I would like to annotate Mass weighted Magnetic field quivers on density projection plot so that i can display the magnetic field features.
Do annotate_magnetic_field() , annotate_quiver() work correctly on projection plot or do they work only on slice plot correctly.
If they work on projection plot then against which quantity magnetic field quivers are weighed or not weighted?
Hi guys,
I am very new to Ytini's mailing list, mailing lists as well as Houdini.
So please bear with me while I pick up the etiquette around this medium.
With that out of the way here's my first question:
After having succeeded installing Ytini for Houdini on a Mac OS X 10.14 I
would now like to achieve the same with my Houdini install on a Windows 10
OS.
I have tried to somewhat reproduce all steps described here
http://www.ytini.com/getstarted.html#collapseTwoOut (Houdini 17.5 Tested on
Mac OS X) on my Windows machine but wasn't surprised to learn that of
course Houdini could not find the ytini module when I tried to import it in
the python shell.
Is there somebody, that could point me . in the right direction of how to
install Ytini for Houdini on a Windows 10 OS environment?
Not afraid of reading so even hints a re more than welcome.
Many Thanks in advance
Ur4n
Hello yt users,
I'm trying to understand magnetic field units used in yt Since I found something that looks strange to me. As stated on the yt website, it uses cgs units just like FLASH.
I'm sending the code bellow, and it does the following:
1) I use yt to trace a ortho ray
2) using that ray I get the magnetic field a gas pressure
3) from the magnetic fiedl I get the magnetic pressure
4) I add gas pressure and magnetic field pressure
5) The answer is wrong, and I don't know why
The data file is here: http://use.yt/upload/a95035d4
The code is here: http://paste.yt-project.org/show/178/
Cheers,
Dear colleagues,
It is my pleasure to announce that applications are now open for Python in Astronomy 2020, to be held 20 - 24 April 2020 at Trinity College, Dublin in Dublin, Ireland.
Though the application form will be open until 23:59 UTC on 6 January 2020, I encourage you to complete the form soon to make sure you don’t miss the deadline.
The application form is at: https://forms.gle/mtdm6QKENdY8Y1Ph9
More information about the conference, including links to past years, is available at: http://openastronomy.org/pyastro/2020/
Finally, a brief excerpt from the description of the conference:
In addition to sharing information about state-of-the art Python Astronomy packages, the workshop will focus on improving interoperability between astronomical Python packages, mentoring current open-source contributors, and developing educational materials for Python in Astronomy. The meeting is therefore not only aimed at current developers, but also educators and research group leaders who are interested in being involved in these efforts.
Participant selection will be made with the goal of enhancing the Python in Astronomy community and we encourage requests to attend from all career levels. Effort will also be made to select participants who have contributed meaningfully to the Python in Astronomy ecosystem via providing educational materials, documentation, and/or code contributions. This conference is neither intended to be an introduction to Python nor only for expert-level Python developers.
Thanks,
Will Barnes
On behalf of the SOC: Monica Bobra (co-chair), Andrew Leonard (co-chair), Will Barnes, Clara Brasseur, Juan Luis Cano, Rebecca Lange, Sophie Murray
Hi all,
I wanted to share with you a job posting to work with us at the
University of Illinois. It’s available at:
https://jobs.illinois.edu/academic-job-board/job-details?jobID=123477&job=v…
The short description is that we’re looking to invest in the yt
infrastructure, and bring it more closely in line with the modern
pydata ecosystem. This would mean working to utilize and interoperate
with libraries like dask and xarray, and will include designing and
documenting software changes and infrastructure. Plus, it will also
involve working with libraries used throughout both the scientific
ecosystem and in industry in modern data science. And, you’ll get to
work with fun people in both yt community *and* the pydata community!
All the work will be open source and this project is committed to
contributing to the broader ecosystem *wherever* we can.
I hope you’ll consider either applying, or passing this along to
someone you know that might be interested. All of the information in
the job posting should be considered authoritative, rather than this
email. If you’ve got any questions (including about specifics of the
job, the application process, etc) please do reach out to the contact
person on the form!
Best,
Matt
Dear Andrew Myers and yt users,
Q1. Given a HDF5 data that is dumped by **PLUTO**, how do I check whether this data is in chombo format or not?
In my humble opinion: Run the following script. If the string 'chombo' is shown on screen, then this HDF5 data is in chombo format. Am I right?
------------------------------------------------
import yt
ds=yt.load("data.0000.hdf5")
print (ds['HydroMethod'])
------------------------------------------------
Q2. If the above question is positive, why do I always get white noise in slice plot after execution the following script?
------------------------------------------------
import yt
ds = yt.load("data.0001.hdf5")
yt.SlicePlot(ds, 'z', 'density', center='c').save()
------------------------------------------------
thanks a lot.
Dear Yt-users,
I need to pass the value of the available/derived field corresponds to the
index selected based on some criterion (using numpy.where()) to a scalar
function. It should list out the indexes wheres the condition satisfies. It
happens when this has been done outside the field but instead of getting 3D
indexes it gives 1D YT_Array indexes I think.
But I need to pass this value of field corresponds to the selected index to
scalar function inside the field, which may give some problem (please find
the attachment to see what exactly I am trying to do).
The attached script can run on the ENZO test data set, enzo_tiny_cosmology.
Many thanks and regards
-Prateek
