-
Notifications
You must be signed in to change notification settings - Fork 8
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
NLA model for intrinsic alignments #21
Conversation
Hi @mwiet, Can you add documentation with references and equations to the docstring in the NLA model? There are templates for this in the other functions :) |
Hi there! Thanks for letting me know! The documentation and references are now included in the function's docstring. |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Great first PR! Only a couple of minor changes.
Could you also add your new generator to the documentation by including it in the list at the top of the file?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
That's great! Please take a look at the generated documentation (the link is under the "checks" in this PR), there are a couple of issues there (e.g. the references aren't linked, and math errors).
Closing this, as the code is copied from the |
Ok, the issue has been resolved! I think we can try and merge this again. I will let @NiallJeffrey review this PR. |
Hi Nicolas,
I just tried to make the amendments to the changelog, but I don't seem to have the rights to push to the ia_nla branch anymore. Let me know how I can regain these.
Best,
Max
…________________________________
From: Nicolas Tessore ***@***.***>
Sent: 17 May 2023 15:35
To: glass-dev/glass ***@***.***>
Cc: Von Wietersheim-Kramsta, Maximilian ***@***.***>; Mention ***@***.***>
Subject: Re: [glass-dev/glass] ENH: NLA model for intrinsic alignments (PR #21)
⚠ Caution: External sender
Hi @mwiet<https://github.com/mwiet>, we are trying to get this into the next release. Could you take a look at CHANGELOG.md<https://github.com/glass-dev/glass/blob/main/CHANGELOG.md> and add the corresponding entries for this PR to your branch? Cheers
—
Reply to this email directly, view it on GitHub<#21 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AL36GZ4DGZQENO2BF7VSH7LXGTO4JANCNFSM54YS2YLA>.
You are receiving this because you were mentioned.Message ID: ***@***.***>
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Code looks good to me. Pinging @NiallJeffrey for scientific review.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Let's merge this asap :D
@ntessore I think we can merge this :) |
Have just updated from current |
pre-commit.ci autofix |
Have addressed linting issues so that the CI passes. When the science is ready, this PR is ready to go 🙂 |
From the science pov, both me and @mwiet have reviewed it and it seems solid. But I think it would be great to have @NiallJeffrey to take a quick look :) |
I think this can finally go in. @NiallJeffrey speak now or forever hold your peace 😉 |
This looks good to me! Comment -- it might be useful to put the C1 value in the docs, but it is the industry-standard value, so not essential |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
The implementation appears corrects to me
I'm going to merge this before it falls stale again |
rho_c1 = c1 * cosmo.rho_c0 | ||
|
||
prefactor = -a_ia * rho_c1 * cosmo.Om | ||
inverse_linear_growth = 1.0 / cosmo.gf(zeff) |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
This reverts commit 60dc668.
The ia_nla function computes the effective convergence from intrinsic alignments, calculated using the Non-linear Aligments Model (NLA). The convergence from intrinsic aligments is follows Catelan et al. (2000), Hirata & Seljak (2004), Bridle & King (2007).
Added: The new
kappa_ia_nla()
function computes an effective convergence due to Intrinsic Alignments using the NLA model.Reviewed-by: Nicolas Tessore
Reviewed-by: Arthur Loureiro [email protected]