to create a similar figure by performing the same processing as the Clump Finding below. https://yt-project.org/doc/cookbook/constructing_data_objects.html#cookbook… First of all, I tried to test with the gadget data placed in the data index, but neither the default nor the hdf5 format works. Is it possible to do Clump Finding in Gadget2 format?

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Stars on volume rendering
by Elizabeth Harper-Clark 11 Dec '21

11 Dec '21

Hi all, Thanks for all your help over the last couple of days. One more question: - Can I plot particles on a volume rendered image? I have stars and I want to show where they are! Thanks, Libby -- Elizabeth Harper-Clark MA MSci PhD Candidate, Canadian Institute for Theoretical Astrophysics, UofT Sciences and Engineering Coordinator, Teaching Assistants' Training Program, UofT www.astro.utoronto.ca/~h-clark <http://www.astro.utoronto.ca/%7Eh-clark> h-clark(a)cita.utoronto.ca Astronomy office phone: +1-416-978-5759

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yt_astro_analysis
by Roya Hamedani Golshan 31 Aug '21

31 Aug '21

Dear yt-user members, I am writing to you in connection with yt_astro_analysis package. I would like to use this package to visualize my ALMA data cubes to look into the volume structures from a 3-d point of view. However, I can not step forward since yt package is unhappy about the fits file header and raise error. I tried both directly with yt package and also transforming the fits file to yt object via SpectralCube package. I would appreciate if you comment on what the problem is. Here are the two efforts: loading the dataset via yt package: ds = yt.load(fits_file, suppress_astropy_warnings = True) ds.print_stats() the last line raises the error1, attached here. And loading the dataset via SpectralCube transformation: cube = SpectralCube.read(fits_file, format='fits') ytcube = cube.to_yt(spectral_factor=0.5) ds = ytcube.dataset this gives the error2, in the attachment. Thanks in advance, With regards, Roya -- Roya Hamedani Golshan PhD Candidate --------------------------------------------------------------------- I. Physikalisches Institut, Universität zu Köln, Zülpicher Strasse 77, 50937 Cologne, Germany Office: Gebäude (Building) 312, Room 1.10 Phone: +49 (0)2214703485 e-mail: rhgolshan(a)ph1.uni-koeln.de

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ANN: ytree 3.1 released
by Britton Smith 30 Aug '21

30 Aug '21

Hello again! I am very pleased to announce the release of ytree version 3.1! ytree is an extension of yt for analyzing merger trees. This is the second major release this month, but the last for a while as the summer draws to a close. The 3.1 release includes two fun new features. - the addition of parallel iterator functions for processing trees and nodes in parallel. - the addition of the AnalysisPipeline, a framework for creating advanced analysis workflows. ytree can be installed with pip: pip install ytree Full documentation can be found at https://ytree.readthedocs.io/ Thanks as always to the fantastic yt community. Enjoy the rest of the summer. Britton

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Creating a sequence of volume renders of the enzo test problem: amr_simulation
by Ian Woodward 27 Aug '21

27 Aug '21

I've just recently compiled enzo with grackle and run the enzo test problem: amr_cosmology. I've loaded the results using: ts = yt.load("/home/ian/enzo-grackle/run/CosmologySimulation/amr_cosmology/DD*/DD*") Inspecting ts, I see that it is a DatasetSeries object, with outputs: [DD0000, DD0000.boundary, DD0000.boundary.hdf, DD0000.configure, DD0000.cpu0000, DD0000.hierarchy, DD0000.memorymap, DD0001, DD0001.boundary, DD0001.boundary.hdf, DD0001.configure, DD0001.cpu0000, DD0001.hierarchy, DD0001.memorymap, DD0002, DD0002.boundary, DD0002.boundary.hdf, DD0002.configure, DD0002.cpu0000, DD0002.hierarchy, DD0002.memorymap, etc] As a first step in learning how to work with DatasetSeries, I'd like to generate a sequence of volume renders of density for each DD step. I presume that this will require me to access DD0000, DD0001, DD0002...etc sequentially inside a loop or iteration, while skipping the intervening DD.boundary, DD.boundary.hdf, DD.configure, DD.cpu0000, DD.hierarchy and DD.memorymap outputs at each step. I'm struggling to work out how to do this. Is anyone able to help me with a line or so of code to show me the way? Thanks Ian

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symlog and set_zlim not working in yt-4.0.1
by mogrodnik＠umk.pl 27 Aug '21

27 Aug '21

Hi, I'd like to illustrate few fields (e.g. velocity, velocity divergence) in dataset in logarythmic or symlog scale, for this I am using SlicePlot class. These fields contain negative ranges of which I am aware and in which case I gladly use yt and it's easy symlog switch. The problem appears however, if one tries to append zlim of given SlicePlot and sets the scale to log. If one wants to reproduce the problem, here's an example, using available sample data from piernik (sedov, I got it here https://yt-project.org/data/sedov_tst_0004.tar.gz and unpacked in /tmp): sd = yt.load("/tmp/sedov/sedov_tst_0004.h5") field = ('gdf','mag_field_x') p = yt.SlicePlot(sd, "x", field) # The below will work p.set_log(field, True) p.save(sedov_tst_0004_Slice_x_velocity_z-log.png) # But the below will result in error: p.set_zlim(field,-650.,650.) p.set_log(field, True) p.save('sedov_tst_0004_Slice_x_velocity_z-log2.png') Error is raised by matplotlibs' colors.py module, as it is getting 'nan' as lower limit. Has anyone encountered this problem? Thanks, mao

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Replicating Enzo test problem output in jupyter notebook
by Ian Woodward 19 Aug '21

19 Aug '21

I've built Enzo in ubuntu and I've successfully run the first test problem in terminal mode and also used $ yt plot DD0000/DD0000 in the terminal to generate the output slice plots, as per the enzo guide. I'm trying to replicate the slice plotting in a jupyter notebook. When I try to load the DD data using ds = yt.load('/home/ian/enzo-dev/run/Hydro/Hydro-3D/CollapseTestNonCosmological/DD0000') I get the error YTUnidentifiedDataType: Could not determine input format from /home/ian/enzo-dev/run/Hydro/Hydro-3D/CollapseTestNonCosmological/DD0000' By looking at the CollapseTestNonCosmological.enzo file, I see that the data is an AMR format. I therefore tried to load it using ds = yt.load_amr_grids('/home/ian/enzo-dev/run/Hydro/Hydro-3D/CollapseTestNonCosmological/DD0000') but this failed because it was missing the domain_dimensions argument. I think this means it needs to have grid_data added as the first argument: ds = yt.load_amr_grids(grid_data, '/home/ian/enzo-dev/run/Hydro/Hydro-3D/CollapseTestNonCosmological/DD0000') I can try and work out how to define the grid_data but I don't understand why doing so wasn't necessary when I simply ran $ yt plot DD0000/DD0000 in terminal mode. Does yt plot extract the domain_dimensions automatically from the outputs, and if so is there an easy way of doing this in jupyter's yt.load_amr_grids, without having to manually set up grid_data?

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Replicating Enzo test problem output in jupyter notebook
by Ian Woodward 19 Aug '21

19 Aug '21

I've built Enzo in ubuntu and I've successfully run the first test problem in terminal mode and also used $ yt plot DD0000/DD0000 in the terminal to generate the output slice plots, as per the enzo guide. I'm trying to replicate the slice plotting in a jupyter notebook. When I try to load the DD data using ds = yt.load('/home/ian/enzo-dev/run/Hydro/Hydro-3D/CollapseTestNonCosmological/DD0000') I get the error YTUnidentifiedDataType: Could not determine input format from /home/ian/enzo-dev/run/Hydro/Hydro-3D/CollapseTestNonCosmological/DD0000' By looking at the CollapseTestNonCosmological.enzo file, I see that the data is an AMR format. I therefore tried to load it using ds = yt.load_amr_grids('/home/ian/enzo-dev/run/Hydro/Hydro-3D/CollapseTestNonCosmological/DD0000') but this failed because it was missing the domain_dimensions argument. I think this means it needs to have grid_data added as the first argument: ds = yt.load_amr_grids(grid_data, '/home/ian/enzo-dev/run/Hydro/Hydro-3D/CollapseTestNonCosmological/DD0000') I can try and work out how to define the grid_data but I don't understand why doing so wasn't necessary when I simply ran $ yt plot DD0000/DD0000 in terminal mode. Does yt plot extract the domain_dimensions automatically from the outputs, and if so is there an easy way of doing this in jupyter's yt.load_amr_grids, without having to manually set up grid_data?

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