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7 participants
2683 discussions

by h.fathie＠gmail.com

Hello, I would like to plot the HI column density as a function of the radius. To do this I follow these steps. But instead of the column density (in cm-2) the y-axis is number density (in cm-3): fn = '../IsolatedGalaxy/galaxy0030/galaxy0030' ds = yt.load(fn) trident.add_ion_fields(ds, ions = ['H I'], ftype = 'gas') sphere = ds.sphere('c', (100., 'kpc')) plot = yt.ProfilePlot(sphere, 'radius', 'H_p0_number_density', weight_field = None) plot.save('my_fig.png') The field 'H_p0_number_density' should return the column density because it does so when I use the following line of code: plot = yt.ProjectionPlot(ds, 'z', 'H_p0_number_density') plot.save('fig.png') Here the 'H_p0_number_density' is interpreted as column density but not as number density. I would be very grateful if some one could help me with this issue. Many thanks Best regards, Hassan

23 hours, 48 minutes

yt Help / .SILO Export

by Egeln,Anthony A,Jr

Good afternoon! I am a PhD student at the University of Florida and am looking to use yt for a relatively specific function. In the past I have used it to create flat grids of data to export and give to other groups. These worked well due to their ability to flatten the adaptive mesh and interpolate between points to provide a nice, smooth mesh. What I would like to do now is be able to iterate through the grids that are stored in the yt object in order to output the whole data array. I need to do this in order to get the full spectrum of data and output it into a different file format (.SILO). The group requesting this information is looking to avoid flattening the data and wants access to the different levels of information in the adaptive mesh. I’ve come across several ways to access information about the individual grids of the stored data. Once I have loaded the file [often as an object called ds, ds = yt.load(file)], I can view information such as the grid names, the number of grids, and the size of grids through functions such as ds.index.grids, etc. Is there another function similar to index that allows the user to call data from an individual grid? For example, with index.grids[XXXX].size I can see that grid XXXX is [16 16 1]. I would like to be able to output that individual grid to an array. If it’s simpler maybe only export the data for say, ‘temperature’. I have found some calls to a similar process in the URL below: https://yt-project.org/doc/quickstart/data_inspection.html Thank you for your time. Please let me know if you are able to provide assistance in this matter. Have a great day! Anthony Egeln Jr. University of Florida anthony.egeln(a)ufl.edu<mailto:anthony.egeln@ufl.edu> 904 652 3159

1 day, 20 hours

No module named 'yt.loaders'

by h.fathie＠gmail.com

Hello, I have installed yt successfully and then I tried to install 'trident' using the following command pip install trident But when I issued import trident, I got the following error: It seems that it is complaining that loader does not exist in yt. >>> import trident /usr/lib/python3.8/_collections_abc.py:666: MatplotlibDeprecationWarning: The global colormaps dictionary is no longer considered public API. self[key] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/pc/.local/lib/python3.8/site-packages/trident/__init__.py", line 63, in <module> from trident.ray_generator import \ File "/home/pc/.local/lib/python3.8/site-packages/trident/ray_generator.py", line 14, in <module> from trident.light_ray import \ File "/home/pc/.local/lib/python3.8/site-packages/trident/light_ray.py", line 19, in <module> from yt_astro_analysis.cosmological_observation.cosmology_splice import \ File "/home/pc/yt_astro_analysis/yt_astro_analysis/cosmological_observation/cosmology_splice.py", line 19, in <module> from yt.loaders import \ ModuleNotFoundError: No module named 'yt.loaders' >>> I would be grateful if some one could provide some help on this. Best regards, Hassan

2 days, 3 hours

Problem with 'import rockstar_interface'

by h.fathie＠gmail.com

Dear all, I have installed yt and its associated rockstar but when I execute the following command: from yt.analysis_modules.halo_finding.rockstar import rockstar_interface I get the following error: >>> from yt.analysis_modules.halo_finding.rockstar import rockstar_interface Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/pc/yt-conda/src/yt-git/yt/__init__.py", line 21, in <module> from yt.data_objects.api import ( File "/home/pc/yt-conda/src/yt-git/yt/data_objects/api.py", line 1, in <module> from . import construction_data_containers as __cdc, selection_objects as __sdc File "/home/pc/yt-conda/src/yt-git/yt/data_objects/construction_data_containers.py", line 15, in <module> from yt.data_objects.selection_objects.data_selection_objects import ( File "/home/pc/yt-conda/src/yt-git/yt/data_objects/selection_objects/__init__.py", line 1, in <module> from .boolean_operations import ( File "/home/pc/yt-conda/src/yt-git/yt/data_objects/selection_objects/boolean_operations.py", line 5, in <module> from yt.data_objects.selection_objects.data_selection_objects import ( File "/home/pc/yt-conda/src/yt-git/yt/data_objects/selection_objects/data_selection_objects.py", line 11, in <module> from yt.data_objects.data_containers import YTDataContainer File "/home/pc/yt-conda/src/yt-git/yt/data_objects/data_containers.py", line 8, in <module> from yt.data_objects.profiles import create_profile File "/home/pc/yt-conda/src/yt-git/yt/data_objects/profiles.py", line 14, in <module> from yt.utilities.lib.misc_utilities import ( File "yt/utilities/lib/misc_utilities.pyx", line 1, in init yt.utilities.lib.misc_utilities ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject >>> I would be grateful if some one could help me with this issue. With best regards, Hassan

5 days, 20 hours

Toomre's criterion

by Cynthia Saad

Dear all, Did anyone calculate and plot the toomre criterion of a disk from an enzo dataset? Any tips on how to do that? Best, Cynthia

1 week, 3 days

Relaunch of the yt-project blog!

by Madicken Munk

Hi yters! I have been working of a relaunch of the yt blog with Matt over the past few weeks (it was previewed at the RHytHM workshop if you want to watch the talk about it (linked below)! Check it out at https://blog.yt-project.org/ Some of the things we tried to do when relaunching the blog was: - find a format that allowed for easy filtering of posts (in this blog we have tags, categories, and a search feature) - Find a format that has a nice post preview (with images) - Choose something that is accessible to various levels of contribution. We would love your feedback and contributions on the new blog! What can make it *even better*? What topics would you like to see on the blog? What could *you* add to the blog???? I personally think it would be cool to see stuff like: - How you use yt for YOUR SCIENCE - What cool tips and tricks do you use in yt? - Do you have a favorite feature? What is it and why? - Did you write a cool extension that uses yt? Let's hear about it! - Do you have a very cool colormap theme that you use with yt based on album covers of an artist??? What does science data look like with them??? - And so much more! We have two different ways of contributing a blog post: either as an issue or as a PR. You can check out the differences in the contributor guide. We've moved the blog repo into the yt project organization, it is now located at https://github.com/yt-project/blog You can find the blog hosted at https://blog.yt-project.org/ I can't wait to see all of your posts!!! Madicken PS -- Chris Havlin has already contributed two new posts to the blog! Dask! Napari! So many cool things! Check them out.

3 weeks

triage meetings -- early 2021!

by Madicken Munk

Hi yt-users! It's been a while since we've had scheduled triage meetings during the week. We use triage meetings to do development and maintenance work on the project. If you'd like to help contribute to making yt *better* and maybe even more useful for you, consider attending! All skill levels in development are welcome and encouraged to attend. If you're a bit shy, don't worry, you can also attend and just listen! I've created two polls. The first is morning in central US timezone to hopefully catch times where project members located in Europe can join, and the second is for afternoon/early evening in the central US timezone so project members on the west coast and asia can hopefully join. Vote in whatever poll applies to you (or both if you find all times work). We will choose times to accommodate the most people, and I personally would love to see all of you attend!!! I've put times for next week, but know that these polls are your *general availability *weekly for the next few months. Morning Poll: http://whenisgood.net/tmdfp2i Afternoon Poll: http://whenisgood.net/i2c8n3b - Madicken

3 weeks, 2 days

3D field and spherical object

by Salome Mtchedlidze

Hello! I want to create 3D field within a spherical object. For example, I create 3D electron density in the following manner: ds = yt.load("DATA") dd = ds.all_data() max_level = ds.index.max_level ref = 2**max_level low = ds.domain_left_edge dims = ds.domain_dimensions*ref nx, ny, nz = dims L = (ds.domain_right_edge - ds.domain_left_edge).d all_data_level_max = ds.covering_grid(level=max_level,left_edge=low,dims=dims) def _elec_den(field,data): N_A = 1/1.6726219e-24 X = 0.70 return ((all_data_level_max['gas','density'])*N_A*(1+X)/2/ds.quan(1,'g') ) ds.add_field(('gas','elec_den'), function=_elec_den, units='auto', dimensions=dimensions.number_density) Then if I do: dd['elec_den'] it will give me a 3D field which will have the same dimensions as the root grid of the dataset. However, if I create spheres and then a spherical object between these two spheres: rvir = 4.2454307068129566e+24 #virial radius of a halo [cm]. xyz = [0.4208984375, 0.2216796875, 0.5185546875] #centre of a halo. sph1 = ds.sphere(xyz, (2*rvir, 'cm')) sph2 = ds.sphere(xyz, (4*rvir, 'cm')) cutout_obj = sph2 - sph1 cutout_obj['elec_den'] or sph1['elec_den'] and sph2['elec_den'] will have the same dimensions as dd['elec_den'] ; but this cannot be true since sph1 and sph2 include less grid points. Is there a way I can create 3D field and use it within a different yt objects? Thanks, Salome

3 weeks, 3 days

Issue with stereo-spherical lens for plotting merging galaxies

by david.smolinski＠hs.uni-hamburg.de

Hi yt-Users, I have an issue with the stereo-spherical lens in volume rendering. I am simulating galaxy collusions with the Enzo Code and now I want to try to visualize these collusions in VR with the help of the stereo-spherical lens. My problem right now is that my box I am simulating the galaxies in, is much bigger than the galaxies itself. So, the galaxies are very small in the end and the plot is quite inexpressive. My approach to solve this problem was to reduce the volume, by putting a sphere around my galaxies like: data=yt.load(…) ds= data.h.sphere(‘max’, (100, ‘kpc’) (Please feel free to check the whole code on: https://cloud.hs.uni-hamburg.de/s/NZMiAWkSX9Zztse) But in the end this doesn´t changed the look of plot at all. The galaxies were as small as before. Do you have an idea how to solve this problem and getting a better view on the merging galaxies? Many thanks, David Smolinski

3 weeks, 4 days

yt-4: Migration to a new configuration system | action required on your side

by Corentin CADIOU

Dear all, TLDR; We recently migrated yt's configuration system from the yt-3 format to a new and more flexible format in yt-4 (the toml format, see https://github.com/yt-project/yt/pull/2981). *This requires a manual intervention to perform the migration (see details below).* ------------------------------------------------------------------------ *What does it change for users?* The new configuration system is documented online here: https://yt-project.org/docs/dev/reference/configuration.html. *Performing the migration* The change requires a one-time manual intervention on your side to perform the migration automatically. To perform the migration, simply type in your console yt config migrate This should migrate your old configuration to the new format (stored in ~/.config/yt/yt.toml) and store a backup of your old configuration file in ~/.config/yt/ytrc.bak should any error happen. Please report any issue you may encounter in the migration procedure so that we can fix them before releasing officially yt-4. If you get an error about a missing toml package, you may also have to install the toml package manually| | | conda install -c conda-forge toml # if you are using conda pip install toml # otherwise | Per-folder configuration The new configuration system allows you to configure yt per-folder. In particular, if a file named yt.toml is present in your current working folder, this file will override the global configuration. You can easily configure yt from the command line using yt config set yt log_level 40 --global # this will write in ~/.config/yt/yt.toml # or yt config set yt log_level 40 --local # this will write in ./yt.toml Naming convention We have also rationalized the naming convention of configurable keys in the configuration file: all keys now use snake case (i.e. words separated by an underscore). For example loglevel has become log_level. This is handled automatically by the configuration script, but bear that in mind if you modify the configuration file. For reference, all configurable keys can currently be found online https://github.com/yt-project/yt/blob/main/yt/config.py#L12 and the most important ones are documented online (https://yt-project.org/docs/dev/reference/configuration.html). What does it change for developers? The new format should allow more flexible configuration options. In particular, it supports nested configuration blocks and allows to find the most specific key in the configuration file # yt.toml [fields] cmap = "arbre" [fields.gas] cmap = "viridis" [fields.gas.temperature] cmap = "plasma" In Python, you can then query the "most specific" key matching a given path: from yt.config import ytcfg ytcfg.get_most_specific("fields", "gas", "temperature", "cmap") == "plasma" ytcfg.get_most_specific("fields", "gas", "density", "cmap") == "viridis" ytcfg.get_most_specific("fields", "io", "velocity_x", "cmap") == "arbre" This isn't used anywhere /yet/. The other breaking change compared to the old configuration system is that ytcfg.get returns typed quantities (as read by the toml parser) instead of strings. Best, Corentin -- Dr. Corentin Cadiou Post Doctoral Research Assistant Cosmoparticle Initiative Hub, desk 27 University College London (UCL) Gower St, Bloomsbury, London WC1E 6BT mobile: +33.6.43.18.66.83

1 month

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