Hi yt-users,
This is a quick note to ask you to save some time during the weeks of *June
7-11* and *August 2-6 *this year! We are going to try and push through PRs
those weeks, with each week having its own theme! I hope that everyone can
make both (meaning be active on slack and engaged in PRs)!! We will be
sending out details with our vision for each week shortly.
Mischief Managing week (we solemnly swear to be up to *only* good!)
We will have a managing mischief week to focus on cleaning up the codebase.
This is when we want dead code, code styling, and other PRs both submitted
and merged. MM week will be on June 7-11 this year.
PR Mentorship Week
This is a week that we will help get older PRs and PRs from new
contributors across the finish line. PRs from new contributors are always
welcome; this week is specifically for extra focused time to boost the work
of new contributors. This will include dedicated time from the development
community on taking over PRs or mentoring newer contributors whose PRs have
been waiting a while. PR Mentorship week will be held on August 2-6 this
year.
Can't wait to "see" you!
-The yt steering committee
--
Dr. Stephanie Tonnesen
Associate Research Scientist
CCA, Flatiron Institute
New York, NY
stonnes(a)gmail.com
Hello,
I wanted to ask if yt supports the registration of external data as a field
of an existing dataset.
In case it helps clarify my question, I just wanted to briefly elaborate on
what I'm looking to do. I'm trying to characterize the turbulent velocities
in some high resolution unigrid simulations. Because this involves
convolution, I need to compute the turbulent velocity outside of the yt
infrastructure (this seems beyond the scope of what a user-defined derived
field can support). It would be convenient to be able to load the results
back into yt to use the existing analysis machinery (e.g. for phase plots
and slices). I have thought about using the "Generic Unigrid Data"
frontend, but the simulation's size unfortunately makes that approach
somewhat intractable.
I'm pretty confident that the answer to my question is "no," but I wanted
to be sure before I rolled my own solution. Thank you for your help.
Best,
Matthew Abruzzo
Dear yt and rockstar users,
I recently installed the newest version of rockstar-galaxies as I had been
using a much older version. Although the output reports a particle mass of
1.31418e+05 Msun/h, I don't see any halos smaller than 1e+08 Msun/h. I was
expecting to get the minimum masses an order of magnitude lower.
I see in the config includes MIN_HALO_OUTPUT_SIZE = 25, set as a default. I
tried to change this parameter to 10 and restart from the beginning, but I
run rockstar within yt with RockstarHaloFinder (
yt.extensions.astro_analysis.halo_finding.rockstar.api), but my config file
was overwritten by the defaults. Is this even the right approach? If so,
how do I restart rockstar (more detailed than just rh.run(restart=True),
please) with customized parameters within yt's RockstarHaloFinder?
Thanks in advance,
--
Carla Bernhardt
PhD Student
Universität Heidelberg
ZAH Institut für Theoretische Astrophysik
Hello All,
I was having an issue with the yt.create_profile command, and I wanted to see if updating yt would help fix the issue. However, when I updated my anaconda yt installation to yt 3.6.1, I am now having this issue every time I try to load yt:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-1-3f99c158a398> in <module>
----> 1 import yt
2 import numpy as np
3 from yt import YTQuantity
4
5 import glob
~/anaconda3/lib/python3.7/site-packages/yt/__init__.py in <module>
61 display_ytarray
62
---> 63 from yt.fields.api import \
64 field_plugins, \
65 DerivedField, \
~/anaconda3/lib/python3.7/site-packages/yt/fields/api.py in <module>
17 field_plugins
18
---> 19 from . import angular_momentum
20 from . import astro_fields
21 from . import cosmology_fields
~/anaconda3/lib/python3.7/site-packages/yt/fields/angular_momentum.py in <module>
24 register_field_plugin
25
---> 26 from .vector_operations import \
27 create_magnitude_field
28
~/anaconda3/lib/python3.7/site-packages/yt/fields/vector_operations.py in <module>
30 handle_mks_cgs
31
---> 32 from yt.geometry.geometry_handler import \
33 is_curvilinear
34
~/anaconda3/lib/python3.7/site-packages/yt/geometry/geometry_handler.py in <module>
27 from yt.utilities.io_handler import io_registry
28 from yt.utilities.logger import ytLogger as mylog
---> 29 from yt.utilities.parallel_tools.parallel_analysis_interface import \
30 ParallelAnalysisInterface, parallel_root_only
31 from yt.utilities.exceptions import YTFieldNotFound
~/anaconda3/lib/python3.7/site-packages/yt/utilities/parallel_tools/parallel_analysis_interface.py in <module>
28
29 from yt.config import ytcfg
---> 30 from yt.data_objects.image_array import ImageArray
31 import yt.utilities.logger
32 from yt.utilities.lib.quad_tree import \
~/anaconda3/lib/python3.7/site-packages/yt/data_objects/image_array.py in <module>
16 from yt.config import \
17 ytcfg
---> 18 from yt.visualization.image_writer import write_bitmap, write_image
19 from yt.units.yt_array import YTArray
20
~/anaconda3/lib/python3.7/site-packages/yt/visualization/image_writer.py in <module>
24 from yt.units.yt_array import YTQuantity
25 from yt.utilities.exceptions import YTNotInsideNotebook
---> 26 from .color_maps import mcm
27 from . import _colormap_data as cmd
28 import yt.utilities.lib.image_utilities as au
~/anaconda3/lib/python3.7/site-packages/yt/visualization/color_maps.py in <module>
162 }
163
--> 164 add_colormap("cubehelix", _cubehelix_data)
165
166 # The turbo colormap, by Anton Mikhailov.
~/anaconda3/lib/python3.7/site-packages/yt/visualization/color_maps.py in add_colormap(name, cdict)
50 mcm.__dict__[name] = cdict
51 try: # API compatibility
---> 52 mcm.register_cmap(name, yt_colormaps[name])
53 except AttributeError:
54 pass
~/anaconda3/lib/python3.7/site-packages/matplotlib/cm.py in register_cmap(name, cmap, override_builtin)
147 if not override_builtin and name in __builtin_cmaps:
148 msg = f"Trying to re-register the builtin cmap {name!r}."
--> 149 raise ValueError(msg)
150 else:
151 msg = f"Trying to register the cmap {name!r} which already exists."
ValueError: Trying to re-register the builtin cmap 'cubehelix'.
I was wondering if anyone else had experienced a similar issue?
Hello All,
I am doing some work using the yt.create_profile function, and it seems to be returning incorrect results, but that may be based just me misunderstanding something. I am currently working on collecting the dark matter profile within the virial radius of halos in an ART simulation, and have been using this create_profile function for a while. It was pointed out to me that two different profiles I created (one linearly spaced, and one logarithmacilly spaced seemed to disagree on the total mass in a given sphere. Upon looking into this I noticed that there appears to be a drastic falloff in mass for the inner most profiles which does not appear physical. Here is a script that shows the issue:
import yt
import numpy as np
ds.quan(float(19.97536), 'Mpccm/h')
center = [ds.quan(19.97536, 'Mpccm/h'), ds.quan(19.58991, 'Mpccm/h'), ds.quan(20.38296, 'Mpccm/h')]
rvir = ds.quan(185.12684881603383, 'kpc')
ds = yt.load('/Volumes/My Passport for Mac/VELAhalos_4_1_2021/GEN6/VELA07_snap/10MpcBox_csf512_a0.500.d')
sp = ds.sphere(center, rvir)
#space = np.logspace(-2,0,30)
radius_bins = ds.arr(np.logspace(-2, 0, 30)*float(rvir), 'kpc')
#print(radius_bins)
#create the profile
rp_darkmatter = yt.create_profile(sp, ('darkmatter', 'particle_radius'), [('darkmatter', 'particle_mass')], accumulation = True,
units = {('darkmatter', 'particle_radius'): 'kpc', ('darkmatter', 'particle_mass'): 'Msun'},
weight_field=None, override_bins={('darkmatter', 'particle_radius'): radius_bins})
#now just find the mass within the smallest sphere to compare
sp = ds.sphere(center, (1.85126849, 'kpc'))
darkmatter_mass_rvir= sp.quantities.total_quantity([('darkmatter', 'particle_mass')])
Here is the outputs for the profile:
print(rp_darkmatter.x_bins)
print(rp_darkmatter[('darkmatter', 'particle_mass')])
[ 1.85126849 2.16987605 2.5433167 2.98102735 3.49406901
4.09540631 4.80023514 5.62636664 6.59467727 7.72963638
9.05992455 10.61915839 12.44673994 14.58885248 17.09962751
20.0425127 23.49187518 27.53488087 32.27369713 37.82807456
44.3383731 51.96910898 60.91311203 71.39639856 83.68388279
98.08607129 114.96690951 134.75297878 157.94427603 185.12684882] kpc
[1.71640907e+09 4.08670014e+09 7.29731648e+09 1.15396909e+10
1.70891641e+10 2.43093919e+10 3.36631560e+10 4.56267933e+10
6.02872054e+10 7.78791509e+10 9.85060803e+10 1.22442170e+11
1.49759934e+11 1.80141955e+11 2.13532847e+11 2.51746816e+11
2.95421277e+11 3.46319791e+11 4.05501975e+11 4.73278346e+11
5.52642140e+11 6.41302652e+11 7.43654270e+11 8.45108184e+11
9.51028253e+11 1.06624695e+12 1.17616790e+12 1.29792900e+12
1.43690732e+12] Msun
And here is the result for the two inner most spheres centered at the same center:
3597806296.1175537 Msun - 1.85126849 kpc
4420085989.534953 Msun - 2.16987605 kpc
This is not the same mass as found by any of the inner spheres of the profile, and contains over twice as big as the inner most sphere. I have tried this for several radii, and it appears to always be off by a bit, but the difference gets smaller as the radii gets larger, as shown by a sphere for the total virial radius:
1440505125868.4753 Msun - 185.12684882 kpc
Vs the total mass enclosed in the profile of 1.43690732e+12 (only about a 1% difference).
I am wondering if there might be something wrong how I am using this, or if there is an issue with the profile maker. I had asked about profile before, and was told to use the rp_darkmatter.x, but rp_darkmatter.x_bins field for the radii. Has something been changed in this function? (Note, I have tried looking at the rp_darkmatter.x radii, but those also do not agree with a ds.sphere of the same radii) (PSS: This is using yt 3.5.1, as I tried to update to 3.6.1 and ran into an error importing yt)
Hello, I hope whoever reading this is doing well.
I am trying to make a 1D profile plot with a custom y label, however I am
getting the error: AttributeError: 'ProfilePlot' object has no attribute
'set_ylabel' and I am confused. This is also the case when I try to set a
xlabel. I am creating multiple profiles from 2 datasets by appending them
to a list as is shown in the yt cookbook, I'm not sure if this would cause
an error.
Thank you
--
Edward N. Buie II (he/him),
*Ph.D. Candidate*
Astrophysics
School of Earth and Space Exploration (SESE)
Arizona State University
Dear all,
I have read a Gadget snapshot as follows:
ds = yt.load('../GadgetDiskGalaxy/snapshot_200.hdf5')
partID = ad[('PartType0', 'ParticleIDs')]
I then defined a sphere around a Type0 particle using the following lines of code:
j = 9000
sp = ds.sphere([px[j],py[j],pz[j]],(20.0,'kpc'))
When I issue the following command:
print(sp["particle_index"])
I get:
[ 841624. 890649. 841457. 890473. 865599. 865772. 6258099. 5752659.
5752660. 5777940. 6229883. 5803543.] dimensionless
This shows that there are 12 particles inside the sphere.
I checked and found that the following IDs exist in the 'partID' array:
841624. 890649. 841457. 890473. 865599. 865772.
but these IDs (see below) do NOT exist in the 'partID' array:
6258099. 5752659. 5752660. 5777940. 6229883. 5803543
So the IDs of these 6 particles inside the sphere do not exist in the 'partID' array.
How is this possible since 'partID' (as defined above) must contain the IDs of all
Type0 particles ?
I would be grateful if someone could help me with this issue.
Best regards,
Hassan
Hi,
I am trying to read a RAMSES snapshot which has a size of a few TB. Please
let me know what are methods I can use to read this using yt. I have good
computation available but I can see from here: (
https://yt-project.org/doc/analyzing/parallel_computation.html) that yt
can't perform the reading operation in parallel. I tried using bbox
argument to get a smaller region but that didn't help. I would really
appreciate any help in this regard.
Thanks,
Ankit Singh
Dear all,
I have a simulation of an isolated galaxy with dark matter, bulge stars, disk stars and gas particles.
I would like to probe how dust evolves over time by post processing this simulation.
I am new in this subject and I would be very grateful if some one could introduce some references
or post-processing libraries, or ... that could be used to trace dust evolution in simulations.
Many thanks in advance.
Best regards,
Hassan
Hi yt-users,
I have a question about spheres, because I am having a problem that I don't
really know how to solve. Basically, I have clusters of stars, and I want
to know how many stars are within 6 pc of each star. So, what I have done
is taken a sphere at each star position with a radius of 6 pc, and then
performed
sp.quantities.total_quantity(["particle_mass"])
Now I wanted to double-check this number by brute-force, so I calculated
the distance between all the particles and then summed the masses of all
the particles that were less than 6 pc.
I am not getting the same values--they are close, but not the same (they
seem to mostly scatter up or down by a factor of 2).
So...to the question!! Because I am measuring particles in a grid code
(Enzo) is there any sort of shifting to the grid position instead of using
the particle positions here? Because stars are pretty packed I could
imagine that this could cause the differences I am seeing.
I am not sure that the problem is not something silly I am doing, but
wanted to check this possibility as well.
Thanks!
Stephanie
--
Dr. Stephanie Tonnesen
Associate Research Scientist
CCA, Flatiron Institute
New York, NY
stonnes(a)gmail.com
