将R代码转换为C代码 [英] Converting R code to C code
问题描述
出于速度原因以及将其打包为.exe的能力，我正在考虑将R脚本转换为C代码.我是C的新手.
I'm looking into converting an R script into C-code for speed reasons and for the ability to have it packaged as an .exe. I'm new to C.
我的问题是，使用C语言会更快吗?速率限制步骤是一种排序算法，必须多次将其应用于大向量.我不确定R中的矢量化功能是否会帮助或降低它.我也读过for循环在R中效率低下.
My question is will it be significantly faster in C? The rate limiting step is a sort algorithm that has to be applied a lot of times to big vectors. I'm not sure if the vectorized functionality in R will help this or slow it down. Also I've read that for-loops are inefficient in R.
如果我应该在C中执行此操作，那么哪些库可以帮助我模仿R的某些数据处理功能(如基本矩阵操作)?我应该从哪里开始?现在，我什至不知道如何将数据读入C(逗号分隔的文本文件)中.
If I should do this in C, what libraries might help me mimic some of the data-processing functions of R like basic matrix manipulations? Where should I look to get started? Right now I don't even know how to read my data into C (comma delimited text file).
推荐答案
我将尽力回答这个问题.
I'll try to answer this question as well as I can.
...但是您不问的问题可能更相关:R算法可以在R中更快地进行开发吗?答案通常是是".可以足够快"吗?好吧，如果不尝试(并查看当前的R代码)，就不可能回答.
...but the question your NOT asking is perhaps more relevant: Can the R algorithm be made faster in R? The answer here is usually "yes". Can it be "fast enough"? Well, that is impossible to answer without trying (and seeing the current R code).
问:我的R算法在C语言中会更快吗?
Q: Will my R algorithm be faster in C?
A:是的！如果为该算法编写最佳" C代码，则很有可能会更快.这样做还很可能会很多.
A: Yes! If you write the "best" C code for the algorithm, it will most likely be faster. It will most likely also be a lot more work to do so.
问:大型向量的排序可以在C语言中更快地完成吗?
Q: Can sorting of large vectors be done faster in C?
A:是的.使用多线程，可以大大提高速度. ...但是从在R中调用sort(x, method='quick')开始，看看是否可以改善！对于随机数据，默认方法不是很快.
A: Yes. Using multi-threading, you can improve the speed quite a lot. ...But start by calling sort(x, method='quick') in R and see if that improves things! The default method isn't very fast for random data.
x <- runif(1e7)
system.time( sort(x) ) # 2.50 secs
system.time( sort(x, method='quick') ) # 1.37 secs
#system.time( tommysort(x) ) # 0.51 secs (4 threads)
问:哪些库模仿基本的R函数?
Q: What libraries mimic basic R functions?
A:LAPACK/BLAS处理R中的矩阵数学.如果仅此而已，您会发现比R中的原始库要快得多的库(您也可以在R中使用其中的一些库来提高性能！).
A: LAPACK/BLAS handles matrix math in R. If that's all you need, you can find libraries that are much faster than the vanilla ones in R (you can use some of them in R too to improve performance!).
另一种方法是从R到C进行.Call，从那里您可以使用R的所有功能！ inline软件包和Rcpp软件包可以帮助简化该过程.
Another way is to make a .Call from R to C and from there you have access to all of R's functionality! The inline package and the Rcpp package can help make it easier.
第三种方法是将R嵌入到您的应用程序中. Rinside可以使这一过程变得更容易.
A third way is to embed R in your application. Rinside can help make that easier.
问:如何将CSV数据读入C?
Q: How do I read CSV data into C?
A:查看fopen和fscanf函数. ...并使用它们编写数据导入功能.
A: Look at the fopen and fscanf functions. ...and use them to write a data import function.
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