Shulou(Shulou.com)06/02 Report--

This article mainly introduces how to create C++ files in RStudio, with a certain reference value, interested friends can refer to, I hope you can learn a lot after reading this article, the following let the editor take you to know about it.

Create a C++ file in RStudio

By default, everyone has installed RStudio here, and we all create a C++ file from it. There is an advantage of creating it from here, that is, it will directly show a piece of sample code, and we only need to make some changes on it.

First of all, we select: file-- New file-- C++ file in RStudio. After creating a new file, it contains the following contents (here to install the Rcpp package in R, if not, RStudio will automatically help with the installation):

# include using namespace Rcpp;// This is a simple example of exporting a C++ function to R. You can// source this function into an R session using the Rcpp::sourceCpp / / function (or via the Source button on the editor toolbar). Learn// more about Rcpp at://// http://www.rcpp.org/// http://adv-r.had.co.nz/Rcpp.html// http://gallery.rcpp.org///// [[Rcpp::export]] NumericVector timesTwo (NumericVector x) {return x * 2;} / You can include R code blocks in C++ files processed with sourceCpp// (useful for testing and development). The R code will be automatically / / run after the compilation.///*** RtimesTwo (42) * /

We understand it according to the English instructions above.

Details # include using namespace Rcpp

This is the header file, as well as using the Rcpp namespace. In fact, the same is true for the first two lines of a normal C++ code, which is actually very much like library in our R and import in Python, with this, we can name vectors, matrices, data boxes and other object forms that are unique to R in the code, so as to facilitate the mutual transmission of R and some content in C++.

The code in the sample file actually names a function whose input and output objects are numeric vectors. This function is also very simple: an operation that multiplies the vector by 2.

If we want to use the function defined in C++ file in R, we need to add / / [[Rcpp::export]] to the top of the function in C++. It is important to note that a cpp file can define multiple functions, but only one function can be emitted.

Then we click Source at the top right of the file to load our function into the variable space, or run the following command directly in another R script file:

Rcpp::sourceCpp ('Desktop/myfun.cpp')

There is another trick in the sample file, which adds the following command directly to our cpp file:

/ * RtimesTwo (42) * /

After adding this sentence, after we Source this file, we can directly test the function just defined and see the running results of timesTwo (42), which can be used more often during testing.

More content

About some common data types and functions in Rcpp, you can refer to the blog: Rcpp related knowledge collation, which is very good. Carry some content here:

Data type description int integer double numerical bool Boolean (TRUE, FALSE) String character type IntegerVector integer vector NumericVector numerical vector (element type is double) ComplexVector complex vector LogicalVector logical type vector; logical variables of R can take three values: TRUE, FALSE, NA; and C++ Boolean only two, true or false. If the NA of R is converted to a Boolean in C++, true is returned. CharacterVector character type vector IntegerMatrix integer matrix NumericMatrix numerical type matrix (element type is double) LogicalMatrix logical type matrix CharacterMatrix character matrix List list; lists; is similar to the list in R, its elements can make any data type DataFrame data box; data frames; inside Rcpp, the data box is actually Function functional Environment environment type implemented through list Can be used to reference functions in the R environment, functions in other R packages, and types that can be recognized by R by manipulating variables in the R environment RObject

About some basic operations and common functions for matrices and data boxes:

Operation description [n] for a vector type or list, access the nth element. For matrix types, first connect the next column of the matrix to the previous column to form a long column vector and access the nth element. Unlike RMagne, n starts at 0. For the matrix type, access the first element (iQuery j). Unlike RBI and j, they start at 0. Unlike vectors, parentheses are used here. List ["name1"] accesses an element named name1 in List. DataFrame ["name2"] accesses a column named name2 in DataFrame. X.size () returns the length of X; for vectors or matrices, if it is a matrix, first vectorize X.push_back (a) to add a to the end of X; for vector X.push_front (b) to add b to the beginning of X. Applicable to vector X.ncol () returns X number of columns X.nrow () returns X number of rows Thank you for reading this article carefully, I hope the article "how to create C++ documents in RStudio" shared by the editor is helpful to you, and I also hope you can support us, pay attention to the industry information channel, and more related knowledge is waiting for you to learn!

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.