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> R is the only real game in town for free software for scientific computing these days. You have a very very narrow definition of scientific computing, exclud

> R is the only real game in town for free software for scientific computing these days. You have a very very narrow definition of scientific computing, excluding a huge part of the field, i.e. anything written in C, C++ or Fortran. And I've never seen people in aerospace or civil engineering use R, it seems to be mostly popular in statistics heavy, "softer" fields such as biology or economics. Edit: to give some examples of what I mean: show me a (molecular dynamics|computational fluid dynamics|finite element method|Poisson solver|magnetohydrodynamics solver|electrodynamics solver|general relativity code|quantum many-body solver|lattice field theory code) written in R. I haven't seen any.

baldfat 11y ago
Just wanted to see a few. R has such a strong Fortran code base that I knew that they needed to be in R somewhere. Molecular Dynamic - https://cran.r-project.org/web/packages/bio3d/index.html https://cran.r-project.org/web/packages/bio3d/index.html computational fluid dynamics - http://search.r-project.org/library/rjacobi/html/xinterp.html http://search.r-project.org/library/rjacobi/html/xinterp.htm... finite element method - https://cran.r-project.org/web/packages/RTriangle/RTriangle.pdf https://cran.r-project.org/web/packages/RTriangle/RTriangle.... Poisson - https://cran.r-project.org/web/packages/isotone/isotone.pdf https://cran.r-project.org/web/packages/isotone/isotone.pdf
- semi-extrinsic 11y ago
  None of those are actually simulation codes. The first and third are pre- and post-processing tools. The second is an interpolation tool. The fourth uses Poisson distributions, which is very different from solving the Poisson equation.
  - s_q_b 11y ago
    We just have a mismatch in the term "scientific programming" based on our perspectives. You seem like you're in the harder sciences in academia, while I'm in data science in industry. I'll certainly cede the point that there's a great deal of important scientific code in many languages that can't be accessed from R.
    - semi-extrinsic 11y ago
      >We just have a mismatch in the term "scientific programming" based on our perspectives. Yes, exactly this.
Mikeb85 11y ago
The thing is, R interoperates very well with C, C++ and Fortran. So when someone who uses R needs to solve one of those problems, they'll generally just use C, C++ and Fortran, then you can call the function/program from R, get your results, chart/analyse them, etc... And of course, R makes data exploration, statistics, and all those easier problems incredibly simple.
- semi-extrinsic 11y ago
  Don't get me wrong, I'm a frequent R user, and it is definitely useful for analysing at simulation results. My point was just that there is a lot of things outside of R's capabilities. Even for analysis there are areas where R is of no use, e.g. when plotting data from 3D turbulence simulations, like Q-criterion isosurfaces: https://www.nas.nasa.gov/SC12/assets/images/content/Chaderjian_N_Blachawk_1.jpg https://www.nas.nasa.gov/SC12/assets/images/content/Chaderji...
  - s_q_b 11y ago
    Yeah, for legacy or speed, you might need to drop down to lower libraries. But R makes that pretty easy.

baldfat 11y ago

Just wanted to see a few. R has such a strong Fortran code base that I knew that they needed to be in R somewhere. Molecular Dynamic - https://cran.r-project.org/web/packages/bio3d/index.html https://cran.r-project.org/web/packages/bio3d/index.html computational fluid dynamics - http://search.r-project.org/library/rjacobi/html/xinterp.html http://search.r-project.org/library/rjacobi/html/xinterp.htm... finite element method - https://cran.r-project.org/web/packages/RTriangle/RTriangle.pdf https://cran.r-project.org/web/packages/RTriangle/RTriangle.... Poisson - https://cran.r-project.org/web/packages/isotone/isotone.pdf https://cran.r-project.org/web/packages/isotone/isotone.pdf

semi-extrinsic 11y ago
None of those are actually simulation codes. The first and third are pre- and post-processing tools. The second is an interpolation tool. The fourth uses Poisson distributions, which is very different from solving the Poisson equation.
- s_q_b 11y ago
  We just have a mismatch in the term "scientific programming" based on our perspectives. You seem like you're in the harder sciences in academia, while I'm in data science in industry. I'll certainly cede the point that there's a great deal of important scientific code in many languages that can't be accessed from R.
  - semi-extrinsic 11y ago
    >We just have a mismatch in the term "scientific programming" based on our perspectives. Yes, exactly this.

Mikeb85 11y ago

The thing is, R interoperates very well with C, C++ and Fortran. So when someone who uses R needs to solve one of those problems, they'll generally just use C, C++ and Fortran, then you can call the function/program from R, get your results, chart/analyse them, etc... And of course, R makes data exploration, statistics, and all those easier problems incredibly simple.

semi-extrinsic 11y ago
Don't get me wrong, I'm a frequent R user, and it is definitely useful for analysing at simulation results. My point was just that there is a lot of things outside of R's capabilities. Even for analysis there are areas where R is of no use, e.g. when plotting data from 3D turbulence simulations, like Q-criterion isosurfaces: https://www.nas.nasa.gov/SC12/assets/images/content/Chaderjian_N_Blachawk_1.jpg https://www.nas.nasa.gov/SC12/assets/images/content/Chaderji...
- s_q_b 11y ago
  Yeah, for legacy or speed, you might need to drop down to lower libraries. But R makes that pretty easy.