Mailman 3 May 2020 - yt-users

Porting .ply files to Blender with colors?
by Jill P. Naiman Aug. 15, 2022

Aug. 15, 2022

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 Dec. 11, 2021

Dec. 11, 2021

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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comoving scale annotation?
by Salome Mtchedlidze Dec. 5, 2020

Dec. 5, 2020

Hello again, I am using yt slices and projections with scale annotation. I have my plots in comoving units ("Mpccm/h") but whenever I want to use the same units for annotation: slc.annotate_scale(corner='lower_right', coeff=10, units='Mpccm/h'), yt does not recognize these units. Am I missing something or only the physical scale annotation is possible ? Thanks, Salome

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Question about Projection Plot Color Coding
by sflarkin＠ucsc.edu July 12, 2020

July 12, 2020

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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Reminder: June 01 Deadline for the 2020 John Hunter Excellence in Plotting contest!
by Madicken Munk June 1, 2020

June 1, 2020

Dear yt-users and yt-dev, My apologies for repeated in-list and cross-list posts! I'd like to remind everybody that the 2020 John Hunter Excellence in Plotting Contest submission deadline is on June 01 -- only a few days away. We welcome and look forward to your submissions! In memory of John Hunter, we are pleased to announce the John Hunter Excellence in Plotting Contest for 2020. This open competition aims to highlight the importance of data visualization to scientific progress and showcase the capabilities of open source software. Participants are invited to submit scientific plots to be judged by a panel. The winning entries will be announced and displayed at SciPy 2020 or announced in the John Hunter Excellence in Plotting Contest website and youtube channel. John Hunter’s family are graciously sponsoring cash prizes for the winners in the following amounts: - 1st prize: $1000 - 2nd prize: $750 - 3rd prize: $500 - Entries must be submitted by June 1st to the form at https://forms.gle/SrexmkDwiAmDc7ej7 - Winners will be announced at Scipy 2020 or publicly on the John Hunter Excellence in Plotting Contest website and youtube channel - Participants do not need to attend the Scipy conference. - Entries may take the definition of “visualization” rather broadly. Entries may be, for example, a traditional printed plot, an interactive visualization for the web, a dashboard, or an animation. - Source code for the plot must be provided, in the form of Python code and/or a Jupyter notebook, along with a rendering of the plot in a widely used format. The rendering may be, for example, PDF for print, standalone HTML and Javascript for an interactive plot, or MPEG-4 for a video. If the original data can not be shared for reasons of size or licensing, "fake" data may be substituted, along with an image of the plot using real data. - Each entry must include a 300-500 word abstract describing the plot and its importance for a general scientific audience. - Entries will be judged on their clarity, innovation and aesthetics, but most importantly for their effectiveness in communicating a real-world problem. Entrants are encouraged to submit plots that were used during the course of research or work, rather than merely being hypothetical. - SciPy and the John Hunter Excellence in Plotting Contest organizers reserves the right to display any and all entries, whether prize-winning or not, at the conference, use in any materials or on its website, with attribution to the original author(s). - Past entries can be found at https://jhepc.github.io/ - Questions regarding the contest can be sent to jhepc.organizers(a)gmail.com John Hunter Excellence in Plotting Contest Co-Chairs Madicken Munk Nelle Varoquaux

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magnetic fields with particle data
by Siegfried Vanaverbeke May 28, 2020

May 28, 2020

All, I have output from an SPH code including magnetic fields for each particle. I see there are no specific fields for MHD data related to particles. For example, I have data = { 'particle_position_x': pos_x, 'particle_position_y': pos_y, 'particle_position_z': pos_z, 'particle_mass': pmass, 'particle_velocity_x': v_x, 'particle_velocity_y': v_y, 'particle_velocity_z': v_z, 'magnetic_field_x':b_x, 'magnetic_field_y':b_y, 'magnetic_field_z':b_z, 'magnetic_field_divergence': eb, 'smoothing_length': h, 'density': rho, 'temperature': Tgas, 'magnetic_field_magnitude': bmag } and then want to plot mag = yt.SlicePlot(ds, 'z', ('gas', 'magnetic_field_divergence'),width=(6.0,'pc')) But 'magnetic_field_x' is not known for particle data, so yt gives an error message. Is there a way to circumvent the problem ? Siegfried

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Saving and Reloading Data Objects in yt
by fushstep＠msu.edu May 26, 2020

May 26, 2020

Hello everyone, I am working with cosmological simulations and I am trying to make use of the ability to save spatial plots as datasets. I am running into an issue after reloading the data when I try to center the plot on a specific halo. When I specify the center in the yt.ProjectionPlot function after reading in the .h5 file, if I print the center of the projection it returns "[0.5,0.5]", which is the center of the simulation not the center I specified. I am confused why this doesn't work because creating the same plot without saving and reloading data results in a projection with the correct center. The script I am using is below: import yt import numpy as np #load in the simulation ds = yt.load('/mnt/research/galaxies-REU/sims/cosmological/set1_LR/halo_008508/RD0032/RD0032') center = [0.4915,0.478,0.5066] # Creating the projection from the dataset proj = ds.proj('density','x',weight_field=None) #Saving projection as a dataset fn = proj.save_as_dataset() # Making a regular projection plot to compare to plot = yt.ProjectionPlot(ds,'x','density',center=center,width=(2,'Mpc'),weight_field='density') plot.save('projection_from_ProjectionPlot.png') # Print the center for the Projection Plot print('\n\n',plot.center,'\n\n') # Load in the saved object from before new_plot = yt.load(fn) #Make a new projection plot from the loaded in saved dataset new_proj = yt.ProjectionPlot(new_plot,'x','density',center=center,width=(2,'Mpc'),weight_field='density') new_proj.save('projection_from_ds_proj.png') #Print the center of the new projection plot print('\n\n',new_proj.center,'\n\n') This script will save two plots, one will be made from the saved and reloaded data and the other will be just from yt.ProjectionPlot. It will also print the center for the projection after saving and loading the data (which seems to always be [0.5,0.5]) and the center for the normal projection (which will always be [0.478,0.5066]). By comparing the two plots that it saves, the "projection_from_ProjectionPlot.png" image is centered on the correct halo, while the "projection_from_ds_proj.png" is centered on the center of the simulation and not the correct halo. I have tried specifying the center in the "ds.proj" arguments to no avail, and I have tried specifying the center in "ds.proj" and not setting it in yt.ProjectionPlot for the saved data and this did not work either. Any help would be much appreciated! Thank you, Trevor Fush

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How to assign variable fig for animation function with yt.create_scene
by henri petit May 25, 2020

May 25, 2020

I want to make an animation of multiple plots whose rendering evolves in time. The files that I need are under the format, for example for one : `DD0043/DD0043`. So I use the trick : `f'{43:04}'` to fill the zeros leading for each file (the files go from `DD0000/DD0000` to `DD0922/DD0922`. Here the script, warning, the plot is done with `yt-project` tool : import yt import os, sys import numpy as np from matplotlib.animation import FuncAnimation from matplotlib import rc_context from matplotlib import pyplot as plt # animate must accept an integer frame number. We use the frame number # to identify which dataset in the time series we want to load def animate(i): plot._switch_ds(array_data[i]) # Number of files numFiles = os.system('ls -dl DD* | wc -l') # Array for each data directory array_data = np.array(numFiles) for i in range(numFiles): data = yt.load('DD'+str(f'{i:04}')+'/DD'+str(f'{i:04}')) sc = yt.create_scene(data, lens_type='perspective') source = sc[0] source.set_field('density') source.set_log(True) # Set up the camera parameters: focus, width, resolution, and image orientation sc.camera.focus = ds.domain_center sc.camera.resolution = 1024 sc.camera.north_vector = [0, 0, 1] sc.camera.position = [1.7, 1.7, 1.7] # You may need to adjust the alpha values to get an image with good contrast. # For the annotate_domain call, the fourth value in the color tuple is the # alpha value. sc.annotate_axes(alpha=.02) sc.annotate_domain(ds, color=[1, 1, 1, .01]) text_string = "T = {} Gyr".format(float(array_data[i].current_time.to ('Gyr'))) fig = plt.figure() animation = FuncAnimation(fig, animate, frames=numFiles) # Override matplotlib's defaults to get a nicer looking font with rc_context({'mathtext.fontset': 'stix'}): animation.save('animation.mp4') But at the execution, I get the following error : 923 Traceback (most recent call last): File "vol-annotated.py", line 52, in <module> animation.save('animation.mp4') File "/Users/fab/Library/Python/3.7/lib/python/site-packages/matplotlib/animation.py", line 1135, in save anim._init_draw() File "/Users/fab/Library/Python/3.7/lib/python/site-packages/matplotlib/animation.py", line 1743, in _init_draw self._draw_frame(next(self.new_frame_seq())) StopIteration I don't know if I do the things correctly, especially for the variable `fig` that I initialize with : fig = plt.figure() Actually, I am trying to adapt to my case this script which creates a movie : i.e : import yt from matplotlib.animation import FuncAnimation from matplotlib import rc_context ts = yt.load('GasSloshingLowRes/sloshing_low_res_hdf5_plt_cnt_*') plot = yt.SlicePlot(ts[0], 'z', 'density') plot.set_zlim('density', 8e-29, 3e-26) fig = plot.plots['density'].figure # animate must accept an integer frame number. We use the frame number # to identify which dataset in the time series we want to load def animate(i): ds = ts[i] plot._switch_ds(ds) animation = FuncAnimation(fig, animate, frames=len(ts)) # Override matplotlib's defaults to get a nicer looking font with rc_context({'mathtext.fontset': 'stix'}): animation.save('animation.mp4') Any help is welcome, Regards [1]: https://yt-project.org/doc/cookbook/complex_plots.html#time-series-movie

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Return type of 'obtain_position_vector' and 'gravitational_binding_energy'
by Sam Patrick May 11, 2020

May 11, 2020

Hello, I'm editing code which contains the functions 'obtain_position_vector' and 'gravitational_binding_energy' within the utilities.lib.misc_utilities module and looking through their documentation. Although mostly self-explanatory I couldn't find any further information on this module on the yt website other than a list of it's comprising functions. Could anyone elaborate on the exact format of the data these functions return? Many thanks, Sam Patrick

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Logarithmic sampling of points for line_plot
by piyush.suneet＠gmail.com May 11, 2020

May 11, 2020

Dear yt Developers and Users, I am interested in creating line plots using my simulation data from FLASH. As I understand, the yt class 'yt.visualization.line_plot.LineBuffer' by default performs a linear sampling of points between the given starting and ending point of the line along which some field will be sampled. Is there a way to carry out a logarithmic sampling? This would be very useful because my simulations covers lengthscales ranging from few au to few pc and I would like to sample more data in the inner regions in my line plots. One way I could do this is by giving a very large value for "npoints" such that the data is sampled at every possible lengthscale irrespective of whether the sampling is linear or log, but I am wondering if there is a neater solution(s) to this? Cheers, Piyush Sharda PhD Student, Astrophysics, Australian National University

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