Earlier quoted context omitted.
I don't think that's accurate: https://trends.google.com/trends/explore?date=today%205-y&ge...
Relieved to know I can still trust HNers to always take hyperbolic statements literally
Not always.
Array Programming with NumPy
11–20 of 114 posts
Re: Array Programming with NumPy
#12For some reason this struck me as inappropriate for the outlet. It's a nice piece as an introduction to array programming with numpy, but seemed out of place to me.
Yeah, this is a review article. Nature is not the right spot for it.
Re: Array Programming with NumPy
#13For some reason this struck me as inappropriate for the outlet. It's a nice piece as an introduction to array programming with numpy, but seemed out of place to me.
Seems to me like it's just a way for the journal and the authors to collect a gigantic number of citations to win the academic citation game. Not that there's anything necessarily wrong with that; NumPy deserves it of course.
Re: Array Programming with NumPy
#14For some reason this struck me as inappropriate for the outlet. It's a nice piece as an introduction to array programming with numpy, but seemed out of place to me.
I think this is great. Nature is really a way for scientists to score points, not a publication that you read cover to cover that needs stylistic consistency. Right now the academic citation-count scoring mechanism doesn’t give enough incentive for people to work on the important infrastructure pieces like Numpy. So this is a good step towards putting scientific priorities in the right place.
Re: Array Programming with NumPy
#15Earlier quoted context omitted.
If, going forward, 5% of all papers that use NumPy to get their results actually cite this paper, it will be one of Nature's most cited papers every year.
There's an interesting trend of what content gets published in peer-reviewed journals vs. blogs/github/etc. I suspect there is an audience segment that strongly values peer reviewed pieces that are equivalent content wise to introductory material in a variety of formats. I wonder if github should add a "Review" feature to provide a similar content authoring experience.
It would be nice if citing repositories were easier-- either for generating a reference for my own code or acknowledging when I've used someone else's code in my research.
There's tons of math and physics blogs that contain useful results that the author wanted to make available but didn't manage to incorporate into a paper. I wonder if there'd be any interest in a sort of GitHub for proofs? It could even use git, since (assuming consistency) isn't math just a DAG anyways (and therefore isomorphic to a neural net, as are all things).
Re: Array Programming with NumPy
#16Looks like there's a new citation for NumPy in town.
"Citing packages in the SciPy ecosystem" lists the existing citations for SciPy, NumPy, scikits, and other -Py things: https://www.scipy.org/citing.html ( source: https://github.com/scipy/scipy.org/blob/master/www/citing.rs... )
A better way to cite requisite software might involve referencing a https://schema.org/SoftwareApplication record in JSON-LD, RDFa, or Microdata; for example: https://news.ycombinator.com/item?id=24489651
But there's as of yet no way to publish JSON-LD, RDFa, or Microdata Linked Data from LaTeX with Computer Modern.
Re: Array Programming with NumPy
#17For some reason this struck me as inappropriate for the outlet. It's a nice piece as an introduction to array programming with numpy, but seemed out of place to me.
I think this is great. Nature is really a way for scientists to score points, not a publication that you read cover to cover that needs stylistic consistency. Right now the academic citation-count scoring mechanism doesn’t give enough incentive for people to work on the important infrastructure pieces like Numpy. So this is a good step towards putting scientific priorities in the right place.
Yep, especially when the author are the people who wrote numpy, I have absolutely no problem with that. It's about time they be recognized for their contribution to the tools of science.
Re: Array Programming with NumPy
#18Ah, just the right time to publish about numpy - right when everyone is moving over to Julia because of numpy's warts.
I'm interested in Julia, but if numpy has warts, I suppose Julia has not yet had time to even grow its skin.
Re: Array Programming with NumPy
#19For some reason this struck me as inappropriate for the outlet. It's a nice piece as an introduction to array programming with numpy, but seemed out of place to me.
I think this is great. Nature is really a way for scientists to score points, not a publication that you read cover to cover that needs stylistic consistency. Right now the academic citation-count scoring mechanism doesn’t give enough incentive for people to work on the important infrastructure pieces like Numpy. So this is a good step towards putting scientific priorities in the right place.
I definitely think things like the infrastructure don't get enough credit. I also mean no criticism of numpy. But is Numpy per se conceptually that innovative, from a computer science perspective? I guess to me this just seemed unusually introductory, about a specific library for a specific language.
Put another way: if I was going to cite numpy, would I cite this? Probably not. Would I cite this paper for any of the more general concepts it covers? Probably not. I'd probably even argue someone shouldn't cite it for that latter reason, as those concepts supercede numpy (and appear in other languages under other names).
Re: Array Programming with NumPy
#20Earlier quoted context omitted.
There's an interesting trend of what content gets published in peer-reviewed journals vs. blogs/github/etc. I suspect there is an audience segment that strongly values peer reviewed pieces that are equivalent content wise to introductory material in a variety of formats. I wonder if github should add a "Review" feature to provide a similar content authoring experience.
It would be nice if citing repositories were easier-- either for generating a reference for my own code or acknowledging when I've used someone else's code in my research. There's tons of math and physics blogs that contain useful results that the author wanted to make available but didn't manage to incorporate into a paper. I wonder if there'd be any interest in a sort of GitHub for proofs? It could even use git, si…
Traditionally that sort of stuff goes in tech reports, dissertations, or text books.
What's missing is the dissemination piece. Somehow people will absolutely refuse to take seriously the job of citing code they use, even when their main result is obtainable by "and then I ran something from scipy/numpy/pytorch/etc."