If you're interested in HMC, we showed how to apply it to the Ising model in https://arxiv.org/abs/1912.03278 with code available in https://github.com/HISKP-LQCD/ising_hmc
Statistical Physics with R: Ising Model with Monte Carlo
11–20 of 70 posts
Re: Statistical Physics with R: Ising Model with Monte Carlo
#12Earlier quoted context omitted.
I wonder how close R was to also take over the scientific computing/machine learning space, instead of Python's numpy/scipy ecosystem.
R is really not for production deployment. It lacks a lot of what made python popular, and its target users were radically different.
R was developed for and by statisticians, for better and worse. I used R a little bit 15-20 years ago, what I remember was that quite a few libraries and function interfaces seemed to be designed to be convenient for interactive use, but if you tried to use them in an automated script, e.g. some analysis you wanted to scale up and repeat 10,000 times while bootstrap sampling or hyperparameter sweeping or what have you, those same library and interface design choices involved bizarre edge cases where functions would sometimes do something completely different (perhaps changing the return type) when invoked with slightly different arguments. All these automation hostile edge causes were annoying to discover and then work around.
None of this was forced by R the language, it was purely a library design thing by the folks writing the libraries. Whereas in contrast, you simply wouldn't and didn't get such library design in mainstream general purpose programming languages (e.g. in C++, java some of this stuff wouldn't even type check) and similarly in python, even though python being dynamic was fertile ground for people to develop completely bonkers and unautomatable numeric and scientific libraries, the customs for how libraries should work were different
This is maybe just a reflection that R and R's libraries were being designed for interactive use by humans doing exploratory data analysis, model fitting etc, unlike other programming languages which are used to automate things or build software products that can be shipped.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#13Earlier quoted context omitted.
I wonder how close R was to also take over the scientific computing/machine learning space, instead of Python's numpy/scipy ecosystem.
I love and use R, but it never became the dominant ML in part because it has three (or more) different object systems and many libraries sort of use their own style. This makes it seem a bit disjointed, in a way that other languages don’t. The R community should have anointed one object system and made tidyverse a core part of R. All that said, R is fantastic and the depth of libraries is extensive. Libs are often wr…
Agree 100% on tidyverse becoming part of the standard library. Some of the language's greatest libraries (like Hyndman's forecasting stuff) basically assume you're using tidyverse already
Re: Statistical Physics with R: Ising Model with Monte Carlo
#14Earlier quoted context omitted.
I wonder how close R was to also take over the scientific computing/machine learning space, instead of Python's numpy/scipy ecosystem.
R is really not for production deployment. It lacks a lot of what made python popular, and its target users were radically different.
Completely disagree. I work at a central bank, helping people make some of the most important economic decisions in my country and plenty of analyses are done purely with R.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#15Earlier quoted context omitted.
One general purpose web framework away
I disagree. R is just not a very nice language. It has some really great statistical and data science packages that were well ahead of the competition 10-15 years ago. The web frameworks were good enough for dashboards and what most people were using R for. But if you wanted to write fast and elegant nom-vectorized code, R is really lacking. I left it for Julia for that reason.
How is Julia in terms of data science dev experience? Nothing ever felt as good as the R+tidyverse combo to me, at least in Python.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#16Does the use of "Statistical Physics" as opposed to "Statistical Mechanics" indicates a European author or a broader scope?
Re: Statistical Physics with R: Ising Model with Monte Carlo
#17Earlier quoted context omitted.
R is really not for production deployment. It lacks a lot of what made python popular, and its target users were radically different.
Completely disagree. I work at a central bank, helping people make some of the most important economic decisions in my country and plenty of analyses are done purely with R.
Were they run in production as nightly jobs or something?
Re: Statistical Physics with R: Ising Model with Monte Carlo
#18Anyone can recommend a good and straightforward to understand -- general -- tutorial or book in Monte Carlo methods, for beginners?
Re: Statistical Physics with R: Ising Model with Monte Carlo
#19Earlier quoted context omitted.
I disagree. R is just not a very nice language. It has some really great statistical and data science packages that were well ahead of the competition 10-15 years ago. The web frameworks were good enough for dashboards and what most people were using R for. But if you wanted to write fast and elegant nom-vectorized code, R is really lacking. I left it for Julia for that reason.
How is Julia in terms of data science dev experience? Nothing ever felt as good as the R+tidyverse combo to me, at least in Python.
Julia is pretty good at basic data science. Working with dataframes is comparable to R's data.tables with the benefit that I don't need to switch languages if I want to run a fast loop over some data as part of a calculation or use a custom data structure.
I'm not a fan of pandas, so I'd say Julia and R beat python at basic dataframe manipulation. Nothing beats kdb+/q at dataframes though imo.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#20Earlier quoted context omitted.
R is really not for production deployment. It lacks a lot of what made python popular, and its target users were radically different.
Completely disagree. I work at a central bank, helping people make some of the most important economic decisions in my country and plenty of analyses are done purely with R.
It is used in finance and banking to build statistical models for research not for deployments in production in the technical sense, I hope.