使用S3将包转换为S4类，性能会下降吗?

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问题描述

我有一个R包，当前使用S3类系统，具有两个不同的类和几种用于通用S3函数的方法，例如plot，logLik和update(用于模型公式更新).由于由于没有基于S3中两个参数的继承或分派的事实，我的代码在所有有效性检查和if/else结构上都变得更加复杂，因此我开始考虑将程序包转换为S4 .但是后来我开始阅读S3与S4的优缺点，因此我不确定.我发现 R-bloggers博客帖子关于以下方面的效率问题: S3 vs S4，就像5年前一样，我现在测试了同一件事:

I have an R package which currently uses S3 class system, with two different classes and several methods for generic S3 functions like plot, logLik and update (for model formula updating). As my code has become more complex with all the validity checking and if/else structures due to to the fact that there's no inheritance or dispatching based on two arguments in S3, I have started to think of converting my package to S4. But then I started to read about the advantages and and disadvantages of S3 versus S4, and I'm not so sure anymore. I found R-bloggers blog post about efficiency issues in S3 vs S4, and as that was 5 years ago, I tested the same thing now:

library(microbenchmark)
setClass("MyClass", representation(x="numeric"))
microbenchmark(structure(list(x=rep(1, 10^7)), class="MyS3Class"),
               new("MyClass", x=rep(1, 10^7)) )
Unit: milliseconds
                                                   expr
 structure(list(x = rep(1, 10^7)), class = "MyS3Class")
                       new("MyClass", x = rep(1, 10^7))
       min       lq   median       uq      max neval
 148.75049 152.3811 155.2263 159.8090 323.5678   100
  75.15198 123.4804 129.6588 131.5031 241.8913   100

因此在这个简单的示例中，S4实际上要快一些.然后，我阅读了 SO问题关于使用S3 vs S4，这在很大程度上支持S3.特别是@ joshua-ulrich的回答使我对S4表示怀疑，因为它说

So in this simple example, S4 was actually bit faster. Then I read SO question about using S3 vs S4, which was quite much in favor of S3. Especially @joshua-ulrich 's answer made me doubt against S4, as it said that

如果考虑在优化模型的对数似然性时每次迭代都要更新对象的情况，那将是一个大问题.经过一番谷歌搜索后，我发现约翰·钱伯斯(John Chambers)发布关于此问题，该问题似乎在R 3.0.0中有所更改.

That feels like a big issue if I consider my case where I'm updating my object in every iteration when optimizing log-likelihood of my model. After some googling I found John Chambers post about this issue, which seems to be changing in R 3.0.0.

因此，尽管我认为在代码中使用S4类会有所帮助(例如，从主模型类继承的更多类)以及进行有效性检查等，这还是有益的，但我现在想知道是否值得所有工作都在表现方面?因此，就性能而言，S3和S4之间是否存在真正的性能差异?我还应该考虑其他一些性能问题吗?或者甚至有可能就这个问题说些什么?

So although I feel it would be beneficial to use S4 classes for some clarity in my codes (for example more classes inheriting from the main model class), and for the validity checks etc, I am now wondering is it worth all the work in terms of performance? So, performance wise, is there real performance differences between S3 and S4? Is there some other performance issues I should be considering? Or is it even possible to say something about this issue in general?

如@DWin和@ g-grothendieck所建议，上述基准测试未考虑更改现有对象的插槽的情况.因此，这是另一个与实际应用更为相关的基准(示例中的函数可以是模型中某些元素的获取/设置函数，在最大化对数似然性时会对其进行更改):

As @DWin and @g-grothendieck suggested, the above benchmarking doesn't consider the case where the slot of an existing object is altered. So here's another benchmark which is more relevant to the true application (the functions in the example could be get/set functions for some elements in the model, which are altered when maximizing the log-likelihood):

objS3<-structure(list(x=rep(1, 10^3), z=matrix(0,10,10), y=matrix(0,10,10)),
                 class="MyS3Class")
fnS3<-function(obj,a){
  obj$y<-a
  obj
}

setClass("MyClass", representation(x="numeric",z="matrix",y="matrix"))
objS4<-new("MyClass", x=rep(1, 10^3),z=matrix(0,10,10),y=matrix(0,10,10))
fnS4<-function(obj,a){
  obj@y<-a
  obj
}

a<-matrix(1:100,10,10)
microbenchmark(fnS3(objS3,a),fnS4(objS4,a))
Unit: microseconds
           expr    min     lq median     uq    max neval
 fnS3(objS3, a)  6.531  7.464  7.932  9.331 26.591   100
 fnS4(objS4, a) 21.459 22.393 23.325 23.792 73.708   100

基准测试是在64位Windows 7上的R 2.15.2上执行的.因此，这里S4显然要慢一些.

The benchmarks are performed on R 2.15.2, on 64bit Windows 7. So here S4 is clearly slower.

包转换为S4

使用S3将包转换为S4类，性能会下降吗?

问题描述

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