Mailman 3 February 2020 - yt-users

Porting .ply files to Blender with colors?
by Jill P. Naiman 15 Aug '22

15 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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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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Question about Projection Plot Color Coding
by sflarkin＠ucsc.edu 12 Jul '20

12 Jul '20

Hello All, I have a question about the Projection plot function in yt. I have a script that plots the smallest mass darkmatter particles of a simulation in all 3 of the 2-d coordinate projections, and overplots the halos found by a halo finder. This script works, and currently plots the colorbar based on the mass in a given 2-d bin as done in some of the basic yt plots included in the website. I am wondering if it is possible to have the color scheme of the particles be based on the squared mass or squared density of the particles in any given 2-d bin, so that the higher density regions are highlighted compared to the background lower density regions. I have included the plotting part of my script below, in case it is helpful. I hope everyone is having a great New Year! ds = yt.load(VELA_snaps[position[0]]) domain_width = float(ds.domain_width.in_units('Mpc/h')[0]) ad = ds.all_data() masses = yt.np.unique(ad[('darkmatter', 'particle_mass')]) #filter out the darkmatter0 particles def mass_filter(pfilter, data): filter = data[(pfilter.filtered_type, 'particle_mass')] == masses[0] return filter yt.add_particle_filter('darkmatter0', function=mass_filter, filtered_type='darkmatter', requires=['particle_mass']) ds.add_particle_filter('darkmatter0') scale = float(ds.scale_factor) fig = plt.figure() grid = AxesGrid(fig, (0.075,0.075,10,5), nrows_ncols = (3, 1), axes_pad = 1.0, label_mode = "L", share_all = False, cbar_location="right", cbar_mode="each", cbar_size="3%", cbar_pad="0%") zoom = 10 x0 = float(consistent.halo_data_sorted[index][0][17]) * scale / domain_width y0 = float(consistent.halo_data_sorted[index][0][18]) * scale / domain_width z0 = float(consistent.halo_data_sorted[index][0][19]) * scale / domain_width center = [x0, y0, z0] a = yt.ParticlePlot(ds, ('darkmatter0', 'particle_position_x'), ('darkmatter0', 'particle_position_y'),\ ('darkmatter0', 'particle_mass'), center=center) a.set_unit(('darkmatter0','particle_mass'), 'Msun') a.zoom(zoom) b = yt.ParticlePlot(ds, ('darkmatter0', 'particle_position_y'), ('darkmatter0', 'particle_position_z'),\ ('darkmatter0', 'particle_mass'), center=center) b.set_unit(('darkmatter0','particle_mass'), 'Msun') b.zoom(zoom) c = yt.ParticlePlot(ds, ('darkmatter0', 'particle_position_z'), ('darkmatter0', 'particle_position_x'),\ ('darkmatter0', 'particle_mass'), center=center) c.set_unit(('darkmatter0','particle_mass'), 'Msun') c.zoom(zoom) for halos in consistent.halo_data_sorted[index]: x = float(halos[17]) * scale / domain_width y = float(halos[18]) * scale / domain_width z = float(halos[19]) * scale / domain_width r = float(halos[11]) * scale / .7 center = [x, y, z] a.annotate_sphere(center, radius=(r, 'kpc'), circle_args={'color':'red'}) b.annotate_sphere(center, radius=(r, 'kpc'), circle_args={'color':'red'}) c.annotate_sphere(center, radius=(r, 'kpc'), circle_args={'color':'red'}) index = 0 for letter in [a,b,c]: plot = letter.plots[('darkmatter0', 'particle_mass')] plot.figure = fig plot.axes = grid[index].axes plot.cax = grid.cbar_axes[index] letter._setup_plots() index = index + 1 plt.savefig('{}/CatalogProjectionYT_VELA{}_Scale{}.png'.format(out_dir, VELA_number, str(scale)[2:5]), bbox_inches='tight') plt.close()

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Variance in phase/profiles
by david collins 11 Apr '20

11 Apr '20

Hi, Everybody! Does anyone out there have a technique for getting the variance out of a profile object? A profile object is good at getting <X> vs. B, I'd then like to get < (X - <X>)^2 > vs B. Matt and I had spittballed the possibility some time ago, but I was wondering if anyone out there had successfully done it. Thanks, d. -- Sent from my computer.

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[JOB] full-time yt development
by Matthew Turk 27 Feb '20

27 Feb '20

Hi folks, I'm writing with an update about a previous email I sent a while ago: https://mail.python.org/archives/list/yt-users@python.org/thread/3LKFCHKZXJ… At the University of Illinois, we're looking to hire a visiting research scientist to work full-time on yt and yt-related projects. This position *can* be remote, and the expected salary will be at or above $65k (plus benefits). I also want to note that this position will certainly involve engagement beyond yt's traditional applications in astronomy! The job posting is here -- we extended the search, and it will now close on March 15, with a flexible start date that could be as soon as April. https://jobs.illinois.edu/academic-job-board/job-details?jobID=123477&job=v… This job would be to work on the underlying infrastructure of yt, and would present opportunities to familiarize yourself with some other components of the modern data science ecosystem and the pydata stack, including things like dask, xarray and so forth. I think that this position may be particularly interesting to individuals looking to transition to industry, as well as those who are interested in pursuing jobs in academia that are more focused on research software. This job is posted as part of the School of Information Sciences, but it's within a research group that spans the National Center for Supercomputing Applications (NCSA), the Astronomy department, the Institute for Genomic Biology and other groups and institutes on campus. This position will also provide ample opportunities for interdisciplinary work with academics, the open source scientific software ecosystem (SciPy, PyData, etc) and for travel and professional development. You'd get to work with folks involved in yt and you'd get to have a hand in developing and designing some really fun tools for data analysis and visualization. (*And* we have an annual sweetcorn festival in Urbana -- $1/cob!) Please do reach out to let me know if you have any questions about the opportunity, and if you know anyone you think might be interested, it would be very helpful if you could pass this information along to them. Thanks, Matt

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gigabit managed switches
by brainharry12＠gmail.com 27 Feb '20

27 Feb '20

When designing a network, a network switch is effectively its core, or its “brain”. It’s networking hardware that connects all devices together on a LAN (Local Area Network), redirecting and forwarding data to the correct destination. When running a business, it’s important to ensure that you have a network switch that helps you effectively cover the needs of your entire IT scope. Switches come in various sizes that allow them to have any number of ports up to 48, but the differences go deeper than that when it comes to managed switches and unmanaged switches. Here, we’re going to define the two types, look at the differences between them, and help you decide which is right for you. <a ahref="https://extnoc.com/managed-switch-services">gigabit managed switches</a> The Differences Between Managed and Unmanaged Network Switches On a basic level, an unmanaged switch allows you to immediately plug-and-play devices into your network, while a managed switch allows for greater control over it. However, the differences go deeper, so it’s time to look at the features, performance, security, cost, and application of each.

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by Java by Kiran digital 18 Feb '20

18 Feb '20

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volume rendering north_vector problems
by Stephanie Tonnesen 10 Feb '20

10 Feb '20

Hi all, I am having trouble with using north_vector--basically it is doing nothing as I am writing it. As far as I can tell there are a few ways I can call camera, and I am doing this: scall = yt.create_scene(ds) source_all = scall[0] source_all.set_field('density') source_all.set_log(True) #cam = scall.add_camera() scall.camera.set_width(ds.quan(80,'kpc')) scall.camera.position = ds.arr([0.5,1.0,0.3],'unitary') scall.camera.focus = ds.arr([0.5,0.5,0.36],'unitary') scall.camera.north_vector = ds.arr([0.0,0.0,1.0],'unitary') scall.camera.resolution = (2048,2048) What I want is a nearly edge-on view of a disk in the x-y plane where the disk is aligned on the x-y plane (horizontal) and instead I get the picture below. I have run this with the north_vector line commented out, with it as ds.arr([1.0,0.0,0.0],'unitary') and as np.array([0.0,0.0,1.0]) and always get the same image. Any help is always appreciated!! Thanks in advance, Stephanie [image: image.png] -- Dr. Stephanie Tonnesen Associate Research Scientist CCA, Flatiron Institute New York, NY stonnes(a)gmail.com

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yt - sunrise_exporter
by Santi Roca Fabrega 08 Feb '20

08 Feb '20

Dear yt users, I am writing to you to know if somebody is using the sunrise_exporter to convert ART or RAMSES snapshots to sunrise. I have tried to update it but I found a problem I have not been able to solve by now. The problem is that sunrise_exporter needs of a "index.grids" object that is not defined in the ART or RAMSES frontends. It is defined in the enzo and ytdata frontends but I have not succedeed on exporting it to ART or RAMSES. Has somebody tried it? I would really appreciate any help you can provide me. Have a nice weekend. Best regrads. Santi -- Santi Roca-Fabrega Office 231, Plaza de las Ciencias, 1 Departamento de Física de la Tierra y Astrofísica Facultad de Ciencias Físicas, Universidad Complutense de Madrid E-28040, Madrid, Spain Phone: +34 658310823

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