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Suggested improvements and fixes to JOSS paper #35
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Thank you for the feedbacks, we are tackling them.
We will try to rephrase some things to make this clearer. This package's main argument is visualisation. This is totally complementary to the packages that you mention and not at all to be compared with. SALib, which I am a maintainer of, is the most complete package in Python for computing indices. Here we have one extra method to compute indices, but it's theoretically, and asymptotically, Sobol' indices. i.e. the same as what is in SALib and SciPy (recent version, I am a maintainer and the one who added it to SciPy with help from even Saltelli, Kucherenko and Owen). I am not talking about the others are not in the same league IMHO. OpenTURNS if you want to cite something else would be better. The value proposition here is the visualisation method. It's not just a tool to show things, but a tool providing new insights and analysis. |
@matt-graham we addressed your points, thanks again. What remains is providing a script to reproduce the figure itself. Moving this to the other issues. |
Sorry missed this part of your response previously:
Being 'in the same league' is very subjective and I would say not of relevance here. There is an explicit requirement as part of the review checklist to check that the paper 'describe[s] how this software compares to other commonly-used packages' which I still think the current paper does not satisfy completely. I would also say only citing other packages for which you are a developer is not ideal. The examples I gave were not meant to be prescriptive and agree that OpenTURNS looks like it would be another relevant package to compare to, though I also think
would itself be a useful comparison point to put in paper to make clear what SimDec brings over existing available packages. |
Not relevant for this paper yes. Still, SALib and SciPy are the references in Python. Like sensobol would be a reference in R. This is not an opinion but a fact. See https://www.sciencedirect.com/science/article/pii/S1364815224000380
Well, I contributed to almost all of them in the Python space. Either by creating issues, talking privately to maintainers, or at workshops. This is a small space and we all know each other. Both on the dev side and the research side. OpenTURNS, I made my PhD with it and interacted with the devs and collaborated on a few projects with them (see my Batman paper in JOSS for a quick glance.) chaospy is only providing Sobol' indices as an output from the Polynomial Chaos decomposition. i.e. not at all the focus of the project. It's similar to scikit-learn which proposes to get feature importance with a Random Forest.
The text now reads:
Without rewriting an article about SimDec, I don't see what is missing here to say that the visualisation is the new thing. No other package has it because none of them is focused on visualisation. I don't see what it would bring to the discussion to add the list of packages about SA and say they don't do it. It's out of their scope, nothing more. |
Raising as part of JOSS review openjournals/joss-reviews/issues/6713
Some assorted changes I would recommend making to the JOSS paper
https://simdec.io
pointing to web dashboard a hyperlinkchaospy
allows computing sensitivity indices as doesSALib
, and it looks like the packagesensitivity
might also be relevant.The text was updated successfully, but these errors were encountered: