Submitting author: @vc1492a (Valentino Constantinou)
Repository: https://www.github.com/vc1492a/PyNomaly
Version: v0.2.4
Editor: @Kevin-Mattheus-Moerman
Reviewers: @llllllllll
Archive: 10.5281/zenodo.1472519
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HTML: <a href="http://joss.theoj.org/papers/f4d2cfe680768526da7c1f6a2c103266"><img src="http://joss.theoj.org/papers/f4d2cfe680768526da7c1f6a2c103266/status.svg"></a>
Markdown: [](http://joss.theoj.org/papers/f4d2cfe680768526da7c1f6a2c103266)
Reviewers and authors:
Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)
@yzhao062, @llllllllll, please carry out your review in this issue by updating the checklist below. If you cannot edit the checklist please:
The reviewer guidelines are available here: https://joss.theoj.org/about#reviewer_guidelines. Any questions/concerns please let @Kevin-Mattheus-Moerman know.
โจ Please try and complete your review in the next two weeks โจ
paper.md
file include a list of authors with their affiliations?paper.md
file include a list of authors with their affiliations?Hello human, I'm @whedon. I'm here to help you with some common editorial tasks. @yzhao062 it looks like you're currently assigned as the reviewer for this paper :tada:.
:star: Important :star:
If you haven't already, you should seriously consider unsubscribing from GitHub notifications for this (https://github.com/openjournals/joss-reviews) repository. As a reviewer, you're probably currently watching this repository which means for GitHub's default behaviour you will receive notifications (emails) for all reviews ๐ฟ
To fix this do the following two things:
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Attempting PDF compilation. Reticulating splines etc...
@vc1492a @yzhao062 this is where the review takes place. I aim to find more reviewers but to avoid further delay we can get started here.
@yzhao062 could you provide an estimate as to when you think you'll be able to finish the review? Thanks! :robot: :rocket:
@yzhao062 Current GitHub release is 0.2.1, as PyNomaly received an update after submission.
@Kevin-Mattheus-Moerman @vc1492a I am about to start by following the review schedule above. Given I need some time to familiarize myself with the process, I would say 7-10 days is a safe estimate (should be faster though).
@yzhao062 thanks. Okay, let me know if you need help.
Hi @Kevin-Mattheus-Moerman @vc1492a ,
I have followed the tasklist to conduct the first round review and marked most of the items as done. There are 2 items unchecked and want to list them below:
Functionality documentation: the parameters are introduced in readme.MD. Given there are only 2 parameters to tweak (extent and n_neighbors), it should be fine without a full documentation (e.g. readthedocs). However, it may be helpful to open another section to list the the default values (0.997 and 10) and your recommendations for picking the parameters.
Automated tests: it could be helpful to include some basic tests to make sure the model is running. For example, it is easy to generate some pseudo data and use loOP to do a classification and verify the result, which could at least make sure it is doing the job on the simplest data. Feel free to use the data_generation model here if that saves some time.
Other than those two items, I think it is a very solid and useful package to go which I used in my last paper. Since I am a first-time reviewer, please advise what is the best way to address the above two tasks.
Thanks,
Yue
@vc1492a how are you getting on? Are you able to respond to the issues raised by @yzhao062 ? Thanks
@Kevin-Mattheus-Moerman Thanks for the message. I was under the impression that the work would be reviewed by a second reviewer prior to moving to the revision process. As such, I have not yet started on the recommendations @yzhao062 provided above but please let me know whether I should move forward with the revision process. I can get started in the next few days, and should be able to provide solutions to the above recommendations in about two weeks time.
@vc1492a I am searching for a second reviewer but please do start working on the revision process already.
@Kevin-Mattheus-Moerman Thanks for reply. Will get started on the revision process and will get back in touch once I have pushed the suggested changes.
@Kevin-Mattheus-Moerman I have addressed the issues raised by @yzhao062. Additional documentation for parameter has been added to the readme, and a series of automated tests are available in the PyNomaly/tests
directory (using pytest
). Additionally, examples have been added to the examples
directory. Please let me know if there's any additional items I should address.
@llllllllll is this something you'd be interested in reviewing?
I am interested in this, but I am moving tomorrow and will need a few days to unpack. I can look at this in a week or so.
@llllllllll great thanks. I'll add you as reviewer and look forward to seeing your comments. All the best with the move :house_with_garden:
@whedon assign @llllllllll as reviewer
OK, the reviewer is @llllllllll
@yzhao062 could you respond to how @vc1492a has dealt with your feedback? Thanks
@Kevin-Mattheus-Moerman will do a review in 3 days for sure:)
@Kevin-Mattheus-Moerman I have successfully run the newly added tests. I am confident it is a sound and useful package! Great work @vc1492a ! I think it is good to go:)
Thanks @yzhao062 for your end of the review work! :tada:
@vc1492a we will now await @llllllllll review comments.
@llllllllll could you give us an estimate as to when you expect to work on this review process? Thanks
@llllllllll could you give us an estimate as to when you expect to work on this review process? :rabbit: :rose: :robot:
Sorry, really let this slip. I will review this tonight.
Sorry it took me so long to get to this. This is a really cool project.
It looks like you just merged my install pr, so I will check that off. Thanks! I had one small comment about clarifying the layout of the input. It only took me a minute to figure it out once I played with it, but it made it hard to follow the examples.
For testing I used daily returns of US equities for the year of 2016. I played around with different ways of extracting features. I also tried using sector labels as my cluster labels. I was very happy to see that this library identified some known data quality issues, mostly around missing splits. More importantly, it found a few new issues. I will definitely try to use this more in the future. Thanks again, and sorry for taking so long on this.
@llllllllll Thanks for your comments and suggestions, and thanks for submitting the pr. I'll take a look at your opened issue regarding the layout of the input and will see what changes I can make to PyNomaly and/or the documentation to improve clarification.
@Kevin-Mattheus-Moerman I have added additional clarification in readme.md
following @llllllllll's review and comments. Please let me know if there are any additional steps I should take, thanks!
Thanks @vc1492a. @llllllllll can you please check out these new developments.
That looks great, thank you!
@whedon generate pdf
Attempting PDF compilation. Reticulating splines etc...
This is looking good now. Thanks @yzhao062, @llllllllll for your review efforts! :rocket:
@vc1492a at this point could you please:
1) Inform us if the version number (v0.2.0) assigned here is still accurate or if you've since created a new release?
2) Deposit an archived version of the reviewed software in a service like Zenodo (see also: https://guides.github.com/activities/citable-code/) and report back with the DOI of the archived version.
@Kevin-Mattheus-Moerman Thanks for the update. The current version number is v0.2.4 - there's been a few releases since the start of the review process. I've deposited an archived version of the software, it's DOI is 10.5281/zenodo.1472519
. Besides the version number, the article proof looks good to me as well. Thanks @yzhao062 and @llllllllll for the review!
@arfon I recommend we accept this work in JOSS. Above is the archive DOI. Please also note the version number change. Thanks.
:wave: Hey @Kevin-Mattheus-Moerman...
Letting you know, @arfon
is currently OOO until Monday, October 29th 2018. :heart:
@whedon set 10.5281/zenodo.1472519 as archive
OK. 10.5281/zenodo.1472519 is the archive.
@whedon accept
Attempting dry run of processing paper acceptance...
Check final proof :point_right: https://github.com/openjournals/joss-papers/pull/38
If the paper PDF and Crossref deposit XML look good in https://github.com/openjournals/joss-papers/pull/38, then you can now move forward with accepting the submission by compiling again with the flag deposit=true
e.g.
@whedon accept deposit=true
@whedon accept deposit=true
Doing it live! Attempting automated processing of paper acceptance...
๐จ๐จ๐จ THIS IS NOT A DRILL, YOU HAVE JUST ACCEPTED A PAPER INTO JOSS! ๐จ๐จ๐จ
Here's what you must now do:
Party like you just published a paper! ๐๐๐ฆ๐๐ป๐ค
Any issues? notify your editorial technical team...
@llllllllll - many thanks for your review here and to @Kevin-Mattheus-Moerman for editing this submission โจ
@vc1492a - your paper is now accepted into JOSS and your DOI is https://doi.org/10.21105/joss.00845 :zap: :rocket: :boom:
:tada::tada::tada: Congratulations on your paper acceptance! :tada::tada::tada:
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@Kevin-Mattheus-Moerman @arfon thanks for your help in the review process!
:wave: Hey @vc1492a...
Letting you know, @arfon
is currently OOO until Monday, October 29th 2018. :heart:
Most helpful comment
Sorry it took me so long to get to this. This is a really cool project.
It looks like you just merged my install pr, so I will check that off. Thanks! I had one small comment about clarifying the layout of the input. It only took me a minute to figure it out once I played with it, but it made it hard to follow the examples.
For testing I used daily returns of US equities for the year of 2016. I played around with different ways of extracting features. I also tried using sector labels as my cluster labels. I was very happy to see that this library identified some known data quality issues, mostly around missing splits. More importantly, it found a few new issues. I will definitely try to use this more in the future. Thanks again, and sorry for taking so long on this.