yt-users January 2020

yt-users@python.org

16 participants
14 discussions

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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Re: Ytini installation for Houdini on Windows
by Ian Woodward 31 Jan '20

31 Jan '20

I've now managed to build OpenVDB (including pyopenvdb) against Houdini in Windows, and I've prepared a guide on how to do this. Here's a link to the guide. Feel free to use and distribute as you see fit. https://www.dropbox.com/s/g1tw2q6hw60xrvt/Adding%20OpenVDB%20to%20Houdini%20 in%20Windows%2010%20ver1.0.pdf?dl=0 From Ian Woodward Interested in snippets about space and science? Try my astrofotato blog at <https://astrofotato.blog/> https://astrofotato.blog

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gap between colorbar and panel
by Huanqing 29 Jan '20

29 Jan '20

Hi, I wonder if there is a simple way to adjust the gap between panel and colorbar? I saw a way here https://yt-project.org/doc/cookbook/complex_plots.html#multi-plot-slice-and… <https://yt-project.org/doc/cookbook/complex_plots.html#multi-plot-slice-and…> which uses .to_frb and then use .imshow to do it, but I guess there should be an easier way? I just want to make some white space between the panel and the colorbar, rather than adjacent to each other as default. Thanks, Huanqing

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SciPy 2020 Call for Submissions is open!
by Melissa Mendonça 29 Jan '20

29 Jan '20

Hello all, Apologies for crossposting. - Melissa Weber Mendonça Scipy 2020 Diversity Committee Co-Chair ===== SciPy 2020, the 19th annual Scientific Computing with Python conference, will be held July 6-12, 2020 in Austin, Texas. The annual SciPy Conference brings together over 900 participants from industry, academia, and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. The call for SciPy 2020 talks, posters, and tutorials is now open through February 11, 2020. Talks and Posters (July 8-10, 2020) In addition to the general track, this year will have the following specialized tracks, mini symposia, and sessions: Tracks High Performance Python Machine Learning and Data Science Mini Symposia Astronomy and Astrophysics Biology and Bioinformatics Earth, Ocean, Geo and Atmospheric Science Materials Science Special Sessions Maintainers Track SciPy Tools Plenary Session For additional details and instructions, please see the conference website. <https://www.scipy2020.scipy.org/> Tutorials (July 6-7, 2020) Tutorials should be focused on covering a well-defined topic in a hands-on manner. We are looking for awesome techniques or packages, helping new or advanced Python programmers develop better or faster scientific applications. We encourage submissions to be designed to allow at least 50% of the time for hands-on exercises even if this means the subject matter needs to be limited. Tutorials will be 4 hours in duration. In your tutorial application, you can indicate what prerequisite skills and knowledge will be needed for your tutorial, and the approximate expected level of knowledge of your students (i.e., beginner, intermediate, advanced). Instructors of accepted tutorials will receive a stipend. For examples of content and format, you can refer to tutorials from past SciPy tutorial sessions (SciPy 2018 <https://na-admin.eventscloud.com/emarketing/go.php?i=735095&e=amlsbGNAZW50a…>, SciPy2019 <https://na-admin.eventscloud.com/emarketing/go.php?i=735095&e=amlsbGNAZW50a…> ) and some accepted submissions <https://na-admin.eventscloud.com/emarketing/go.php?i=735095&e=amlsbGNAZW50a…>. For additional details and instructions see the conference website <https://na-admin.eventscloud.com/emarketing/go.php?i=735095&e=amlsbGNAZW50a…> . Submission page: https://easychair.org/conferences/?conf=scipy2020 Submission Deadline: February 11, 2020

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getting list of halo IDs for particles from HaloCatalog
by romeeld＠gmail.com 28 Jan '20

28 Jan '20

I'm trying to retrieve the list of halo IDs for all particles from a HaloCatalog object. I think it is stored in something like "tags" (if I'm correctly reading yt_astro_analysis/halo_finding/halo_objects.py) but the following did *not* work: from yt.extensions.astro_analysis.halo_analysis.api import HaloCatalog data_ds = yt.load(snapname) hc = HaloCatalog(data_ds=data_ds, finder_method='hop') hc.create() fof_tags = hc.tags The error was: AttributeError: 'HaloCatalog' object has no attribute 'tags' Is it possible to access tags somehow? Or is there another way to get the halo ID list? Thanks.

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Finding the temperature of cell with maximum density
by Stephanie Tonnesen 24 Jan '20

24 Jan '20

Hi all, I feel like this should be relatively straightforward, but I have a lot of rather small clouds that I have identified already. I can get info about them by using their position and then creating a sphere around it. I already have the maximum density and minimum temperature values for these clouds. All I want to do is see if these are the same cell, and if not, what the difference in temp (or density) is. So I know how to find a maximum quantity, but not how to then find values of other variables in that cell. I was thinking that I basically want an array with max density, min temperature, density at min temperature, temperature at max density. So can anyone point me to how to find the temperature of the cell with the highest density in a sphere object? Thanks! Stephanie -- -- Dr. Stephanie Tonnesen Associate Research Scientist CCA, Flatiron Institute New York, NY stonnes(a)gmail.com

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Problem running 'Worked Example of Halo Analysis'
by Hanjue Zhu 24 Jan '20

24 Jan '20

Hi all, I've been trying to run this notebook ( https://yt-project.org/doc/cookbook/halo_analysis_example.html). But I'm getting the following error when I get to hc.create(), where all the analysis is done. I'm not exactly sure what the problem is here. Any idea would be much appreciated. ValueError Traceback (most recent call last) <ipython-input-4-331e023f819c> in <module> * 1* hc.add_callback("save_profiles", storage="virial_profiles", output_dir="profiles") * 2* ----> 3 hc.create() * 4* * 5* halos_ds = yt.load(os.path.join(tmpdir, 'halo_catalog/halo_catalog.0.h5')) /home/xx/yt/analysis_modules/halo_analysis/halo_catalog.py in create(self, save_halos, save_catalog, njobs, dynamic) * 335* * 336* """ --> 337 self._run(save_halos, save_catalog, njobs=njobs, dynamic= dynamic) * 338* * 339* def load(self, save_halos=True, save_catalog=False, njobs=-1, dynamic=False): /home/xx/yt/utilities/parallel_tools/parallel_analysis_interface.py in barrierize(*args, **kwargs) * 299* def barrierize(*args, **kwargs): * 300* if not parallel_capable: --> 301 return func(*args, **kwargs) * 302* mylog.debug("Entering barrier before %s", func.__name__) * 303* comm = _get_comm(args) /home/xx/yt/analysis_modules/halo_analysis/halo_catalog.py in _run(self, save_halos, save_catalog, njobs, dynamic) * 439* for action_type, action in self.actions: * 440* if action_type == "callback": --> 441 action(new_halo) * 442* elif action_type == "filter": * 443* halo_filter = action(new_halo) /home/xx/yt/analysis_modules/halo_analysis/halo_callbacks.py in __call__(self, halo) * 58* * 59* def __call__(self, halo): ---> 60 self.function(halo, *self.args, **self.kwargs) * 61* return True * 62* /home/xx/yt/analysis_modules/halo_analysis/halo_callbacks.py in profile(halo, bin_fields, profile_fields, n_bins, extrema, logs, units, weight_field, accumulation, fractional, storage, output_dir) * 229* my_profile = create_profile(halo.data_object, bin_fields, profile_fields, n_bins=n_bins, * 230* extrema=extrema, logs=logs, units= units, weight_field=weight_field, --> 231 accumulation=accumulation, fractional=fractional) * 232* * 233* prof_store = dict([(field, my_profile[field]) \ /home/xx/yt/data_objects/profiles.py in create_profile(data_source, bin_fields, fields, n_bins, extrema, logs, units, weight_field, accumulation, fractional, deposition, override_bins) * 1205* setattr(obj, "fractional", fractional) * 1206* if fields is not None: -> 1207 obj.add_fields([field for field in fields]) * 1208* for field in fields: * 1209* if fractional: /home/xx/yt/data_objects/profiles.py in add_fields(self, fields) * 127* citer = self.data_source.chunks([], "io") * 128* for chunk in parallel_objects(citer): --> 129 self._bin_chunk(chunk, fields, temp_storage) * 130* self._finalize_storage(fields, temp_storage) * 131* /home/xx/yt/data_objects/profiles.py in _bin_chunk(self, chunk, fields, storage) * 496* fdata, wdata, (bf_x,) = rv * 497* bf_x.convert_to_units(self.field_info[self.x_field]. output_units) --> 498 bin_ind = np.digitize(bf_x, self.x_bins) - 1 * 499* new_bin_profile1d(bin_ind, wdata, fdata, * 500* storage.weight_values, storage.values, /data/xx/soft/anaconda3/lib/python3.7/site-packages/numpy/lib/function_base.py in digitize(x, bins, right) * 4799* mono = _monotonicity(bins) * 4800* if mono == 0: -> 4801 raise ValueError("bins must be monotonically increasing or decreasing") * 4802* * 4803* # this is backwards because the arguments below are swapped ValueError: bins must be monotonically increasing or decreasing Many thanks, Hanjue

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yAC: yt at the CCA
by Michael Zingale 24 Jan '20

24 Jan '20

Dear all, Registration is open for the upcoming "yAC: yt at CCA" workshop, to take place at the Flatiron Institute from Monday March 23rd through Wednesday March 25th: https://forms.gle/56bmuYKcX5NCDF5aA This workshop will introduce the yt visualization and analysis tool ( https://yt-project.org/), provide tutorials and example workflows, and time to interact with the developers. Additionally, there will be ample free time for practice and hacking in the afternoons. Participation is limited to ~40, so please register early if you are interested. More details and a schedule will come in a few weeks. local organizers: Stephanie Tonnesen Michael Zingale -- Michael Zingale Associate Professor Dept. of Physics & Astronomy • Stony Brook University • Stony Brook, NY 11794-3800 *phone*: 631-632-8225 *e-mail*: Michael.Zingale(a)stonybrook.edu *web*: http://www.astro.sunysb.edu/mzingale github: http://github.com/zingale

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yt-users January 2020