Comments (20)
from joss-reviews.
@arfon I think for COI we should say bug fix patches are ok (need to be declared) but not feature additions. This is clearly a bug fix. With reviewers who are active and projects that are useful bug fixes may be common, and the last thing we want is to inhibit our reviewers from fixing bugs.
from joss-reviews.
I recommend publication on revision of my minor comments.
from joss-reviews.
Thanks for the review @tacaswell
@dfm your DOI will be http://dx.doi.org/10.21105/joss.00024 once the Crossref queue is processed (looks a little backed up right now).
from joss-reviews.
/ cc @openjournals/joss-reviewers - would anyone be willing to review this submission?
If you would like to review this submission then please comment on this thread so that others know you're doing a review (so as not to duplicate effort). Something as simple as :hand: I am reviewing this
will suffice.
Reviewer instructions
- Please work through the checklist at the start of this issue.
- If you need any further guidance/clarification take a look at the reviewer guidelines here http://joss.theoj.org/about#reviewer_guidelines
- Please make a publication recommendation at the end of your review
Any questions, please ask for help by commenting on this issue!
from joss-reviews.
I actually have 1 commit into this project (completely forgot about that until my name showed up in the author list on zenodo). It is an almost trivial change: dfm/corner.py@8b87b92
I suspect that I am being pedantic about conflict of interest here, but is this a problem?
from joss-reviews.
Thanks for bringing this to my attention. Given that the commit is very small I think it's ok to proceed with the review.
from joss-reviews.
@genomematt - I've added a small clarification here: openjournals/joss@dad0605
Perhaps we should add something to the reviewer guidelines too?
from joss-reviews.
@dfm quantile
is exported in the __all__
, but is not in the built docs nor is it's docstring numpydoc format. Was this intended to be part of the public API?
This paper makes no performance claims, how does that get handled?
The mpl paper has a DOI http://dx.doi.org/10.1109/MCSE.2007.55
The citation to the ADS search results seems strange to me, I think it is ok to assert an 'also known as' with out citation.
from joss-reviews.
This paper makes no performance claims, how does that get handled?
In that case you can just check the box.
from joss-reviews.
@tacaswell: Thanks for the suggestions. I've added some tests and documentation for the quantiles function. I added the DOI for the matplotlib paper and removed the ADS citation.
Thanks!
from joss-reviews.
@arfon: what are your thoughts on submitting a paper from joss to arxiv?
On Wed, Jun 8, 2016 at 12:05 PM Arfon Smith [email protected]
wrote:
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
#24 (comment),
or mute the thread
https://github.com/notifications/unsubscribe/AAVYSsARCgrBHONi_QdMMZ1cgzsml0Beks5qJugWgaJpZM4IoH4j
.
from joss-reviews.
@arfon: what are your thoughts on submitting a paper from joss to arxiv?
Fine by me. My only request would be that you update the arXiv metadata to point to the JOSS DOI.
from joss-reviews.
Done. One request for the future: I had to download the pandoc latex template and generate the .tex file to submit to arxiv (they spot PDFs that were generated by LaTeX) so it would be great to make the tex available somewhere!
from joss-reviews.
I notice that "References: Do all archival references that should have a DOI list one (e.g. papers, datasets, software)?" never got checked in the review. There are references listed, and while one has a DOI, the Matplotlib paper also should (specifically, 10.1109/MCSE.2007.55). I wonder if we have a process problem here? It seems like the review shouldn't be finalized and the paper shouldn't be published until all the boxes are checked. Also for the third reference, I don't think Astrophysics Data System is a proper name that should be written as "System, Astrophysics Data".
This is based on what I see right now at http://joss.theoj.org/papers/10.21105/joss.00024 as well as in the PDF at https://github.com/openjournals/joss-papers/blob/master/joss.00024/10.21105.joss.00024.pdf . I also notice that these doesn't seem to match the comments above, which seem to indicate that there may be later version that already has these fixes.
from joss-reviews.
These changes were made here: https://github.com/dfm/corner.py/blob/master/paper/paper.bib ... I'm not sure if there was something else I needed to do.
from joss-reviews.
It looks like there was a paper regeneration step that didn't get done. @arfon ?
from joss-reviews.
It looks like there was a paper regeneration step that didn't get done. @arfon ?
Darn it, yes, looks like human error (on my part). Will update.
from joss-reviews.
It looks like you have updated it now. Should we close this issue again or are there outstanding problems?
from joss-reviews.
agreed
from joss-reviews.
Related Issues (20)
- [REVIEW]: OceanBioME.jl: A flexible environment for modelling the coupled interactions between ocean biogeochemistry and physics HOT 18
- [REVIEW]: Pycapacity: a real-time task-space capacity calculation package for robotics and biomechanics HOT 8
- [REVIEW]: UQTestFuns: A Python3 library of uncertainty quantification (UQ) test functions HOT 7
- [PRE REVIEW]: GPU Code Generation of Cardiac Electrophysiology Simulation with MLIR HOT 12
- [REVIEW]: PurpleCaffeine: tracking of quantum programs and experiments HOT 11
- [PRE REVIEW]: BlackBIRDS: Black-Box Inference foR Differentiable Simulators HOT 10
- [PRE REVIEW]: Using the tidyverse with terra objects: the tidyterra package HOT 20
- [PRE REVIEW]: measr: Bayesian psychometric measurement using Stan HOT 8
- [PRE REVIEW]: Iterative-stats: A Python package for basic iterative statistics HOT 10
- [PRE REVIEW]: Bibat: batteries-included Bayesian analysis template HOT 11
- [PRE REVIEW]: FluxNLPModels.jl and KnetNLPModels.jl: Connecting Deep Learning Models with Optimization Solvers HOT 13
- [PRE REVIEW]: epiworldR: Fast Agent-Based Epi Models HOT 11
- [PRE REVIEW]: ZOSPy: optical ray tracing in Python through OpticStudio HOT 14
- [PRE REVIEW]: OpenSkill: A faster asymmetric multi-team, multiplayer rating system HOT 9
- [PRE REVIEW]: StableRLS: Stable Reinforcement Learning for Simulink HOT 7
- [PRE REVIEW]: TensorInference: A Julia package for tensor-based probabilistic inference HOT 41
- [PRE REVIEW]: concstats: Market Structure, Concentration and Inequality Measures, with R HOT 7
- [REVIEW]: PATATO: a Python photoacoustic tomography analysis toolkit HOT 22
- [REVIEW]: GGoutlieR: an R package to identify and visualize unusual geo-genetic patterns of biological samples HOT 7
- [REVIEW]: surtvep: An R package for estimating time-varying effects HOT 10
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from joss-reviews.