[PRE REVIEW]: PyProximal - scalable convex optimization in Python

[editorialbot]

Submitting author: @mrava87 (Matteo Ravasi)
Repository: http://github.com/pylops/pyproximal/
Branch with paper.md (empty if default branch): joss
Version: v0.7.0
Editor: @sappelhoff
Reviewers: @nirum, @nwu63, @Leo-Simpson
Managing EiC: Arfon Smith

Status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/c953d2cc2f446d83595cc858baadb15d"><img src="https://joss.theoj.org/papers/c953d2cc2f446d83595cc858baadb15d/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/c953d2cc2f446d83595cc858baadb15d/status.svg)](https://joss.theoj.org/papers/c953d2cc2f446d83595cc858baadb15d)

Author instructions

Thanks for submitting your paper to JOSS @mrava87. Currently, there isn't a JOSS editor assigned to your paper.

@mrava87 if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). You can search the list of people that have already agreed to review and may be suitable for this submission.

Editor instructions

The JOSS submission bot @editorialbot is here to help you find and assign reviewers and start the main review. To find out what @editorialbot can do for you type:

@editorialbot commands

[editorialbot]

Hello human, I'm @editorialbot, a robot that can help you with some common editorial tasks.

For a list of things I can do to help you, just type:

@editorialbot commands

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

@editorialbot generate pdf

[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.14 s (788.1 files/s, 92334.8 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          79           1983           3798           4820
Markdown                         5            145              0            527
reStructuredText                12            300            277            387
YAML                             8             29             47            190
TeX                              1             12              0             95
CSS                              1             23              7             87
make                             2             18              8             48
TOML                             1              4              0             45
HTML                             1              6              0             32
-------------------------------------------------------------------------------
SUM:                           110           2520           4137           6231
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1318

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1016/j.softx.2019.100361 is OK
- 10.1561/2200000016 is OK
- 10.1007/s10851-010-0251-1 is OK
- 10.1093/gji/ggab388 is OK
- 10.1109/GlobalSIP.2013.6737048 is OK
- 10.1190/tle42070457.1 is OK
- 10.3997/2214-4609.2022616015 is OK
- 10.3997/2214-4609.2021612003 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

Five most similar historical JOSS papers:

pyOptSparse: A Python framework for large-scale constrained nonlinear optimization of sparse systems
Submitting author: @nwu63
Handling editor: @poulson (Retired)
Reviewers: @jgoldfar, @vissarion, @matbesancon
Similarity score: 0.8196

c-lasso - a Python package for constrained sparse and robust regression and classification
Submitting author: @Leo-Simpson
Handling editor: @mjsottile (Retired)
Reviewers: @jbytecode, @glemaitre
Similarity score: 0.8144

Minimalist And Customisable Optimisation Package
Submitting author: @jbuisine
Handling editor: @melissawm (Retired)
Reviewers: @stsievert, @torressa
Similarity score: 0.8133

Linopy: Linear optimization with n-dimensional labeled variables
Submitting author: @fabianhofmann
Handling editor: @Fei-Tao (Active)
Reviewers: @torressa, @g4brielvs
Similarity score: 0.8115

Capytaine: a Python-based linear potential flow solver
Submitting author: @mancellin
Handling editor: @leouieda (Retired)
Reviewers: @mikaem, @harpolea
Similarity score: 0.8099

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[mrava87]

@arfon, I see you have been assigned as Managing EiC. Since this is my first time submitting to JOSS, am I expected to do anything at this point or I just need to wait for an Editor to be assigned to my manuscript?

[arfon]

@mrava87 – my apologies, I forgot to notify you that this submission is waitlisted for now while we await an available editor to take on your submission. Thanks in advance for your patience!

[mrava87]

@arfon alright, no worries! As long as I know there is nothing on my side needed before things can proceed, I can patiently wait :D

[sappelhoff]

@editorialbot assign me as editor

[editorialbot]

Assigned! @sappelhoff is now the editor

[sappelhoff]

Hi @mrava87, I will be editing your submission to JOSS. Do you have suggestions for potential reviewers?

[mrava87]

Great :) @sappelhoff, nice to e-meet you!

I had a look at the Five most similar historical JOSS papers but I am not so convinced they are that similar to our work/library. Perhaps c-lasso is the most affine, so I would suggest one of their devs Leo-Simpson.

There exists a few libraries similar to pyproximal (as we mention in our doc), so based on that, here are few additional reccomended reviewers who contributed to those libraries:

• nirum
• matthieumeo
• pmelchior

PS: I gave you GitHub usernames but I am explicitely not tagging them, so in case you don't select them, they won't know :)

[sappelhoff]

Thanks a lot for the suggestions @mrava87! Pleased to e-meet you too. I am going to invite all except nirum for now, but we may potentially get back to him if we have some refusals.

[sappelhoff]

👋 @Leo-Simpson & @pmelchior & @matthieumeo, would any of you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

I will also try to send you a more formal invitation via email.

[sappelhoff]

@Leo-Simpson & @pmelchior & @matthieumeo I am giving this a little bump up your notifications list: I'd still be happy to receive a response from you regarding #6185 (comment)

[sappelhoff]

👋 @nirum & @nwu63 & @mancellin, would any of you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

I will also try to send you a more formal invitation via email.

[nirum]

Yep I can review this one

[ewu63]

I am also happy to review this submission :)

[sappelhoff]

@editorialbot assign @nirum as reviewer

[editorialbot]

I'm sorry human, I don't understand that. You can see what commands I support by typing:

@editorialbot commands

[sappelhoff]

@editorialbot add @nirum as reviewer

[editorialbot]

@nirum added to the reviewers list!

[sappelhoff]

@editorialbot add @nwu63 as reviewer

[editorialbot]

@nwu63 added to the reviewers list!

[sappelhoff]

Thanks for taking this one on @nwu63 and @nirum.

I received some declines via email, but will wait for some more hours for a reply for a potential third reviewer. Else, I will move this review on to the next step, as two reviewers would also suffice.

[Leo-Simpson]

Dear all,
Sorry for the late reply.
I don't think I am an expert on this topics, but I can do my best, so I am happy to review this submission.
How much time do we have (roughly) to proceed to the review?

[sappelhoff]

@editorialbot add @Leo-Simpson as reviewer

[editorialbot]

@Leo-Simpson added to the reviewers list!

[sappelhoff]

Hi @Leo-Simpson thanks for being a reviewer, there are plenty of aspects to review for a software and you do not need to be an expert in all of these aspects. That's also why we usually have two to three reviewers (covering more areas of expertise). I appreciate you taking this on.

How much time do we have (roughly) to proceed to the review?

At JOSS we aim to have the review process completed withing 4-6 weeks (unless a reviewer explicitly informs me that they can only start later, or for other reasons)

[sappelhoff]

@editorialbot start review

[editorialbot]

OK, I've started the review over in #6326.

[matthieumeo]

Hi @sappelhoff and all ! Very sorry for the late reply, I was trying to find a potential replacement. Unfortunately I have left academia and my new job leaves me very little time for reviewing activities. It seems you already have enough reviewers however if needed, I can recommend a close collaborator of mine and co-creator of the Pyxu framework, that provides similar functionalities as pyproximal ! Let me know.

[sappelhoff]

Thanks for your reply @matthieumeo -- I'll gladly take your collaborator's GitHub handle or email address (either in this thread without tagging them directly, or as response to the email I sent you). Just in case we will need another reviewer some time down the line.

All the best with your new career!

[matthieumeo]

You're very welcome! His GitHub handle is: SepandKashani. I asked him and he is available if needed.

Thanks for your wishes and happy reviewing :)