55 lines
2.5 KiB
Plaintext
55 lines
2.5 KiB
Plaintext
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New Rcpp versions 0.6.0 and 0.6.1
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The Rcpp package provides C++ classes that greatly facilitate interfacing C
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or C++ code in R packages using the .Call() interface provided by R.
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Rcpp provides matching C++ classes for a large number of basic R data
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types. Hence, a package author can keep his data in normal R data structure
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without having to worry about translation or transfer to C++. At the same
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time, the data structures can be accessed as easily at the C++ level, and
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used in the normal manner.
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The mapping of data types works in both directions. It is as straightforward
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to pass data from R to C++, as it is it return data from C++ to R. The
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following two sections list supported data types.
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Transfer from R to C++:
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Standard R datatypes that are understood in C++ are
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o named lists containing numeric (i.e. floating point), integer,
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character, logical (i.e. boolean) or Date and Datetime (i.e. POSIXct at
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the microsecond granularity) arguments;
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o data frames containing numeric, integer, logical, character,
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Date, Datetime or Factor columns;
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o named vectors containing numeric or integer values,
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o vectors and matrices of different values
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o character strings
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Transfer from C++ to R:
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Standard C++ datatypes can be returned to R in a named list, the most
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general data type in R. Permissible components of the returns list
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are the following C++ types:
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o double (scalar as well as vectors and vectors of vectors),
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o int (scalar as well as vectors and vectors of vectors), string,
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o STL vector types and vector<vector> types of int and double
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o STL vector of strings
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o internal Rcpp types RcppDate, RcppDateVector, RcppDatetime,
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RcppDatetimeVector, RcppStringVector, RcppVector of int or double,
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RcppMatrix of int or double, RcppFrame
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Rcpp was initially written by Dominick Samperi as part of his contributions
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to RQuantLib, and later released as a standalone package (under both the Rcpp
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and RcppTemplate names). Its development had ceased in late 2006.
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As of November 2008, I have made new release with substantially expanded
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documentation, simpler yet more comprehensive build structure leading to
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easier use of Rcpp from other packages, and support for Windows, Linux and
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Mac OS X (with special thanks to Simon for some extended cluebat waving).
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More information for Rcpp can be found at
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o the package homepage at http://dirk.eddelbuettel.com/code/rcpp.html
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o the R-forge repository at https://r-forge.r-project.org/projects/rcpp/
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o the CRAN page at http://cran.r-project.org/web/packages/Rcpp/index.html
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Regards, Dirk
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