Category: R Programming
FAQ about R Programming
Namespaces in R Language
In R language, the packages can have namespaces, and currently, all of the base and recommended packages do except the dataset packages. Understanding the use of namespaces is vital if one’s plan to submit a package to CRAN because CRAN requires that the package plays nicely with other submitted packages on CRAN. Namespaces ensure that other packages will not interfere with your code and the package works regardless of the environment in which it’s run.
For example, plyr and Hmisc both provide a function namely summarize(). Loading plyr package and then Hmise, the summarize() function will refer to the Hmisc. However, loading the package in the opposite order, the summarize() function will refer to the plyr package version.
To avoid confusion, one can explicitly refer to the specific function, for example,
> Hmisc::summarize()
and
> plyr::summarize()
Now, the order in which the packages are loaded would not matter.
Namespaces do three things:
- Namespaces allow the package writer to hide functions and data that are meant only for internal use,
- Namespaces prevent functions from breaking when a user (or other package writers) picks a name that clashes with one in the package, and
- Namespaces provide a way to refer to an object within a particular package
Namespace Operators
In R language, there are two operators that work with namespaces.
- Doule-Colon Operator
The double-colon operator:: selects definitions from a particular namespace. The transpose function t() will always be available as the base::t, because it is defined in the base package. Only functions that are exported from the package can be retrieved in this way. - Triple-Colon Operator
The triple-colon operator ::: acts like the double-colon operator but also allows access to hidden objects. Users are more likely to use the getAnywhere() function, which searches multiple packages.
Packages are often inter-dependent, and loading one may cause others to be automatically loaded. The colon operators will also cause automatic loading of the associated package. When packages with namespaces are loaded automatically they are not added to the search list.
How to View Source Code of R Method/ Function?
Source Code of R Method
There are different ways to view the source code of an R method or function. It will help to know how the function is working.
Internal Functions
If you want to see the source code of the internal function (functions from base packages), just type the name of the function at R prompt such as;
> rowMeans
Functions or Methods from S3 Class System
For S3 classes, methods function can be used to list the methods for a particular generic function or class.
> methods(predict)
Note that “Non-Visible functions are asterisked” means that the function is not exported from its package’s namespace.
One can still view its source code via the ::: function such as
> stats:::predict.lm
or by using getAnywhere() function, such as
> getAnywhere(predict.lm)
Note that the getAnywhere() function is useful as you don’t need to know from which package the function or method comes from.
Functions or Methods from S4 Class System
The S4 system is a newer method dispatch system and is an alternative to the S3 system. The package ‘Matrix’ is an example of S4 function.
> library(Matrix)
> chol2inv
The output already offers a lot of information. The standardGeneric is an indicator of an S4 function. The method to see defined S4 methods is to use showMethods(chol2inv), that is;
> showMethods(chol2inv)
The getMethod can be used to see the source code of one of the methods, such as,
> getMethod (“chol2inv”, “diagonalMatrix”)
Functions that Calls Unexported Functions
In the case of unexported functions such as ts.union, .cbindts and .makeNamesTs from the stats namespace, one can view source code of these unexported functions using ::: operator or getAnywhere() function, for example;
> stats::: .makeNamesTs
> getAnywhere(.makeNamesTs)
View on Youtube
