\input texinfo
@c %**start of header
@setfilename R-exts.info
@settitle Writing R Extensions
@setchapternewpage on
@c %**end of header

@c @documentencoding ISO-8859-1

@syncodeindex fn vr

@dircategory Programming
@direntry
* R Extensions: (R-exts).      Writing R Extensions.
@end direntry

@finalout

@include R-defs.texi
@include version.texi

@ifinfo
This is a guide to extending R.

@Rcopyright{1999}

@ignore
Permission is granted to process this file through TeX and print the
results, provided the printed document carries a copying permission
notice identical to this one except for the removal of this paragraph
(this paragraph not being relevant to the printed manual).

@end ignore

@permission{}
@c ---------- ^- read that
@end ifinfo

@titlepage
@title Writing R Extensions
@subtitle Version @value{VERSION}
@author R Development Core Team
@page
@vskip 0pt plus 1filll
@permission{}

@Rcopyright{1999}

@value{ISBN-exts}
@end titlepage

@c @ifnothtml
@contents
@c @end ifnothtml

@ifnottex
@node Top, Acknowledgements, (dir), (dir)
@top Writing R Extensions

This is a guide to extending @R{}, describing the process of creating
@R{} add-on packages, writing @R{} documentation, @R{}'s system and
foreign language interfaces, and the @R{} @acronym{API}.

The current version of this document is @value{VERSION}.

@value{ISBN-exts}
@end ifnottex

@menu
* Acknowledgements::
* Creating R packages::
* Writing R documentation files::
* Tidying and profiling R code::
* Debugging::
* System and foreign language interfaces::
* The R API::
* Generic functions and methods::
* Linking GUIs and other front-ends to R::
* Function and variable index::
* Concept index::
@end menu

@node Acknowledgements, Creating R packages, Top, Top
@unnumbered Acknowledgements


The contributions of Saikat DebRoy (who wrote the first draft of a guide
to using @code{.Call} and @code{.External}) and of Adrian Trapletti (who
provided information on the C++ interface) are gratefully acknowledged.

@node Creating R packages, Writing R documentation files, Acknowledgements, Top
@chapter Creating R packages
@cindex Packages
@cindex Creating packages

Packages provide a mechanism for loading optional code and attached
documentation as needed.  The @R{} distribution itself includes about 25
packages.

In the following, we assume that you know the @samp{library()} command,
including its @samp{lib.loc} argument, and we also assume basic
knowledge of the @code{INSTALL} utility.  Otherwise, please look at @R{}'s
help pages

@example
?library
?INSTALL
@end example

@noindent
before reading on.

A computing environment including a number of tools is assumed; the
``R Installation and Administration'' manual describes what is needed.
Under a Unix-alike most of the tools are likely to be present by
default, but Microsoft Windows and Mac OS X will require careful setup.

Once a source package is created, it must be installed by
the command @code{R CMD INSTALL}.
@ifset UseExternalXrefs
@xref{Add-on packages, , Add-on-packages,
R-admin, R Installation and Administration}, for further details.
@end ifset

Other types of extensions are supported (but rare): @xref{Package types}.

@menu
* Package structure::
* Configure and cleanup::
* Checking and building packages::
* Writing package vignettes::
* Submitting a package to CRAN::
* Package name spaces::
* Writing portable packages::
* Diagnostic messages::
* Internationalization::
* CITATION files::
* Package types::
* Services::
@end menu

@node Package structure, Configure and cleanup, Creating R packages, Creating R packages
@section Package structure
@cindex Package structure

The sources of a @R{} package consists of a subdirectory containing a
file @file{DESCRIPTION} and the subdirectories @file{R}, @file{data},
@file{demo}, @file{exec}, @file{inst}, @file{man}, @file{po},
@file{src}, and @file{tests} (some of which can be missing).  The
package subdirectory may also contain files @file{INDEX},
@file{NAMESPACE}, @file{configure}, @file{cleanup}, @file{LICENSE},
@file{LICENCE}, @file{COPYING} and @file{NEWS}.  Other files such as
@file{INSTALL} (for non-standard installation instructions),
@file{README} or @file{ChangeLog} will be ignored by @R{}, but may be
useful to end-users.

The @file{DESCRIPTION} and @file{INDEX} files are described in the
subsections below.  The @file{NAMESPACE} file is described in the
section on @ref{Package name spaces}.

@cindex configure file
@cindex cleanup file

The optional files @file{configure} and @file{cleanup} are (Bourne
shell) script files which are executed before and (provided that option
@option{--clean} was given) after installation on Unix-alikes, see
@ref{Configure and cleanup}.  The analogues on Windows are
@file{configure.win} and @file{cleanup.win}

@cindex LICENSE file
@cindex LICENCE file
@cindex COPYING file

The optional file @file{LICENSE}/@file{LICENCE} or @file{COPYING} (where
the former names are preferred) contains a copy of the license to the
package, e.g.@: a copy of the @acronym{GNU} public license.  Whereas you
should feel free to include a license file in your @emph{source}
distribution, please do not arrange to @emph{install} yet another copy
of the @acronym{GNU} @file{COPYING} or @file{COPYING.LIB} files but
refer to the copies on @url{http://www.r-project.org/Licenses/} and
included in the @R{} distribution (in directory @file{share/licenses}).

For the conventions for files @file{NEWS} and @file{ChangeLog} in the
@acronym{GNU} project see
@uref{http://@/www.gnu.org/prep/standards/standards.html#Documentation}.

The package subdirectory should be given the same name as the package.
Because some file systems (e.g., those on Windows and by default on Mac
OS X) are not case-sensitive, to maintain portability it is strongly
recommended that case distinctions not be used to distinguish different
packages.  For example, if you have a package named @file{foo}, do not
also create a package named @file{Foo}.

To ensure that file names are valid across file systems and supported
operating system platforms, the @acronym{ASCII} control characters as
well as the characters @samp{"}, @samp{*}, @samp{:}, @samp{/}, @samp{<},
@samp{>}, @samp{?}, @samp{\}, and @samp{|} are not allowed in file
names.  In addition, files with names @samp{con}, @samp{prn},
@samp{aux}, @samp{clock$}, @samp{nul}, @samp{com1} to @samp{com9}, and
@samp{lpt1} to @samp{lpt9} after conversion to lower case and stripping
possible ``extensions'' (e.g., @samp{lpt5.foo.bar}), are disallowed.
Also, file names in the same directory must not differ only by case (see
the previous paragraph).  In addition, the names of @samp{.Rd} files
will be used in URLs and so must be @acronym{ASCII} and not contain
@code{%}.  For maximal portability filenames should only contain only
@acronym{ASCII} characters not excluded already (that is
@code{A-Za-z0-9._!#$%&+,;=@@^()@{@}'[]} --- we exclude space as many
utilities do not accept spaces in file paths): non-English alphabetic
characters cannot be guaranteed to be supported in all locales.  It
would be good practice to avoid the shell metacharacters
@code{()@{@}'[]$}.

A source package if possible should not contain binary executable files:
they are not portable, and a security risk if they are of the
appropriate architecture.  @command{R CMD check} will warn about
them@footnote{false positives are possible, but only a handful have been
seen so far.} unless they are listed (one filepath per line) in a file
@file{BinaryFiles} at the top level of the package.  Note that
@acronym{CRAN} will no longer accept submissions containing binary files
even if they are listed.

The @R{} function @code{package.skeleton} can help to create the
structure for a new package: see its help page for details.

@menu
* The DESCRIPTION file::
* The INDEX file::
* Package subdirectories::
* Package bundles::
* Data in packages::
@end menu

@node The DESCRIPTION file, The INDEX file, Package structure, Package structure
@subsection The @file{DESCRIPTION} file
@cindex DESCRIPTION file

The @file{DESCRIPTION} file contains basic information about the package
in the following format:

@quotation
@cartouche
@smallexample
Package: pkgname
Version: 0.5-1
Date: 2004-01-01
Title: My First Collection of Functions
Author@@R: c(person("Joe", "Developer",
                    email = "Joe.Developer@@some.domain.net"),
             person("A.", "User", role = "ctb",
	            email = "A.User@@whereever.net"))
Author: Joe Developer <Joe.Developer@@some.domain.net>, with
  contributions from A. User <A.User@@whereever.net>.
Maintainer: Joe Developer <Joe.Developer@@some.domain.net>
Depends: R (>= 1.8.0), nlme
Suggests: MASS
Description: A short (one paragraph) description of what
  the package does and why it may be useful.
License: GPL (>= 2)
URL: http://www.r-project.org, http://www.another.url
BugReports: http://pkgname.bugtracker.url
@end smallexample
@end cartouche
@end quotation

@noindent
The format is that of a `Debian Control File' (see the help for
@samp{read.dcf} and
@uref{http://www.debian.org/@/doc/@/debian-policy/@/ch-controlfields.html}:
@R{} does not require encoding in UTF-8).  Continuation lines (for
example, for descriptions longer than one line) start with a space or
tab.  The @samp{Package}, @samp{Version}, @samp{License},
@samp{Description}, @samp{Title}, @samp{Author}, and @samp{Maintainer}
fields are mandatory, all other fields are optional.

For maximal portability, the @file{DESCRIPTION} file should be written
entirely in @acronym{ASCII} --- if this is not possible it must contain
an @samp{Encoding} field (see below).

The mandatory @samp{Package} field gives the name of the package.  This should
contain only letters, numbers and dot, and start with a letter.
(Translation packages are allowed names of the form
@samp{Translation-@var{ll}}.)

The mandatory @samp{Version} field gives version of the package.  This is a
sequence of at least @emph{two} (and usually three) non-negative
integers separated by single @samp{.} or @samp{-} characters.  The
canonical form is as shown in the example, and a version such as
@samp{0.01} or @samp{0.01.0} will be handled as if it were @samp{0.1-0}.

The mandatory @samp{License} field should specify the license of the package in
the following standardized form.  Alternatives are indicated @emph{via}
vertical bars.  Individual specifications must be one of
@itemize @bullet
@item
One of the ``standard'' short specifications
@example
GPL-2 GPL-3 LGPL-2 LGPL-2.1 LGPL-3 AGPL-3 Artistic-1.0 Artistic-2.0
@end example
as made available @emph{via} @uref{http://@/www.r-project.org/@/Licenses/} and
contained in subdirectory @file{share/licenses} of the @R{} source or home
directory.
@item
The names of abbreviations of free or open source software (FOSS, e.g.,
@uref{http://en.wikipedia.org/wiki/FOSS}) licenses as contained in the
license data base in file @file{share/licenses/license.db} in the @R{}
source or home directory, possibly (for versioned licenses) followed by
a version restriction of the form @samp{(@var{op} @var{v})} with
@var{op} one of the comparison operators @samp{<}, @samp{<=}, @samp{>},
@samp{>=}, @samp{==}, or @samp{!=} and @var{v} a numeric version
specification (strings of non-negative integers separated by @samp{.}),
possibly combined @emph{via} @samp{,} (see below for an example).  For
versioned licenses, one can also specify the name followed by the
version, or combine an existing abbreviation and the version with a
@samp{-}.  Further free (see
@uref{http://@/www.fsf.org/@/licenses/@/license-list.html}) or open
software (see
@uref{http://@/www.opensource.org/@/licenses/@/bsd-license.php})
licenses will be added to this data base if necessary.
@item
One of the strings @samp{file LICENSE} or @samp{file LICENCE} referring
to a file named @file{LICENSE} or @file{LICENCE} in the package (source
and installation) top-level directory.
@item
The string @samp{Unlimited}, meaning that there are no restrictions on
distribution or use other than those imposed by relevant laws.
@end itemize
If a package license @emph{extends} a base FOSS license (e.g., using
GPL-3 or AGPL-3 with an attribution clause), the extension should be
placed in file @file{LICENSE} (or @file{LICENCE}), and the string
@samp{+ file LICENSE} (or @samp{+ file LICENCE}, respectively) should be
appended to the corresponding individual license specification.

Examples for standardized specifications include
@example
License: GPL-2
License: GPL (>= 2) | BSD
License: LGPL (>= 2.0, < 3) | Mozilla Public License
License: GPL-2 | file LICENCE
License: Artistic-1.0 | AGPL-3 + file LICENSE
@end example
Please note in particular that ``Public domain'' is not a valid license.

It is very important that you include this license information!
Otherwise, it may not even be legally correct for others to distribute
copies of the package.  Do not use the @samp{License} field for
copyright information: if needed, use a @samp{Copyright} field.

Please ensure that the license you choose also covers any dependencies
(including system dependencies) of your package: it is particularly
important that any restrictions on the use of such dependencies are
evident to people reading your @file{DESCRIPTION} file.

The mandatory @samp{Description} field should give a comprehensive description of
what the package does.  One can use several (complete) sentences, but
only one paragraph.

The mandatory @samp{Title} field should give a short description of the
package. Some package listings may truncate the title to 65 characters
in order to keep the overall size of the listing limited.
It should be capitalized, not use any markup, not have any continuation
lines, and not end in a period.

The mandatory @samp{Author} field describes who wrote the package.  It
is a plain text field intended for human readers, but not for automatic
processing (such as extracting the email addresses of all listed
contributors).  The @samp{Author@@R} field can be used to provide a
refined, machine-readable description of the package ``authors'' (in
particular specifying their precise @emph{roles}), via suitable @R{}
code (see @code{?citation} for more information).  In @R{} 2.12.0 or
later, auto-generated citation information takes advantage of this
specification, and eventually, Author and Maintainer fields will be
auto-generated from it if needed.

The mandatory @samp{Maintainer} field should give a @emph{single} name
with a @emph{valid} (RFC 2822) email address in angle brackets (for
sending bug reports etc.).  It should not end in a period or comma.

The @samp{Date} field gives the release date of the current
version of the package.  It is strongly recommended to use the yyyy-mm-dd
format conforming to the ISO 8601 standard.

The @samp{Depends} field gives a comma-separated list of
package names which this package depends on.  The package name may be
optionally followed by a comment in parentheses.  The comment should
contain a comparison operator@footnote{only @samp{>=} and @samp{<=} were
supported prior to @R{} 2.7.0, and only @samp{>=} is supported for
package versions by @code{install.packages}.}, whitespace and a valid
version number).  You can also use the special package name @samp{R} if
your package depends on a certain version of @R{} --- e.g., if the
package works only with @R{} version 2.11.0 or later, include @samp{R
(>= 2.11.0)} in the @samp{Depends} field.  Both @code{library} and the
@R{} package checking facilities use this field, hence it is an error to
use improper syntax or misuse the @samp{Depends} field for comments on
other software that might be needed.  Other dependencies (external to
the @R{} system) should be listed in the @samp{SystemRequirements}
field, possibly amplified in a separate @file{README} file.  The @R{}
@command{INSTALL} facilities check if the version of @R{} used is recent
enough for the package being installed, and the list of packages which
is specified will be attached (after checking version requirements)
before the current package, both when @code{library} is called and when
preparing for lazy-loading.

As from @R{} 2.7.0 a package (or @samp{R}) can appear more than once in
the @samp{Depends}, but only the first occurrence will be used in
earlier versions of @R{}.  (Unfortunately all occurrences will be checked,
so only @samp{>=} and @samp{<=} can be used.)

The @samp{Imports} field lists packages whose name spaces are
imported from (as specified in the @file{NAMESPACE} file) but which do
not need to be attached.  Name spaces accessed by the @samp{::} and
@samp{:::} operators must be listed here, or in @samp{Suggests} or
@samp{Enhances} (see below).  Ideally this field will include all the
standard packages that are used, and it is important to include S4-using
packages (as their class definitions can change and the
@file{DESCRIPTION} file is used to decide which packages to re-install
when this happens).  Packages declared in the @samp{Depends} field
should not also be in the @samp{Imports} field.  Version requirements
can be specified, but will @strong{not} be checked when the namespace is
loaded (whereas they are checked by @command{R CMD check}).

The @samp{Suggests} field uses the same syntax as
@samp{Depends} and lists packages that are not necessarily needed.  This
includes packages used only in examples, tests or vignettes
(@pxref{Writing package vignettes}), and packages loaded in the body of
functions.  E.g., suppose an example from package @pkg{foo} uses a
dataset from package @pkg{bar}. Then it is not necessary to have
@pkg{bar} use of @pkg{foo} unless one wants to execute all the
examples/tests/vignettes: it is useful to have @pkg{bar}, but not
necessary.   Version requirements can be specified, and will be used by
@command{R CMD check}.

Finally, the @samp{Enhances} field lists packages ``enhanced''
by the package at hand, e.g., by providing methods for classes from
these packages.  Version requirements can be specified, but are
currently not used.

The general rules are

@itemize @bullet
@item
Packages whose name space only is needed to load the package using
@code{library(@var{pkgname})} must be listed in the @samp{Imports}
field and not in the @samp{Depends} field.
@item
Packages that need to be attached to successfully load the package using
@code{library(@var{pkgname})} must be listed in the @samp{Depends}
field, only.
@item
All packages that are needed to successfully run @code{R CMD check} on
the package must be listed in one of @samp{Depends} or @samp{Suggests}
or @samp{Imports}.  Packages used to run examples or tests conditionally
(e.g.@: @emph{via} @code{if(require(@var{pkgname}))}) should be listed
in @samp{Suggests} or @samp{Enhances}.  (This allows checkers to ensure
that all the packages needed for a complete check are installed.)
@end itemize

@noindent
In particular, large packages providing ``only'' data for examples or
vignettes should be listed in @samp{Suggests} rather than @samp{Depends}
in order to make lean installations possible.

Version dependencies in the @samp{Depends} field are used by
@code{library} when it loads the package, and @code{install.packages}
checks versions for the @samp{Imports} and (for @code{dependencies =
TRUE}) @samp{Suggests} fields.

The @samp{URL} field may give a list of @acronym{URL}s
separated by commas or whitespace, for example the homepage of the
author or a page where additional material describing the software can
be found.  These @acronym{URL}s are converted to active hyperlinks in
@acronym{CRAN} package listings.

The @samp{BugReports} field may contain a single
@acronym{URL} to which bug reports about the package should be
submitted.  This @acronym{URL} will be used by @code{bug.reports}
instead of sending an email to the maintainer.

Base and recommended packages (i.e., packages contained in the @R{}
source distribution or available from @acronym{CRAN} and recommended to
be included in every binary distribution of @R{}) have a @samp{Priority}
field with value @samp{base} or @samp{recommended}, respectively.  These
priorities must not be used by other packages.

An @samp{Collate} field can be used for controlling the
collation order for the @R{} code files in a package when these are
processed for package installation.  The default is to collate according
to the @samp{C} locale.  If present, the collate specification must list
@emph{all} @R{} code files in the package (taking possible OS-specific
subdirectories into account, see @ref{Package subdirectories}) as a
whitespace separated list of file paths relative to the @file{R}
subdirectory.
@c % double quotes are not allowed in path names, for Windows
Paths containing white space or quotes need to be quoted.  An
OS-specific collation field (@samp{Collate.unix} or
@samp{Collate.windows}) will be used instead of @samp{Collate}.

The @samp{LazyLoad} and @samp{LazyData} fields control whether
the @R{} objects and the datasets (respectively) use lazy-loading: set
the field's value to @samp{yes} or @samp{true} for lazy-loading and
@samp{no} or @samp{false} for no lazy-loading.  (Capitalized values are
also accepted.)  If the package you are writing uses the @pkg{methods}
package, specify @samp{LazyLoad: yes}.

The @samp{ZipData} field controls whether the automatic
Windows build will zip up the data directory or no: set this to
@samp{no} if your package will not work with a zipped data directory.

If the @file{DESCRIPTION} file is not entirely in @acronym{ASCII} it
should contain an @samp{Encoding} field specifying an encoding.  This is
used as the encoding of the @file{DESCRIPTION} file itself and of the
@file{R} and @file{NAMESPACE} files, and as the default encoding of
@file{.Rd} files.  The examples are assumed to be in this encoding when
running @command{R CMD check}, and it is used for the encoding of the
@code{CITATION} file.  Only encoding names @code{latin1}, @code{latin2}
and @code{UTF-8} are known to be portable.  (Do not specify an encoding
unless one is actually needed: doing so makes the package @emph{less}
portable.)

The @samp{OS_type} field specifies the OS(es) for which the
package is intended.  If present, it should be one of @code{unix} or
@code{windows}, and indicates that the package can only be installed
on a platform with @samp{.Platform$OS.type} having that value.

The @samp{Type} field specifies the type of the package:
@pxref{Package types}.

@quotation Note
There should be no @samp{Built} or @samp{Packaged} fields, as these are
added by the package management tools.
@end quotation

One can add subject classifications for the content of the package using
the fields @samp{Classification/ACM} (using the Computing
Classification System of the Association for Computing Machinery,
@uref{http://www.acm.org/class/}), @samp{Classification/JEL} (the
Journal of Economic Literature Classification System,
@uref{http://www.aeaweb.org/journal/jel_class_system.html}), or
@samp{Classification/MSC} (the Mathematics Subject Classification of the
American Mathematical Society, @uref{http://www.ams.org/msc/}).  The
subject classifications should be comma-separated lists of the
respective classification codes, e.g., @samp{Classification/ACM: G.4,
H.2.8, I.5.1}.

Finally, an @samp{Language} field can be used to indicate if
the package documentation is not in English: this should be a
comma-separated list of standard (not private use or grandfathered) IETF
language tags as currently defined by RFC 5646
(@uref{http://tools.ietf.org/html/rfc5646}, see also
@uref{http://en.wikipedia.org/wiki/IETF_language_tag}), i.e., use
language subtags which in essence are 2-letter ISO 639-1
(@uref{http://en.@/wikipedia.@/org/wiki/ISO_639-1}) or 3-letter ISO
639-3 (@uref{http://en.@/wikipedia.@/org/wiki/ISO_639-3}) language
codes.

@node The INDEX file, Package subdirectories, The DESCRIPTION file, Package structure
@subsection The @file{INDEX} file
@cindex INDEX file

The optional file @file{INDEX} contains a line for each sufficiently
interesting object in the package, giving its name and a description
(functions such as print methods not usually called explicitly might not
be included).  Normally this file is missing and the corresponding
information is automatically generated from the documentation sources
(using @code{tools::Rdindex()}) when installing from source.

Rather than editing this file, it is preferable to put customized
information about the package into an overview man page
(@pxref{Documenting packages}) and/or a vignette (@pxref{Writing package
vignettes}).

@node Package subdirectories, Package bundles, The INDEX file, Package structure
@subsection Package subdirectories
@cindex Package subdirectories

The @file{R} subdirectory contains @R{} code files, only.  The code
files to be installed must start with an @acronym{ASCII} (lower or upper
case) letter or digit and have one of the extensions @file{.R},
@file{.S}, @file{.q}, @file{.r}, or @file{.s}.  We recommend using
@file{.R}, as this extension seems to be not used by any other software.
It should be possible to read in the files using @code{source()}, so
@R{} objects must be created by assignments.  Note that there need be no
connection between the name of the file and the @R{} objects created by it.
Ideally, the @R{} code files should only directly assign @R{} objects
and definitely should not call functions with side effects such as
@code{require} and @code{options}.  If computations are required to
create objects these can use code `earlier' in the package (see the
@samp{Collate} field) plus, @emph{only if lazyloading is used},
functions in the @samp{Depends} packages provided that the objects
created do not depend on those packages except @emph{via} name space
imports.  (Packages without namespaces will work under somewhat less
restrictive assumptions.)

Two exceptions are allowed: if the @file{R} subdirectory contains a file
@file{sysdata.rda} (a saved image of @R{} objects) this will be
lazy-loaded into the name space/package environment -- this is intended
for system datasets that are not intended to be user-accessible @emph{via}
@code{data}.  Also, files ending in @samp{.in} will be allowed in the
@file{R} directory to allow a @file{configure} script to generate
suitable files.

Only @acronym{ASCII} characters (and the control characters tab,
formfeed, LF and CR) should be used in code files.  Other characters are
accepted in comments, but then the comments may not be readable in
e.g.@: a UTF-8 locale.  Non-@acronym{ASCII} characters in object names
will normally@footnote{This is true for OSes which implement the
@samp{C} locale: Windows' idea of the @samp{C} locale uses the WinAnsi
charset.} fail when the package is installed.  Any byte will be
allowed@footnote{It is good practice to encode them as octal or hex
escape sequences.} in a quoted character string (but @code{\uxxxx}
escapes should not be used unless the package depends on @code{R (>=
2.10)}), but non-@acronym{ASCII} character strings may not be usable in
some locales and may display incorrectly in others.


@findex .First.lib
@findex .Last.lib
@findex library.dynam
Various @R{} functions in a package can be used to initialize and clean
up.  For packages without a name space, these are @code{.First.lib} and
@code{.Last.lib}.  (@xref{Load hooks}, for packages with a name space.)
It is conventional to define these functions in a file called
@file{zzz.R}.  If @code{.First.lib} is defined in a package, it is
called with arguments @code{libname} and @code{pkgname} after the
package is loaded and attached.  A common use is to call
@code{library.dynam} inside @code{.First.lib} to load compiled code:
another use is to call those functions with side effects.  If
@code{.Last.lib} exists in a package it is called (with argument the
full path to the installed package) just before the package is detached.
It is uncommon to detach packages and rare to have a @code{.Last.lib}
function: one use is to call @code{library.dynam.unload} to unload
compiled code.


The @file{man} subdirectory should contain (only) documentation files
for the objects in the package in @dfn{R documentation} (Rd) format.
The documentation filenames must start with an @acronym{ASCII} (lower or
upper case) letter or digit and have the extension @file{.Rd} (the
default) or @file{.rd}.  Further, the names must be valid in
@samp{file://} URLs, which means@footnote{More precisely, they can
contain the English alphanumeric characters and the symbols @samp{$ - _
. + ! ' ( ) , ; @ = &}.}  they must be entirely @acronym{ASCII} and not
contain @samp{%}.  @xref{Writing R documentation files}, for more
information.  Note that all user-level objects in a package should be
documented; if a package @var{pkg} contains user-level objects which are
for ``internal'' use only, it should provide a file
@file{@var{pkg}-internal.Rd} which documents all such objects, and
clearly states that these are not meant to be called by the user.  See
e.g.@: the sources for package @pkg{grid} in the @R{} distribution for
an example.  Note that packages which use internal objects extensively
should hide those objects in a name space, when they do not need to be
documented (@pxref{Package name spaces}).

Having a @file{man} directory containing no documentation files may give
an installation error.

The @file{R} and @file{man} subdirectories may contain OS-specific
subdirectories named @file{unix} or @file{windows}.

The sources and headers for the compiled code are in @file{src}, plus
optionally a file @file{Makevars} or @file{Makefile}.  When a package is
installed using @code{R CMD INSTALL}, @command{make} is used to control
compilation and linking into a shared object for loading into @R{}.
There are default variables and rules for this (determined when @R{} is
configured and recorded in
@file{@var{R_HOME}/etc@var{R_ARCH}/Makeconf}), providing support for C,
C++, FORTRAN 77, Fortran 9x@footnote{Note that Ratfor is not supported.
If you have Ratfor source code, you need to convert it to FORTRAN.  Only
FORTRAN-77 (which we write in upper case) is supported on all platforms,
but most also support Fortran-95 (for which we use title case).  If you
want to ship Ratfor source files, please do so in a subdirectory of
@file{src} and not in the main subdirectory.}, Objective C and Objective
C++@footnote{either or both of which may not be supported on particular
platforms} with associated extensions @file{.c}, @file{.cc} or
@file{.cpp}, @file{.f}, @file{.f90} or @file{.f95}, @file{.m}, and
@file{.mm} or @file{.M}, respectively.  We recommend using @file{.h} for
headers, also for C++@footnote{Using @file{.hpp}, although somewhat
popular, is not guaranteed to be portable.} or Fortran 9x include files.
(Use of extension @file{.C} for C++ is now defunct.)


It is not portable (and may not be possible at all) to mix all these
languages in a single package, and we do not support using both C++ and
Fortran 9x. Because @R{} itself uses it, we know that C and FORTRAN 77
can be used together and mixing C and C++ seems to be widely successful.

If your code needs to depend on the platform there are certain defines
which can used in C or C++.  On all Windows builds (even 64-bit ones)
@samp{WIN32} will be defined: on 64-bit Windows builds also
@samp{WIN64}, and on Mac OS X @samp{__APPLE__} and @samp{__APPLE_CC__}
are defined.

The default rules can be tweaked by setting macros@footnote{the POSIX
terminology, called `make variables' by GNU make.} in a file
@file{src/Makevars} (@pxref{Using Makevars}).  Note that this mechanism
should be general enough to eliminate the need for a package-specific
@file{src/Makefile}.  If such a file is to be distributed, considerable
care is needed to make it general enough to work on all @R{} platforms.
If it has any targets at all, it should have an appropriate first target
named @samp{all} and a (possibly empty) target @samp{clean} which
removes all files generated by Make (to be used by @samp{R CMD INSTALL
--clean} and @samp{R CMD INSTALL --preclean}).  There are
platform-specific file names on Windows: @file{src/Makevars.win} takes
precedence over @file{src/Makevars} and @file{src/Makefile.win} must be
used. Some @command{make} programs require makefiles to have a complete
final line, including a newline.

A few packages use the @file{src} directory for purposes other than
making a shared object (e.g.@: to create executables).  Such packages
should have files @file{src/Makefile} and @file{src/Makefile.win}
(unless intended for only Unix-alikes or only Windows).

The @file{data} subdirectory is for data files: @xref{Data in packages}.

The @file{demo} subdirectory is for @R{} scripts (for running @emph{via}
@code{demo()}) that demonstrate some of the functionality of the
package.  Demos may be interactive and are not checked automatically, so
if testing is desired use code in the @file{tests} directory.  The
script files must start with a (lower or upper case) letter and have one
of the extensions @file{.R} or @file{.r}.  If present, the @file{demo}
subdirectory should also have a @file{00Index} file with one line for
each demo, giving its name and a description separated by white
space. (Note that it is not possible to generate this index file
automatically.)

The contents of the @file{inst} subdirectory will be copied recursively
to the installation directory (except perhaps hidden files with names
starting with @samp{.}).  Subdirectories of @file{inst} should not
interfere with those used by @R{} (currently, @file{R}, @file{data},
@file{demo}, @file{exec}, @file{libs}, @file{man}, @file{help},
@file{html}, @file{latex}, @file{R-ex} and @file{Meta}).  The copying of
the @file{inst} happens after @file{src} is built so its @file{Makefile}
can create files to be installed.  Note that with the exceptions of
@file{INDEX}, @file{LICENSE}/@file{LICENCE}, @file{COPYING} and
@file{NEWS}, information files at the top level of the package will
@emph{not} be installed and so not be known to users of Windows and Mac
OS X compiled packages (and not seen by those who use @command{R CMD
INSTALL} or @command{install.packages} on the tarball).  So any
information files you wish an end user to see should be included in
@file{inst}.

Note that if the named exceptions also occur in @file{inst}, the version
in @file{inst} will be that seen in the installed package.

@findex CITATION
@cindex citation
One thing you might like to add to @file{inst} is a @file{CITATION} file
for use by the @code{citation} function.

Subdirectory @file{tests} is for additional package-specific test code,
similar to the specific tests that come with the @R{} distribution.
Test code can either be provided directly in a @file{.R} file, or
@emph{via} a @file{.Rin} file containing code which in turn creates the
corresponding @file{.R} file (e.g., by collecting all function objects
in the package and then calling them with the strangest arguments).  The
results of running a @file{.R} file are written to a @file{.Rout} file.
If there is a corresponding@footnote{The best way to generate such a
file is to copy the @file{.Rout} from a successful run of @command{R CMD
check}.  If you want to generate it separately, do run @R{} with options
@option{--vanilla --slave} and with environment variable
@env{LANGUAGE=en} set to get messages in English.} @file{.Rout.save}
file, these two are compared, with differences being reported but not
causing an error.  The directory @file{tests} is copied to the check
area, and the tests are run with the copy as the working directory and
with @code{R_LIBS} set to ensure that the copy of the package installed
during testing will be found by @code{library(@var{pkg_name})}.

If @file{tests} has a subdirectory @file{Examples} containing a file
@code{@var{pkg}-Ex.Rout.save},  this is compared to the output file for
running the examples when the latter are checked.

Subdirectory @file{exec} could contain additional executables the package
needs, typically scripts for interpreters such as the shell, Perl, or
Tcl.  This mechanism is currently used only by a very few packages, and
still experimental.

Subdirectory @file{po} is used for files related to @emph{localization}:
@pxref{Internationalization}.

@node Package bundles, Data in packages, Package subdirectories, Package structure
@subsection Package bundles
@cindex Package bundles

Support for package bundles was removed in @R{} 2.11.0.

@node Data in packages,  , Package bundles, Package structure
@subsection Data in packages

The @file{data} subdirectory is for data files, either to be made
available @emph{via} lazy-loading or for loading using @code{data()}.
(The choice is made by the @samp{LazyData} field in the
@file{DESCRIPTION} file.)  It should not be used for other data files
needed by the package, and the convention has grown up to use directory
@file{inst/extdata} for such files.

Data files can have one of three types as indicated by their extension:
plain @R{} code (@file{.R} or @file{.r}), tables (@file{.tab}, @file{.txt},
or @file{.csv}, see @code{?data} for the file formats, and note that
@file{.csv} is @strong{not} the
standard@footnote{e.g@: @uref{http://tools.ietf.org/html/rfc4180}.} CSV
format), or @code{save()} images (@file{.RData} or @file{.rda}). Note
that @R{} code should be ``self-sufficient'' and not make use of extra
functionality provided by the package, so that the data file can also be
used without having to load the package.

If your data files are enormous and you are not using @samp{LazyData}
you can speed up installation by providing a file @file{datalist} in the
@file{data} subdirectory.  This should have one line per topic that
@code{data()} will find, in the format @samp{foo} if @code{data(foo)}
provides @samp{foo}, or @samp{foo: bar bah} if @code{data(foo)} provides
@samp{bar} and @samp{bah}.

Tables (@file{.tab}, @file{.txt}, or @file{.csv} files) can be
compressed by @command{gzip}, @command{bzip2} or @command{xz},
optionally with additional extension @file{.gz}, @file{.bz2} or
@file{.xz}.  However, such files can only be used with @R{} 2.10.0 or
later, and so the package should have an appropriate @samp{Depends}
entry in its DESCRIPTION file.

If your package is to be distributed, do consider the resource
implications for your users of large datasets: they can make packages
very slow to download and use up unwelcome amounts of storage space, as
well as taking many seconds to load.  It is normally best to distribute
large datasets as @file{.rda} images prepared by @code{save(, compress =
TRUE)} (the default): there is no excuse for distributing ASCII saves.
Using @command{bzip2} or @command{xz} compression will usually reduce
the size of both the package tarball and the installed package, in some
cases by a factor of two or more.  However, such compression can only be
used with @R{} 2.10.0 or later, and so the package should have an
appropriate @samp{Depends} entry in its DESCRIPTION file.

Package @pkg{tools} has a couple of functions to help with data images:
@code{checkRdaFiles} reports on the way the image was saved, and
@code{resaveRdaFiles} will re-save with a different type of compression,
including choosing the best type for that particular image.

@node Configure and cleanup, Checking and building packages, Package structure, Creating R packages
@section Configure and cleanup

Note that most of this section is Unix-alike-specific: see the comments
later on about the Windows port of @R{}.

If your package needs some system-dependent configuration before
installation you can include an executable (Bourne shell) script
@file{configure} in your package which (if present) is executed by
@code{R CMD INSTALL} before any other action is performed.  This can be
a script created by the Autoconf mechanism, but may also be a script
written by yourself.  Use this to detect if any nonstandard libraries
are present such that corresponding code in the package can be disabled
at install time rather than giving error messages when the package is
compiled or used.  To summarize, the full power of Autoconf is available
for your extension package (including variable substitution, searching
for libraries, etc.).

Under a Unix-alike only, an executable (Bourne shell) script
@file{cleanup} is executed as the last thing by @code{R CMD INSTALL} if
option @option{--clean} was given, and by @code{R CMD build} when
preparing the package for building from its source.  It can be used to
clean up the package source tree.  In particular, it should remove all
files created by @command{configure}.

As an example consider we want to use functionality provided by a (C or
FORTRAN) library @code{foo}.  Using Autoconf, we can create a configure
script which checks for the library, sets variable @code{HAVE_FOO} to
@code{TRUE} if it was found and with @code{FALSE} otherwise, and then
substitutes this value into output files (by replacing instances of
@samp{@@HAVE_FOO@@} in input files with the value of @code{HAVE_FOO}).
For example, if a function named @code{bar} is to be made available by
linking against library @code{foo} (i.e., using @option{-lfoo}), one
could use

@example
@group
AC_CHECK_LIB(foo, @var{fun}, [HAVE_FOO=TRUE], [HAVE_FOO=FALSE])
AC_SUBST(HAVE_FOO)
......
AC_CONFIG_FILES([foo.R])
AC_OUTPUT
@end group
@end example

@noindent
in @file{configure.ac} (assuming Autoconf 2.50 or later).

The definition of the respective @R{} function in @file{foo.R.in} could be

@example
@group
foo <- function(x) @{
    if(!@@HAVE_FOO@@)
      stop("Sorry, library 'foo' is not available"))
    ...
@end group
@end example

@noindent
From this file @command{configure} creates the actual @R{} source file
@file{foo.R} looking like

@example
@group
foo <- function(x) @{
    if(!FALSE)
      stop("Sorry, library 'foo' is not available"))
    ...
@end group
@end example

@noindent
if library @code{foo} was not found (with the desired functionality).
In this case, the above @R{} code effectively disables the function.

One could also use different file fragments for available and missing
functionality, respectively.

You will very likely need to ensure that the same C compiler and
compiler flags are used in the @file{configure} tests as when compiling
@R{} or your package.  Under a Unix-alike, you can achieve this by
including the following fragment early in @file{configure.ac}

@example
@group
: $@{R_HOME=`R RHOME`@}
if test -z "$@{R_HOME@}"; then
  echo "could not determine R_HOME"
  exit 1
fi
CC=`"$@{R_HOME@}/bin/R" CMD config CC`
CFLAGS=`"$@{R_HOME@}/bin/R" CMD config CFLAGS`
CPPFLAGS=`"$@{R_HOME@}/bin/R" CMD config CPPFLAGS`
@end group
@end example

@noindent
(Using @samp{$@{R_HOME@}/bin/R} rather than just @samp{R} is necessary
in order to use the correct version of @R{} when running the script as
part of @code{R CMD INSTALL}, and the quotes since @samp{$@{R_HOME@}}
might contain spaces.)

@findex R CMD config
You can use @code{R CMD config} for getting the value of the basic
configuration variables, or the header and library flags necessary for
linking against @R{}, see @kbd{R CMD config --help} for details.

To check for an external BLAS library using the @code{ACX_BLAS} macro
from the official Autoconf Macro Archive, one can simply do

@example
@group
F77=`"$@{R_HOME@}/bin/R" CMD config F77`
AC_PROG_F77
FLIBS=`"$@{R_HOME@}/bin/R" CMD config FLIBS`
ACX_BLAS([], AC_MSG_ERROR([could not find your BLAS library], 1))
@end group
@end example

Note that @code{FLIBS} as determined by @R{} must be used to ensure that
FORTRAN 77 code works on all @R{} platforms.  Calls to the Autoconf macro
@code{AC_F77_LIBRARY_LDFLAGS}, which would overwrite @code{FLIBS}, must
not be used (and hence e.g.@: removed from @code{ACX_BLAS}).  (Recent
versions of Autoconf in fact allow an already set @code{FLIBS} to
override the test for the FORTRAN linker flags.  Also, recent versions
of @R{} can detect external BLAS and LAPACK libraries.)

You should bear in mind that the configure script will not be used on
Windows systems.  If your package is to be made publicly available,
please give enough information for a user on a non-Unix-alike platform
to configure it manually, or provide a @file{configure.win} script to be
used on that platform.  (Optionally, there can be a @file{cleanup.win}
script.  Both should be shell scripts to be executed by @command{ash},
which is a minimal version of Bourne-style @command{sh}.)  When
@file{configure.win} is run the environment variables
@env{R_HOME}@footnote{formerly also @env{RHOME}, but this was removed in
@R{} 2.12.0.} (which uses @code{/} as the file separator) and
@env{R_ARCH} will be set.  Use @env{R_ARCH} to decide if this is a
64-bit build (its value there is @samp{/x64}) and to install DLLs to the
correct place (@code{$@{R_HOME@}/libs$@{R_ARCH@}}).  Use
@env{R_ARCH_BIN} to find the correct place under the @file{bin}
directory, e.g.@: @code{$@{R_HOME@}/bin$@{R_ARCH_BIN@}/Rscript.exe}.

In some rare circumstances, the configuration and cleanup scripts need
to know the location into which the package is being installed.  An
example of this is a package that uses C code and creates two shared
object/DLLs.  Usually, the object that is dynamically loaded by @R{}
is linked against the second, dependent, object.  On some systems, we
can add the location of this dependent object to the object that is
dynamically loaded by @R{}.  This means that each user does not have to
set the value of the @env{LD_LIBRARY_PATH} (or equivalent) environment
variable, but that the secondary object is automatically resolved.
Another example is when a package installs support files that are
required at run time, and their location is substituted into an @R{}
data structure at installation time. (This happens with the Java Archive
files in the @pkg{SJava} package.)
@vindex R_LIBRARY_DIR
@vindex R_PACKAGE_DIR
@vindex R_PACKAGE_NAME
The names of the top-level library directory (i.e., specifiable
@emph{via} the @samp{-l} argument) and the directory of the package
itself are made available to the installation scripts @emph{via} the two
shell/environment variables @env{R_LIBRARY_DIR} and @env{R_PACKAGE_DIR}.
Additionally, the name of the package (e.g.@: @samp{survival} or
@samp{MASS}) being installed is available from the environment variable
@env{R_PACKAGE_NAME}.  (Currently the value of @env{R_PACKAGE_DIR} is
always @code{$@{R_LIBRARY_DIR@}/$@{R_PACKAGE_NAME@}}, but this used not to
be the case when versioned installs were allowed.  Its main use is in
@file{configure.win} scripts for the installation path of external
software's DLLs.)

@menu
* Using Makevars::
* Configure example::
* Using F95 code::
@end menu

@node Using Makevars, Configure example, Configure and cleanup, Configure and cleanup
@subsection Using @file{Makevars}

Sometimes writing your own @file{configure} script can be avoided by
supplying a file @file{Makevars}: also one of the most common uses of a
@file{configure} script is to make @file{Makevars} from
@file{Makevars.in}.

The most common use of a @file{Makevars} file is to set additional
preprocessor options (for example include paths) for C/C++ files
@emph{via} @code{PKG_CPPFLAGS}, and additional compiler flags by setting
@code{PKG_CFLAGS}, @code{PKG_CXXFLAGS}, @code{PKG_FFLAGS} or
@code{PKG_FCFLAGS}, for C, C++, FORTRAN or Fortran 9x respectively
(@pxref{Creating shared objects}).

@file{Makevars} can also be used to set flags for the linker, for
example @samp{-L} and @samp{-l} options, @emph{via} @code{PKG_LIBS}.

When writing a @file{Makevars} file for a package you intend to
distribute, take care to ensure that it is not specific to your
compiler: flags such as @option{-O2 -Wall -pedantic} are all specific to
GCC.

There are some macros@footnote{in POSIX parlance: GNU @command{make}
calls these `make variables'.}  which are set whilst configuring the
building of @R{} itself and are stored in
@file{@var{R_HOME}/etc@var{R_ARCH}/Makeconf}.  That makefile is included
as a @file{Makefile} @emph{after} @file{Makevars[.win]}, and the macros
it defines can be used in macro assignments and make command lines in
the latter.  These include

@table @code
@item FLIBS
@vindex FLIBS
A macro containing the set of libraries need to link FORTRAN code.  This
may need to be included in @code{PKG_LIBS}: it will normally be included
automatically if the package contains FORTRAN source files.

@item BLAS_LIBS
@vindex BLAS_LIBS
A macro containing the BLAS libraries used when building @R{}.  This may
need to be included in @code{PKG_LIBS}.  Beware that if it is empty then
the @R{} executable will contain all the double-precision and
double-complex BLAS routines, but no single-precision or complex
routines.  If @code{BLAS_LIBS} is included, then @code{FLIBS} also needs
to be@footnote{at least on Unix-alikes: the Windows build currently
resolves such dependencies to a static FORTRAN library when
@file{Rblas.dll} is built.}, as most BLAS libraries are written at least
partially in FORTRAN.

@item LAPACK_LIBS
@vindex LAPACK_LIBS
A macro containing the LAPACK libraries (and paths where appropriate)
used when building @R{}.  This may need to be included in
@code{PKG_LIBS}.  It may point to a dynamic library @code{libRlapack}
which contains all the double-precision LAPACK routines as well as those
double-complex LAPACK and BLAS routines needed to build @R{}, or it may
point to an external LAPACK library, or may be empty if an external BLAS
library also contains LAPACK.

[There is no guarantee that the LAPACK library will provide more than
all the double-precision and double-complex routines, and some do not
provide all the auxiliary routines.]

For portability, the macros @code{BLAS_LIBS} and @code{FLIBS} should
always be included @emph{after} @code{LAPACK_LIBS}.

@item SAFE_FFLAGS
@vindex SAFE_FFLAGS
A macro containing flags which are needed to circumvent
over-optimization of FORTRAN code: it is typically @samp{-g -O2
-ffloat-store} on @cputype{ix86} platforms using @command{gfortran}.
Note that this is @strong{not} an additional flag to be used as part of
@code{PKG_FFLAGS}, but a replacement for @code{FFLAGS}, and that it is
intended for the FORTRAN-77 compiler @samp{F77} and not necessarily for
the Fortran 90/95 compiler @samp{FC}.  See the example later in this
section.
@end table

@vindex OBJECTS
Setting certain macros in @file{Makevars} will prevent @command{R CMD
SHLIB} setting them: in particular if @file{Makevars} sets
@samp{OBJECTS} it will not be set on the @command{make} command line.
This can be useful in conjunction with implicit rules to allow other
types of source code to be compiled and included in the shared object.
It can also be used to control the set of files which are compiled,
either by excluding some files in @file{src} or including some files in
subdirectories.  For example

@example
OBJECTS = 4dfp/endianio.o 4dfp/Getifh.o R4dfp-object.o
@end example


Note that @file{Makevars} should not normally contain targets, as it is
included before the default makefile and @command{make} is called with
target @code{all} which is defined in the default makefile.  If you
really need to circumvent that, use a suitable (phony) target @code{all}
before any actual targets in @file{Makevars.[win]}: for example package
@pkg{fastICA} has

@smallexample
PKG_LIBS = @@BLAS_LIBS@@

SLAMC_FFLAGS=$(R_XTRA_FFLAGS) $(FPICFLAGS) $(SHLIB_FFLAGS) $(SAFE_FFLAGS)

all: $(SHLIB)

slamc.o: slamc.f
        $(F77) $(SLAMC_FFLAGS) -c -o slamc.o slamc.f
@end smallexample

@noindent
needed to ensure that the LAPACK routines find some constants without
infinite looping.  The Windows equivalent is

@smallexample
all: $(SHLIB)

slamc.o: slamc.f
        $(F77) $(SAFE_FFLAGS) -c -o slamc.o slamc.f
@end smallexample

@noindent
(since the other macros are all empty on that platform, and @R{}'s
internal BLAS is not used).  Note that the first target in
@file{Makevars} will be called, but for back-compatibility it is best
named @code{all}.

If you want to create and then link to a library, say using code in a
subdirectory, use something like

@smallexample
.PHONY: all mylibs

all: $(SHLIB)
$(SHLIB): mylibs

mylibs:
        (cd subdir; make)
@end smallexample

@noindent
Be careful to create all the necessary dependencies, as there is a no
guarantee that the dependencies of @code{all} will be run in a
particular order (and some of the @acronym{CRAN} build machines use
multiple CPUs and parallel makes).

Note that on Windows it is required that @file{Makevars[.win]} does
create a DLL: this is needed as it is the only reliable way to ensure
that building a DLL succeeded.  If you want to use the @file{src}
directory for some purpose other than building a DLL, use a
@file{Makefile.win} file.

It is sometimes useful to have a target @samp{clean} in @file{Makevars}
or @file{Makevars.win}: this will be used by @command{R CMD build} to
clean up (a copy of) the package sources.  When it is run by
@command{build} it will have fewer macros set, in particular not
@code{$(SHLIB)}, nor @code{$(OBJECTS)} unless set in the file itself.
It would also be possible to add tasks to the target @samp{shlib-clean}
which is run by @command{R CMD INSTALL} and @command{R CMD SHLIB} with
options @option{--clean} and @option{--preclean}.

If you want to run @R{} code in @file{Makevars}, e.g.@: to find
configuration information, please do ensure that you use the correct
copy of @code{R} or @code{Rscript}: there might not be one in the path
at all, or it might be the wrong version or architecture.  The correct
way to do this is @emph{via}

@example
$(R_HOME)/bin$(R_ARCH_BIN)/Rscript @var{filename}
$(R_HOME)/bin$(R_ARCH_BIN)/Rscript -e '@var{R expression}'
@end example

@noindent
where @code{$(R_ARCH_BIN)} is only needed currently on Windows.

Environment or make variables can be used to select different macros for
32- and 64-bit code, for example (GNU syntax, allowed on Windows)

@example
ifeq "$@{R_ARCH@}" "/x64"
PKG_LIBS = @var{value for 64-bit Windows}
else
PKG_LIBS = @var{value for 32-bit Windows}
endif
@end example

@noindent
To make this simpler, as from @R{} 2.11.1 (but not in @R{} 2.11.0) you
can use

@example
ifeq "$(WIN)" "64"
PKG_LIBS = @var{value for 64-bit Windows}
else
PKG_LIBS = @var{value for 32-bit Windows}
endif
@end example

On Windows there is normally a choice between linking to an import
library or directly to a DLL.  Where possible, the latter is much more
reliable: import libraries are tied to a specific toolchain, and in
particular on 64-bit Windows two different conventions are common, and
@R{} 2.11.x and 2.12.x use different ones.  So for example instead of

@example
PKG_LIBS = -L$(XML_DIR)/lib -lxml2
@end example

@noindent
one can use

@example
PKG_LIBS = -L$(XML_DIR)/bin -lxml2
@end example

@noindent
since on Windows @code{-lxxx} will look in turn for

@example
libxxx.dll.a
xxx.dll.a
libxxx.a
xxx.lib
libxxx.dll
xxx.dll
@end example

@noindent
where the first and second are conventionally import libraries, the
third and fourth often static libraries (with @code{.lib} intended for
Visual C++), but might be import libraries.  See for example
@uref{http://sourceware.org/@/binutils/@/docs-2.20/@/ld/@/WIN32.html#WIN32}.

The fly in the ointment is that the DLL might not be named
@file{libxxx.dll}, and in fact on 32-bit Windows there is
@file{libxml2.dll} whereas on 64-bit Windows the DLL is called
@file{libxml2-2.dll}.  Using import libraries can cover over these
differences but can cause equal difficulties.

If static libraries are available they can save a lot of problems with
run-time finding of DLLs, especially when binary packages are to be
distributed and even more when these support both architectures.  Where
using DLLs is unavoidable we normally arrange (@emph{via}
@file{configure.win}) to ship them in the same directory as the package
DLL.

@node Configure example, Using F95 code, Using Makevars, Configure and cleanup
@subsection Configure example

It may be helpful to give an extended example of using a
@file{configure} script to create a @file{src/Makevars} file: this is
based on that in the @pkg{RODBC} package.

The @file{configure.ac} file follows: @file{configure} is created from
this by running @command{autoconf} in the top-level package directory
(containing @file{configure.ac}).

@quotation
@c @cartouche
@smallexample
AC_INIT([RODBC], 1.1.8) dnl package name, version

dnl A user-specifiable option
odbc_mgr=""
AC_ARG_WITH([odbc-manager],
            AC_HELP_STRING([--with-odbc-manager=MGR],
                           [specify the ODBC manager, e.g. odbc or iodbc]),
            [odbc_mgr=$withval])

if test "$odbc_mgr" = "odbc" ; then
  AC_PATH_PROGS(ODBC_CONFIG, odbc_config)
fi

dnl Select an optional include path, from a configure option
dnl or from an environment variable.
AC_ARG_WITH([odbc-include],
            AC_HELP_STRING([--with-odbc-include=INCLUDE_PATH],
                           [the location of ODBC header files]),
            [odbc_include_path=$withval])
RODBC_CPPFLAGS="-I."
if test [ -n "$odbc_include_path" ] ; then
   RODBC_CPPFLAGS="-I. -I$@{odbc_include_path@}"
else
  if test [ -n "$@{ODBC_INCLUDE@}" ] ; then
     RODBC_CPPFLAGS="-I. -I$@{ODBC_INCLUDE@}"
  fi
fi

dnl ditto for a library path
AC_ARG_WITH([odbc-lib],
            AC_HELP_STRING([--with-odbc-lib=LIB_PATH],
                           [the location of ODBC libraries]),
            [odbc_lib_path=$withval])
if test [ -n "$odbc_lib_path" ] ; then
   LIBS="-L$odbc_lib_path $@{LIBS@}"
else
  if test [ -n "$@{ODBC_LIBS@}" ] ; then
     LIBS="-L$@{ODBC_LIBS@} $@{LIBS@}"
  else
    if test -n "$@{ODBC_CONFIG@}"; then
      odbc_lib_path=`odbc_config --libs | sed s/-lodbc//`
      LIBS="$@{odbc_lib_path@} $@{LIBS@}"
    fi
  fi
fi

dnl Now find the compiler and compiler flags to use
: $@{R_HOME=`R RHOME`@}
if test -z "$@{R_HOME@}"; then
  echo "could not determine R_HOME"
  exit 1
fi
CC=`"$@{R_HOME@}/bin/R" CMD config CC`
CPP=`"$@{R_HOME@}/bin/R" CMD config CPP`
CFLAGS=`"$@{R_HOME@}/bin/R" CMD config CFLAGS`
CPPFLAGS=`"$@{R_HOME@}/bin/R" CMD config CPPFLAGS`
AC_PROG_CC
AC_PROG_CPP


if test -n "$@{ODBC_CONFIG@}"; then
  RODBC_CPPFLAGS=`odbc_config --cflags`
fi
CPPFLAGS="$@{CPPFLAGS@} $@{RODBC_CPPFLAGS@}"

dnl Check the headers can be found
AC_CHECK_HEADERS(sql.h sqlext.h)
if test "$@{ac_cv_header_sql_h@}" = no ||
   test "$@{ac_cv_header_sqlext_h@}" = no; then
   AC_MSG_ERROR("ODBC headers sql.h and sqlext.h not found")
fi

dnl search for a library containing an ODBC function
if test [ -n "$@{odbc_mgr@}" ] ; then
  AC_SEARCH_LIBS(SQLTables, $@{odbc_mgr@}, ,
      AC_MSG_ERROR("ODBC driver manager $@{odbc_mgr@} not found"))
else
  AC_SEARCH_LIBS(SQLTables, odbc odbc32 iodbc, ,
      AC_MSG_ERROR("no ODBC driver manager found"))
fi

dnl for 64-bit ODBC need SQL[U]LEN, and it is unclear where they are defined.
AC_CHECK_TYPES([SQLLEN, SQLULEN], , , [# include <sql.h>])
dnl for unixODBC header
AC_CHECK_SIZEOF(long, 4)

dnl substitute RODBC_CPPFLAGS and LIBS
AC_SUBST(RODBC_CPPFLAGS)
AC_SUBST(LIBS)
AC_CONFIG_HEADERS([src/config.h])
dnl and do substitution in the src/Makevars.in and src/config.h
AC_CONFIG_FILES([src/Makevars])
AC_OUTPUT
@end smallexample
@c @end cartouche
@end quotation

@noindent
where @file{src/Makevars.in} would be simply

@quotation
@example
PKG_CPPFLAGS = @@RODBC_CPPFLAGS@@
PKG_LIBS = @@LIBS@@
@end example
@end quotation

A user can then be advised to specify the location of the ODBC driver
manager files by options like (lines broken for easier reading)

@example
R CMD INSTALL
  --configure-args='--with-odbc-include=/opt/local/include
  --with-odbc-lib=/opt/local/lib --with-odbc-manager=iodbc'
  RODBC
@end example

@noindent
or by setting the environment variables @code{ODBC_INCLUDE} and
@code{ODBC_LIBS}.

@node Using F95 code,  , Configure example, Configure and cleanup
@subsection Using F95 code

@R{} assumes that source files with extension @file{.f} are FORTRAN 77,
and passes them to the compiler specified by @samp{F77}.  On most but
not all platforms that compiler will accept Fortran 90/95 code: some
platforms have a separate Fortran 90/95 compiler and a few (typically
older) platforms have no Fortran 90/95 support.

This means that portable packages need to be written in correct
FORTRAN 77, which will also be valid Fortran 95.  See
@uref{http://developer.r-project.org/Portability.html} for reference
resources.  In particular, @emph{free source form} F95 code is not
portable.

On some systems an alternative F95 compiler is available: from the
@code{gcc} family this might be @command{gfortran} or @command{g95}.
Configuring @R{} will try to find a compiler which (from its name)
appears to be a Fortran 90/95 compiler, and set it in macro @samp{FC}.
Note that it does not check that such a compiler is fully (or even
partially) compliant with Fortran 90/95.  Packages making use of Fortran
90/95 features should use file extension @file{.f90} or @file{.f95} for
the source files: the variable @code{PKG_FCFLAGS} specifies any special
flags to be used.  There is no guarantee that compiled Fortran 90/95
code can be mixed with any other type of compiled code, nor that a build
of @R{} will have support for such packages.

@node Checking and building packages, Writing package vignettes, Configure and cleanup, Creating R packages
@section Checking and building packages

Before using these tools, please check that your package can be
installed and loaded.  @code{R CMD check} will @emph{inter alia} do
this, but you may get more detailed error messages doing the checks
directly.

@menu
* Checking packages::
* Building packages::
@end menu

@quotation Note
@code{R CMD check} and @code{R CMD build} run @R{} with
@option{--vanilla}, so none of the user's startup files are read.  If
you need @env{R_LIBS} set (to find packages in a non-standard library)
you can set it in the environment: also as from @R{} 2.12.0 you can use
files@footnote{On systems which use sub-architectures,
architecture-specific versions such as @file{~/.R/check.Renviron.i386}
take precedence.}  @file{~/.R/check.Renviron} and
@file{~/.R/build.Renviron} to set environment variables when using these
utilities.
@end quotation

@quotation Note to Windows users
@code{R CMD check} and @code{R CMD build} require you to have installed
the Windows toolset (see the ``R Installation and Administration''
manual) and have it in your path.  You may need to set @env{TMPDIR} to
point to a suitable writable directory with a path not containing spaces
-- use forward slashes for the separators.  Also, the directory needs to
be on a case-honouring file system (some network-mounted file systems
are not).
@end quotation


@node Checking packages, Building packages, Checking and building packages, Checking and building packages
@subsection Checking packages
@cindex Checking packages

@findex R CMD check
Using @code{R CMD check}, the @R{} package checker, one can test whether
@emph{source} @R{} packages work correctly.  It can be run on one or
more directories, or gzipped package @command{tar}
archives@footnote{This may require @acronym{GNU} @command{tar}: the
command used can be set with environment variable @env{TAR}.}  with
extension @file{.tar.gz} or @file{.tgz}.  This runs a series of checks,
including

@enumerate
@item
The package is installed.  This will warn about missing cross-references
and duplicate aliases in help files.

@item
The file names are checked to be valid across file systems and supported
operating system platforms.

@item
The files and directories are checked for sufficient permissions
(Unix-alikes only).

@item
The files are checked for binary executables, using a suitable version
of @command{file} if available.  (There may be rare false positives.)

@item
The @file{DESCRIPTION} file is checked for completeness, and some of its
entries for correctness.  Unless installation tests are skipped,
checking is aborted if the package dependencies cannot be resolved at
run time.  (You may need to set @env{R_LIBS} if dependent packages are
in a separate library tree.) One check is that the package name is not
that of a standard package, nor one of the defunct standard packages
(@samp{ctest}, @samp{eda}, @samp{lqs}, @samp{mle}, @samp{modreg},
@samp{mva}, @samp{nls}, @samp{stepfun} and @samp{ts}).  Another check is
that all packages mentioned in @code{library} or @code{require}s or from
which the @file{NAMESPACE} file imports or are called @emph{via}
@code{::} or @code{:::} are listed (in @samp{Depends}, @samp{Imports},
@samp{Suggests} or @samp{Contains}): this is not an exhaustive check of
the actual imports.

@item
Available index information (in particular, for demos and vignettes) is
checked for completeness.

@item
The package subdirectories are checked for suitable file names and for
not being empty.  The checks on file names are controlled by the option
@option{--check-subdirs=@var{value}}.  This defaults to @samp{default},
which runs the checks only if checking a tarball: the default can be
overridden by specifying the value as @samp{yes} or @samp{no}.  Further,
the check on the @file{src} directory is only run if the package
does not contain a @file{configure} script (which corresponds to the
value @samp{yes-maybe}) and there is no @file{src/Makefile} or
@file{src/Makefile.in}.

To allow a @file{configure} script to generate suitable files, files
ending in @samp{.in} will be allowed in the @file{R} directory.

A warning is given for directory names that look like @R{} package check
directories -- many packages have been submitted to @acronym{CRAN}
containing these.

@item
The @R{} files are checked for syntax errors.  Bytes which are
non-@acronym{ASCII} are reported as warnings, but these should be
regarded as errors unless it is known that the package will always be
used in the same locale.

@item
It is checked that the package can be loaded, first with the usual
default packages and then only with package @pkg{base} already
loaded. If the package has a namespace, it is checked if this can be
loaded in an empty session with only the @pkg{base} namespace loaded.
(Namespaces and packages can be loaded very early in the session, before
the default packages are available, so packages should work then.)

@item
The @R{} files are checked for correct calls to @code{library.dynam}.
In addition, it is checked whether methods have all arguments of the
corresponding generic, and whether the final argument of replacement
functions is called @samp{value}.  All foreign function calls
(@code{.C}, @code{.Fortran}, @code{.Call} and @code{.External} calls)
are tested to see if they have a @code{PACKAGE} argument, and if not,
whether the appropriate DLL might be deduced from the name space of the
package.  Any other calls are reported.  (The check is generous, and
users may want to supplement this by examining the output of
@code{tools::checkFF("mypkg", verbose=TRUE)}, especially if the
intention were to always use a @code{PACKAGE} argument)

@item
The @file{Rd} files are checked for correct syntax and metadata,
including the presence of the mandatory (@code{\name}, @code{\alias},
@code{\title} and @code{\description}) fields.  The @file{Rd} name and
title are checked for being non-empty, and there is a check for missing
cross-references (links).

@item
A check is made for missing documentation entries, such as undocumented
user-level objects in the package.

@item
Documentation for functions, data sets, and S4 classes is checked for
consistency with the corresponding code.

@item
It is checked whether all function arguments given in @code{\usage}
sections of @file{Rd} files are documented in the corresponding
@code{\arguments} section.

@item
C, C++ and FORTRAN source and header files are tested for portable
(LF-only) line endings.  If there is a @file{Makefile} or
@file{Makefile.in} or @file{Makevars} or @file{Makevars.in} file in the
@file{src} directory, it is checked for portable line endings and the
correct use of @samp{$(BLAS_LIBS)}.

@item
The examples provided by the package's documentation are run.
(@pxref{Writing R documentation files}, for information on using
@code{\examples} to create executable example code.)  If there is a file
@file{tests/Examples/@var{pkg}-Ex.Rout.save}, the output of running the
examples is compared to that file.

Of course, released packages should be able to run at least their own
examples.  Each example is run in a `clean' environment (so earlier
examples cannot be assumed to have been run), and with the variables
@code{T} and @code{F} redefined to generate an error unless they are set
in the example: @xref{Logical vectors, , Logical vectors, R-intro, An
Introduction to R}.

@item
If the package sources contain a @file{tests} directory then the tests
specified in that directory are run.  (Typically they will consist of a
set of @file{.R} source files and target output files
@file{.Rout.save}.)  Please note that the comparison will be done in the
end user's locale, so the target output files should be ASCII if at all
possible.

@item
The code in package vignettes (@pxref{Writing package vignettes}) is
executed, and the vignettes made from the sources as a check of
completeness.

@item
The PDF version of the package's manual is created (to check that the
@file{Rd} files can be converted successfully).
@end enumerate

Use @kbd{R CMD check --help} to obtain more information about the usage
of the @R{} package checker.  A subset of the checking steps can be
selected by adding command-line options. It also allows customization by
setting environment variables @w{@env{_R_CHECK_*_}:}, as described in
@ifset UseExternalXrefs
@ref{Tools, , Tools, R-ints, R Internals},
@end ifset
@ifclear UseExternalXrefs
`R Internals',
@end ifclear

You do need to ensure that the package is checked in a suitable locale
if it contains non-@acronym{ASCII} characters.  Such packages are likely
to fail some of the checks in a @code{C} locale, and @command{R CMD
check} will warn if it spots the problem.  You should be able to check
any package in a UTF-8 locale (if one is available).  Beware that
although a @code{C} locale is rarely used at a console, it may be the
default if logging in remotely or for batch jobs.

@quotation Multiple sub-architectures
On systems which support multiple sub-architectures (principally Windows
and Mac OS X), @command{R CMD check} will install and check a package
which contains compiled code under all available sub-architectures. (Use
option @option{--force-multiarch} to force this for packages without
compiled code, which are otherwise only checked under the main
sub-architecture.)  This will run the loading tests, examples and
@file{tests} directory under each installed sub-architecture in turn,
and give an error if any fail.  Where environment variables (including
@env{PATH}@footnote{this is needed on Windows to select the appropriate
GTK+ and @samp{graphviz} DLLs.}) need to be set differently for each
sub-architecture, these can be set in architecture-specific files such
as @file{@var{R_HOME}/etc/i386/Renviron.site}.

An alternative approach is to use @command{R CMD check --no-multiarch}
to check the primary sub-architecture, and then to use something like
@command{R --arch=x86_64 CMD check --extra-arch} or (Windows)
@command{/path/to/R/bin/x64/Rcmd check --extra-arch} to run for each
additional sub-architecture just the checks@footnote{loading, examples,
tests, vignettes} which differ by sub-architecture.
@end quotation


@node Building packages,  , Checking packages, Checking and building packages
@subsection Building packages
@cindex Building packages

@findex R CMD build
@cindex Package builder
Using @code{R CMD build}, the @R{} package builder, one can build @R{}
packages from their sources (for example, for subsequent release).

Prior to actually building the package in the standard gzipped tar file
format, a few diagnostic checks and cleanups are performed.  In
particular, it is tested whether object indices exist and can be assumed
to be up-to-date, and C, C++ and FORTRAN source files and relevant make
files are tested and converted to LF line-endings if necessary.

Run-time checks whether the package works correctly should be performed
using @code{R CMD check} prior to invoking the build procedure.

To exclude files from being put into the package, one can specify a list
of exclude patterns in file @file{.Rbuildignore} in the top-level source
directory.  These patterns should be Perl-like regexps (see the help for
@code{regexp} in @R{} for the precise details), one per line, to be
matched against the file names relative to the top-level source
directory.  In addition, directories from source control
systems@footnote{called @file{CVS} or @file{.svn} or @file{.arch-ids} or
@file{.bzr} or @file{.git} or @file{.hg}.}, directories with names
ending @file{.Rcheck} or @file{Old} or @file{old} and files
@file{GNUMakefile}, @file{Read-and-delete-me} or with base names
starting with @samp{.#}, or starting and ending with @samp{#}, or ending
in @samp{~}, @samp{.bak} or @samp{.swp}, are excluded by default.  In
addition, those files in the @file{R}, @file{demo} and @file{man}
directories which are flagged by @code{R CMD check} as having invalid
names will be excluded.

Use @kbd{R CMD build --help} to obtain more information about the usage
of the @R{} package builder.

Unless @kbd{R CMD build} is invoked with the @option{--no-vignettes}
option, it will attempt to rebuild the vignettes (@pxref{Writing package
vignettes}) in the package.  To do so it installs the current package
into a temporary library tree, but any dependent packages need to be
installed in an available library tree (see the Note: below).

Similarly, if the @file{.Rd} documentation files contain any
@code{\Sexpr} macros (@pxref{Dynamic pages}), the package will be
temporarily installed to execute them.  Post-execution binary copies of
those pages containing build-time macros will be saved in
@file{build/partial.rdb}.  If there are any install-time or render-time
macros, a @file{.pdf} version of the package manual will be built and
installed in the @file{build/} subdirectory.  (This allows CRAN or other
repositories to display the manual even if they are unable to install
the package.)

One of the checks that @code{R CMD build} runs is for empty source
directories.  These are in most cases unintentional, in which case they
should be removed and the build re-run.

It can be useful to run @code{R CMD check --check-subdirs=yes} on the
built tarball as a final check on the contents.

@code{R CMD build} can also build pre-compiled version of packages for
binary distributions, but @code{R CMD INSTALL --build} is preferred (and
is considerably more flexible).

@code{R CMD build} currently does some cleaning in the supplied source
directory, but this will no longer happen in @R{} 2.13.0.

@node Writing package vignettes, Submitting a package to CRAN, Checking and building packages, Creating R packages
@section Writing package vignettes
@cindex vignettes
@cindex Sweave

In addition to the help files in @file{Rd} format, @R{} packages allow the
inclusion of documents in arbitrary other formats.  The standard
location for these is subdirectory @file{inst/doc} of a source package,
the contents will be copied to subdirectory @file{doc} when the package
is installed.  Pointers from package help indices to the installed
documents are automatically created.  Documents in @file{inst/doc} can
be in arbitrary format, however we strongly recommend to provide them in
PDF format, such that users on all platforms can easily read them.  To
ensure that they can be accessed from a browser, the file names should
start with an @acronym{ASCII} letter and be comprised entirely of
@acronym{ASCII} letters or digits or hyphen or underscore.

A special case are documents in Sweave format, which we call
@emph{package vignettes}.  Sweave allows the integration of @LaTeX{}
documents and @R{} code and is contained in package @pkg{utils} which is
part of the base @R{} distribution, see the @code{Sweave} help page for
details on the document format.  Package vignettes found in directory
@file{inst/doc} are tested by @code{R CMD check} by executing all @R{}
code chunks they contain to ensure consistency between code and
documentation.  (Code chunks with option @code{eval=FALSE} are not
tested.) The @R{} working directory for all vignette tests in @code{R
CMD check} is the @emph{installed} version of the @file{doc}
subdirectory. Make sure all files needed by the vignette (data sets,
@dots{}) are accessible by either placing them in the @file{inst/doc}
hierarchy of the source package, or using calls to @code{system.file()}.

@code{R CMD build} will automatically create PDF versions of the
vignettes for distribution with the package sources.  By including the
PDF version in the package sources it is not necessary that the
vignettes can be compiled at install time, i.e., the package author can
use private @LaTeX{} extensions which are only available on his
machine.@footnote{provided the conditions of the package's licence are
met: many would see these as incompatible with an Open Source licence.}

By default @code{R CMD build} will run @code{Sweave} on all files in
Sweave format.  If no @file{Makefile} is found in directory
@file{inst/doc}, then @code{tool::texi2dvi(pdf = TRUE)} is run on all
vignettes.  Whenever a @file{Makefile} is found, then @code{R CMD build}
will try to run @command{make} after the @code{Sweave} step, so PDF
manuals can be created from arbitrary source formats (plain @LaTeX{}
files, @dots{}).  The first target in the @file{Makefile} should take
care of both creation of PDF files and cleaning up afterwards, i.e.,
delete all files that shall not appear in the final package archive.
Note that the @code{make} step is executed independently from the
presence of any files in Sweave format, and that if it runs @R{} it
needs to be careful to respect the environment value of @env{R_LIBS}.

It is no longer necessary to provide a @file{00Index.dcf} file in the
@file{inst/doc} directory---the corresponding information is generated
automatically from the @code{\VignetteIndexEntry} statements in all
Sweave files when installing from source, or when using the package
builder (@pxref{Checking and building packages}).  The
@code{\VignetteIndexEntry} statement is best placed in @LaTeX{} comment,
as then no definition of the command is necessary.

At install time an @HTML{} index for all vignettes is automatically
created from the @code{\VignetteIndexEntry} statements unless a file
@file{index.html} exists in directory @file{inst/doc}. This index is
linked into the @HTML{} help system for each package.  If you do supply
a @file{inst/doc/html/index.html} file it should contain relative links
only to files under the installed @file{doc} directory, or perhaps (not
really an index) to HTML help files or to the @file{DESCRIPTION} file.

@node Submitting a package to CRAN, Package name spaces, Writing package vignettes, Creating R packages
@section Submitting a package to @acronym{CRAN}
@cindex CRAN
@cindex CRAN submission
@cindex Submitting to CRAN

@acronym{CRAN} is a network of WWW sites holding the @R{} distributions
and contributed code, especially @R{} packages.  Users of @R{} are
encouraged to join in the collaborative project and to submit their own
packages to @acronym{CRAN}.

Before submitting a package @var{mypkg}, do run the following steps to
test it is complete and will install properly.  (Run from the directory
containing @file{@var{mypkg}} as a subdirectory.)

@enumerate
@item
Run @code{R CMD build} to make the release @file{.tar.gz} file.

@item
Run @code{R CMD check} on the @file{.tar.gz} file to check that the
package will install and will run its examples, and that the
documentation is complete and can be processed.  If the package contains
code that needs to be compiled, try to enable a reasonable amount of
diagnostic messaging (``warnings'') when compiling, such as e.g.@:
@option{-Wall -pedantic} for tools from GCC, the @acronym{GNU} Compiler
Collection.  If @R{} was not configured accordingly, one can achieve
this @emph{via} personal @file{Makevars} files.
@ifset UseExternalXrefs
@xref{Customizing package compilation,
Customizing package compilation, R-admin,
R Installation and Administration},
@end ifset

Note that it is particularly important to use @option{-Wall -pedantic}
with C++ code: the @acronym{GNU} C++ compiler has many extensions which
are not supported by other compilers, and this will report @emph{some}
of them (such as the misuse of variable-length arrays).  If possible,
check C++ code on a standards-conformant compiler.

@item
Study the output from running your examples, in file
@file{@var{pkg}.Rcheck/@var{pkg}-Ex.Rout}.  Often warnings there
indicate actual errors, and warnings about your mistakes (which the @R{}
developers are warning you that they are working around for you) will
just annoy or confuse your users.

If your package has tests, study their output too.

@item
Look for any problems with help file conversions.  For example, you
should
@itemize
@item
Read through the PDF manual that was produced by @code{R CMD check} at
@file{@var{mypkg}.Rcheck/@var{mypkg}-manual.pdf}, or produce another copy by
@code{R CMD Rd2pdf @var{mypkg}}.

@item
Look at the rendering of your help pages in text from within @R{}.
@end itemize

Many aspects of help rendering changed in @R{} 2.10.0, and in particular
the interpretation of comment lines (which are rendered as blank lines,
so do not put comment lines in the middle of a paragraph of text).

@end enumerate

@noindent
Please ensure that you can run through the complete procedure with only
warnings that you understand and have reasons not to eliminate.  In
principle, packages must pass @code{R CMD check} without warnings to be
admitted to the main @acronym{CRAN} package area.  If there are warnings
you cannot eliminate (for example because you believe them to be
spurious) send an explanatory note with your submission.

When all the testing is done, upload the @file{.tar.gz} file, using
@samp{anonymous} as log-in name and your e-mail address as password, to
@uref{ftp://CRAN.R-project.org/incoming/} (note: use
@samp{ftp}@footnote{for Windows users the simplest way may be to open
that URL in Internet Explorer and (depending on the version) follow the
instructions to view it as a folder, then copy the submission to the
folder.} and not @samp{sftp} to connect to this server) and send a
message to @email{CRAN@@R-project.org} about it.  The @acronym{CRAN}
maintainers will run these tests before putting a submission in the main
archive.

Note also that for running @LaTeX{}, the Debian @acronym{GNU}/Linux
@acronym{CRAN} check systems use reasonably recent versions of the
Debian TexLive distribution
(@uref{http://packages.debian.org/de/sid/texlive}); for the Windows
@acronym{CRAN} server, a reasonably recent version of MikTeX (including
all packages available directly for MikTeX) is employed: the Mac OS X
builders use a current full version of MacTeX.  Developers wanting to
have their vignettes use @TeX{} packages or style files not (yet)
included in these distributions should add the corresponding style files
to the @file{inst/doc} subdirectory of their package.

Note that @acronym{CRAN} does not accept submissions of precompiled
binaries due to security concerns, and does not allow binary executables
in packages.  Maintainers who need additional software for the Windows
binaries of their packages on @acronym{CRAN} have three options
@enumerate
@item
To arrange for installation of the package to download the
additional software from a URL, as e.g.@: package @pkg{Cairo} does.

@item
To negotiate with Uwe Ligges to host the additional components on
WinBuilder, and write a @file{configure.win} file to install them.
There are many examples, e.g.@: package @pkg{rgdal}.

@item
To negotiate with Brian Ripley to host the package on @acronym{CRAN}
extras, as was done for package @pkg{BRugs}.
@end enumerate

@noindent
Be aware that in all cases license requirements will need to be met so
you may need to supply the sources for the additional components (and
will if your package has a GPL-like license).

Also be aware that there are both 32- and 64-bit builds of @R{} for
Windows with a combined distribution of binary packages, so the CRAN
team will be reluctant to support a package that works under just one of
the architectures.


@node Package name spaces, Writing portable packages, Submitting a package to CRAN, Creating R packages
@section Package name spaces
@cindex name spaces

@R{} has a name space management system for packages.  This system
allows the package writer to specify which variables in the package
should be @emph{exported} to make them available to package users, and
which variables should be @emph{imported} from other packages.

The current mechanism for specifying a name space for a package is to
place a @file{NAMESPACE} file in the top level package directory.  This
file contains @emph{name space directives} describing the imports and
exports of the name space.  Additional directives register any shared
objects to be loaded and any S3-style methods that are provided.  Note
that although the file looks like @R{} code (and often has @R{}-style
comments) it is not processed as @R{} code.  Only very simple
conditional processing of @code{if} statements is implemented.

Like other packages, packages with name spaces are loaded and attached
to the search path by calling @code{library}.  Only the exported
variables are placed in the attached frame.  Loading a package that
imports variables from other packages will cause these other packages to
be loaded as well (unless they have already been loaded), but they will
@emph{not} be placed on the search path by these implicit loads.

Name spaces are @emph{sealed} once they are loaded.  Sealing means that
imports and exports cannot be changed and that internal variable
bindings cannot be changed.  Sealing allows a simpler implementation
strategy for the name space mechanism.  Sealing also allows code
analysis and compilation tools to accurately identify the definition
corresponding to a global variable reference in a function body.

Note that adding a name space to a package changes the search strategy.
The package name space comes first in the search, then the imports, then
the base name space and then the normal search path.

@menu
* Specifying imports and exports::
* Registering S3 methods::
* Load hooks::
* An example::
* Summary -- converting an existing package::
* Name spaces with S4 classes and methods::
@end menu


@node Specifying imports and exports, Registering S3 methods, Package name spaces, Package name spaces
@subsection Specifying imports and exports

Exports are specified using the @code{export} directive in the
@file{NAMESPACE} file.  A directive of the form

@findex export
@example
export(f, g)
@end example

@noindent
specifies that the variables @code{f} and @code{g} are to be exported.
(Note that variable names may be quoted, and reserved words and
non-standard names such as @code{[<-.fractions} must be.)

For packages with many variables to export it may be more convenient to
specify the names to export with a regular expression using
@code{exportPattern}.  The directive

@findex exportPattern
@example
exportPattern("^[^\\.]")
@end example

@noindent
exports all variables that do not start with a period.

A package with a name space implicitly imports the base name space.
Variables exported from other packages with name spaces need to be
imported explicitly using the directives @code{import} and
@code{importFrom}.  The @code{import} directive imports all exported
variables from the specified package(s).  Thus the directives

@findex import
@example
import(foo, bar)
@end example

@noindent
specifies that all exported variables in the packages @pkg{foo} and
@pkg{bar} are to be imported.  If only some of the exported variables
from a package are needed, then they can be imported using
@code{importFrom}.  The directive

@findex importFrom
@example
importFrom(foo, f, g)
@end example

@noindent
specifies that the exported variables @code{f} and @code{g} of the
package @pkg{foo} are to be imported.

It is possible to export variables from a name space that it has
imported from other namespaces.

If a package only needs a few objects from another package it can use a
fully qualified variable reference in the code instead of a formal
import.  A fully qualified reference to the function @code{f} in package
@pkg{foo} is of the form @code{foo:::f}.  This is less efficient than a
formal import and also loses the advantage of recording all dependencies
in the @file{NAMESPACE} file, so this approach is usually not
recommended.  Evaluating @code{foo:::f} will cause package @pkg{foo} to
be loaded, but not attached, if it was not loaded already---this can be
an advantage in delaying the loading of a rarely used package.

Using @code{foo:::f} allows access to unexported objects: to confine
references to exported objects use @code{foo::f}.

@node Registering S3 methods, Load hooks, Specifying imports and exports, Package name spaces
@subsection Registering S3 methods

The standard method for S3-style @code{UseMethod} dispatching might fail
to locate methods defined in a package that is imported but not attached
to the search path.  To ensure that these methods are available the
packages defining the methods should ensure that the generics are
imported and register the methods using @code{S3method} directives.  If
a package defines a function @code{print.foo} intended to be used as a
@code{print} method for class @code{foo}, then the directive

@findex S3method
@example
S3method(print, foo)
@end example

@noindent
ensures that the method is registered and available for @code{UseMethod}
dispatch.  The function @code{print.foo} does not need to be exported.
Since the generic @code{print} is defined in @pkg{base} it does not need
to be imported explicitly.  This mechanism is intended for use with
generics that are defined in a name space.  Any methods for a generic
defined in a package that does not use a name space should be exported,
and the package defining and exporting the methods should be attached to
the search path if the methods are to be found.

(Note that function and class names may be quoted, and reserved words
and non-standard names such as @code{[<-} and @code{function} must
be.)

@node Load hooks, An example, Registering S3 methods, Package name spaces
@subsection Load hooks

There are a number of hooks that apply to packages with name spaces.
See @code{help(".onLoad")} for more details.

@findex .onLoad
@findex .onAttach
Packages with name spaces do not use the @code{.First.lib} function.
Since loading and attaching are distinct operations when a name space is
used, separate hooks are provided for each.  These hook functions are
called @code{.onLoad} and @code{.onAttach}.  They take the same
arguments as @code{.First.lib}; they should be defined in the name space
but not exported.

@findex .Last.lib
@findex .onUnload
However, packages with name spaces @emph{do} use the @code{.Last.lib}
function (provided it is exported from the name space) when
@code{detach} is called on the package.  There is also a hook
@code{.onUnload} which is called when the name space is unloaded
(@emph{via} a call to @code{unloadNamespace}, perhaps called by
@code{detach(unload=TRUE)}) with argument the full path to the installed
package's directory.  @code{.onUnload} should be defined in the name
space and not exported, but @code{.Last.lib} does need to be exported.

Packages are not likely to need @code{.onAttach} (except perhaps for a
start-up banner); code to set options and load shared objects should be
placed in a @code{.onLoad} function, or use made of the @code{useDynLib}
directive described next.

There can be one or more @code{useDynLib} directives which allows shared
objects that need to be loaded to be specified in the @file{NAMESPACE}
file.  The directive

@findex useDynLib
@example
useDynLib(foo)
@end example

@noindent
registers the shared object @code{foo} for loading with
@code{library.dynam}.  Loading of registered object(s) occurs after the
package code has been loaded and before running the load hook function.
Packages that would only need a load hook function to load a shared
object can use the @code{useDynLib} directive instead.

User-level hooks are also available: see the help on function
@code{setHook}.

The @code{useDynLib} directive also accepts the names of the native
routines that are to be used in @R{} @emph{via} the @code{.C}, @code{.Call},
@code{.Fortran} and @code{.External} interface functions.  These are given as
additional arguments to the directive, for example,

@example
useDynLib(foo, myRoutine, myOtherRoutine)
@end example

By specifying these names in the @code{useDynLib} directive, the native
symbols are resolved when the package is loaded and @R{} variables
identifying these symbols are added to the package's name space with
these names.  These can be used in the @code{.C}, @code{.Call},
@code{.Fortran} and @code{.External} calls in place of the name of the
routine and the @code{PACKAGE} argument.  For instance, we can call the
routine @code{myRoutine} from @R{} with the code

@example
 .Call(myRoutine, x, y)
@end example

@noindent
rather than

@example
 .Call("myRoutine", x, y, PACKAGE = "foo")
@end example

There are at least two benefits to this approach.  Firstly, the symbol
lookup is done just once for each symbol rather than each time the
routine is invoked. Secondly, this removes any ambiguity in resolving
symbols that might be present in several compiled DLLs.

In some circumstances, there will already be an @R{} variable in the
package with the same name as a native symbol. For example, we may have
an @R{} function in the package named @code{myRoutine}.  In this case,
it is necessary to map the native symbol to a different @R{} variable
name. This can be done in the @code{useDynLib} directive by using named
arguments. For instance, to map the native symbol name @code{myRoutine}
to the @R{} variable @code{myRoutine_sym}, we would use

@example
useDynLib(foo, myRoutine_sym = myRoutine, myOtherRoutine)
@end example

We could then call that routine from @R{} using the command

@example
 .Call(myRoutine_sym, x, y)
@end example

Symbols without explicit names are assigned to the @R{} variable with
that name.

In some cases, it may be preferable not to create @R{} variables in the
package's name space that identify the native routines.  It may be too
costly to compute these for many routines when the package is loaded
if many of these routines are not likely to be used.  In this case,
one can still perform the symbol resolution correctly using the DLL,
but do this each time the routine is called.  Given a reference to the
DLL as an @R{} variable, say @code{dll}, we can call the routine
@code{myRoutine} using the expression

@example
 .Call(dll$myRoutine, x, y)
@end example

The @code{$} operator resolves the routine with the given name in the
DLL using a call to @code{getNativeSymbol}.  This is the same
computation as above where we resolve the symbol when the package is
loaded. The only difference is that this is done each time in the case
of @code{dll$myRoutine}.

In order to use this dynamic approach (e.g., @code{dll$myRoutine}), one
needs the reference to the DLL as an @R{} variable in the package.  The
DLL can be assigned to a variable by using the @code{variable =
dllName} format used above for mapping symbols to @R{} variables.  For
example, if we wanted to assign the DLL reference for the DLL
@code{foo} in the example above to the variable @code{myDLL}, we would
use the following directive in the @file{NAMESPACE} file:

@example
myDLL = useDynLib(foo, myRoutine_sym = myRoutine, myOtherRoutine)
@end example

Then, the @R{} variable @code{myDLL} is in the package's name space and
available for calls such as @code{myDLL$dynRoutine} to access routines
that are not explicitly resolved at load time.

If the package has registration information (see @ref{Registering native
routines}), then we can use that directly rather than specifying the
list of symbols again in the @code{useDynLib} directive in the
@file{NAMESPACE} file.  Each routine in the registration information is
specified by giving a name by which the routine is to be specified along
with the address of the routine and any information about the number and
type of the parameters.  Using the @code{.registration} argument of
@code{useDynLib}, we can instruct the name space mechanism to create
@R{} variables for these symbols.  For example, suppose we have the
following registration information for a DLL named @code{myDLL}:

@example
R_CMethodDef cMethods[] = @{
   @{"foo", (DL_FUNC) &foo, 4, @{REALSXP, INTSXP, STRSXP, LGLSXP@}@},
   @{"bar_sym", (DL_FUNC) &bar, 0@},
   @{NULL, NULL, 0@}
@};

R_CallMethodDef callMethods[] = @{
   @{"R_call_sym", (DL_FUNC) &R_call, 4@},
   @{"R_version_sym", (DL_FUNC) &R_version, 0@},
   @{NULL, NULL, 0@}
@};
@end example

Then, the directive in the @file{NAMESPACE} file

@example
useDynLib(myDLL, .registration = TRUE)
@end example

@noindent
causes the DLL to be loaded and also for the @R{} variables @code{foo},
@code{bar_sym}, @code{R_call_sym} and @code{R_version_sym} to be
defined in the package's name space.

Note that the names for the @R{} variables are taken from the entry in
the registration information and do not need to be the same as the name
of the native routine.  This allows the creator of the registration
information to map the native symbols to non-conflicting variable names
in @R{}, e.g.@: @code{R_version} to @code{R_version_sym} for use in an
@R{} function such as

@example
R_version <- function()
@{
  .Call(R_version_sym)
@}
@end example

Using argument @code{.fixes} allows an automatic prefix to be added to
the registered symbols, which can be useful when working with an
existing package.  For example, package @pkg{KernSmooth} has

@example
useDynLib(KernSmooth, .registration = TRUE, .fixes = "F_")
@end example

@noindent
which makes the @R{} variables corresponding to the FORTRAN symbols
@code{F_bkde} and so on, and so avoid clashes with @R{} code in the name
space.


More information about this symbol lookup, along with some approaches
for customizing it, is available from
@uref{http://www.omegahat.org/examples/RDotCall}.

@node An example, Summary -- converting an existing package, Load hooks, Package name spaces
@subsection An example

As an example consider two packages named @pkg{foo} and @pkg{bar}.  The
@R{} code for package @pkg{foo} in file @file{foo.R} is

@quotation
@cartouche
@example
x <- 1
f <- function(y) c(x,y)
foo <- function(x) .Call("foo", x, PACKAGE="foo")
print.foo <- function(x, ...) cat("<a foo>\n")
@end example
@end cartouche
@end quotation

@noindent
Some C code defines a C function compiled into DLL @code{foo} (with an
appropriate extension).  The @file{NAMESPACE} file for this package is

@quotation
@cartouche
@example
useDynLib(foo)
export(f, foo)
S3method(print, foo)
@end example
@end cartouche
@end quotation

@noindent
The second package @pkg{bar} has code file @file{bar.R}

@quotation
@cartouche
@example
c <- function(...) sum(...)
g <- function(y) f(c(y, 7))
h <- function(y) y+9
@end example
@end cartouche
@end quotation

@noindent
and @file{NAMESPACE} file

@quotation
@cartouche
@example
import(foo)
export(g, h)
@end example
@end cartouche
@end quotation

@noindent
Calling @code{library(bar)} loads @pkg{bar} and attaches its exports to
the search path.  Package @pkg{foo} is also loaded but not attached to
the search path.  A call to @code{g} produces

@example
> g(6)
[1]  1 13
@end example

@noindent
This is consistent with the definitions of @code{c} in the two settings:
in @pkg{bar} the function @code{c} is defined to be equivalent to
@code{sum}, but in @pkg{foo} the variable @code{c} refers to the
standard function @code{c} in @pkg{base}.

@node Summary -- converting an existing package, Name spaces with S4 classes and methods, An example, Package name spaces
@subsection Summary -- converting an existing package

To summarize, converting an existing package to use a name space involves
several simple steps:

@itemize @bullet
@item
Identify the public definitions and place them in @code{export} directives.
@item
Identify S3-style method definitions and write corresponding
@code{S3method} declarations.
@item
Identify dependencies and replace any @code{require} calls by
@code{import} directives (and make appropriate changes in the
@code{Depends} and @code{Imports} fields of the @file{DESCRIPTION}
file).
@item
Replace @code{.First.lib} functions with @code{.onLoad} functions or
@code{useDynLib} directives.
@end itemize

@c or were in ca 2003
@c @noindent
@c Some code analysis tools to aid in this process are currently under
@c development.

@node Name spaces with S4 classes and methods,  , Summary -- converting an existing package, Package name spaces
@subsection Name spaces with S4 classes and methods

Some additional steps are needed for packages which make use of formal
(S4-style) classes and methods (unless these are purely used
internally).  The package should have @code{Depends: methods} in its
@file{DESCRIPTION} file and any classes and methods which are to be
exported need to be declared in the @file{NAMESPACE} file.  For example,
the @pkg{stats4} package has

@findex exportClasses
@findex exportMethods

@example
export(mle)
importFrom(graphics, plot)
importFrom(stats, AIC, coef, confint, logLik, optim, profile,
	   qchisq, update, vcov)
exportClasses(mle, profile.mle, summary.mle)
exportMethods(BIC, coef, confint, logLik, plot, profile,
              summary, show, update, vcov)
export(AIC)
@end example

@noindent
All S4 classes need to be listed in an @code{exportClasses}
directive. Alternatively, a pattern can be specified using
@code{exportClassPattern}. Generics for which S4 methods are defined
need to be declared in an @code{exportMethods} directive, and where the
generics are formed by taking over existing functions, those functions
need to be imported (explicitly unless they are defined in the
@code{base} name space).

Note that exporting methods on a generic in the namespace will also
export the generic, and exporting a generic in the namespace will also
export its methods.  Where a generic has been created in the package
solely to add S4 methods to it, it can be declared @emph{via} either or
both of @code{exports} or @code{exportMethods}, but the latter seems
clearer (and is used in the @pkg{stats4} example above).  On the other
hand, where a generic is created in a package without setting any
methods for it (such as @code{AIC} in @pkg{stats4}), @code{exports} must
be used.

Further, a package using classes and methods defined in another package
needs to import them, with directives

@findex importClassesFrom
@findex importMethodsFrom

@example
importClassesFrom(package, ...)
importMethodsFrom(package, ...)
@end example

@noindent
listing the classes and functions with methods respectively.  Suppose we
had two small packages @pkg{A} and @pkg{B} with @pkg{B} using @pkg{A}.
Then they could have @code{NAMESPACE} files

@quotation
@cartouche
@example
export(f1, ng1)
exportMethods("[")
exportClasses(c1)
@end example
@end cartouche
@end quotation

@noindent
and

@quotation
@cartouche
@example
importFrom(A, ng1)
importClassesFrom(A, c1)
importMethodsFrom(A, f1)
export(f4, f5)
exportMethods(f6, "[")
exportClasses(c1, c2)
@end example
@end cartouche
@end quotation

@noindent
respectively.

Note that @code{importMethodsFrom} will also import any generics defined
in the namespace on those methods.

If your package imports the whole of a name space, it will automatically
import the classes from that namespace.  It will also import methods,
but it is best to do so explicitly, especially where there are methods
being imported from more than one namespace.


@node Writing portable packages, Diagnostic messages, Package name spaces, Creating R packages
@section Writing portable packages

@menu
* Encoding issues::
* Binary distribution::
@end menu

Portable packages should have simple file names: use only alphanumeric
@acronym{ASCII} characters and @code{.}, and avoid those names not
allowed under Windows which are mentioned above.

@code{R CMD check} provides a basic set of checks, but often further
problems emerge when people try to install and use packages submitted to
@acronym{CRAN} -- many of these involve compiled code.  Here are some
further checks that you can do to make your package more portable.

@itemize

@item
If your package has a @file{configure} script, provide a
@file{configure.win} script to be used on Windows.  The @acronym{CRAN}
binary packages for Windows are built automatically, and if your package
does not build without intervention it is unlikely to be easily
available to a high proportion of @R{} users.

@item
If your package has a @file{Makevars} or @file{Makefile} file, make sure
that you use only portable make features.  Such files should be
LF-terminated (including the final line of the file) and not make use of
GNU extensions.  Commonly misused GNU extensions are conditional
inclusions (@code{ifeq} and the like), @code{$@{shell ...@}} and
@code{$@{wildcard ...@}}, and the use of @code{+=} and @code{:=}.  Also,
the use of @code{$<} other than in implicit rules is a GNU extension.
Unfortunately makefiles which use GNU extensions often run on other
platforms but do not have the intended results.

The use of @code{$@{shell ...@}} can be avoided by using backticks, e.g.@:

@example
PKG_CFLAGS = `gsl-config --cflags`
@end example

@noindent
which works in all versions of @command{make} known@footnote{GNU make,
BSD make as in FreeBSD and @command{bsdmake} on Darwin, AT&T make as
implemented on Solaris.} to be used with @R{}.

If you really must assume GNU make, declare it in the @file{DESCRIPTON}
file by

@example
SystemRequirements: GNU make
@end example

Since the only viable make for Windows is GNU make, it is permissible to
use GNU extensions in files @file{Makevars.win} or @file{Makefile.win}.

@item
Make use of the abilities of your compilers to check the
standards-conformance of your code.  For example, @command{gcc} can be used
with options @option{-Wall -pedantic} to alert you to potential
problems.  This is particularly important for C++, where @code{g++ -Wall
-pedantic} will alert you to the use of GNU extensions which fail to
compile on most other C++ compilers.  @R{} assumes a C99 compiler as
from version 2.12.0, but if you want your package to be portable to
earlier versions you should write in C90.  (In practice C99 has been
available on most platforms since @emph{ca} 2007 but old versions of
@command{gcc} were still in use for @R{} 2.11.x.)

If you use FORTRAN 77, @code{ftnchek}
(@uref{http://www.dsm.fordham.edu/~ftnchek/}) provides thorough testing
of conformance to the standard.

@item
Do be very careful with passing arguments between @R{}, C and
@acronym{FORTRAN} code.  In particular, @code{long} in C will be 32-bit
on most @R{} platforms (including those mostly used by the
@acronym{CRAN} maintainers), but 64-bit on many modern Unix and Linux
platforms.  It is rather unlikely that the use of @code{long} in C code
has been thought through: if you need a longer type than @code{int} you
should use a configure test for a C99 type such as @code{int_fast64_t}
(and failing that, @code{long long} @footnote{but note that @code{long
long} is not a standard C++ type, and C++ compilers set up for strict
checking will reject it.}) and typedef your own type to be @code{long} or
@code{long long}, or use another suitable type (such as @code{size_t}).

It is not safe to assume that @code{long} and pointer types are the same
size, and they are not on 64-bit Windows.  If you need to convert
pointers to and from integers use the C99 integer types @code{intptr_t}
and @code{uintptr_t}.

Note that @code{integer} in @acronym{FORTRAN} corresponds to @code{int}
in C on all @R{} platforms.

@item
Errors in memory allocation and reading/writing outside arrays are very
common causes of crashes (e.g., segfaults) on some machines.
See @ref{Using valgrind} for a tool which can be used to look for this.

@item
Many platforms will allow unsatisfied entry points in compiled code, but
will crash the application (here @R{}) if they are ever used.  Some
(notably Windows) will not.  Looking at the output of

@example
nm -pg mypkg.so  # @r{or other extension such as @file{.sl}}
@end example

@noindent
and checking if any of the symbols marked @code{U} is unexpected is a
good way to avoid this.

@item
Conflicts between symbols in DLLs are handled in very platform-specific
ways.  Good ways to avoid trouble are to make as many symbols as
possible static (check with @code{nm -pg}), and to use unusual names, as
well as ensuring you have used the @code{PACKAGE} argument that @code{R
CMD check} checks for.

@end itemize

Some notes on issues specific to porting to x64 Windows are available at
@url{http://www.stats.ox.ac.uk/~ripley/Win64/W64porting.html}.


@node Encoding issues, Binary distribution, Writing portable packages, Writing portable packages
@subsection Encoding issues

Care is needed if your package contains non-@acronym{ASCII} text, and in
particular if it is intended to be used in more than one locale.  It is
possible to mark the encoding used in the @file{DESCRIPTION} file and in
@file{.Rd} files, as discussed elsewhere in this manual.

First, consider carefully if you really need non-@acronym{ASCII} text.  Most
users of @R{} will only be able to view correctly text in their native
language group (e.g.@: Western European, Eastern European, Simplified
Chinese) and @acronym{ASCII}.  Other characters may not be rendered at all,
rendered incorrectly, or cause your @R{} code to give an error.
For documentation, marking the encoding and including @acronym{ASCII}
transliterations is likely to do a reasonable job.

Function @code{showNonASCII} in package @pkg{tools} can help in
finding non-@acronym{ASCII} bytes in files.


The most favourable circumstance is using UTF-8-encoded text in a
package that will only ever be used in a UTF-8 locale (and hence not on
Windows, for example).  In that case it is likely that text will be
rendered correctly in the terminal/console used to run @R{}, and files
written will be readable by other UTF-8-aware applications.  However,
plotting will be problematic.  On-screen plotting using the @samp{X11()}
device needs to find a font that covers the glyphs used, and this will
be machine-dependent: you may have Russian or Japanese fonts installed
but your users may not.  Using @samp{postscript} or @samp{pdf} will
choose a default 8-bit encoding depending on the language of the UTF-8
locale, and your users would need to be told how to select the
@samp{encoding} argument.  UTF-8-encoded text works reasonably well on
Windows using the @code{Rgui} console and the @code{windows} family of
devices, since they work internally in Unicode (UCS-2).

Another fairly common scenario is where a package will only be used in
one language, e.g.@: French.  It is not very safe to assume that all
such users would have their computers set to a French locale, but let us
assume so.  The problem then is that there are several possible
encodings for French locales, the most common ones being @samp{CP1252}
(Windows), @samp{ISO 8859-1} (Latin-1), @samp{ISO 8859-15} (Latin-9
which includes the Euro), and @samp{UTF-8}.  For characters in the
French language the first three agree, but they do not agree with
@samp{UTF-8}.  Further, you (or different users of your machine) can run
@R{} in different locales in different sessions, say @samp{fr_CA.utf8}
one day and @samp{fr_CH.iso88591} the next.  Declaring the encoding as
either @samp{latin1} or @samp{UTF-8} in the @file{DESCRIPTION} file will
enable this to work.

From @R{} 2.10.0 there is a fairly portable way to have arbitrary text
in character strings (only) in your @R{} code, which is to supply them
in Unicode as @code{\uxxxx} escapes.  If there are any characters not in
the current encoding the parser will encode the character string as
UTF-8 and mark it as such.  A variation of this approach that has worked
for Latin-1 text since @R{} 2.5.0 is to enter the text with @code{\x}
escapes and using @code{Encoding(x) <- "latin1"} to declare its
encoding, but that may not work in future versions of @R{}.

If you want to run @command{R CMD check} on a Unix-alike over a package
that sets the encoding you may need to specify a suitable locale
@emph{via} environment variable @env{R_ENCODING_LOCALES}.  The default
is equivalent to the value

@example
"latin1=en_US:latin2=pl_PL:UTF-8=en_US.utf8:latin9=fr_FR.iso885915@@euro"
@end example

@noindent
(which is appropriate for a system based on @code{glibc}) except that if
the current locale is UTF-8 when the package code is translated to UTF-8
for syntax checking.

@node Binary distribution,  , Encoding issues, Writing portable packages
@subsection Binary distribution

If you want to distribute a binary version of a package on Windows or
Mac OS X, there are further checks you need to do to check it is
portable: it is all too easy to depend on external software on your own
machine that other users will not have.

For Windows, check what other DLLs your package's DLL depends on
(`imports' from in the DLL tools' parlance).  A convenient GUI-based
tool to do so is `Dependency Walker'
(@uref{http://www.dependencywalker.com/}) for both 32-bit and 64-bit
DLLs -- note that this will report as missing links to @R{}'s own DLLs
such as @file{R.dll} and @file{Rblas.dll}.  For 32-bit DLLs only, the
command-line tool @command{pedump.exe -i} (in @file{Rtools*.exe}) can be
used, and for the brave, the @command{objdump} tool in the appropriate
toolchain will also reveal what DLLs are imported from.  If you use a
toolchain other than one provided by the @R{} developers or use your own
makefiles, watch out in particular for dependencies on the toolchain's
runtime DLLs such as @file{libgfortran}, @file{libstdc++} and
@file{libgcc_s}.

For Mac OS X, using @code{R CMD otool -L} on the package's shared
objects under @file{libs} will show what they depend on: watch for any
dependencies in @file{/usr/local/lib}, notably @file{libgfortran.2.dylib}.

@node Diagnostic messages, Internationalization, Writing portable packages, Creating R packages
@section Diagnostic messages

Now that diagnostic messages can be made available for translation, it
is important to write them in a consistent style.  Using the tools
described in the next section to extract all the messages can give a
useful overview of your consistency (or lack of it).

Some guidelines follow.

@itemize
@item
Messages are sentence fragments, and not viewed in isolation.  So it is
conventional not to capitalize the first word and not to end with a
period (or other punctuation).

@item
Try not to split up messages into small pieces.  In C error messages use
a single format string containing all English words in the messages.

In @R{} error messages do not construct a message with @code{paste} (such
messages will not be translated) but @emph{via} multiple arguments to
@code{stop} or @code{warning}, or @emph{via} @code{gettextf}.

@item
Do not use colloquialisms such as ``can't'' and ``don't''.

@item
If possible, make quotation marks part of your message as different
languages have different conventions.  In @R{} messages this means not
using @code{sQuote} or @code{dQuote} except where the argument is a
variable.

Conventionally single quotation marks are used for quotations such as

@example
'ord' must be a positive integer, at most the number of knots
@end example

@noindent
and double quotation marks when referring to an @R{} character string
such as

@example
'format' must be "normal" or "short" - using "normal"
@end example

Since @acronym{ASCII} does not contain directional quotation marks, it
is best to use @samp{'} and let the translator (including automatic
translation) use directional quotations where available.  The range of
quotation styles is immense: unfortunately we cannot reproduce them in a
portable @code{texinfo} document.  But as a taster, some languages use
`up' and `down' (comma) quotes rather than left or right quotes, and
some use guillemets (and some use what Adobe calls `guillemotleft' to
start and others use it to end).


@item
Occasionally messages need to be singular or plural (and in other
languages there may be no such concept or several plural forms --
Slovenian has four).  So avoid constructions such as was once used in
@code{library}

@example
if((length(nopkgs) > 0) && !missing(lib.loc)) @{
    if(length(nopkgs) > 1)
        warning("libraries ",
                paste(sQuote(nopkgs), collapse = ", "),
                " contain no packages")
    else
        warning("library ", paste(sQuote(nopkgs)),
                " contains no package")
@}
@end example

@noindent
and was replaced by

@example
if((length(nopkgs) > 0) && !missing(lib.loc)) @{
    pkglist <- paste(sQuote(nopkgs), collapse = ", ")
    msg <- sprintf(ngettext(length(nopkgs),
                     "library %s contains no packages",
                     "libraries %s contain no packages"),
                   pkglist)
    warning(msg, domain=NA)
@}
@end example

@noindent
Note that it is much better to have complete clauses as here, since
in another language one might need to say `There is no package in library
%s' or `There are no packages in libraries %s'.

@end itemize

@node Internationalization, CITATION files, Diagnostic messages, Creating R packages
@section Internationalization

There are mechanisms to translate the @R{}- and C-level error and warning
messages.  There are only available if @R{} is compiled with NLS support
(which is requested by @command{configure} option @option{--enable-nls},
the default).

The procedures make use of @code{msgfmt} and @code{xgettext} which are
part of @acronym{GNU} @code{gettext} and this will need to be installed:
Windows users can find pre-compiled binaries at the @acronym{GNU}
archive mirrors and packaged with the @code{poEdit} package
(@uref{http://@/poedit.sourceforge.net/@/download.php#win32}).

@menu
* C-level messages::
* R messages::
* Installing translations::
* Makefile support::
@end menu

@node C-level messages, R messages, Internationalization, Internationalization
@subsection C-level messages

The process of enabling translations is

@itemize
@item
In a header file that will be included in all the C files
containing messages that should be translated, declare

@example
#include <R.h>  /* to include Rconfig.h */

#ifdef ENABLE_NLS
#include <libintl.h>
#define _(String) dgettext ("@var{pkg}", String)
/* replace @var{pkg} as appropriate */
#else
#define _(String) (String)
#endif
@end example

@item
For each message that should be translated, wrap it in @code{_(...)},
for example

@example
error(_("'ord' must be a positive integer"));
@end example

If you want to use different messages for singular and plural forms, you
need to add

@example
#ifndef ENABLE_NLS
#define dngettext(pkg, String, StringP, N) (N > 1 ? StringP: String)
#endif
@end example

@noindent
and mark strings by

@example
dngettext(("@var{pkg}", @var{<singular string>}, @var{<plural string>}, n)
@end example

@noindent
(This is only supported from @R{} 2.10.0, so packages which use it need
to depend on @code{R (>= 2.10)}.)

@item
In the package's @file{src} directory run

@example
xgettext --keyword=_ -o @var{pkg}.pot *.c
@end example

@end itemize

The file @file{src/@var{pkg}.pot} is the template file, and
conventionally this is shipped as @file{po/@var{pkg}.pot}.  A translator
to another language makes a copy of this file and edits it (see the
@code{gettext} manual) to produce say @file{@var{ll}.po}, where @var{ll}
is the code for the language in which the translation is to be used.
(This file would be shipped in the @file{po} directory.)  Next run
@code{msgfmt} on @file{@var{ll}.po} to produce @file{@var{ll}.mo}, and
copy that to @file{inst/po/@var{ll}/LC_MESSAGES/@var{pkg}.mo}.  Now when
the package is loaded after installation it will look for translations
of its messages in the @file{po/@var{lang}/LC_MESSAGES/@var{pkg}.mo} file
for any language @var{lang} that matches the user's preferences (@emph{via} the
setting of the @code{LANGUAGE} environment variable or from the locale
settings).

@node R messages, Installing translations, C-level messages, Internationalization
@subsection R messages

Mechanisms to support the automatic translation of @R{} @code{stop},
@code{warning} and @code{message} messages are in place, most easily
if the package has a name space.  They make use of message catalogs in
the same way as C-level messages, but using domain @code{R-@var{pkg}}
rather than @code{@var{pkg}}.  Translation of character strings inside
@code{stop}, @code{warning} and @code{message} calls is automatically
enabled, as well as other messages enclosed in calls to @code{gettext}
or @code{gettextf}.  (To suppress this, use argument
@code{domain=NA}.)

Tools to prepare the @file{R-@var{pkg}.pot} file are provided in package
@pkg{tools}: @code{xgettext2pot} will prepare a file from all strings
occurring inside @code{gettext}/@code{gettextf}, @code{stop},
@code{warning} and @code{message} calls.  Some of these are likely to be
spurious and so the file is likely to need manual editing.
@code{xgettext} extracts the actual calls and so is more useful when
tidying up error messages.

Translation of messages which might be singular or plural can be very
intricate: languages can have up to four different forms.  The @R{}
function @code{ngettext} provides an interface to the C function of the
same name, and will choose an appropriate singular or plural form for
the selected language depending on the value of its first argument
@code{n}.

Packages without name spaces will need to use @code{domain="R-@var{pkg}"}
explicitly in calls to @code{stop}, @code{warning}, @code{message},
@code{gettext}/@code{gettextf} and @code{ngettext}.


@node Installing translations, Makefile support, R messages, Internationalization
@subsection Installing translations

Once the template files have been created, translations can be made.
Conventional translations have file extension @file{.po} and are placed
in the @file{po} subdirectory of the package with a name that is either
@samp{@var{ll}.po} or @samp{R-@var{ll}.po} for translations of the C and @R{}
messages respectively to language with code @samp{@var{ll}}.

@ifset UseExternalXrefs
@xref{Localization of messages, Localization of messages,
Customizing package compilation, R-admin,
R Installation and Administration}, for details of language codes.
@end ifset
@ifclear UseExternalXrefs
See `Localization of messages' in `R Installation and Administration',
for details of language codes.
@end ifclear

Translations need to be prepared and installed in @file{inst/po/} to be
usable once the package is installed.  To do this use the appropriate
lines of

@example
mkdir -p inst/po/@var{ll}/LC_MESSAGES
msgfmt -c --statistics -o inst/po/@var{ll}/LC_MESSAGES/R-@var{pkg}.mo po/R-@var{ll}.po
msgfmt -c --statistics -o inst/po/@var{ll}/LC_MESSAGES/@var{pkg}.mo po/@var{ll}.po
@end example

@noindent
from the package's top-level directory.  Using @option{-c} does some
useful validity checks, and @option{--statistics} notes the coverage.

@node Makefile support,  , Installing translations, Internationalization
@subsection Makefile support

There is some makefile support in the @file{po} directory of the @R{}
sources.  To use this to create the template files, use

@example
mkdir -p @var{pkgdir}/po
@end example

@noindent
where @file{@var{pkgdir}} is the top-level directory of the package
sources.  If the package has C source files in its @file{src} directory
that are marked for translation, use

@example
touch @var{pkgdir}/po/@var{pkg}.pot
@end example

@noindent
to create a dummy template file.  Then

@example
cd @var{R_BUILD_DIR}/po
make pkg-update PKG=@var{pkg} PKGDIR=@var{pkgdir}
@end example

@noindent
will create a template file of @R{} messages and update any template of
C messages.  It will also prepare and install a translation for the
@samp{en@@quot} pseudo-language, which if selected interprets (single
and double) quotes in their directional forms in suitable (e.g.@: UTF-8)
locales.

If translations to new languages are added in the @file{@var{pkgdir}/po}
directory, running the same @command{make} command will check and then
install the translations.

If the package sources are updated, the same @command{make} command will
update the template files, merge the changes into the translation
@file{.po} files and then installed the updated translations.  You will
often see that merging marks translations as `fuzzy' and this is
reported in the coverage statistics.  As fuzzy translations are
@emph{not} used, this is an indication that the translation files need
human attention.


This support is only for Unix-alikes, and the tools did not work
correctly on at least one Mac OS X system.

@findex CITATION
@cindex citation
@node CITATION files, Package types, Internationalization, Creating R packages
@section CITATION files

An installed file named @file{CITATION} will be used by the
@code{citation()} function.  (To be installed, it needed to be in the
@file{inst} subdirectory of the package sources.)

The @file{CITATION} file is parsed as @R{} code (in the package's
declared encoding@footnote{as from @R{} 2.8.0: this used to default to
Latin-1 but no longer does so}, or in ASCII if note is declared).  If no
such file is present, @code{citation} auto-generates citation
information from the package @file{DESCRIPTION} metadata, and an example
of what that would look like as a @file{CITATION} file can be seen in
recommended package @pkg{nlme} (see below): recommended packages
@pkg{boot}, @pkg{cluster} and @pkg{mgcv} have further examples.

A @file{CITATION} file will contain calls to function @code{bibentry}
(new style, only works with @R{} 2.12.0 or later), or to the functions
@code{citHeader}, @code{citEntry} and (optionally) @code{citFooter} (old
style).

Here is that for @pkg{nlme}, re-formatted:

@example
citHeader("To cite package 'nlme' in publications use:")

## R >= 2.8.0 passes package metadata to citation().
if(!exists("meta") || is.null(meta)) meta <- packageDescription("nlme")
year <- sub(".*(2[[:digit:]]@{3@})-.*", "\\1", meta$Date)
vers <- paste("R package version", meta$Version)

citEntry(entry="Manual",
         title = "nlme: Linear and Nonlinear Mixed Effects Models",
         author = personList(as.person("Jose Pinheiro"),
                             as.person("Douglas Bates"),
                             as.person("Saikat DebRoy"),
                             as.person("Deepayan Sarkar"),
                             person("R Development Core Team")),
         year = year,
         note = vers,

         textVersion =
         paste("Jose Pinheiro, Douglas Bates, Saikat DebRoy,",
               "Deepayan Sarkar and the R Development Core Team (",
               year,
               "). nlme: Linear and Nonlinear Mixed Effects Models. ",
               vers, ".", sep=""))
@end example

Note the way that information that may need to be updated is picked up
from the @file{DESCRIPTION} file -- it is tempting to hardcode such
information, but it normally then gets outdated.  See @code{?bibentry}
for further details of the information which can be provided.

The @file{CITATION} file should itself produce no output when
@code{source}-d.


@node Package types, Services, CITATION files, Creating R packages
@section Package types

The @file{DESCRIPTION} file has an optional field @code{Type} which if
missing is assumed to be @code{Package}, the sort of extension discussed
so far in this chapter.  Currently two other types are recognized, both
of which need write permission in the @R{} installation tree.

@menu
* Frontend::
* Translation::
@end menu

@node Frontend, Translation, Package types, Package types
@subsection Frontend

This is a rather general mechanism, designed for adding new front-ends
such as the former @pkg{gnomeGUI} package (see the @samp{Archve} area on
@acronym{CRAN}).  If a @file{configure} file is found in the top-level
directory of the package it is executed, and then if a @code{Makefile}
is found (often generated by @file{configure}), @code{make} is called.
If @code{R CMD INSTALL --clean} is used @code{make clean} is called.  No
other action is taken.

@code{R CMD build} can package up this type of extension, but @code{R
CMD check} will check the type and skip it.

@node Translation,  , Frontend, Package types
@subsection Translation

Conventionally, a translation package for language @var{ll} is called
@pkg{Translation-@var{ll}} and has @code{Type: Translation}.  It needs
to contain the directories @file{share/@/locale/@var{ll}} and
@file{library/@/@var{pkgname}/@/po/@/@var{ll}}, or at least those for
which translations are available.  The files @file{.mo} are installed in
the parallel places in the @R{} installation tree.

For example, a package @pkg{Translation-it} might be prepared from an
installed (and tested) version of @R{} by

@example
mkdir Translation-it
cd Translation-it
(cd $R_HOME; tar cf - share/locale/it library/*/po/it) | tar xf -
# the next step is not needed on Windows
msgfmt -c -o share/locale/it/LC_MESSAGES/RGui.mo $R_SRC_HOME/po/RGui-it.gmo
# create a DESCRIPTION file
cd ..
R CMD build Translation-it
@end example

It is probably appropriate to give the package a version number based on
the version of @R{} which has been translated.  So the
@file{DESCRIPTION} file might look like

@example
Package: Translation-it
Type: Translation
Version: 2.2.1-1
Title: Italian Translations for R 2.2.1
Description: Italian Translations for R 2.2.1
Author: The translators
Maintainer: Some Body <somebody@@some.where.net>
License: GPL (>= 2)
@end example

@node Services,  , Package types, Creating R packages
@section Services

Several members of the @R{} project have set up services to assist those
writing @R{} packages, particularly those intended for public
distribution.

@uref{http://win-builder.r-project.org, win-builder.r-project.org}
offers the automated preparation of (32/64-bit) Windows binaries from
well-tested source packages.

R-Forge (@uref{http://R-Forge.r-project.org, R-Forge.r-project.org}) and
RForge (@uref{http://www.rforge.net, www.rforge.net}) are similar
services with similar names.  Both provide source-code management
through SVN, daily building and checking, mailing lists and a repository
that can be accessed @emph{via} @code{install.packages} (R-Forge can be
selected by @code{setRepositories} and the GUI menus that use it).
Package developers have the opportunity to present their work on the
basis of project websites or news announcements.  Mailing lists, forums
or wikis provide useRs with convenient instruments for discussions and
for exchanging information between developers and/or interested useRs.


@node Writing R documentation files, Tidying and profiling R code, Creating R packages, Top
@chapter Writing R documentation files
@cindex Documentation, writing

@menu
* Rd format::
* Sectioning::
* Marking text::
* Lists and tables::
* Cross-references::
* Mathematics::
* Insertions::
* Indices::
* Platform-specific sections::
* Conditional text::
* Dynamic pages::
* User-defined macros::
* Encoding::
* Processing Rd format::
@end menu

@node Rd format, Sectioning, Writing R documentation files, Writing R documentation files
@section Rd format

@R{} objects are documented in files written in ``@R{} documentation''
(Rd) format, a simple markup language much of which closely resembles
(La)@TeX{}, which can be processed into a variety of formats,
including @LaTeX{}, @HTML{} and plain text.  The translation is
carried out by functions in the @pkg{tools} package called by the
script @command{Rdconv} in @file{@var{R_HOME}/bin} and by the
installation scripts for packages.

@c 1225 just prior to 2.9.0
The @R{} distribution contains more than 1200 such files which can be
found in the @file{src/library/@var{pkg}/man} directories of the @R{}
source tree, where @var{pkg} stands for one of the standard packages
which are included in the @R{} distribution.

As an example, let us look at a simplified version of
@file{src/library/base/man/load.Rd} which documents the @R{} function
@code{load}.

@quotation
@cartouche
@smallexample
% File src/library/base/man/load.Rd
\name@{load@}
\alias@{load@}
\title@{Reload Saved Datasets@}
\description@{
  Reload the datasets written to a file with the function
  \code@{save@}.
@}
\usage@{
load(file, envir = parent.frame())
@}
\arguments@{
  \item@{file@}@{a connection or a character string giving the
    name of the file to load.@}
  \item@{envir@}@{the environment where the data should be
    loaded.@}
@}
\seealso@{
  \code@{\link@{save@}@}.
@}
\examples@{
## save all data
save(list = ls(), file= "all.RData")

## restore the saved values to the current environment
load("all.RData")

## restore the saved values to the workspace
load("all.RData", .GlobalEnv)
@}
\keyword@{file@}
@end smallexample
@end cartouche
@end quotation

An @file{Rd} file consists of three parts.  The header gives basic
information about the name of the file, the topics documented, a title,
a short textual description and @R{} usage information for the objects
documented.  The body gives further information (for example, on the
function's arguments and return value, as in the above example).
Finally, there is an optional footer with keyword information.  The
header is mandatory.

Information is given within a series of @emph{sections} with standard
names (and user-defined sections are also allowed).  Unless otherwise
specified@footnote{e.g.@: @code{\alias}, @code{\keyword} and
@code{\note} sections.} these should occur only once in an @file{Rd}
file (in any order), and the processing software will retain only the
first occurrence of a standard section in the file, with a warning.

See @uref{http://developer.r-project.org/Rds.html, ``Guidelines for Rd
files''} for guidelines for writing documentation in @file{Rd} format
which should be useful for package writers.
@findex prompt
The @R{}
generic function @code{prompt} is used to construct a bare-bones @file{Rd}
file ready for manual editing.  Methods are defined for documenting
functions (which fill in the proper function and argument names) and
data frames.  There are also functions @code{promptData},
@code{promptPackage}, @code{promptClass}, and @code{promptMethods} for
other types of @file{Rd} file.

The general syntax of @file{Rd} files is summarized below.  For a detailed
technical discussion of current @file{Rd} syntax, see
@uref{http://developer.r-project.org/parseRd.pdf, ``Parsing Rd files''}.
Note that there have been a number of changes to the @file{Rd} format over the
years, which can be important if a package is intended to be used with
earlier versions of @R{}: see earlier versions of this manual if a
package is intended to be used with @R{} before 2.10.0.

@file{Rd} files consists of three types of text input.  The most common
is @LaTeX{}-like, with the backslash used as a prefix on markup
(e.g. @code{\alias}), and braces used to indicate arguments
(e.g. @code{@{load@}}).  The least common type of text is verbatim text,
where no markup is processed. The third type is @R{}-like, intended for
@R{} code, but allowing some embedded macros.  Quoted strings within
@R{}-like text are handled specially: regular character escapes such as
@code{\n} may be entered as-is.  Only markup starting with @code{\l}
(e.g.  @code{\link}) or @code{\v} (e.g. @code{\var}) will be recognized
within quoted strings.  The rarely used vertical tab @code{\v} must be
entered as @code{\\v}.

Each macro defines the input type for its argument.  For example, the
file initially uses @LaTeX{}-like syntax, and this is also used in the
@code{\description} section, but the @code{\usage} section uses
@R{}-like syntax, and the @code{\alias} macro uses verbatim syntax.
Comments run from a percent symbol @code{%} to the end of the line in
all types of text (as on the first line of the @code{load} example).

Because backslashes, braces and percent symbols have special meaning, to
enter them into text sometimes requires escapes using a backslash.  In
general balanced braces do not need to be escaped, but percent symbols
always do.  For the complete list of macros and rules for escapes, see
@uref{http://developer.r-project.org/parseRd.pdf, ``Parsing Rd files''}.

@menu
* Documenting functions::
* Documenting data sets::
* Documenting S4 classes and methods::
* Documenting packages::
@end menu

@node Documenting functions, Documenting data sets, Rd format, Rd format
@subsection Documenting functions

The basic markup commands used for documenting @R{} objects (in
particular, functions) are given in this subsection.

@table @code
@item \name@{@var{name}@}
@findex \name
@var{name} typically@footnote{There can be exceptions: for example
@file{Rd} files are not allowed to start with a dot, and have to be
uniquely named on a case-insensitive file system.} is the basename of
the @file{Rd} file containing the documentation.  It is the ``name'' of
the @file{Rd} object represented by the file and has to be unique in a
package.  To avoid problems with indexing the package manual, it may not
contain @samp{!}  @samp{|} nor @samp{@@}.  (@LaTeX{} special characters
are allowed, but may not be collated correctly in the index.)  There can
only be one @code{\name} entry in a file, and it must not contain any
markup.  Entries in the package manual will be in alphabetic@footnote{in
the current locale, and with special treatment for @LaTeX{} special
characters and with any @samp{@var{pkgname}-package} topic moved to
the top of the list.} order of the @code{\name} entries.

@item \alias@{@var{topic}@}
@findex \alias
The @code{\alias} sections specify all ``topics'' the file documents.
This information is collected into index data bases for lookup by the
on-line (plain text and @HTML{}) help systems.  The @var{topic} can
contain spaces, but (for historical reasons) leading and trailing spaces
will be stripped.  Percent and left brace need to be escaped by
a backslash.

There may be several @code{\alias} entries.  Quite often it is
convenient to document several @R{} objects in one file.  For example,
file @file{Normal.Rd} documents the density, distribution function,
quantile function and generation of random variates for the normal
distribution, and hence starts with

@example
@group
\name@{Normal@}
\alias@{Normal@}
\alias@{dnorm@}
\alias@{pnorm@}
\alias@{qnorm@}
\alias@{rnorm@}
@end group
@end example

@noindent
Also, it is often convenient to have several different ways to refer to
an @R{} object, and an @code{\alias} does not need to be the name of an
object.

Note that the @code{\name} is not necessarily a topic documented, and if
so desired it needs to have an explicit @code{\alias} entry (as in this
example).

@item \title@{@var{Title}@}
@findex \title
Title information for the @file{Rd} file.  This should be capitalized
and not end in a period; try to limit its length to at most 65
characters for widest compatibility.

Since @R{} version 2.12.0 markup has been supported
in the text, but use of characters other than English text and
punctuation (e.g., @samp{<}) may limit portability.

There must be one (and only one) @code{\title} section in a help file.

@item \description@{@dots{}@}
@findex \description
A short description of what the function(s) do(es) (one paragraph, a few
lines only).  (If a description is too long and cannot easily be
shortened, the file probably tries to document too much at once.)
This is mandatory except for package-overview files.

@item \usage@{@var{fun}(@var{arg1}, @var{arg2}, @dots{})@}
@findex \usage
One or more lines showing the synopsis of the function(s) and variables
documented in the file.  These are set in typewriter font.  This is an
@R{}-like command.

The usage information specified should match the function definition
@emph{exactly} (such that automatic checking for consistency between
code and documentation is possible).

It is no longer advisable to use @code{\synopsis} for the actual
synopsis and show modified synopses in the @code{\usage}.  Support for
@code{\synopsis} will be removed eventually.  To indicate that a
function can be used in several different ways, depending on the named
arguments specified, use section @code{\details}.  E.g.,
@file{abline.Rd} contains

@example
@group
\details@{
  Typical usages are
\preformatted@{
abline(a, b, untf = FALSE, \dots)
......
@}
@end group
@end example

@findex \method
Use @code{\method@{@var{generic}@}@{@var{class}@}} to indicate the name
of an S3 method for the generic function @var{generic} for objects
inheriting from class @code{"@var{class}"}.  In the printed versions,
this will come out as @var{generic} (reflecting the understanding that
methods should not be invoked directly but @emph{via} method dispatch), but
@code{codoc()} and other QC tools always have access to the full name.

For example, @file{print.ts.Rd} contains

@example
@group
\usage@{
\method@{print@}@{ts@}(x, calendar, \dots)
@}
@end group
@end example

@noindent
which will print as

@example
@group
Usage:

     ## S3 method for class 'ts':
     print(x, calendar, ...)
@end group
@end example

Usage for replacement functions should be given in the style of
@code{dim(x) <- value} rather than explicitly indicating the name of the
replacement function (@w{@code{"dim<-"}} in the above).  Similarly, one
can use @code{\method@{@var{generic}@}@{@var{class}@}(@var{arglist}) <-
value} to indicate the usage of an S3 replacement method for the generic
replacement function @code{"@var{generic}<-"} for objects inheriting
from class @code{"@var{class}"}.

Usage for S3 methods for extracting or replacing parts of an object, S3
methods for members of the Ops group, and S3 methods for user-defined
(binary) infix operators (@samp{%@var{xxx}%}) follows the above rules,
using the appropriate function names.  E.g., @file{Extract.factor.Rd}
contains

@example
@group
\usage@{
\method@{[@}@{factor@}(x, \dots, drop = FALSE)
\method@{[[@}@{factor@}(x, \dots)
\method@{[@}@{factor@}(x, \dots) <- value
@}
@end group
@end example

@noindent
which will print as

@example
@group
Usage:

     ## S3 method for class 'factor':
     x[..., drop = FALSE]
     ## S3 method for class 'factor':
     x[[...]]
     ## S3 replacement method for class 'factor':
     x[...] <- value
@end group
@end example

@findex \S3method
@code{\S3method} is accepted as an alternative to @code{\method}.

@item \arguments@{@dots{}@}
@findex \arguments
Description of the function's arguments, using an entry of the form

@example
\item@{@var{arg_i}@}@{@var{Description of arg_i}.@}
@end example

@noindent for each element of the argument list.  (Note that there is
no whitespace between the three parts of the entry.) There may be
optional text outside the @code{\item} entries, for example to give
general information about groups of parameters.


@item \details@{@dots{}@}
@findex \details
A detailed if possible precise description of the functionality
provided, extending the basic information in the @code{\description}
slot.

@item \value@{@dots{}@}
@findex \value
Description of the function's return value.

If a list with multiple values is returned, you can use entries of the
form

@example
\item@{@var{comp_i}@}@{@var{Description of comp_i}.@}
@end example

@noindent
for each component of the list returned.  Optional text may
precede@footnote{Text between or after list items was discarded prior to
@R{} 2.10.0, and is discouraged.} this list (see for example the help
for @code{rle}).  Note that @code{\value} is implicitly a
@code{\describe} environment, so that environment should not be used for
listing components, just individual @code{\item@{@}@{@}} entries.

@item \references@{@dots{}@}
@findex \references
A section with references to the literature.  Use @code{\url@{@}} or
@code{\href@{@}@{@}} for web pointers.

@item \note@{...@}
@findex \note
Use this for a special note you want to have pointed out.  Multiple
@code{\note} sections are allowed, but might be confusing to the end users.

For example, @file{pie.Rd} contains

@example
@group
\note@{
  Pie charts are a very bad way of displaying information.
  The eye is good at judging linear measures and bad at
  judging relative areas.
  ......
@}
@end group
@end example

@item \author@{@dots{}@}
@findex \author
Information about the author(s) of the @file{Rd} file.  Use
@code{\email@{@}} without extra delimiters (such as @samp{( )} or
@samp{< >}) to specify email addresses, or @code{\url@{@}} or
@code{\href@{@}@{@}} for web pointers.

@item \seealso@{@dots{}@}
@findex \seealso
Pointers to related @R{} objects, using @code{\code@{\link@{...@}@}} to
refer to them (@code{\code} is the correct markup for @R{} object names,
and @code{\link} produces hyperlinks in output formats which support
this.  @xref{Marking text}, and @ref{Cross-references}).

@findex \examples
@item \examples@{@dots{}@}
Examples of how to use the function.  Code in this section is set
in typewriter font without reformatting and is run by
@code{example()} unless marked otherwise (see below).

Examples are not only useful for documentation purposes, but also
provide test code used for diagnostic checking of @R{} code.  By
default, text inside @code{\examples@{@}} will be displayed in the
output of the help page and run by @code{example()} and by @code{R CMD
check}.  You can use @code{\dontrun@{@}}
@findex \dontrun
for text that should only be shown, but not run, and
@code{\dontshow@{@}}
@findex \dontshow
for extra commands for testing that should not be shown to users, but
will be run by @code{example()}.  (Previously this was called
@code{\testonly}, and that is still accepted.)

Text inside @code{\dontrun@{@}} is verbatim, but the other parts
of the @code{\examples} section are @R{}-like text.

For example,

@example
@group
x <- runif(10)       # @r{Shown and run.}
\dontrun@{plot(x)@}    # @r{Only shown.}
\dontshow@{log(x)@}    # @r{Only run.}
@end group
@end example

Thus, example code not included in @code{\dontrun} must be executable!
In addition, it should not use any system-specific features or require
special facilities (such as Internet access or write permission to
specific directories).  Text included in @code{\dontrun} is indicated by
comments in the processed help files: it need not be valid @R{} code but
the escapes must still be used for @code{%}, @code{\} and unpaired
braces as in other verbatim text.

Data needed for making the examples executable can be obtained by random
number generation (for example, @code{x <- rnorm(100)}), or by using
standard data sets listed by @code{data()} (see @code{?data} for more
info).

Finally, there is @code{\donttest}, used (at the beginning of a separate
line) to mark code that should be run by @code{examples()} but not by
@code{R CMD check}.  This should be needed only occasionally but can be
used for code which might fail in circumstances that are hard to test
for, for example in some locales.  (Use e.g. @code{capabilities()} to
test for features needed in the examples wherever possible, and you can
also use @code{try()} or @code{trycatch()}.)

@findex \keyword
@item \keyword@{@var{key}@}
There can be zero or more @code{\keyword} sections per file.
Each @code{\keyword} section should specify a single keyword, preferably
one of the standard keywords as listed in file @file{KEYWORDS} in the
@R{} documentation directory (default @file{@var{R_HOME}/doc}).  Use
e.g.@: @code{RShowDoc("KEYWORDS")} to inspect the standard keywords from
within @R{}.  There can be more than one @code{\keyword} entry if the @R{}
object being documented falls into more than one category, or none.

The special keyword @samp{internal} marks a page of internal objects
that are not part of the package's API.  If the help page for object
@code{foo} has keyword @samp{internal}, then @code{help(foo)} gives this
help page, but @code{foo} is excluded from several object indices,
including the alphabetical list of objects in the @HTML{} help system.

@code{help.search()} can search by keyword, including user-defined
values: however the `Search Engine & Keywords' HTML page accessed
@emph{via} @code{help.start()} provides single-click access only to a
pre-defined list of keywords.
@end table


@node Documenting data sets, Documenting S4 classes and methods, Documenting functions, Rd format
@subsection Documenting data sets

The structure of @file{Rd} files which document @R{} data sets is slightly
different.  Sections such as @code{\arguments} and @code{\value} are not
needed but the format and source of the data should be explained.

As an example, let us look at @file{src/library/datasets/man/rivers.Rd}
which documents the standard @R{} data set @code{rivers}.

@quotation
@cartouche
@smallexample
\name@{rivers@}
\docType@{data@}
\alias@{rivers@}
\title@{Lengths of Major North American Rivers@}
\description@{
  This data set gives the lengths (in miles) of 141 \dQuote@{major@}
  rivers in North America, as compiled by the US Geological
  Survey.
@}
\usage@{rivers@}
\format@{A vector containing 141 observations.@}
\source@{World Almanac and Book of Facts, 1975, page 406.@}
\references@{
  McNeil, D. R. (1977) \emph@{Interactive Data Analysis@}.
  New York: Wiley.
@}
\keyword@{datasets@}
@end smallexample
@end cartouche
@end quotation

This uses the following additional markup commands.

@table @code
@item \docType@{@dots{}@}
Indicates the ``type'' of the documentation object.  Always @samp{data}
for data sets, and @samp{package} for @file{@var{pkg}-package.Rd}
overview files.  Documentation for S4 methods and classes uses
@samp{methods} (from @code{promptMethods()}) and @samp{class} (from
@code{promptClass()}).

@item \format@{@dots{}@}
@findex \format
A description of the format of the data set (as a vector, matrix, data
frame, time series, @dots{}).  For matrices and data frames this should
give a description of each column, preferably as a list or table.
@xref{Lists and tables}, for more information.

@item \source@{@dots{}@}
@findex \source
Details of the original source (a reference or @acronym{URL}).  In
addition, section @code{\references} could give secondary sources and
usages.
@end table

Note also that when documenting data set @var{bar},

@itemize @bullet
@item
The @code{\usage} entry is always @code{@var{bar}} or (for packages
which do not use lazy-loading of data) @code{data(@var{bar})}.  (In
particular, only document a @emph{single} data object per @file{Rd} file.)
@item
The @code{\keyword} entry should always be @samp{datasets}.
@end itemize

If @code{@var{bar}} is a data frame, documenting it as a data set can
be initiated @emph{via} @code{prompt(@var{bar})}.  Otherwise, the @code{promptData}
function may be used.

@node Documenting S4 classes and methods, Documenting packages, Documenting data sets, Rd format
@subsection Documenting S4 classes and methods

There are special ways to use the @samp{?}  operator, namely
@samp{class?@var{topic}} and @samp{methods?@var{topic}}, to access
documentation for S4 classes and methods, respectively.  This mechanism
depends on conventions for the topic names used in @code{\alias}
entries.  The topic names for S4 classes and methods respectively are of
the form

@example
@var{class}-class
@var{generic},@var{signature_list}-method
@end example

@noindent
where @var{signature_list} contains the names of the classes in the
signature of the method (without quotes) separated by @samp{,} (without
whitespace), with @samp{ANY} used for arguments without an explicit
specification.  E.g., @samp{genericFunction-class} is the topic name for
documentation for the S4 class @code{"genericFunction"}, and
@samp{coerce,ANY,NULL-method} is the topic name for documentation for
the S4 method for @code{coerce} for signature @code{c("ANY", "NULL")}.

Skeletons of documentation for S4 classes and methods can be generated
by using the functions @code{promptClass()} and @code{promptMethods()}
from package @pkg{methods}.  If it is necessary or desired to provide an
explicit function declaration (in a @code{\usage} section) for an S4
method (e.g., if it has ``surprising arguments'' to be mentioned
explicitly), one can use the special markup

@example
\S4method@{@var{generic}@}@{@var{signature_list}@}(@var{argument_list})
@end example

@noindent
(e.g., @samp{\S4method@{coerce@}@{ANY,NULL@}(from, to)}).

To make full use of the potential of the on-line documentation system,
all user-visible S4 classes and methods in a package should at least
have a suitable @code{\alias} entry in one of the package's @file{Rd} files.
If a package has methods for a function defined originally somewhere
else, and does not change the underlying default method for the
function, the package is responsible for documenting the methods it
creates, but not for the function itself or the default method.

An S4 replacement method is documented in the same way as an S3 one: see
the description of  @code{\method} in @ref{Documenting functions}.


See @kbd{help("Documentation", package = "methods")} for more
information on using and creating on-line documentation for S4 classes and
methods.

@node Documenting packages,  , Documenting S4 classes and methods, Rd format
@subsection Documenting packages

Packages may have an overview help page with an @code{\alias}
@code{@var{pkgname}-package}, e.g.@: @samp{utils-package} for the
@pkg{utils} package, when @code{package?@var{pkgname}} will open that
help page.  If a topic named @code{@var{pkgname}} does not exist in
another @file{Rd} file, it is helpful to use this as an additional
@code{\alias}.

Skeletons of documentation for a package can be generated using the
function @code{promptPackage()}.  If the @code{final = TRUE} argument
is used, then the @file{Rd} file will be generated in final form, containing
the information that would be produced up to
@code{library(help = @var{pkgname})}.  Otherwise (the default) comments
will be inserted giving suggestions for content.

Apart from the mandatory @code{\name} and @code{\title} and the
@code{@var{pkgname}-package} alias, the only requirement for the package
overview page is that it include a @code{\docType@{package@}} statement.
All other content is optional.  We suggest that it should be a short
overview, to give a reader unfamiliar with the package enough
information to get started.  More extensive documentation is better
placed into a package vignette (@pxref{Writing package vignettes}) and
referenced from this page, or into individual man pages for the
functions, datasets, or classes.

@node Sectioning, Marking text, Rd format, Writing R documentation files
@section Sectioning

To begin a new paragraph or leave a blank line in an example, just
insert an empty line (as in (La)@TeX{}).  To break a line, use
@code{\cr}.
@findex \cr

In addition to the predefined sections (such as @code{\description@{@}},
@code{\value@{@}}, etc.), you can ``define'' arbitrary ones by
@code{\section@{@var{section_title}@}@{@dots{}@}}.
@findex \section
For example

@example
\section@{Warning@}@{
  You must not call this function unless @dots{}
@}
@end example

@noindent
For consistency with the pre-assigned sections, the section name (the
first argument to @code{\section}) should be capitalized (but not all
upper case).  Whitespace between the first and second braced expressions
is not allowed.  Markup (e.g.@: @code{\code}) within the section title
may cause problems with the latex conversion (depending on the version
of macro packages such as @samp{hyperref}) and so should be avoided.

The @code{\subsection} macro takes arguments in the same format as
@code{\section}, but is used within a section, so it may be used to
nest subsections within sections or other subsections.  There is no
predefined limit on the nesting level, but formatting is not designed
for more than 3 levels (i.e. subsections within subsections within
sections).

Note that additional named sections are always inserted at a fixed
position in the output (before @code{\note}, @code{\seealso} and the
examples), no matter where they appear in the input (but in the same
order amongst themselves as in the input).


@node Marking text, Lists and tables, Sectioning, Writing R documentation files
@section Marking text
@cindex Marking text in documentation

The following logical markup commands are available for emphasizing or
quoting text.

@table @code
@item \emph@{@var{text}@}
@findex \emph
@itemx \strong@{@var{text}@}
@findex \strong
Emphasize @var{text} using @emph{italic} and @strong{bold} font if
possible; @code{\strong} is regarded as stronger (more emphatic).

@item \bold@{@var{text}@}
@findex \bold
Set @var{text} in @b{bold} font if possible.

@item \sQuote@{@var{text}@}
@findex \sQuote
@itemx \dQuote@{@var{text}@}
@findex \dQuote
Portably single or double quote @var{text} (without hard-wiring the
characters used for quotation marks).
@end table

Each of the above commands takes @LaTeX{}-like input, so other macros
may be used within @var{text}.

The following logical markup commands are available for indicating
specific kinds of text.  Except as noted, these take verbatim text
input, and so other macros may not be used within them.  Some characters
will need to be escaped (@pxref{Insertions}).

@table @code
@item \code@{@var{text}@}
@findex \code
Indicate text that is a literal example of a piece of an @R{} program,
e.g., a fragment of @R{} code or the name of an @R{} object.  Text is
entered in @R{}-like syntax, and displayed using @code{typewriter} font
if possible.  Macros @code{\var} and @code{\link} are interpreted within
@var{text}.

@item \preformatted@{@var{text}@}
@findex \preformatted
Indicate text that is a literal example of a piece of a program.  Text
is displayed using @code{typewriter} font if possible.  Formatting,
e.g.@: line breaks, is preserved.

Due to limitations in @LaTeX{} as of this writing, this macro may not be
nested within other markup macros other than @code{\dQuote} and
@code{\sQuote}, as errors or bad formatting may result.

@item \kbd@{@var{keyboard-characters}@}
@findex \kbd
Indicate keyboard input, using @kbd{slanted typewriter} font if
possible, so users can distinguish the characters they are supposed to
type from computer output.  Text is entered verbatim.

@item \samp@{@var{text}@}
@findex \samp
Indicate text that is a literal example of a sequence of characters,
entered verbatim.  No wrapping or reformatting will occur.  Displayed
using @code{typewriter} font if possible.


@item \verb@{@var{text}@}
@findex \verb
Indicate text that is a literal example of a sequence of characters,
with no interpretation of e.g.@: @code{\var}, but which will be included
within word-wrapped text.  Displayed using @code{typewriter} font if
possible.

@item \pkg@{@var{package_name}@}
@findex \pkg
Indicate the name of an @R{} package.  @LaTeX{}-like.

@item \file@{@var{file_name}@}
@findex \file
Indicate the name of a file.  Text is @LaTeX{}-like, so backslash needs
to be escaped.  Displayed using a distinct font if possible.

@item \email@{@var{email_address}@}
@findex \email
Indicate an electronic mail address.  @LaTeX{}-like, will be rendered as
a hyperlink in HTML and PDF conversion.  Displayed using
@code{typewriter} font if possible.

@item \url@{@var{uniform_resource_locator}@}
@findex \url
Indicate a uniform resource locator (@acronym{URL}) for the World Wide
Web.  The argument is handled verbatim, and rendered as a hyperlink in
HTML and PDF conversion.  Displayed using @code{typewriter} font if
possible.

@item \href@{@var{uniform_resource_locator}@}@{@var{text}@}
@findex \href
Indicate a hyperlink to the World Wide Web. The first argument is handled
verbatim, and is used as the @acronym{URL} in the hyperlink, with the
second argument of @LaTeX{}-like text displayed to the user.

@item \var@{@var{metasyntactic_variable}@}
@findex \var
Indicate a metasyntactic variable.  In some cases this will be rendered
distinctly, e.g.@: in italic, but not in all@footnote{Currently it is
rendered differently only in HTML conversions, and @LaTeX{} conversion
outside @samp{\usage} and @samp{\examples} environments.}. @LaTeX{}-like.
@item \env@{@var{environment_variable}@}
@findex \env
Indicate an environment variable. Verbatim.
Displayed using @code{typewriter} font if possible
@item \option@{@var{option}@}
@findex \option
Indicate a command-line option.  Verbatim.
Displayed using @code{typewriter} font if possible.
@item \command@{@var{command_name}@}
@findex \command
Indicate the name of a command. @LaTeX{}-like, so @code{\var} is
interpreted.  Displayed using @code{typewriter} font if possible.
@item \dfn@{@var{term}@}
@findex \dfn
Indicate the introductory or defining use of a term. @LaTeX{}-like.
@item \cite@{@var{reference}@}
@findex \cite
Indicate a reference without a direct cross-reference @emph{via} @code{\link}
(@pxref{Cross-references}), such as the name of a book. @LaTeX{}-like.
@item \acronym@{@var{acronym}@}
@findex \acronym
Indicate an acronym (an abbreviation written in all capital letters),
such as @acronym{GNU}. @LaTeX{}-like.
@end table


@node Lists and tables, Cross-references, Marking text, Writing R documentation files
@section Lists and tables
@cindex Lists and tables in documentation

@findex \itemize
@findex \enumerate
The @code{\itemize} and @code{\enumerate} commands take a single
argument, within which there may be one or more @code{\item} commands.
The text following each @code{\item} is formatted as one or more
paragraphs, suitably indented and with the first paragraph marked with a
bullet point (@code{\itemize}) or a number (@code{\enumerate}).

Note that unlike argument lists, @code{\item} in these formats is
followed by a space and the text (not enclosed in braces).  For example

@example
  \enumerate@{
    \item A database consists of one or more records, each with one or
    more named fields.
    \item Regular lines start with a non-whitespace character.
    \item Records are separated by one or more empty lines.
  @}
@end example

@code{\itemize} and @code{\enumerate} commands may be nested.

@findex \describe
The @code{\describe} command is similar to @code{\itemize} but allows
initial labels to be specified.  Each @code{\item} takes two arguments,
the label and the body of the item, in exactly the same way as an
argument or value @code{\item}.  @code{\describe} commands are mapped to
@code{<DL>} lists in @HTML{} and @code{\description} lists in @LaTeX{}.

@findex \tabular
The @code{\tabular} command takes two arguments.  The first gives for
each of the columns the required alignment (@samp{l} for
left-justification, @samp{r} for right-justification or @samp{c} for
centring.)  The second argument consists of an arbitrary number of
lines separated by @code{\cr}, and with fields separated by @code{\tab}.
For example:

@example
@group
  \tabular@{rlll@}@{
    [,1] \tab Ozone   \tab numeric \tab Ozone (ppb)\cr
    [,2] \tab Solar.R \tab numeric \tab Solar R (lang)\cr
    [,3] \tab Wind    \tab numeric \tab Wind (mph)\cr
    [,4] \tab Temp    \tab numeric \tab Temperature (degrees F)\cr
    [,5] \tab Month   \tab numeric \tab Month (1--12)\cr
    [,6] \tab Day     \tab numeric \tab Day of month (1--31)
  @}
@end group
@end example

@noindent
There must be the same number of fields on each line as there are
alignments in the first argument, and they must be non-empty (but can
contain only spaces).  (There is no whitespace between @code{\tabular}
and the first argument, nor between the two arguments.)

@node Cross-references, Mathematics, Lists and tables, Writing R documentation files
@section Cross-references
@cindex Cross-references in documentation

@findex \link
The markup @code{\link@{@var{foo}@}} (usually in the combination
@code{\code@{\link@{@var{foo}@}@}}) produces a hyperlink to the help for
@var{foo}.  Here @var{foo} is a @emph{topic}, that is the argument of
@code{\alias} markup in another @file{Rd} file (possibly in another package).
Hyperlinks are supported in some of the formats to which @file{Rd} files are
converted, for example @HTML{} and PDF, but ignored in others, e.g.@:
the text format.

One main usage of @code{\link} is in the @code{\seealso} section of the
help page, @pxref{Rd format}.

Note that whereas leading and trailing spaces are stripped when
extracting a topic from a @code{\alias}, they are not stripped when
looking up the topic of a @code{\link}.

@cindex \linkS4class
You can specify a link to a different topic than its name by
@code{\link[=@var{dest}]@{@var{name}@}} which links to topic @var{dest}
with name @var{name}.  This can be used to refer to the documentation
for S3/4 classes, for example @code{\code@{"\link[=abc-class]@{abc@}"@}}
would be a way to refer to the documentation of an S4 class @code{"abc"}
defined in your package, and
@code{\code@{"\link[=terms.object]@{terms@}"@}} to the S3 @code{"terms"}
class (in package @pkg{stats}).  To make these easy to read in the
source file, @code{\code@{"\linkS4class@{abc@}"@}} expands to the form
given above.

There are two other forms of optional argument specified as
@code{\link[@var{pkg}]@{@var{foo}@}} and
@code{\link[@var{pkg:bar}]@{@var{foo}@}} to link to the package
@pkg{@var{pkg}}, to @emph{files} @file{@var{foo}.html} and
@file{@var{bar}.html} respectively.  These are rarely needed, perhaps to
refer to not-yet-installed packages (but there the @HTML{} help system
will resolve the link at run time) or in the normally undesirable event
that more than one package offers help on a topic@footnote{a common
example in @acronym{CRAN} packages is @code{\link[mgcv]@{gam@}}.} (in
which case the present package has precedence so this is only needed to
refer to other packages).  They are currently only used in HTML help
(and ignored for hyperlinks in @LaTeX{} conversions of help pages), and
link to the file rather than the topic (since there is no way to know
which topics are in which files in an uninstalled package).  The
@strong{only} reason to use these forms for base and recommended
packages is to force a reference to a package that might be further down
the search path.  Because they have been frequently misused, as from
@R{} 2.10.0 the HTML help system looks for topic @code{@var{foo}} in
package @pkg{@var{pkg}} if it does not find file @file{@var{foo}.html}.

@node Mathematics, Insertions, Cross-references, Writing R documentation files
@section Mathematics
@cindex Mathematics in documentation
@findex \eqn
@findex \deqn

Mathematical formulae should be set beautifully for printed
documentation yet we still want something useful for text and @HTML{}
online help.  To this end, the two commands
@code{\eqn@{@var{latex}@}@{@var{ascii}@}} and
@code{\deqn@{@var{latex}@}@{@var{ascii}@}} are used.  Whereas @code{\eqn}
is used for ``inline'' formulae (corresponding to @TeX{}'s
@code{$@dots{}$}), @code{\deqn} gives ``displayed equations'' (as in
@LaTeX{}'s @code{displaymath} environment, or @TeX{}'s
@code{$$@dots{}$$}).  Both arguments are treated as verbatim text.

Both commands can also be used as @code{\eqn@{@var{latexascii}@}} (only
@emph{one} argument) which then is used for both @var{latex} and
@var{ascii}.  No whitespace is allowed between command and the first
argument, nor between the first and second arguments.

The following example is from @file{Poisson.Rd}:

@example
@group
  \deqn@{p(x) = \frac@{\lambda^x e^@{-\lambda@}@}@{x!@}@}@{%
        p(x) = \lambda^x exp(-\lambda)/x!@}
  for \eqn@{x = 0, 1, 2, \ldots@}.
@end group
@end example

@iftex
For the @LaTeX{} manual, this becomes

@quotation
@cartouche
@tex
$$ p(x) = \lambda^x\ {e^{-\lambda} \over x!} $$
for $x = 0, 1, 2, \ldots$.
@end tex
@end cartouche
@end quotation
@end iftex

For text on-line help we get

@quotation
@cartouche
@example
    p(x) = lambda^x exp(-lambda)/x!

for x = 0, 1, 2, ....
@end example
@end cartouche
@end quotation

As from \R 2.11.0 Greek letters (both cases) will be rendered in HTML if
preceded by a backslash, @code{\dots} and @code{\ldots} will be rendered
as ellipses and @code{\sqrt}, @code{\ge} and @code{\le} as mathematical
symbols.

Note that only basic @LaTeX{} can be used, there being no provision to
specify @LaTeX{} style files such as the AMS extensions.

@node Insertions, Indices, Mathematics, Writing R documentation files
@section Insertions

@findex \R
Use @code{\R} for the @R{} system
itself.  Use
@code{\dots}
@findex \dots
for the dots in function argument lists @samp{@dots{}}, and
@code{\ldots}
@findex \ldots
for ellipsis dots in ordinary text.@footnote{There is only a fine
distinction between @code{\dots} and @code{\ldots}.  It is technically
incorrect to use @code{\ldots} in code blocks and @code{tools::checkRd}
will warn about this---on the other hand the current converters treat
them the same way in code blocks, and elsewhere apart from the small
distinction between the two in LaTeX.}  These can be followed by
@code{@{@}}, and should be unless followed by whitespace.

After an unescaped @samp{%}, you can put your own comments regarding the
help text.  The rest of the line (but not the newline at the end) will
be completely disregarded.  Therefore, you can also use it to make part
of the ``help'' invisible.

You can produce a backslash (@samp{\}) by escaping it by another
backslash.  (Note that @code{\cr} is used for generating line breaks.)

The ``comment'' character @samp{%} and unpaired braces@footnote{See the
examples section in the file @file{Paren.Rd} for an example.}
@emph{almost always} need to be escaped by @samp{\}, and @samp{\\} can
be used for backslash and needs to be when there two or more adjacent
backslashes).  In @R{}-like code quoted strings are handled slightly
differently; see @uref{http://developer.r-project.org/parseRd.pdf,
``Parsing Rd files''} for details -- in particular braces should not be
escaped in quoted strings.

All of @samp{% @{ @} \} should be escaped in @LaTeX{}-like text.

@findex \enc
Text which might need to be represented differently in different
encodings should be marked by @code{\enc}, e.g.@:
@code{\enc@{J@"oreskog@}@{Joreskog@}} (with no whitespace between the
braces) where the first argument will be used where encodings are
allowed and the second should be @acronym{ASCII} (and is used for e.g.@:
the text conversion in locales that cannot represent the encoded form).
(This is intended to be used for individual words, not whole sentences
or paragraphs.)

@node Indices, Platform-specific sections, Insertions, Writing R documentation files
@section Indices
@cindex Indices

The @code{\alias} command (@pxref{Documenting functions}) is used to
specify the ``topics'' documented, which should include @emph{all} @R{}
objects in a package such as functions and variables, data sets, and S4
classes and methods (@pxref{Documenting S4 classes and methods}).  The
on-line help system searches the index data base consisting of all
alias topics.

@findex \concept
In addition, it is possible to provide ``concept index entries'' using
@code{\concept}, which can be used for @code{help.search()} lookups.
E.g., file @file{cor.test.Rd} in the standard package @pkg{stats}
contains

@example
\concept@{Kendall correlation coefficient@}
\concept@{Pearson correlation coefficient@}
\concept@{Spearman correlation coefficient@}
@end example

@noindent
so that e.g.@: @kbd{??Spearman} will succeed in finding the
help page for the test for association between paired samples using
Spearman's @eqn{\rho, rho}.


(Note that @code{help.search()} only uses ``sections'' of documentation
objects with no additional markup.)

If you want to cross reference such items from other help files @emph{via}
@code{\link}, you need to use @code{\alias} and not @code{\concept}.


@node  Platform-specific sections, Conditional text, Indices, Writing R documentation files
@section Platform-specific documentation
@cindex Platform-specific documentation

Sometimes the documentation needs to differ by platform.  Currently two
OS-specific options are available, @samp{unix} and @samp{windows}, and
lines in the help source file can be enclosed in

@example
@group
#ifdef @var{OS}
   ...
#endif
@end group
@end example

@noindent
or

@example
@group
#ifndef @var{OS}
   ...
#endif
@end group
@end example

@noindent
for OS-specific inclusion or exclusion.  Such blocks should not be
nested, and should be entirely within a block (that, is between the
opening and closing brace of a section or item), or at top-level contain
one or more complete sections.

If the differences between platforms are extensive or the @R{} objects
documented are only relevant to one platform, platform-specific @file{Rd} files
can be put in a @file{unix} or @file{windows} subdirectory.

@node  Conditional text, Dynamic pages, Platform-specific sections, Writing R documentation files
@section Conditional text
@cindex conditionals
@findex \if
@findex \ifelse
@findex \out

Occasionally the best content for one output format is different from
the best content for another.  For this situation, the
@code{\if@{@var{format}@}@{@var{text}@}} or
@code{\ifelse@{@var{format}@}@{@var{text}@}@{@var{alternate}@}} markup
is used.  Here @var{format} is a comma separated list of formats in
which the @var{text} should be rendered.  The @var{alternate} will be
rendered if the format does not match.  Both @var{text} and
@var{alternate} may be any sequence of text and markup.

Currently the following formats are recognized:  @code{example},
@code{html}, @code{latex} and @code{text}.  These select output for
the corresponding targets. (Note that @code{example} refers to
extracted example code rather than the displayed example in some other
format.)  Also accepted are @code{TRUE} (matching all formats) and
@code{FALSE} (matching no formats).  These could be the output
of the @code{\Sexpr} macro (@pxref{Dynamic pages}).

The @code{\out@{@var{literal}@}} macro would usually be used within
the @var{text} part of @code{\if@{@var{format}@}@{@var{text}@}}.  It
causes the renderer to output the literal text exactly, with no
attempt to escape special characters.  For example, use
the following to output the markup necessary to display the Greek letter in
@LaTeX{} or HTML, and the text string @code{alpha} in other formats:
@example
\if@{latex@}@{\out@{\alpha@}@}\ifelse@{html@}@{\out@{&alpha;@}@}@{alpha@}
@end example

@node Dynamic pages, User-defined macros, Conditional text, Writing R documentation files
@section Dynamic pages
@cindex dynamic pages
@findex \Sexpr
@findex \RdOpts

Two new macros supporting dynamically generated man pages were
introduced in @R{} 2.10.0, @code{\Sexpr} and @code{\RdOpts}.  These
are modelled after Sweave, and are intended to contain executable @R{}
expressions in the @file{Rd} file.

The main argument to @code{\Sexpr} must be valid @R{} code that can be
executed. It may also take options in square brackets before the main
argument. Depending on the options, the code may be executed at
package build time, package install time, or man page rendering time.

The options follow the same format as in Sweave, but different options
are supported.  Currently the allowed options and their defaults are:

@itemize @bullet
@item @code{eval=TRUE}
Whether the @R{} code should be evaluated.

@item @code{echo=FALSE}
Whether the @R{} code should be echoed.  If @code{TRUE}, a display will
be given in a preformatted block.  For example,
@code{\Sexpr[echo=TRUE]@{ x <- 1 @}} will be displayed as
@example
> x <- 1
@end example

@item @code{keep.source=TRUE}
Whether to keep the author's formatting when displaying the
code, or throw it away and use a deparsed version.

@item @code{results=text}
How should the results be displayed?  The possibilities
are:

@itemize @minus
@item @code{results=text}
Apply @code{as.character()} to the result of the code, and insert it
as a text element.

@item @code{results=verbatim}
Print the results of the code just as if it was executed at the console,
and include the printed results verbatim.  (Invisible results will not print.)

@item @code{results=rd}
The result is assumed to be a character vector containing markup to
be passed to @code{parse_Rd(fragment=TRUE)}, with the result inserted in place.
This could be used to insert computed aliases, for instance.

@item @code{results=hide}
Insert no output.
@end itemize

@item @code{strip.white=TRUE}
Remove leading and trailing white space from each line of
output if @code{strip.white=TRUE}.  With
@code{strip.white=all}, also remove blank lines.

@item @code{stage=install}
Control when this macro is run.  Possible values are
@itemize @minus
@item @code{stage=build}
The macro is run when building a source tarball.

@item @code{stage=install}
The macro is run when installing from source.

@item @code{stage=render}
The macro is run when displaying the help page.
@end itemize

Conditionals such as @code{#ifdef}
(@pxref{Platform-specific sections}) are applied after the
@code{build} macros but before the @code{install} macros.  In some
situations (e.g. installing directly from a source directory without a
tarball, or building a binary package) the above description is not
literally accurate, but authors can rely on the sequence being
@code{build}, @code{#ifdef}, @code{install}, @code{render}, with all
stages executed.

Code is only run once in each stage, so a @code{\Sexpr[results=rd]}
macro can output an @code{\Sexpr} macro designed for a later stage,
but not for the current one or any earlier stage.

@item @code{width, height, fig}
These options are currently allowed but ignored.
@end itemize

The @code{\RdOpts} macro is used to set new defaults for options to apply
to following uses of @code{\Sexpr}.

For more details, see the online document
@uref{http://developer.r-project.org/parseRd.pdf, ``Parsing Rd
files''}.

@node User-defined macros, Encoding, Dynamic pages, Writing R documentation files
@section User-defined macros
@cindex user-defined macros
@findex \newcommand
@findex \renewcommand

Two new macros supporting user-defined macros were introduced in
R 2.12.0.  The @code{\newcommand} and @code{\renewcommand} macros allow
new macros to be defined within an Rd file.  These are similar but
not identical to the same-named LaTeX macros.

They each take two arguments which are parsed verbatim.  The first is
the name of the new macro including the initial backslash, and the second
is the macro definition.  As in @LaTeX{}, @code{\newcommand} requires that the
new macro not have been previously defined, whereas @code{\renewcommand}
allows existing macros (including all built-in ones) to be replaced.

Also as in @LaTeX{}, the new macro may be defined to take arguments,
and numeric placeholders such as @code{#1} are used in the macro
definition. However, unlike @LaTeX{}, the number of arguments is
determined automatically from the highest placeholder number seen in
the macro definition.  For example, a macro definition containing
@code{#1} and @code{#3} (but no other placeholders) will define a
three argument macro (whose second argument will be ignored). As in
@LaTeX{}, at most 9 arguments may be defined. If the @code{#}
character is followed by a non-digit it will have no special
significance.  All arguments to user-defined macros will be parsed as
verbatim text, and simple text-substitution will be used to replace
the place-holders, after which the replacement text will be parsed.

For example, the @file{NEWS.Rd} file currently uses the definition
@example
\newcommand@{\PR@}@{\Sexpr[results=rd]@{tools:::Rd_expr_PR(#1)@}@}
@end example
which defines @code{\PR} to be a single argument macro; then code like
@example
\PR@{1234@}
@end example
will expand to
@example
\Sexpr[results=rd]@{tools:::Rd_expr_PR(1234)@}
@end example
when parsed.

@node Encoding, Processing Rd format, User-defined macros, Writing R documentation files
@section Encoding
@cindex encoding

Rd files are text files and so it is impossible to deduce the encoding
they are written in unless @acronym{ASCII}: files with 8-bit characters
could be UTF-8, Latin-1, Latin-9, KOI8-R, EUC-JP, @emph{etc}.  So an
@code{\encoding@{@}} section must be used to specify the encoding if it
is not @acronym{ASCII}.  (The @code{\encoding@{@}} section must be on a
line by itself, and in particular one containing no non-@acronym{ASCII}
characters.  The encoding declared in the @file{DESCRIPTION} file will
be used if none is declared in the file.)  The @file{Rd} files are
converted to UTF-8 before parsing and so the preferred encoding for the
files themselves is now UTF-8.

Wherever possible, avoid non-@acronym{ASCII} chars in @file{Rd} files, and
even symbols such as @samp{<}, @samp{>}, @samp{$}, @samp{^}, @samp{&},
@samp{|}, @samp{@@}, @samp{~}, and @samp{*} outside verbatim
environments (since they may disappear in fonts designed to render
text).  (Function @code{showNonASCII} in package @pkg{tools} can help
in finding non-@acronym{ASCII} bytes in the files.)

For convenience, encoding names @samp{latin1} and @samp{latin2} are
always recognized: these and @samp{UTF-8} are likely to work fairly
widely.  However, this does not mean that all characters in UTF-8 will
be recognized, and the coverage of non-Latin characters@footnote{@R{}
2.9.0 added support for UTF-8 Cyrillic characters in @LaTeX{}, but on
some OSes this will need Cyrillic support added to @LaTeX{}, so
environment variable @env{_R_CYRILLIC_TEX_} needs to be set to a
non-empty value to enable this.} is low.

The @code{\enc} command (@pxref{Insertions}) can be used to provide
transliterations which will be used in conversions that do not support
the declared encoding.

The @LaTeX{} conversion converts the file to UTF-8 from the declared
encoding, and includes a

@example
\inputencoding@{utf8@}
@end example

@noindent
command, and this needs to be matched by a suitable invocation of the
@command{\usepackage@{inputenc@}} command.  The @R{} utility @command{R
CMD Rd2dvi} looks at the converted code and includes the encodings used:
it might for example use

@example
\usepackage[utf8]@{inputenc@}
@end example

@noindent
(Use of @code{utf8} as an encoding requires @LaTeX{} dated 2003/12/01 or
later.  Also, the use of Cyrillic characters in @samp{UTF-8} appears to
also need @samp{\usepackage[T2A]@{fontenc@}}, and @command{R CMD Rd2dvi}
includes this conditionally on the file @file{t2aenc.def} being present
and environment variable @env{_R_CYRILLIC_TEX_} being set.)

Note that this mechanism works best with Latin letters: the coverage of
UTF-8 in @LaTeX{} is quite low.



@node Processing Rd format,  , Encoding, Writing R documentation files
@section Processing Rd format
@cindex Processing Rd format

There are several commands to process Rd files from the system command
line.

@findex R CMD Rdconv
Using @code{R CMD Rdconv} one can convert @R{} documentation format to
other formats, or extract the executable examples for run-time testing.
The currently supported conversions are to plain text, @HTML{} and
@LaTeX{} as well as extraction of the examples.

@findex R CMD Rd2dvi
@findex R CMD Rd2pdf
@code{R CMD Rd2dvi} generates DVI (or, if option @option{--pdf} is
given, or it is invoked as @code{R CMD Rd2pdf}, PDF) output from
documentation in @file{Rd} files, which can be specified either
explicitly or by the path to a directory with the sources of a package.
In the latter case, a reference manual for all documented objects in the
package is created, including the information in the @file{DESCRIPTION}
files.

@findex R CMD Sd2Rd
@code{R CMD Sd2Rd} converts @Sl{} version 3 documentation files (which
use an extended Nroff format) and @Sl{} version 4 documentation (which
uses SGML markup) to @file{Rd} format.  This is useful when porting a
package originally written for the @Sl{} system to @R{}.  @Sl{} version
3 files usually have extension @file{.d}, whereas version 4 ones have
extension @file{.sgml} or @file{.sgm}.  (This command is no longer
supported, and requires Perl to be installed.)

@findex R CMD Sweave
@findex R CMD Stangle
@code{R CMD Sweave} and @code{R CMD Stangle} process @samp{Sweave}
documentation files (usually with extension @samp{.Snw} or @samp{.Rnw}):
@code{R CMD Stangle} is use to extract the @R{} code fragments.

The exact usage and a detailed list of available options for all of
these commands can be obtained by running @code{R CMD @var{command}
--help}, e.g., @kbd{R CMD Rdconv --help}.  All available commands can be
listed using @kbd{R --help} (or @kbd{Rcmd --help} under Windows).

All of these work under Windows.  You will need to have installed the
the tools to build packages from source as described in the ``R
Installation and Administration'' manual.


@node Tidying and profiling R code, Debugging, Writing R documentation files, Top
@chapter Tidying and profiling R code

@menu
* Tidying R code::
* Profiling R code for speed::
* Profiling R code for memory use::
* Profiling compiled code::
@end menu

@R{} code which is worth preserving in a package and perhaps making
available for others to use is worth documenting, tidying up and perhaps
optimizing. The last two of these activities are the subject of this
chapter.

@node Tidying R code, Profiling R code for speed, Tidying and profiling R code, Tidying and profiling R code
@section Tidying R code
@cindex Tidying R code

@R{} treats function code loaded from packages and code entered by users
differently.  Code entered by users has the source code stored in an
attribute, and when the function is listed, the original source is
reproduced.  Loading code from a package (by default) discards the
source code, and the function listing is re-created from the parse tree
of the function.

Normally keeping the source code is a good idea, and in particular it
avoids comments being moved around in the source.  However, we can make
use of the ability to re-create a function listing from its parse tree
to produce a tidy version of the function, for example with consistent
indentation and spaces around operators.  This tidied version is much
easier to read, not least by other users who are used to the standard
format.  Although the deparsing cannot do so, we recommend the
consistent use of the preferred assignment operator @samp{<-} (rather
than @samp{=}) for assignment.

We can subvert the keeping of source in two ways.

@enumerate
@item
The option @code{keep.source} can be set to @code{FALSE} before the code
is loaded into @R{}.
@item
The stored source code can be removed by removing the @code{source}
attribute, for example by

@example
attr(myfun, "source") <- NULL
@end example

@end enumerate

@noindent
In each case if we then list the function we will get the standard
layout.

Suppose we have a file of functions @file{myfuns.R} that we want to
tidy up.  Create a file @file{tidy.R} containing

@example
@group
options(keep.source = FALSE)
source("myfuns.R")
dump(ls(all = TRUE), file = "new.myfuns.R")
@end group
@end example

@noindent
and run @R{} with this as the source file, for example by @kbd{R
--vanilla < tidy.R} or by pasting into an @R{} session.  Then the file
@file{new.myfuns.R} will contain the functions in alphabetical order in
the standard layout.  Warning:  comments in your functions will be lost.

The standard format provides a good starting point for further tidying.
Many package authors use a version of Emacs (on a Unix-alike or Windows)
to edit @R{} code, using the ESS[S] mode of the @acronym{ESS} Emacs
package.  See @ref{R coding standards, , R coding standards, R-ints, R
Internals} for style options within the ESS[S] mode recommended for the
source code of @R{} itself.


@node Profiling R code for speed, Profiling R code for memory use, Tidying R code, Tidying and profiling R code
@section Profiling R code for speed
@cindex Profiling
@findex Rprof

It is possible to profile @R{} code on Windows and most@footnote{@R{}
has to be built to enable this, but the option
@option{--enable-R-profiling} is the default.} Unix-alike versions of
@R{}.

The command @command{Rprof} is used to control profiling, and its help
page can be consulted for full details.  Profiling works by recording at
fixed intervals@footnote{For Unix-alikes these are intervals of CPU
time, and for Windows of elapsed time.} (by default every 20 msecs)
which @R{} function is being used, and recording the results in a file
(default @file{Rprof.out} in the working directory).  Then the function
@code{summaryRprof} or the command-line utility @code{R CMD Rprof
@var{Rprof.out}} can be used to summarize the activity.

As an example, consider the following code (from Venables & Ripley,
2002, pp. 225--6).

@smallexample
@group
library(MASS); library(boot)
storm.fm <- nls(Time ~ b*Viscosity/(Wt - c), stormer,
                start = c(b=30.401, c=2.2183))
st <- cbind(stormer, fit=fitted(storm.fm))
storm.bf <- function(rs, i) @{
    st$Time <-  st$fit + rs[i]
    tmp <- nls(Time ~ (b * Viscosity)/(Wt - c), st,
               start = coef(storm.fm))
    tmp$m$getAllPars()
@}
rs <- scale(resid(storm.fm), scale = FALSE) # remove the mean
Rprof("boot.out")
storm.boot <- boot(rs, storm.bf, R = 4999) # slow enough to profile
Rprof(NULL)
@end group
@end smallexample

@noindent
Having run this we can summarize the results by

@smallexample
@group
R CMD Rprof boot.out

Each sample represents 0.02 seconds.
Total run time: 22.52 seconds.

Total seconds: time spent in function and callees.
Self seconds: time spent in function alone.
@end group

@group
   %       total       %        self
 total    seconds     self    seconds    name
 100.0     25.22       0.2      0.04     "boot"
  99.8     25.18       0.6      0.16     "statistic"
  96.3     24.30       4.0      1.02     "nls"
  33.9      8.56       2.2      0.56     "<Anonymous>"
  32.4      8.18       1.4      0.36     "eval"
  31.8      8.02       1.4      0.34     ".Call"
  28.6      7.22       0.0      0.00     "eval.parent"
  28.5      7.18       0.3      0.08     "model.frame"
  28.1      7.10       3.5      0.88     "model.frame.default"
  17.4      4.38       0.7      0.18     "sapply"
  15.0      3.78       3.2      0.80     "nlsModel"
  12.5      3.16       1.8      0.46     "lapply"
  12.3      3.10       2.7      0.68     "assign"
 ...
@end group

@group
   %        self        %      total
  self    seconds     total   seconds    name
   5.7      1.44       7.5      1.88     "inherits"
   4.0      1.02      96.3     24.30     "nls"
   3.6      0.92       3.6      0.92     "$"
   3.5      0.88      28.1      7.10     "model.frame.default"
   3.2      0.80      15.0      3.78     "nlsModel"
   2.8      0.70       9.8      2.46     "qr.coef"
   2.7      0.68      12.3      3.10     "assign"
   2.5      0.64       2.5      0.64     ".Fortran"
   2.5      0.62       7.1      1.80     "qr.default"
   2.2      0.56      33.9      8.56     "<Anonymous>"
   2.1      0.54       5.9      1.48     "unlist"
   2.1      0.52       7.9      2.00     "FUN"
  ...
@end group
@end smallexample

@noindent
(Function names are not quoted on Windows.)  This often produces
surprising results and can be used to identify bottlenecks or pieces of
@R{} code that could benefit from being replaced by compiled code.

Two warnings: profiling does impose a small performance penalty, and the
output files can be very large if long runs are profiled at the default
sampling interval.

Profiling short runs can sometimes give misleading results.  @R{} from
time to time performs @emph{garbage collection} to reclaim unused
memory, and this takes an appreciable amount of time which profiling
will charge to whichever function happens to provoke it.  It may be
useful to compare profiling code immediately after a call to @code{gc()}
with a profiling run without a preceding call to @code{gc}.

More detailed analysis of the output can be achieved by the tools in the
@acronym{CRAN} packages @pkg{proftools} and @pkg{profr}: in particular
these allow call graphs to be studied.

@node Profiling R code for memory use, Profiling compiled code, Profiling R code for speed, Tidying and profiling R code
@section Profiling R code for memory use
@cindex Profiling
@cindex Memory use

Measuring memory use in @R{} code is useful either when the code takes
more memory than is conveniently available or when memory allocation
and copying of objects is responsible for slow code. There are three
ways to profile memory use over time in @R{} code. All three require
@R{} to have been compiled with @option{--enable-memory-profiling},
which is not the default. All can be misleading, for different
reasons.

In understanding the memory profiles it is useful to know a little more
about @R{}'s memory allocation. Looking at the results of @code{gc()}
shows a division of memory into @code{Vcells} used to store the contents
of vectors and @code{Ncells} used to store everything else, including
all the administrative overhead for vectors such as type and length
information.  In fact the vector contents are divided into two
pools. Memory for small vectors (by default 128 bytes or less) is
obtained in large chunks and then parcelled out by @R{}; memory for
larger vectors is obtained directly from the operating system.

Some memory allocation is obvious in interpreted code, for example,

@smallexample
y <- x + 1
@end smallexample

@noindent
allocates memory for a new vector @code{y}. Other memory allocation is
less obvious and occurs because @code{R} is forced to make good on its
promise of `call-by-value' argument passing.  When an argument is
passed to a function it is not immediately copied. Copying occurs (if
necessary) only when the argument is modified.  This can lead to
surprising memory use. For example, in the `survey' package we have

@smallexample
print.svycoxph <- function (x, ...)
@{
    print(x$survey.design, varnames = FALSE, design.summaries = FALSE,
        ...)
    x$call <- x$printcall
    NextMethod()
@}
@end smallexample

@noindent
It may not be obvious that the assignment to @code{x$call} will cause
the entire object @code{x} to be copied.  This copying to preserve the
call-by-value illusion is usually done by the internal C function
@code{duplicate}.

The main reason that memory-use profiling is difficult is garbage
collection. Memory is allocated at well-defined times in an @R{}
program, but is freed whenever the garbage collector happens to run.

@menu
* Memory statistics from Rprof::
* Tracking memory allocations::
* Tracing copies of an object::
@end menu

@node Memory statistics from Rprof, Tracking memory allocations, Profiling R code for memory use, Profiling R code for memory use
@subsection Memory statistics from @code{Rprof}
@findex Rprof
@findex summaryRprof

The sampling profiler @code{Rprof} described in the previous section can
be given the option @code{memory.profiling=TRUE}. It then writes out the
total @R{} memory allocation in small vectors, large vectors, and cons
cells or nodes at each sampling interval. It also writes out the number
of calls to the internal function @code{duplicate}, which is called to
copy @R{} objects. @code{summaryRprof} provides summaries of this
information.  The main reason that this can be misleading is that the
memory use is attributed to the function running at the end of the
sampling interval. A second reason is that garbage collection can make
the amount of memory in use decrease, so a function appears to use
little memory.  Running under @code{gctorture} helps with both problems:
it slows down the code to effectively increase the sampling frequency
and it makes each garbage collection release a smaller amount of memory.
Changing the memory limits with @code{mem.limits()} may also be useful,
to see how the code would run under different memory conditions.

@node Tracking memory allocations, Tracing copies of an object, Memory statistics from Rprof, Profiling R code for memory use
@subsection Tracking memory allocations
@findex Rprofmem

The second method of memory profiling uses a memory-allocation
profiler, @code{Rprofmem()}, which writes out a stack trace to an
output file every time a large vector is allocated (with a
user-specified threshold for `large') or a new page of memory is
allocated for the @R{} heap. Summary functions for this output are still
being designed.

Running the example from the previous section with

@smallexample
> Rprofmem("boot.memprof",threshold=1000)
> storm.boot <- boot(rs, storm.bf, R = 4999)
> Rprofmem(NULL)
@end smallexample

@noindent
shows that apart from some initial and final work in @code{boot} there
are no vector allocations over 1000 bytes.

@node  Tracing copies of an object,  , Tracking memory allocations, Profiling R code for memory use
@subsection Tracing copies of an object
@findex tracemem
@findex untracemem

The third method of memory profiling involves tracing copies made of a
specific (presumably large) @R{} object. Calling @code{tracemem} on an
object marks it so that a message is printed to standard output when
the object is copied @emph{via} @code{duplicate} or coercion to another type,
or when a new object of the same size is created in arithmetic
operations. The main reason that this can be misleading is that
copying of subsets or components of an object is not tracked. It may
be helpful to use @code{tracemem} on these components.


In the example above we can run @code{tracemem} on the data frame
@code{st}

@smallexample
> tracemem(st)
[1] "<0x9abd5e0>"
> storm.boot <- boot(rs, storm.bf, R = 4)
memtrace[0x9abd5e0->0x92a6d08]: statistic boot
memtrace[0x92a6d08->0x92a6d80]: $<-.data.frame $<- statistic boot
memtrace[0x92a6d80->0x92a6df8]: $<-.data.frame $<- statistic boot
memtrace[0x9abd5e0->0x9271318]: statistic boot
memtrace[0x9271318->0x9271390]: $<-.data.frame $<- statistic boot
memtrace[0x9271390->0x9271408]: $<-.data.frame $<- statistic boot
memtrace[0x9abd5e0->0x914f558]: statistic boot
memtrace[0x914f558->0x914f5f8]: $<-.data.frame $<- statistic boot
memtrace[0x914f5f8->0x914f670]: $<-.data.frame $<- statistic boot
memtrace[0x9abd5e0->0x972cbf0]: statistic boot
memtrace[0x972cbf0->0x972cc68]: $<-.data.frame $<- statistic boot
memtrace[0x972cc68->0x972cd08]: $<-.data.frame $<- statistic boot
memtrace[0x9abd5e0->0x98ead98]: statistic boot
memtrace[0x98ead98->0x98eae10]: $<-.data.frame $<- statistic boot
memtrace[0x98eae10->0x98eae88]: $<-.data.frame $<- statistic boot
@end smallexample

@noindent
The object is duplicated fifteen times, three times for each of the
@code{R+1} calls to @code{storm.bf}.  This is surprising, since none of the duplications happen inside @code{nls}. Stepping through @code{storm.bf} in the debugger shows that all three happen in the line

@smallexample
st$Time <- st$fit + rs[i]
@end smallexample

Data frames are slower than matrices and this is an example of why.
Using @code{tracemem(st$Viscosity)} does not reveal any additional
copying.

@node Profiling compiled code,  , Profiling R code for memory use, Tidying and profiling R code
@section Profiling compiled code
@cindex Profiling

Profiling compiled code is highly system-specific, but this section
contains some hints gleaned from various @R{} users.  Some methods need
to be different for a compiled executable and for dynamic/shared
libraries/objects as used by @R{} packages.  We know of no good way to
profile DLLs on Windows.

@menu
* Linux::
* Solaris::
* Mac OS X::
@end menu

@node Linux, Solaris, Profiling compiled code, Profiling compiled code
@subsection Linux

Options include using @command{sprof} for a shared object, and
@command{oprofile} (see @uref{http://@/oprofile.sourceforge.net/}) for any
executable or shared object.

@subsubsection sprof

You can select shared objects to be profiled with @command{sprof} by
setting the environment variable @env{LD_PROFILE}.  For example

@example
% setenv LD_PROFILE /path/to/R_HOME/library/stats/libs/stats.so
R
... run the boot example
% sprof /path/to/R_HOME/library/stats/libs/stats.so \
  /var/tmp/path/to/R_HOME/library/stats/libs/stats.so.profile

Flat profile:

Each sample counts as 0.01 seconds.
  %   cumulative   self              self     total
 time   seconds   seconds    calls  us/call  us/call  name
 76.19      0.32     0.32        0     0.00           numeric_deriv
 16.67      0.39     0.07        0     0.00           nls_iter
  7.14      0.42     0.03        0     0.00           getListElement

rm /path/to/R_HOME/library/stats/libs/stats.so.profile
... to clean up ...
@end example

It is possible that root access is needed to create the directories used
for the profile data.

@subsubsection oprofile

@code{oprofile} works by running a daemon which collects information.
The daemon must be started as root, e.g.

@example
% su
% opcontrol --no-vmlinux
% (optional, some platforms) opcontrol --callgraph=5
% opcontrol --start
% exit
@end example

Then as a user

@example
% R
... run the boot example
% opcontrol --dump
% opreport -l /path/to/R_HOME/library/stats/libs/stats.so
...
samples  %        symbol name
1623     75.5939  anonymous symbol from section .plt
349      16.2552  numeric_deriv
113       5.2632  nls_iter
62        2.8878  getListElement
% opreport -l /path/to/R_HOME/bin/exec/R
...
samples  %        symbol name
76052    11.9912  Rf_eval
54670     8.6198  Rf_findVarInFrame3
37814     5.9622  Rf_allocVector
31489     4.9649  Rf_duplicate
28221     4.4496  Rf_protect
26485     4.1759  Rf_cons
23650     3.7289  Rf_matchArgs
21088     3.3250  Rf_findFun
19995     3.1526  findVarLocInFrame
14871     2.3447  Rf_evalList
13794     2.1749  R_Newhashpjw
13522     2.1320  R_gc_internal
...
@end example

Shutting down the profiler and clearing the records needs to be done as
root.  You can use @command{opannotate} to annotate the source code with
the times spent in each section, if the appropriate source code was
compiled with debugging support, and @command{opreport -c} to generate a
callgraph (if collection was enabled and the platform supports this).

@node Solaris, Mac OS X, Linux, Profiling compiled code
@subsection Solaris

On 64-bit (only) Solaris, the standard profiling tool @command{gprof}
collects information from shared objects compiled with @option{-pg}.

@node Mac OS X,  , Solaris, Profiling compiled code
@subsection Mac OS X

Developers have recommended @command{sample} (or @command{Sampler.app},
which is a GUI version) and @command{Shark} (see
@uref{http://developer.apple.com/tools/sharkoptimize.html} and
@uref{http://@/developer.@/apple.com/tools/shark_optimize.html}).


@node Debugging, System and foreign language interfaces, Tidying and profiling R code, Top
@chapter Debugging

This chapter covers the debugging of @R{} extensions, starting with the
ways to get useful error information and moving on to how to deal with
errors that crash @R{}.  For those who prefer other styles there are
contributed packages such as @pkg{debug} on @acronym{CRAN} (described in
an article in
@uref{http://cran.r-project.org/doc/Rnews/Rnews_2003-3.pdf, R-News
3/3}).  (There are notes from 2002 provided by Roger Peng at
@uref{http://www.biostat.jhsph.edu/~rpeng/docs/R-debug-tools.pdf} which
provide complementary examples to those given here.)

@menu
* Browsing::
* Debugging R code::
* Using gctorture and valgrind::
* Debugging compiled code::
@end menu


@node Browsing, Debugging R code, Debugging, Debugging
@section Browsing

@findex browser
Most of the @R{}-level debugging facilities are based around the
built-in browser.  This can be used directly by inserting a call to
@code{browser()} into the code of a function (for example, using
@code{fix(my_function)} ).  When code execution reaches that point in
the function, control returns to the @R{} console with a special prompt.
For example

@example
> fix(summary.data.frame) ## insert browser() call after for() loop
> summary(women)
Called from: summary.data.frame(women)
Browse[1]> ls()
 [1] "digits" "i"      "lbs"    "lw"     "maxsum" "nm"     "nr"     "nv"
 [9] "object" "sms"    "z"
Browse[1]> maxsum
[1] 7
Browse[1]>
     height         weight
 Min.   :58.0   Min.   :115.0
 1st Qu.:61.5   1st Qu.:124.5
 Median :65.0   Median :135.0
 Mean   :65.0   Mean   :136.7
 3rd Qu.:68.5   3rd Qu.:148.0
 Max.   :72.0   Max.   :164.0
> rm(summary.data.frame)
@end example

@noindent
At the browser prompt one can enter any @R{} expression, so for example
@code{ls()} lists the objects in the current frame, and entering the
name of an object will@footnote{With the exceptions of the commands
listed below: an object of such a name can be printed @emph{via} an
explicit call to @code{print}.} print it.  The following commands are
also accepted

@itemize @bullet
@item @code{n}

Enter `step-through' mode.  In this mode, hitting return executes the
next line of code (more precisely one line and any continuation lines).
Typing @code{c} will continue to the end of the current context, e.g.@:
to the end of the current loop or function.

@item @code{c}

In normal mode, this quits the browser and continues execution, and just
return works in the same way.  @code{cont} is a synonym.

@item @code{where}

This prints the call stack.  For example

@example
> summary(women)
Called from: summary.data.frame(women)
Browse[1]> where
where 1: summary.data.frame(women)
where 2: summary(women)

Browse[1]>
@end example

@item @code{Q}

Quit both the browser and the current expression, and return to the
top-level prompt.
@end itemize

Errors in code executed at the browser prompt will normally return
control to the browser prompt.  Objects can be altered by assignment,
and will keep their changed values when the browser is exited.  If
really necessary, objects can be assigned to the workspace from the
browser prompt (by using @code{<<-} if the name is not already in
scope).

@node Debugging R code, Using gctorture and valgrind, Browsing, Debugging
@section Debugging R code

@findex traceback
Suppose your @R{} program gives an error message.  The first thing to
find out is what @R{} was doing at the time of the error, and the most
useful tool is @code{traceback()}.  We suggest that this is run whenever
the cause of the error is not immediately obvious.  Daily, errors are
reported to the @R{} mailing lists as being in some package when
@code{traceback()} would show that the error was being reported by some
other package or base @R{}.  Here is an example from the regression
suite.

@smallexample
> success <- c(13,12,11,14,14,11,13,11,12)
> failure <- c(0,0,0,0,0,0,0,2,2)
> resp <- cbind(success, failure)
> predictor <- c(0, 5^(0:7))
> glm(resp ~ 0+predictor, family = binomial(link="log"))
Error: no valid set of coefficients has been found: please supply starting values
> traceback()
3: stop("no valid set of coefficients has been found: please supply
         starting values", call. = FALSE)
2: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart,
       mustart = mustart, offset = offset, family = family, control = control,
       intercept = attr(mt, "intercept") > 0)
1: glm(resp ~ 0 + predictor, family = binomial(link ="log"))
@end smallexample

@noindent
The calls to the active frames are given in reverse order (starting with
the innermost).  So we see the error message comes from an explicit
check in @code{glm.fit}.  (@code{traceback()} shows you all the lines of
the function calls, which can be limited by setting @code{option}
@option{"deparse.max.lines"}.)

Sometimes the traceback will indicate that the error was detected inside
compiled code, for example (from @code{?nls})

@smallexample
Error in nls(y ~ a + b * x, start = list(a = 0.12345, b = 0.54321), trace = TRUE) :
        step factor 0.000488281 reduced below 'minFactor' of 0.000976563
>  traceback()
2: .Call(R_nls_iter, m, ctrl, trace)
1: nls(y ~ a + b * x, start = list(a = 0.12345, b = 0.54321), trace = TRUE)
@end smallexample

@noindent
This will be the case if the innermost call is to @code{.C},
@code{.Fortran}, @code{.Call}, @code{.External} or @code{.Internal}, but
as it is also possible for such code to evaluate @R{} expressions, this
need not be the innermost call, as in

@smallexample
> traceback()
9: gm(a, b, x)
8: .Call(R_numeric_deriv, expr, theta, rho, dir)
7: numericDeriv(form[[3]], names(ind), env)
6: getRHS()
5: assign("rhs", getRHS(), envir = thisEnv)
4: assign("resid", .swts * (lhs - assign("rhs", getRHS(), envir = thisEnv)),
       envir = thisEnv)
3: function (newPars)
   @{
       setPars(newPars)
       assign("resid", .swts * (lhs - assign("rhs", getRHS(), envir = thisEnv)),
           envir = thisEnv)
       assign("dev", sum(resid^2), envir = thisEnv)
       assign("QR", qr(.swts * attr(rhs, "gradient")), envir = thisEnv)
       return(QR$rank < min(dim(QR$qr)))
   @}(c(-0.00760232418963883, 1.00119632515036))
2: .Call(R_nls_iter, m, ctrl, trace)
1: nls(yeps ~ gm(a, b, x), start = list(a = 0.12345, b = 0.54321))
@end smallexample

Occasionally @code{traceback()} does not help, and this can be the case
if S4 method dispatch is involved.  Consider the following example

@example
> xyd <- new("xyloc", x=runif(20), y=runif(20))
Error in as.environment(pkg) : no item called "package:S4nswv"
on the search list
Error in initialize(value, ...) : S language method selection got
an error when called from internal dispatch for function 'initialize'
> traceback()
2: initialize(value, ...)
1: new("xyloc", x = runif(20), y = runif(20))
@end example

@noindent
which does not help much, as there is no call to @code{as.environment}
in @code{initialize} (and the note ``called from internal dispatch''
tells us so).  In this case we searched the @R{} sources for the quoted
call, which occurred in only one place,
@code{methods:::.asEnvironmentPackage}.  So now we knew where the
error was occurring.  (This was an unusually opaque example.)

The error message

@example
evaluation nested too deeply: infinite recursion / options(expressions=)?
@end example

@noindent
can be hard to handle with the default value (5000).  Unless you know
that there actually is deep recursion going on, it can help to set
something like

@example
options(expressions=500)
@end example

@noindent and re-run the example showing the error.

Sometimes there is warning that clearly is the precursor to some later
error, but it is not obvious where it is coming from.  Setting
@command{options(warn = 2)} (which turns warnings into errors) can help here.

Once we have located the error, we have some choices.  One way to proceed
is to find out more about what was happening at the time of the crash by
looking a @emph{post-mortem} dump.  To do so, set
@findex dump.frames
@command{options(error=dump.frames)} and run the code again.  Then invoke
@command{debugger()} and explore the dump.  Continuing our example:

@smallexample
> options(error = dump.frames)
> glm(resp ~ 0 + predictor, family = binomial(link ="log"))
Error: no valid set of coefficients has been found: please supply starting values
@end smallexample

@noindent
which is the same as before, but an object called @code{last.dump} has
appeared in the workspace.  (Such objects can be large, so remove it
when it is no longer needed.)  We can examine this at a later time by
calling the function @code{debugger}.
@findex debugger

@smallexample
> debugger()
Message:  Error: no valid set of coefficients has been found: please supply starting values
Available environments had calls:
1: glm(resp ~ 0 + predictor, family = binomial(link = "log"))
2: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, mus
3: stop("no valid set of coefficients has been found: please supply starting values
Enter an environment number, or 0 to exit  Selection:
@end smallexample

@noindent
which gives the same sequence of calls as @code{traceback}, but in
outer-first order and with only the first line of the call, truncated to
the current width.  However, we can now examine in more detail what was
happening at the time of the error.  Selecting an environment opens the
browser in that frame.  So we select the function call which spawned the
error message, and explore some of the variables (and execute two
function calls).

@smallexample
Enter an environment number, or 0 to exit  Selection: 2
Browsing in the environment with call:
   glm.fit(x = X, y = Y, weights = weights, start = start, etas
Called from: debugger.look(ind)
Browse[1]> ls()
 [1] "aic"        "boundary"   "coefold"    "control"    "conv"
 [6] "dev"        "dev.resids" "devold"     "EMPTY"      "eta"
[11] "etastart"   "family"     "fit"        "good"       "intercept"
[16] "iter"       "linkinv"    "mu"         "mu.eta"     "mu.eta.val"
[21] "mustart"    "n"          "ngoodobs"   "nobs"       "nvars"
[26] "offset"     "start"      "valideta"   "validmu"    "variance"
[31] "varmu"      "w"          "weights"    "x"          "xnames"
[36] "y"          "ynames"     "z"
Browse[1]> eta
            1             2             3             4             5
 0.000000e+00 -2.235357e-06 -1.117679e-05 -5.588393e-05 -2.794197e-04
            6             7             8             9
-1.397098e-03 -6.985492e-03 -3.492746e-02 -1.746373e-01
Browse[1]> valideta(eta)
[1] TRUE
Browse[1]> mu
        1         2         3         4         5         6         7         8
1.0000000 0.9999978 0.9999888 0.9999441 0.9997206 0.9986039 0.9930389 0.9656755
        9
0.8397616
Browse[1]> validmu(mu)
[1] FALSE
Browse[1]> c
Available environments had calls:
1: glm(resp ~ 0 + predictor, family = binomial(link = "log"))
2: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart
3: stop("no valid set of coefficients has been found: please supply starting v

Enter an environment number, or 0 to exit  Selection: 0
> rm(last.dump)
@end smallexample

Because @code{last.dump} can be looked at later or even in another @R{}
session, post-mortem debugging is possible even for batch usage of @R{}.
We do need to arrange for the dump to be saved: this can be done either
using the command-line flag @option{--save} to save the workspace at the
end of the run, or @emph{via} a setting such as

@example
> options(error = quote(@{dump.frames(to.file=TRUE); q()@}))
@end example

@noindent
See the help on @code{dump.frames} for further options and a worked
example.

@findex recover
An alternative error action is to use the function @command{recover()}:

@smallexample
> options(error = recover)
> glm(resp ~ 0 + predictor, family = binomial(link = "log"))
Error: no valid set of coefficients has been found: please supply starting values

Enter a frame number, or 0 to exit

1: glm(resp ~ 0 + predictor, family = binomial(link = "log"))
2: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart

Selection:
@end smallexample

@noindent
which is very similar to @code{dump.frames}.  However, we can examine
the state of the program directly, without dumping and re-loading the
dump.  As its help page says, @code{recover} can be routinely used as
the error action in place of @code{dump.calls} and @code{dump.frames},
since it behaves like @code{dump.frames} in non-interactive use.


@findex debug
Post-mortem debugging is good for finding out exactly what went wrong,
but not necessarily why.  An alternative approach is to take a closer
look at what was happening just before the error, and a good way to do
that is to use @command{debug}.  This inserts a call to the browser
at the beginning of the function, starting in step-through mode.  So in
our example we could use

@smallexample
> debug(glm.fit)
> glm(resp ~ 0 + predictor, family = binomial(link ="log"))
debugging in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart,
    mustart = mustart, offset = offset, family = family, control = control,
    intercept = attr(mt, "intercept") > 0)
debug: @{
## lists the whole function
Browse[1]>
debug: x <- as.matrix(x)
...
Browse[1]> start
[1] -2.235357e-06
debug: eta <- drop(x %*% start)
Browse[1]> eta
            1             2             3             4             5
 0.000000e+00 -2.235357e-06 -1.117679e-05 -5.588393e-05 -2.794197e-04
            6             7             8             9
-1.397098e-03 -6.985492e-03 -3.492746e-02 -1.746373e-01
Browse[1]>
debug: mu <- linkinv(eta <- eta + offset)
Browse[1]> mu
        1         2         3         4         5         6         7         8
1.0000000 0.9999978 0.9999888 0.9999441 0.9997206 0.9986039 0.9930389 0.9656755
        9
0.8397616
@end smallexample

@noindent
(The prompt @code{Browse[1]>} indicates that this is the first level of
browsing: it is possible to step into another function that is itself
being debugged or contains a call to @code{browser()}.)

@code{debug} can be used for hidden functions and S3 methods by
e.g.@: @code{debug(stats:::predict.Arima)}.  (It cannot be used for S4
methods, but an alternative is given on the help page for @code{debug}.)
Sometimes you want to debug a function defined inside another function,
e.g.@: the function @code{arimafn} defined inside @code{arima}.  To do so,
set @code{debug} on the outer function (here @code{arima}) and
step through it until the inner function has been defined.  Then
call @code{debug} on the inner function (and use @code{c} to get out of
step-through mode in the outer function).

@findex undebug
To remove debugging of a function, call @code{undebug} with the argument
previously given to @code{debug}; debugging otherwise lasts for the rest
of the @R{} session (or until the function is edited or otherwise
replaced).

@findex trace
@code{trace} can be used to temporarily insert debugging code into a
function, for example to insert a call to @code{browser()} just before
the point of the error.  To return to our running example

@example
## first get a numbered listing of the expressions of the function
> page(as.list(body(glm.fit)), method="print")
> trace(glm.fit, browser, at=22)
Tracing function "glm.fit" in package "stats"
[1] "glm.fit"
> glm(resp ~ 0 + predictor, family = binomial(link ="log"))
Tracing glm.fit(x = X, y = Y, weights = weights, start = start,
   etastart = etastart,  .... step 22
Called from: eval(expr, envir, enclos)
Browse[1]> n
## and single-step from here.
> untrace(glm.fit)
@end example
@noindent
For your own functions, it may be as easy to use @code{fix} to insert
temporary code, but @code{trace} can help with functions in a name space
(as can @code{fixInNamespace}).  Alternatively, use
@code{trace(,edit=TRUE)} to insert code visually.


@node Using gctorture and valgrind, Debugging compiled code, Debugging R code, Debugging
@section Using gctorture and valgrind

Errors in memory allocation and reading/writing outside arrays are very
common causes of crashes (e.g.,@: segfaults) on some machines.  Often
the crash appears long after the invalid memory access: in particular
damage to the structures which @R{} itself has allocated may only become
apparent at the next garbage collection (or even at later garbage
collections after objects have been deleted).

@menu
* Using gctorture::
* Using valgrind::
@end menu

@node Using gctorture, Using valgrind, Using gctorture and valgrind, Using gctorture and valgrind
@subsection Using gctorture

@findex gctorture
We can help to detect memory problems earlier by running garbage
collection as often as possible.  This is achieved by
@code{gctorture(TRUE)}, which as described on its help page

@quotation
Provokes garbage collection on (nearly) every memory allocation.
Intended to ferret out memory protection bugs.  Also makes @R{} run
@emph{very} slowly, unfortunately.
@end quotation

@noindent
The reference to `memory protection' is to missing C-level calls to
@code{PROTECT}/@code{UNPROTECT} (@pxref{Garbage Collection}) which if
missing allow @R{} objects to be garbage-collected when they are still
in use.  But it can also help with other memory-related errors.

Normally running under @code{gctorture(TRUE)} will just produce a crash
earlier in the @R{} program, hopefully close to the actual cause. See
the next section for how to decipher such crashes.

It is possible to run all the examples, tests and vignettes covered by
@code{R CMD check} under @code{gctorture(TRUE)} by using the option
@option{--use-gct}.

@node Using valgrind,  , Using gctorture, Using gctorture and valgrind
@subsection Using valgrind

If you have access to Linux on an @cputype{ix86}, @cputype{x86_64},
@cputype{ppc32} or @cputype{ppc64} platform, or Mac OS 10.5.x
(`Leopard') on @cputype{i386} you can use @code{valgrind}
(@uref{http://www.valgrind.org/}, pronounced to rhyme with `tinned') to
check for possible problems.  To run some examples under @code{valgrind}
use something like

@example
R -d valgrind --vanilla < mypkg-Ex.R
R -d "valgrind --tool=memcheck --leak-check=full" --vanilla < mypkg-Ex.R
@end example

@noindent
where @file{mypkg-Ex.R} is a set of examples, e.g.@: the file created in
@file{mypkg.Rcheck} by @code{R CMD check}.  Occasionally this reports
memory reads of `uninitialised values' that are the result of compiler
optimization, so can be worth checking under an unoptimized compile.  We
know there will be some small memory leaks from @code{readline} and @R{}
itself --- these are memory areas that are in use right up to the end of
the @R{} session.  Expect this to run around 20x slower than without
@code{valgrind}, and in some cases even slower than that.  Earlier
versions (at least) of @code{valgrind} are not happy with many optimized
BLASes that use @acronym{CPU}-specific instructions (3D now, SSE, SSE2,
SSE3 and similar) so you may need to build a version of @R{}
specifically to use with @code{valgrind}.

On platforms supported by @code{valgrind} you can build a version of
@R{} with extra instrumentation to help @code{valgrind} detect errors in
the use of memory allocated from the @R{} heap.  The configure option is
@option{--with-valgrind-instrumentation=@var{level}}, where @var{level}
is 0, 1, or 2.  Level 0 is the default and does not add any anything.
Level 1 will detect use of uninitialised memory and has little impact on
speed. Level 2 will detect many other memory use bugs but makes @R{}
much slower when running under @code{valgrind}.  Using this in
conjunction with @code{gctorture} can be even more effective (and even
slower).

An example of @code{valgrind} output is
@smallexample
==12539== Invalid read of size 4
==12539==    at 0x1CDF6CBE: csc_compTr (Mutils.c:273)
==12539==    by 0x1CE07E1E: tsc_transpose (dtCMatrix.c:25)
==12539==    by 0x80A67A7: do_dotcall (dotcode.c:858)
==12539==    by 0x80CACE2: Rf_eval (eval.c:400)
==12539==    by 0x80CB5AF: R_execClosure (eval.c:658)
==12539==    by 0x80CB98E: R_execMethod (eval.c:760)
==12539==    by 0x1B93DEFA: R_standardGeneric (methods_list_dispatch.c:624)
==12539==    by 0x810262E: do_standardGeneric (objects.c:1012)
==12539==    by 0x80CAD23: Rf_eval (eval.c:403)
==12539==    by 0x80CB2F0: Rf_applyClosure (eval.c:573)
==12539==    by 0x80CADCC: Rf_eval (eval.c:414)
==12539==    by 0x80CAA03: Rf_eval (eval.c:362)
==12539==  Address 0x1C0D2EA8 is 280 bytes inside a block of size 1996 alloc'd
==12539==    at 0x1B9008D1: malloc (vg_replace_malloc.c:149)
==12539==    by 0x80F1B34: GetNewPage (memory.c:610)
==12539==    by 0x80F7515: Rf_allocVector (memory.c:1915)
...
@end smallexample
@noindent
This example is from an instrumented version of @R{}, while tracking
down a bug in the @pkg{Matrix} package in January, 2006.  The first line
indicates that @R{} has tried to read 4 bytes from a memory address that
it does not have access to. This is followed by a C stack trace showing
where the error occurred. Next is a description of the memory that was
accessed. It is inside a block allocated by @code{malloc}, called from
@code{GetNewPage}, that is, in the internal @R{} heap.  Since this
memory all belongs to @R{}, @code{valgrind} would not (and did not)
detect the problem in an uninstrumented build of @R{}.  In this example
the stack trace was enough to isolate and fix the bug, which was in
@code{tsc_transpose}, and in this example running under
@code{gctorture()} did not provide any additional information.  When the
stack trace is not sufficiently informative the option
@option{--db-attach=yes} to @code{valgrind} may be helpful.  This starts
a post-mortem debugger (by default @code{gdb}) so that variables in the
C code can be inspected (@pxref{Inspecting R objects}).


It is possible to run all the examples, tests and vignettes covered by
@code{R CMD check} under @code{valgrind} by using the option
@option{--use-valgrind}.  If you do this you will need to select the
@code{valgrind} options some other way, for example by having a
@file{~/.valgrindrc} file containing

@example
--tool=memcheck
--memcheck:leak-check=full
@end example

@noindent
or setting the environment variable @env{VALGRIND_OPTS}.

@node Debugging compiled code,  , Using gctorture and valgrind, Debugging
@section Debugging compiled code
@cindex Debugging


Sooner or later programmers will be faced with the need to debug
compiled code loaded into @R{}.   This section is geared to platforms
using @command{gdb} with code compiled by @code{gcc}, but similar things
are possible with front-ends to @command{gdb} such as @command{ddd} and
@command{insight}, and other debuggers such as Sun's @command{dbx}.

Consider first `crashes', that is when @R{} terminated unexpectedly with
an illegal memory access (a `segfault' or `bus error'), illegal
instruction or similar.  Unix-alike versions of @R{} use a signal
handler which aims to give some basic information.  For example

@example
 *** caught segfault ***
address 0x20000028, cause 'memory not mapped'

Traceback:
 1: .identC(class1[[1]], class2)
 2: possibleExtends(class(sloti), classi, ClassDef2 = getClassDef(classi,
where = where))
 3: validObject(t(cu))
 4: stopifnot(validObject(cu <- as(tu, "dtCMatrix")), validObject(t(cu)),
validObject(t(tu)))

Possible actions:
1: abort (with core dump)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Selection: 3
@end example

@noindent
Since the @R{} process may be damaged, the only really safe option is
the first.

Another cause of a `crash' is to overrun the C stack.  @R{} tries to
track that in its own code, but it may happen in third-party compiled
code.  For modern POSIX-compliant OSes we can safely catch that and
return to the top-level prompt.

@example
> .C("aaa")
Error: segfault from C stack overflow
>
@end example

@noindent
However, C stack overflows are fatal under Windows and normally defeat
attempts at debugging on that platform.

If you have a crash which gives a core dump you can use something like

@example
gdb /path/to/R/bin/exec/R core.12345
@end example

@noindent
to examine the core dump.  If core dumps are disabled or to catch errors
that do not generate a dump one can run @R{} directly under a debugger
by for example

@example
$ R -d gdb --vanilla
...
gdb> run
@end example

@noindent
at which point @R{} will run normally, and hopefully the debugger will
catch the error and return to its prompt.  This can also be used to
catch infinite loops or interrupt very long-running code.  For a simple
example

@example
> for(i in 1:1e7) x <- rnorm(100)
[hit Ctrl-C]
Program received signal SIGINT, Interrupt.
0x00397682 in _int_free () from /lib/tls/libc.so.6
(gdb) where
#0  0x00397682 in _int_free () from /lib/tls/libc.so.6
#1  0x00397eba in free () from /lib/tls/libc.so.6
#2  0xb7cf2551 in R_gc_internal (size_needed=313)
    at /users/ripley/R/svn/R-devel/src/main/memory.c:743
#3  0xb7cf3617 in Rf_allocVector (type=13, length=626)
    at /users/ripley/R/svn/R-devel/src/main/memory.c:1906
#4  0xb7c3f6d3 in PutRNGstate ()
    at /users/ripley/R/svn/R-devel/src/main/RNG.c:351
#5  0xb7d6c0a5 in do_random2 (call=0x94bf7d4, op=0x92580e8, args=0x9698f98,
    rho=0x9698f28) at /users/ripley/R/svn/R-devel/src/main/random.c:183
...
@end example

Some ``tricks'' are worth knowing.

@menu
* Finding entry points::
* Inspecting R objects::
@end menu

@node Finding entry points, Inspecting R objects, Debugging compiled code, Debugging compiled code
@subsection Finding entry points in dynamically loaded code

Under most compilation environments, compiled code dynamically loaded
into @R{} cannot have breakpoints set within it until it is loaded.  To
use a symbolic debugger on such dynamically loaded code under
Unix-alikes use

@itemize @bullet
@item
Call the debugger on the @R{} executable, for example by @kbd{R -d gdb}.
@item
Start @R{}.
@item
At the @R{} prompt, use @code{dyn.load} or @code{library} to load your
shared object.
@item
Send an interrupt signal.  This will put you back to the debugger
prompt.
@item
Set the breakpoints in your code.
@item
Continue execution of @R{} by typing @kbd{signal 0@key{RET}}.
@end itemize

Under Windows signals may not be able to be used, and if so the procedure is
more complicated.  See the rw-FAQ and
@uref{http://www.stats.uwo.ca/faculty/murdoch/software/debuggingR/gdb.shtml,
@code{www.stats.uwo.ca/faculty/murdoch/@/software/@/debuggingR/@/gdb.shtml}}.


@node Inspecting R objects,  , Finding entry points, Debugging compiled code
@subsection Inspecting R objects when debugging
@cindex Inspecting R objects when debugging

The key to inspecting @R{} objects from compiled code is the function
@code{PrintValue(SEXP @var{s})} which uses the normal @R{} printing
mechanisms to print the @R{} object pointed to by @var{s}, or the safer
version @code{R_PV(SEXP @var{s})} which will only print `objects'.

One way to make use of @code{PrintValue} is to insert suitable calls
into the code to be debugged.

Another way is to call @code{R_PV} from the symbolic debugger.
(@code{PrintValue} is hidden as @code{Rf_PrintValue}.)  For example,
from @code{gdb} we can use

@example
(gdb) p R_PV(ab)
@end example

@noindent
using the object @code{ab} from the convolution example, if we have
placed a suitable breakpoint in the convolution C code.

To examine an arbitrary @R{} object we need to work a little harder.
For example, let

@example
R> DF <- data.frame(a = 1:3, b = 4:6)
@end example

@noindent
By setting a breakpoint at @code{do_get} and typing @kbd{get("DF")} at
the @R{} prompt, one can find out the address in memory of @code{DF}, for
example

@example
@group
Value returned is $1 = (SEXPREC *) 0x40583e1c
(gdb) p *$1
$2 = @{
  sxpinfo = @{type = 19, obj = 1, named = 1, gp = 0,
    mark = 0, debug = 0, trace = 0, = 0@},
  attrib = 0x40583e80,
  u = @{
    vecsxp = @{
      length = 2,
      type = @{c = 0x40634700 "0>X@@D>X@@0>X@@", i = 0x40634700,
        f = 0x40634700, z = 0x40634700, s = 0x40634700@},
      truelength = 1075851272,
    @},
    primsxp = @{offset = 2@},
    symsxp = @{pname = 0x2, value = 0x40634700, internal = 0x40203008@},
    listsxp = @{carval = 0x2, cdrval = 0x40634700, tagval = 0x40203008@},
    envsxp = @{frame = 0x2, enclos = 0x40634700@},
    closxp = @{formals = 0x2, body = 0x40634700, env = 0x40203008@},
    promsxp = @{value = 0x2, expr = 0x40634700, env = 0x40203008@}
  @}
@}
@end group
@end example

@noindent
(Debugger output reformatted for better legibility).

Using @code{R_PV()} one can ``inspect'' the values of the various
elements of the SEXP, for example,

@example
@group
(gdb) p R_PV($1->attrib)
$names
[1] "a" "b"

$row.names
[1] "1" "2" "3"

$class
[1] "data.frame"

$3 = void
@end group
@end example

To find out where exactly the corresponding information is stored, one
needs to go ``deeper'':

@example
@group
(gdb) set $a = $1->attrib
(gdb) p $a->u.listsxp.tagval->u.symsxp.pname->u.vecsxp.type.c
$4 = 0x405d40e8 "names"
(gdb) p $a->u.listsxp.carval->u.vecsxp.type.s[1]->u.vecsxp.type.c
$5 = 0x40634378 "b"
(gdb) p $1->u.vecsxp.type.s[0]->u.vecsxp.type.i[0]
$6 = 1
(gdb) p $1->u.vecsxp.type.s[1]->u.vecsxp.type.i[1]
$7 = 5
@end group
@end example


@node System and foreign language interfaces, The R API, Debugging, Top
@chapter System and foreign language interfaces

@menu
* Operating system access::
* Interface functions .C and .Fortran::
* dyn.load and dyn.unload::
* Registering native routines::
* Creating shared objects::
* Interfacing C++ code::
* Fortran I/O::
* Linking to other packages::
* Handling R objects in C::
* Interface functions .Call and .External::
* Evaluating R expressions from C::
* Parsing R code from C::
* External pointers and weak references::
* Vector accessor functions::
* Character encoding issues::
@end menu

@node  Operating system access, Interface functions .C and .Fortran, System and foreign language interfaces, System and foreign language interfaces
@section  Operating system access
@cindex Operating system access

Access to operating system functions is @emph{via} the @R{} function
@code{system}.
@findex system
The details will differ by platform (see the on-line help), and about
all that can safely be assumed is that the first argument will be a
string @code{command} that will be passed for execution (not necessarily
by a shell) and the second argument will be @code{internal} which if
true will collect the output of the command into an @R{} character
vector.

The function @code{system.time}
@findex system.time
is available for timing (although the information available may be
limited on non-Unix-alike platforms: these days only on the obsolete
Windows 9x/ME).

@node Interface functions .C and .Fortran, dyn.load and dyn.unload, Operating system access, System and foreign language interfaces
@section Interface functions @code{.C} and @code{.Fortran}
@cindex Interfaces to compiled code

@findex .C
@findex .Fortran

These two functions provide a standard interface to compiled code that
has been linked into @R{}, either at build time or @emph{via} @code{dyn.load}
(@pxref{dyn.load and dyn.unload}).  They are primarily intended for
compiled C and FORTRAN 77 code respectively, but the @code{.C} function can
be used with other languages which can generate C interfaces, for
example C++ (@pxref{Interfacing C++ code}).

The first argument to each function is a character string given the
symbol name as known to C or FORTRAN, that is the function or subroutine
name.  (That the symbol is loaded can be tested by, for example,
@code{is.loaded("cg")}. Use the name you pass to @code{.C} or
@code{.Fortran} rather than the translated symbol name.)

There can be up to 65 further arguments giving @R{} objects to be passed
to compiled code.  Normally these are copied before being passed in, and
copied again to an @R{} list object when the compiled code returns.  If
the arguments are given names, these are used as names for the
components in the returned list object (but not passed to the compiled
code).

The following table gives the mapping between the modes of @R{} vectors
and the types of arguments to a C function or FORTRAN subroutine.

@quotation
@multitable {RRR storage.mode} {RRR unsigned char * RR} {DOUBLE PRECISION}
@headitem @R{} storage mode @tab  C type  @tab   FORTRAN type
@item @code{logical}   @tab @code{int *}     @tab @code{INTEGER}
@item @code{integer}   @tab @code{int *}     @tab @code{INTEGER}
@item @code{double}    @tab @code{double *}  @tab @code{DOUBLE PRECISION}
@item @code{complex}   @tab @code{Rcomplex *} @tab @code{DOUBLE COMPLEX}
@item @code{character} @tab @code{char **}   @tab @code{CHARACTER*255}
@item @code{raw}       @tab @code{unsigned char *}    @tab none
@end multitable
@end quotation

Do please note the first two.  On the 64-bit Unix/Linux platforms,
@code{long} is 64-bit whereas @code{int} and @code{INTEGER} are 32-bit.
Code ported from S-PLUS (which uses @code{long *} for @code{logical} and
@code{integer}) will not work on all 64-bit platforms (although it may
appear to work on some).  Note also that if your compiled code is a
mixture of C functions and FORTRAN subprograms the argument types must
match as given in the table above.

C type @code{Rcomplex} is a structure with @code{double} members
@code{r} and @code{i} defined in the header file @file{R_ext/Complex.h}
included by @file{R.h}.  (On most platforms which have it, this is
compatible with the C99 @code{double complex} type.)  Only a single
character string can be passed to or from FORTRAN, and the success of
this is compiler-dependent.  Other @R{} objects can be passed to
@code{.C}, but it is better to use one of the other interfaces.  An
exception is passing an @R{} function for use with @w{@code{call_R}},
when the object can be handled as @code{void *} en route to
@code{call_R}, but even there @code{.Call} is to be preferred.
Similarly, passing an @R{} list as an argument to a C routine should be
done using the @code{.Call} interface.  If one does use the @code{.C}
function to pass a list as an argument, it is visible to the routine as
an array in C of @code{SEXP} types (i.e., @code{SEXP *}).  The elements
of the array correspond directly to the elements of the @R{} list.
However, this array must be treated as read-only and one must not assign
values to its elements within the C routine --- doing so bypasses @R{}'s
memory management facilities and will corrupt the object and the @R{}
session.

It is possible to pass numeric vectors of storage mode @code{double} to
C as @code{float *} or to FORTRAN as @code{REAL} by setting the
attribute @code{Csingle}, most conveniently by using the @R{} functions
@code{as.single}, @code{single} or @code{mode}.  This is intended only
to be used to aid interfacing to existing C or FORTRAN code.

Logical values are sent as @code{0} (@code{FALSE}), @code{1}
(@code{TRUE}) or @code{INT_MIN = -2147483648} (@code{NA}, but only if
@code{NAOK} is true), and the compiled code should return one of these
three values.  (As from @R{} 2.12.0 non-zero values other than
@code{INT_MIN} are mapped to @code{TRUE}.)

Unless formal argument @code{NAOK} is true, all the other arguments are
checked for missing values @code{NA} and for the @acronym{IEEE} special
values @code{NaN}, @code{Inf} and @code{-Inf}, and the presence of any
of these generates an error.  If it is true, these values are passed
unchecked.

Argument @code{DUP} can be used to suppress copying.  It is dangerous:
see the on-line help for arguments against its use.  It is not possible
to pass numeric vectors as @code{float *} or @code{REAL} if
@code{DUP=FALSE}, and character vectors cannot be used.

Argument @code{PACKAGE} confines the search for the symbol name to a
specific shared object (or use @code{"base"} for code compiled into
@R{}).  Its use is highly desirable, as there is no way to avoid two
package writers using the same symbol name, and such name clashes are
normally sufficient to cause @R{} to crash.  (If it is not present and
the call is from the body of a function defined in a package with a
name space, the shared object loaded by the first (if any)
@code{useDynLib} directive will be used.)

For @code{.C} and @code{.Fortran} you can specify an @code{ENCODING}
argument: this requests that (unless @code{DUP = FALSE}) character
vectors be re-encoded to the requested encoding before being passed in,
and re-encoded from the requested encoding when passed back.  Note that
encoding names are not standardized: but this can be useful to allow
code to work in a UTF-8 locale by specifying @code{ENCODING = "latin1"}.

Note that the compiled code should not return anything except through
its arguments: C functions should be of type @code{void} and FORTRAN
subprograms should be subroutines.

To fix ideas, let us consider a very simple example which convolves two
finite sequences. (This is hard to do fast in interpreted @R{} code, but
easy in C code.)  We could do this using @code{.C} by

@example
@group
void convolve(double *a, int *na, double *b, int *nb, double *ab)
@{
  int i, j, nab = *na + *nb - 1;

  for(i = 0; i < nab; i++)
    ab[i] = 0.0;
  for(i = 0; i < *na; i++)
    for(j = 0; j < *nb; j++)
      ab[i + j] += a[i] * b[j];
@}
@end group
@end example

@noindent
called from @R{} by

@example
@group
conv <- function(a, b)
  .C("convolve",
     as.double(a),
     as.integer(length(a)),
     as.double(b),
     as.integer(length(b)),
     ab = double(length(a) + length(b) - 1))$ab
@end group
@end example

Note that we take care to coerce all the arguments to the correct @R{}
storage mode before calling @code{.C}; mistakes in matching the types
can lead to wrong results or hard-to-catch errors.

Special care is needed in handling @code{character} vector arguments in
C (or C++).  Since only @code{DUP = TRUE} is allowed, on entry the
contents of the elements are duplicated and assigned to the elements of
a @code{char **} array, and on exit the elements of the C array are
copied to create new elements of a character vector.  This means that
the contents of the character strings of the @code{char **} array can be
changed, including to @code{\0} to shorten the string, but the strings
cannot be lengthened.  It is possible to allocate a new string
@emph{via} @code{R_alloc} and replace an entry in the @code{char **}
array by the new string.  However, when character vectors are used other
than in a read-only way, the @code{.Call} interface is much to be
preferred.

Passing character strings to FORTRAN code needs even more care, and
should be avoided where possible.  Only the first element of the
character vector is passed in, as a fixed-length (255) character array.
Up to 255 characters are passed back to a length-one character vector.
How well this works (or even if it works at all) depends on the C and
FORTRAN compilers on each platform.


@node dyn.load and dyn.unload, Registering native routines, Interface functions .C and .Fortran, System and foreign language interfaces
@section @code{dyn.load} and @code{dyn.unload}
@cindex Dynamic loading

@findex dyn.load
@findex dyn.unload

Compiled code to be used with @R{} is loaded as a shared object
(Unix-alikes including Mac OS X, @pxref{Creating shared objects} for
more information) or DLL (Windows).

The shared object/DLL is loaded by @code{dyn.load} and unloaded by
@code{dyn.unload}.  Unloading is not normally necessary, but it is
needed to allow the DLL to be re-built on some platforms, including
Windows.

The first argument to both functions is a character string giving the
path to the object.  Programmers should not assume a specific file
extension for the object/DLL (such as @file{.so}) but use a construction
like

@example
file.path(path1, path2, paste("mylib", .Platform$dynlib.ext, sep=""))
@end example

@noindent
for platform independence.  On Unix-alike systems the path supplied to
@code{dyn.load} can be an absolute path, one relative to the current
directory or, if it starts with @samp{~}, relative to the user's home
directory.

Loading is most often done @emph{via} a call to @code{library.dynam}
@findex library.dynam
in the @code{.First.lib} function of a package.  This has the form

@example
library.dynam("libname", package, lib.loc)
@end example

@noindent
where @code{libname} is the object/DLL name @emph{with the extension
omitted}.  Note that the first argument, @code{chname}, should
@strong{not} be @code{package} since this will not work if the package
is installed under another name.

Under some Unix-alike systems there is a choice of how the symbols are
resolved when the object is loaded, governed by the arguments
@code{local} and @code{now}.  Only use these if really necessary: in
particular using @code{now=FALSE} and then calling an unresolved symbol
will terminate @R{} unceremoniously.

@R{} provides a way of executing some code automatically when a object/DLL
is either loaded or unloaded.  This can be used, for example, to
register native routines with @R{}'s dynamic symbol mechanism, initialize
some data in the native code, or initialize a third party library.  On
loading a DLL, @R{} will look for a routine within that DLL named
@code{R_init_@var{lib}} where @var{lib} is the name of the DLL file with
the extension removed.  For example, in the command

@example
library.dynam("mylib", package, lib.loc)
@end example

@noindent
R looks for the symbol named @code{R_init_mylib}.  Similarly, when
unloading the object, @R{} looks for a routine named
@code{R_unload_@var{lib}}, e.g., @code{R_unload_mylib}.  In either case,
if the routine is present, @R{} will invoke it and pass it a single
argument describing the DLL.  This is a value of type @code{DllInfo}
which is defined in the @file{Rdynload.h} file in the @file{R_ext}
directory.

The following example shows templates for the initialization and
unload routines for the @code{mylib} DLL.

@quotation
@cartouche
@example
#include <R.h>
#include <Rinternals.h>
#include <R_ext/Rdynload.h>

void
R_init_mylib(DllInfo *info)
@{
  /* Register routines, allocate resources. */
@}

void
R_unload_mylib(DllInfo *info)
@{
  /* Release resources. */
@}
@end example
@end cartouche
@end quotation

If a shared object/DLL is loaded more than once the most recent version
is used.  More generally, if the same symbol name appears in several
libraries, the most recently loaded occurrence is used.  The
@code{PACKAGE} argument and registration (see the next section) provide
good ways to avoid any ambiguity in which occurrence is meant.

On Unix-alikes the paths used to resolve dynamically linked dependent
libraries are fixed (for security reasons) when the process is launched,
so @code{dyn.load} will only look for such libraries in the locations
set by the @file{R} shell script (@emph{via} @file{etc/ldpaths}) and in
the OS-specific defaults.

Windows allows more control (and less security) over where dependent
DLLs are looked for.  On all versions this includes the @env{PATH}
environment variable, but with lowest priority: note that it does not
include the directory from which the DLL was loaded.  On XP and later it
is possible@footnote{and we provide an emulation on Windows 2000: see
@samp{?dyn.load}.} to add a single path with quite high priority @emph{via} the
@code{DLLpath} argument to @code{dyn.load}.  This is (by default) used
by @code{library.dynam} to include the package's @file{libs} directory
in the DLL search path.


@node Registering native routines, Creating shared objects, dyn.load and dyn.unload, System and foreign language interfaces
@section Registering native routines
@cindex Registering native routines

By `native' routine, we mean an entry point in compiled code.

In calls to @code{.C}, @code{.Call}, @code{.Fortran} and
@code{.External}, @R{} must locate the specified native routine by looking
in the appropriate shared object/DLL.  By default, @R{} uses the operating
system-specific dynamic loader to lookup the symbol.  Alternatively, the
author of the DLL can explicitly register routines with @R{} and use a
single, platform-independent mechanism for finding the routines in the
DLL.  One can use this registration mechanism to provide additional
information about a routine, including the number and type of the
arguments, and also make it available to @R{} programmers under a different
name.  In the future, registration may be used to implement a form of
``secure'' or limited native access.

@findex R_registerRoutines
To register routines with @R{}, one calls the C routine
@code{R_registerRoutines}.  This is typically done when the DLL is first
loaded within the initialization routine @code{R_init_@var{dll name}}
described in @ref{dyn.load and dyn.unload}.  @code{R_registerRoutines}
takes 5 arguments.  The first is the @code{DllInfo} object passed by
@R{} to the initialization routine. This is where @R{} stores the
information about the methods.  The remaining 4 arguments are arrays
describing the routines for each of the 4 different interfaces:
@code{.C}, @code{.Call}, @code{.Fortran} and @code{.External}.  Each
argument is a @code{NULL}-terminated array of the element types given in
the following table:

@quotation
@multitable {@code{.External  }} {@code{R_ExternalMethodDef}}
@item @code{.C} @tab @code{R_CMethodDef}
@item @code{.Call} @tab @code{R_CallMethodDef}
@item @code{.Fortran} @tab @code{R_FortranMethodDef}
@item @code{.External} @tab @code{R_ExternalMethodDef}
@end multitable
@end quotation

Currently, the @code{R_ExternalMethodDef} is the same as
@code{R_CallMethodDef} type and contains fields for the name of the
routine by which it can be accessed in @R{}, a pointer to the actual native
symbol (i.e., the routine itself), and the number of arguments the
routine expects.  For routines with a variable number of arguments
invoked @emph{via} the @code{.External} interface, one specifies @code{-1} for
the number of arguments which tells @R{} not to check the actual number
passed.  For example, if we had a routine named @code{myCall} defined as

@example
SEXP myCall(SEXP a, SEXP b, SEXP c);
@end example

@noindent
we would describe this as

@example
R_CallMethodDef callMethods[]  = @{
  @{"myCall", (DL_FUNC) &myCall, 3@},
  @{NULL, NULL, 0@}
@};
@end example

@noindent
along with any other routines for the @code{.Call} interface.

Routines for use with the @code{.C} and @code{.Fortran} interfaces are
described with similar data structures, but which have two additional
fields for describing the type and ``style'' of each argument.  Each of
these can be omitted. However, if specified, each should be an array
with the same number of elements as the number of parameters for the
routine.  The types array should contain the @code{SEXP} types
describing the expected type of the argument. (Technically, the elements
of the types array are of type @code{R_NativePrimitiveArgType} which is
just an unsigned integer.)  The @R{} types and corresponding type
identifiers are provided in the following table:

@quotation
@multitable {@code{character  }} {@code{SINGLESXP}}
@item @code{numeric} @tab @code{REALSXP}
@item @code{integer} @tab @code{INTSXP}
@item @code{logical} @tab @code{LGLSXP}
@item @code{single} @tab @code{SINGLESXP}
@item @code{character} @tab @code{STRSXP}
@item @code{list} @tab @code{VECSXP}
@end multitable
@end quotation

Consider a C routine, @code{myC}, declared as

@example
void myC(double *x, int *n, char **names, int *status);
@end example

We would register it as

@example
R_CMethodDef cMethods[] = @{
   @{"myC", (DL_FUNC) &myC, 4, @{REALSXP, INTSXP, STRSXP, LGLSXP@}@},
   @{NULL, NULL, 0@}
@};
@end example

One can also specify whether each argument is used simply as input, or
as output, or as both input and output.  The style field in the
description of a method is used for this.  The purpose is to allow @R{}
to transfer values more efficiently across the @R{}-C/FORTRAN interface
by avoiding copying values when it is not necessary. Typically, one
omits this information in the registration data.

Having created the arrays describing each routine, the last step is to
actually register them with @R{}.  We do this by calling
@code{R_registerRoutines}.  For example, if we have the descriptions
above for the routines accessed by the @code{.C} and @code{.Call}
we would use the following code:

@example
void
R_init_myLib(DllInfo *info)
@{
   R_registerRoutines(info, cMethods, callMethods, NULL, NULL);
@}
@end example

This routine will be invoked when @R{} loads the shared object/DLL named
@code{myLib}.  The last two arguments in the call to
@code{R_registerRoutines} are for the routines accessed by
@code{.Fortran} and @code{.External} interfaces.  In our example, these
are given as @code{NULL} since we have no routines of these types.

When @R{} unloads a shared object/DLL, any registered routines are
automatically removed. There is no (direct) facility for unregistering
a symbol.

Examples of registering routines can be found in the different packages
in the @R{} source tree (e.g., @pkg{stats}).  Also, there is a
brief, high-level introduction in @emph{R News} (volume 1/3, September
2001, pages 20-23).

@c These tools are not currently operational.
@c Additionally, there are (experimental) tools that can be used to
@c automate the generation of the code to register the routines for a
@c collection of C files. See the @code{GccTranslationUnit} module on the
@c Omegahat Web site at @uref{http://www.omegahat.org/GccTranslationUnit/}
@c for more information.

In addition to registering C routines to be called by @R{}, it can at
times be useful for one package to make some of its C routines available
to be called by C code in another package.  An interface to support this
has been provided since @R{} 2.4.0.  The interface consists of two
routines declared as

@findex R_RegisterCCallable
@findex R_GetCCallable
@example
void R_RegisterCCallable(const char *package, const char *name,
                         DL_FUNC fptr);
DL_FUNC R_GetCCallable(const char *package, const char *name);
@end example

A package @pkg{packA} that wants to make a C routine @code{myCfun}
available to C code in other packages would include the call

@example
R_RegisterCCallable("packA", "myCfun", myCfun);
@end example

in its initialization function @code{R_init_packA}.  A package
@pkg{packB} that wants to use this routine would retrieve the function
pointer with a call of the form

@example
p_myCfun = R_GetCCallable("packA", "myCfun");
@end example

The author of @pkg{packB} is responsible for ensuring that
@code{p_myCfun} has an appropriate declaration. In the future @R{} may
provide some automated tools to simplify exporting larger numbers of
routines.

A package that wishes to make use of header files in other packages needs
to declare them as a comma-separated list in the field @code{LinkingTo}
in the @file{DESCRIPTION} file.  For example

@example
Depends: link2, link3
LinkingTo: link2, link3
@end example

It should also `Depend' on those packages for they have to be installed
prior to this one, and loaded prior to this one (so the path to their
compiled code can be found).

This then arranges that the @file{include} directories in the installed
linked-to packages are added to the include paths for C and C++ code.

A @acronym{CRAN} example of the use of this mechanism is package
@pkg{lme4}, which links to @pkg{Matrix}.

@node Creating shared objects, Interfacing C++ code, Registering native routines, System and foreign language interfaces
@section Creating shared objects
@cindex Creating shared objects
@findex R CMD SHLIB

Shared objects for loading into @R{} can be created using @command{R CMD
SHLIB}.  This accepts as arguments a list of files which must be object
files (with extension @file{.o}) or sources for C, C++, FORTRAN 77,
Fortran 9x, Objective C or Objective C++ (with extensions @file{.c},
@file{.cc} or @file{.cpp} or @file{.C}, @file{.f}, @file{.f90} or
@file{.f95}, @file{.m}, and @file{.mm} or @file{.M}, respectively), or
commands to be passed to the linker.  See @kbd{R CMD SHLIB --help} (or
the @R{} help for @code{SHLIB}) for usage information.

If compiling the source files does not work ``out of the box'', you can
specify additional flags by setting some of the variables
@vindex PKG_CPPFLAGS
@code{PKG_CPPFLAGS} (for the C preprocessor, typically @samp{-I} flags),
@vindex PKG_CFLAGS
@vindex PKG_CXXFLAGS
@vindex PKG_FFLAGS
@vindex PKG_FCFLAGS
@vindex PKG_OBJCFLAGS
@code{PKG_CFLAGS}, @code{PKG_CXXFLAGS}, @code{PKG_FFLAGS},
@code{PKG_FCFLAGS}, and @code{PKG_OBJCFLAGS} (for the C, C++, FORTRAN
77, Fortran 9x, and Objective C compilers, respectively) in the file
@file{Makevars} in the compilation directory (or, of course, create the
object files directly from the command line).
@vindex PKG_LIBS
Similarly, variable @code{PKG_LIBS} in @file{Makevars} can be used for
additional @samp{-l} and @samp{-L} flags to be passed to the linker when
building the shared object. (Supplying linker commands as arguments to
@code{R CMD SHLIB} will override @code{PKG_LIBS} in @file{Makevars}.)

@vindex OBJECTS
It is possible to arrange to include compiled code from other languages
by setting the macro @samp{OBJECTS} in file @file{Makevars}, together
with suitable rules to make the objects.

Flags which are already set (for example in file
@file{etc@var{R_ARCH}/Makeconf} on Unix-alikes) can be overridden by the
environment variable @env{MAKEFLAGS} (at least for systems using a
POSIX-compliant @code{make}), as in (Bourne shell syntax)

@example
MAKEFLAGS="CFLAGS=-O3" R CMD SHLIB *.c
@end example

It is also possible to set such variables in personal @file{Makevars}
files, which are read after the local @file{Makevars} and the system
makefiles or in a site-wide @file{Makevars.site} file.
@ifset UseExternalXrefs
@xref{Customizing package compilation,
Customizing package compilation, R-admin,
R Installation and Administration},
@end ifset


Note that as @command{R CMD SHLIB} uses Make, it will not remake a shared
object just because the flags have changed, and if @file{test.c} and
@file{test.f} both exist in the current directory

@example
R CMD SHLIB test.f
@end example

@noindent
will compile @file{test.c}!


If the @file{src} subdirectory of an add-on package contains source code
with one of the extensions listed above or a file @file{Makevars} but
@strong{not} a file @code{Makefile}, @command{R CMD INSTALL} creates a
shared object (for loading into @R{} in the @code{.First.lib} or
@code{.onLoad} function of the package) using the @command{R CMD SHLIB}
mechanism.  If file @file{Makevars} exists it is read first, then the
system makefile and then any personal @file{Makevars} files.

If the @file{src} subdirectory of package contains a file
@file{Makefile}, this is used by @command{R CMD INSTALL} in place of the
@code{R CMD SHLIB} mechanism.  @command{make} is called with makefiles
@file{@var{R_HOME}/etc@var{R_ARCH}/Makeconf}, @file{src/Makefile} and
any personal @file{Makevars} files (in that order).  The first target
found in @file{src/Makefile} is used.

It is better to make use of a @code{Makevars} file rather than a
@code{Makefile}: the latter should be needed only exceptionally.

@c Not so clearcut on case-insensitive file systems.
@c Note that whereas @code{R CMD INSTALL} makes use of a @file{Makefile},
@c @code{R CMD SHLIB} does not.  The file must be named @file{Makefile},
@c not for example @file{makefile} nor @file{GNUmakefile}.

Under Windows the same commands work, but @file{Makevars.win} will be
used in preference to @file{Makevars}, and only @file{src/Makefile.win}
will be used by @code{R CMD INSTALL} with @file{src/Makefile} being
ignored.  For details of building DLLs with a variety of compilers, see
file @samp{README.packages} and
@uref{http://@/www.stats.uwo.ca/@/faculty/@/murdoch/@/software/@/compilingDLLs/}
.  Under Windows you can supply an exports definitions file called
@file{@var{dllname}-win.def}: otherwise all entry points in objects (but
not libraries) supplied to @code{R CMD SHLIB} will be exported from the
DLL.  An example is @file{stats-win.def} for the @pkg{stats} package: a
@acronym{CRAN} example in package @pkg{fastICA}.

If you feel tempted to read the source code and subvert these
mechanisms, please resist.  Far too much developer time has been wasted
in chasing down errors caused by failures to follow this documentation,
and even more by package authors demanding explanations as to why their
packages not longer work.
@c Jasjeet Singh Sekhon: this is your moment of infamy.
In particular, undocumented environment or make variables are not for
use by package writers and are subject to change without notice.

@node Interfacing C++ code, Fortran I/O, Creating shared objects, System and foreign language interfaces
@section Interfacing C++ code
@cindex Interfacing C++ code
@cindex C++ code, interfacing

Suppose we have the following hypothetical C++ library, consisting of
the two files @file{X.hh} and @file{X.cc}, and implementing the two
classes @code{X} and @code{Y} which we want to use in @R{}.

@quotation
@cartouche
@example
// X.hh

class X @{
public: X (); ~X ();
@};

class Y @{
public: Y (); ~Y ();
@};
@end example
@end cartouche
@end quotation

@quotation
@cartouche
@example
// X.cc

#include <iostream>
#include "X.hh"

static Y y;

X::X()  @{ std::cout << "constructor X" << std::endl; @}
X::~X() @{ std::cout << "destructor X"  << std::endl; @}
Y::Y()  @{ std::cout << "constructor Y" << std::endl; @}
Y::~Y() @{ std::cout << "destructor Y"  << std::endl; @}
@end example
@end cartouche
@end quotation

To use with @R{}, the only thing we have to do is writing a wrapper
function and ensuring that the function is enclosed in

@example
@group
extern "C" @{

@}
@end group
@end example

For example,

@quotation
@cartouche
@example
// X_main.cc:

#include "X.hh"

extern "C" @{

void X_main () @{
  X x;
@}

@} // extern "C"
@end example
@end cartouche
@end quotation

Compiling and linking should be done with the C++ compiler-linker
(rather than the C compiler-linker or the linker itself); otherwise, the
C++ initialization code (and hence the constructor of the static
variable @code{Y}) are not called.  On a properly configured system, one
can simply use

@example
R CMD SHLIB X.cc X_main.cc
@end example

@noindent
to create the shared object, typically @file{X.so} (the file name
extension may be different on your platform).  Now starting @R{} yields

@example
@group
R : Copyright 2000, The R Development Core Team
Version 1.1.0 Under development (unstable) (April 14, 2000)
...
Type    "q()" to quit R.
@end group

@group
R> dyn.load(paste("X", .Platform$dynlib.ext, sep = ""))
constructor Y
R> .C("X_main")
constructor X
destructor X
list()
R> q()
Save workspace image? [y/n/c]: y
destructor Y
@end group
@end example

The @R{} for Windows @acronym{FAQ} (@file{rw-FAQ}) contains details of how
to compile this example under various Windows compilers.

Using C++ iostreams, as in this example, is best avoided.  There is no
guarantee that the output will appear in the @R{} console, and indeed it
will not on the @R{} for Windows console.  Use @R{} code or the C entry points
(@pxref{Printing}) for all I/O if at all possible.

Most @R{} header files can be included within C++ programs, and they
should @strong{not} be included within an @code{extern "C"} block (as
they include C++ system headers).  It may not be possible to include
some @R{} headers as they in turn include C header files that may cause
conflicts---if this happens, define @samp{NO_C_HEADERS} before including
the @R{} headers, and include C++ versions (such as @samp{cmath}) of the
appropriate headers yourself before the @R{} headers.

@node Fortran I/O, Linking to other packages, Interfacing C++ code, System and foreign language interfaces
@section Fortran I/O

We have already warned against the use of C++ iostreams not least
because output is not guaranteed to appear on the @R{} console, and this
warning applies equally to Fortran (77 or 9x) output to units @code{*}
and @code{6}. @xref{Printing from FORTRAN}, which describes workarounds.

In the past most Fortran compilers implemented I/O on top of the C I/O
system and so the two interworked successfully.  This was true of
@command{g77}, but it is less true of @command{gfortran} as used in
@code{gcc 4.y.z}.  In particular, any package that makes use of Fortran
I/O will when compiled on Windows interfere with C I/O: when the Fortran
I/O is initialized (typically when the package is loaded) the C
@code{stdout} and @code{stderr} are switched to LF line endings.
(Function @code{La_Init} in file @file{src/main/lapack.c} shows how to
mitigate this.)  Even worse, prior to @R{} 2.6.2 using Fortran output
when running under the Windows GUI console (@code{Rgui}) would hang the
@R{} session.  This is now avoided by ensuring that the Fortran output
is written to a file (@file{fort.6} in the working directory).

@node Linking to other packages, Handling R objects in C, Fortran I/O, System and foreign language interfaces
@section Linking to other packages

It is not in general possible to link a DLL in package @pkg{packA} to a
DLL provided by package @pkg{packB} (for the security reasons mentioned
in @ref{dyn.load and dyn.unload}, and also because some platforms
distinguish between shared objects and dynamic libraries), but it is on
Windows.

Note that there can be tricky versioning issues here, as package
@pkg{packB} could be re-installed after package @pkg{packA} --- it is
desirable that the API provided by package @pkg{packB} remains
backwards-compatible.

@menu
* Unix-alikes::
* Windows::
@end menu

@node Unix-alikes, Windows, Linking to other packages, Linking to other packages
@subsection Unix-alikes

It is possible to link a shared object in package @pkg{packA} to a
library provided by package @pkg{packB} under limited circumstances
on a Unix-alike OS.  There are severe portability issues, so this is not
recommended for a distributed package.

This is easiest if @pkg{packB} provides a static library
@file{packB/libs/libpackB.a}.  (This will need to be compiled with
@code{PIC} flags on platforms where it matters.)  Then as the code from
package @pkg{packB} is incorporated when package @pkg{packA} is
installed, we only need to find the static library at install time for
package @pkg{packB}.  The only issue is to find package @pkg{packB}, and
for that we can ask @R{} by something like

@example
PKGB_PATH=`echo 'cat(system.file("libs", .Platform$r_arch, package="packB", mustWork=TRUE))' \
 | $@{R_HOME@}/bin/R --vanilla --slave`
PKG_LIBS=$(PKGB_PATH)/libpackB.a
@end example

@noindent
which will give an empty path component if sub-architectures are not in
use (but works on current platforms).

For a dynamic library @file{packB/libs/libpackB.so}
(@file{packB/libs/libpackB.dylib} on Mac OS X) we could use

@example
PKGB_PATH=`echo 'cat(system.file("libs", .Platform$r_arch, package="packB", mustWork=TRUE))' \
 | $@{R_HOME@}/bin/R --vanilla --slave`
PKG_LIBS=-L"$(PKGB_PATH)" -lpackB
@end example

@noindent
This will work for installation, but very likely not when package
@code{packB} is loaded, as the path to package @pkg{packB}'s @file{libs}
directory is not in the @command{ld.so}@footnote{@command{dyld} on Mac
OS X, and @env{DYLD_LIBRARY_PATHS} below.}  search path.  You can
arrange to put it there @strong{before} @R{} is launched by setting (on
some platforms) @env{LD_RUN_PATH} or @env{LD_LIBRARY_PATH} or adding to
the @command{ld.so} cache (see @command{man ldconfig}).  On platforms
that support it, the path to the dynamic library can be hardcoded at
install time (which assumes that the location of package @pkg{packB}
will not be changed) nor the package updated to a changed API, as
@pkg{Rcpp} has done all too often).  On systems with the @acronym{GNU}
linker (e.g.@: Linux) and some others (e.g.@: Mac OS X) this can be done
by

@example
PKGB_PATH=`echo 'library(packB); cat(system.file("libs", package="packB"))' \
 | $@{R_HOME@}/bin/R --vanilla --slave`
PKG_LIBS=-L"$(PKGB_PATH)" -rpath "$(PKGB_PATH)" -lpackB
@end example

@noindent
and on some other systems (e.g.@: Solaris with its native linker) use
@code{-R} rather than @code{-rpath}.

It may be possible to figure out what is required semi-automatically
from the result of @command{R CMD libtool --config} (look for
@samp{hardcode}).

Making headers provided by package @pkg{packB} available to the code to
be compiled in package @pkg{packA} can be done by the @code{LinkingTo}
mechanism (@pxref{Registering native routines}).


@node Windows,  , Unix-alikes, Linking to other packages
@subsection Windows

Suppose package @pkg{packA} wants to make use of compiled code provided
by @pkg{packB} in DLL @file{packB/libs/exB.dll}, possibly the package's
DLL @file{packB/libs/packB.dll}.  (This can be extended to linking to
more than one package in a similar way.)  There are three issues to be
addressed:

@itemize

@item
Making headers provided by package @pkg{packB} available to the code to
be compiled in package @pkg{packA}.

This is done by the @code{LinkingTo} mechanism (@pxref{Registering native
routines}).

@item preparing @code{packA.dll} to link to @file{packB/libs/exB.dll}.

This needs an entry in @file{Makevars.win} of the form

@example
PKG_LIBS= -L<something> -lexB
@end example

and one possibility is that @code{<something>} is the path to the
installed @file{pkgB/libs} directory.  To find that we need to ask @R{}
where it is by something like

@example
PKGB_PATH=`echo 'library(packB); cat(system.file("libs", package="packB"))' \
 | rterm --vanilla --slave`
PKG_LIBS= -L"$(PKGB_PATH)" -lexB
@end example

Another possibility is to use an import library, shipping with package
@pkg{packA} an exports file @file{exB.def}.  Then @file{Makevars.win}
could contain

@example
PKG_LIBS= -L. -lexB

all: $(SHLIB) before

before: libexB.dll.a
libexB.dll.a: exB.def
@end example

and then installing package @pkg{packA} will make and use the import
library for @file{exB.dll}.  (One way to prepare the exports file is to
use @file{pexports.exe}.)

@item loading @file{packA.dll} which depends on @file{exB.dll}.

If @code{exB.dll} was used by package @pkg{packB} (because it is in fact
@file{packB.dll} or @file{packB.dll} depends on it) and @pkg{packB} has
been loaded before @pkg{packA}, then nothing more needs to be done as
@file{exB.dll} will already be loaded into the @R{} executable.  (This
is the most common scenario).

More generally, we can use the @code{DLLpath} argument to
@code{library.dynam} to ensure that @code{exB.dll} is found, for example
by setting

@example
library.dynam("packA", pkg, lib,
              DLLpath = system.file("libs", package="packB"))
@end example

Note that @code{DLLpath} can only set one path, and so for linking to
two or more packages you would need to resort to setting @env{PATH}.

@end itemize

@node Handling R objects in C, Interface functions .Call and .External, Linking to other packages, System and foreign language interfaces
@section Handling R objects in C
@cindex Handling R objects in C

Using C code to speed up the execution of an @R{} function is often very
fruitful.  Traditionally this has been done @emph{via} the @code{.C} function
in @R{}.
@c (for details, see the @R{} documentation on @code{.C}).
One restriction of this interface is that the @R{} objects can not be
handled directly in C.  This becomes more troublesome when one wishes to
call @R{} functions from within the C code.  There is a C function
provided called @code{call_R} (also known as @code{call_S} for
compatibility with S) that can do that, but it is cumbersome to use, and
the mechanisms documented here are usually simpler to use, as well as
more powerful.

If a user really wants to write C code using internal @R{} data
structures, then that can be done using the @code{.Call} and
@code{.External} function.  The syntax for the calling function in @R{}
in each case is similar to that of @code{.C}, but the two functions have
different C interfaces.  Generally the @code{.Call} interface (which is
modelled on the interface of the same name in @Sl{} version 4) is a
little simpler to use, but @code{.External} is a little more general.
@findex .Call
@findex .External

A call to @code{.Call} is very similar to @code{.C}, for example

@example
.Call("convolve2", a, b)
@end example

@noindent
The first argument should be a character string giving a C symbol name
of code that has already been loaded into @R{}.  Up to 65 @R{} objects
can passed as arguments.  The C side of the interface is

@example
@group
#include <R.h>
#include <Rinternals.h>

SEXP convolve2(SEXP a, SEXP b)
 ...
@end group
@end example

A call to @code{.External} is almost identical

@example
.External("convolveE", a, b)
@end example

@noindent
but the C side of the interface is different, having only one argument

@example
@group
#include <R.h>
#include <Rinternals.h>

SEXP convolveE(SEXP args)
 ...
@end group
@end example

@noindent
Here @code{args} is a @code{LISTSXP}, a Lisp-style pairlist from which
the arguments can be extracted.

In each case the @R{} objects are available for manipulation @emph{via} a set
of functions and macros defined in the header file @file{Rinternals.h}
or some S4-compatibility macros defined in @file{Rdefines.h}.  See
@ref{Interface functions .Call and .External} for details on
@code{.Call} and @code{.External}.

Before you decide to use @code{.Call} or @code{.External}, you should
look at other alternatives.  First, consider working in interpreted @R{}
code; if this is fast enough, this is normally the best option.  You
should also see if using @code{.C} is enough.  If the task to be
performed in C is simple enough requiring no call to @R{}, @code{.C}
suffices.  The new interfaces are relatively recent additions to @Sl{}
and @R{}, and a great deal of useful code has been written using just
@code{.C} before they were available.  The @code{.Call} and
@code{.External} interfaces allow much more control, but they also
impose much greater responsibilities so need to be used with care.
Neither @code{.Call} nor @code{.External} copy their arguments.  You
should treat arguments you receive through these interfaces as
read-only.

There are two approaches that can be taken to handling @R{} objects from
within C code.  The first (historically) is to use the macros and
functions that have been used to implement the core parts of @R{}
through @code{.Internal} calls.  A public@footnote{ @pxref{The R API}:
note that these are not all part of the API.}  subset of these is
defined in the header file @file{Rinternals.h} in the directory
@file{@var{R_INCLUDE_DIR}} (default @file{@var{R_HOME}/include}) that
should be available on any @R{} installation.

Another approach is to use @R{} versions of the macros and functions
defined for the @Sl{} version 4 interface @code{.Call}, which are
defined in the header file @file{Rdefines.h}.  This is a somewhat
simpler approach, and is to be preferred if the code is intended to be
shared with @Sl{}.  However, it is less well documented and even less
tested.  Note too that some idiomatic S4 constructions with these macros
(such as assigning elements of character vectors or lists) are invalid
in @R{}.

A substantial amount of @R{} is implemented using the functions and
macros described here, so the @R{} source code provides a rich source of
examples and ``how to do it'': indeed many of the examples here were
developed by examining closely @R{} system functions for similar tasks.
Do make use of the source code for inspirational examples.

It is necessary to know something about how @R{} objects are handled in
C code.  All the @R{} objects you will deal with will be handled with
the type @dfn{SEXP}@footnote{SEXP is an acronym for @emph{S}imple
@emph{EXP}ression, common in LISP-like language syntaxes.}, which is a
pointer to a structure with typedef @code{SEXPREC}.  Think of this
structure as a @emph{variant type} that can handle all the usual types
of @R{} objects, that is vectors of various modes, functions,
environments, language objects and so on.  The details are given later
in this section and in @ref{R Internal Structures, , R Internal
Structures, R-ints, R Internals}, but for most
purposes the programmer does not need to know them.  Think rather of a
model such as that used by Visual Basic, in which @R{} objects are
handed around in C code (as they are in interpreted @R{} code) as the
variant type, and the appropriate part is extracted for, for example,
numerical calculations, only when it is needed.  As in interpreted @R{}
code, much use is made of coercion to force the variant object to the
right type.

@menu
* Garbage Collection::
* Allocating storage::
* Details of R types::
* Attributes::
* Classes::
* Handling lists::
* Handling character data::
* Finding and setting variables::
* Some convenience functions::
* Named objects and copying::
@end menu

@node Garbage Collection, Allocating storage, Handling R objects in C, Handling R objects in C
@subsection Handling the effects of garbage collection
@cindex Garbage collection

@findex PROTECT
@findex UNPROTECT

We need to know a little about the way @R{} handles memory allocation.
The memory allocated for @R{} objects is not freed by the user; instead,
the memory is from time to time @dfn{garbage collected}.  That is, some
or all of the allocated memory not being used is freed.

The @R{} object types are represented by a C structure defined by a
typedef @code{SEXPREC} in @file{Rinternals.h}.  It contains several
things among which are pointers to data blocks and to other
@code{SEXPREC}s.  A @code{SEXP} is simply a pointer to a @code{SEXPREC}.

If you create an @R{} object in your C code, you must tell @R{} that you
are using the object by using the @code{PROTECT} macro on a pointer to
the object. This tells @R{} that the object is in use so it is not
destroyed during garbage collection.  Notice that it is the object which
is protected, not the pointer variable.  It is a common mistake to
believe that if you invoked @code{PROTECT(@var{p})} at some point then
@var{p} is protected from then on, but that is not true once a new
object is assigned to @var{p}.

Protecting an @R{} object automatically protects all the @R{} objects
pointed to in the corresponding @code{SEXPREC}, for example all elements
of a protected list are automatically protected.

The programmer is solely responsible for housekeeping the calls to
@code{PROTECT}.  There is a corresponding macro @code{UNPROTECT} that
takes as argument an @code{int} giving the number of objects to
unprotect when they are no longer needed.  The protection mechanism is
stack-based, so @code{UNPROTECT(@var{n})} unprotects the last @var{n}
objects which were protected.  The calls to @code{PROTECT} and
@code{UNPROTECT} must balance when the user's code returns.  @R{} will
warn about @code{"stack imbalance in .Call"} (or @code{.External}) if
the housekeeping is wrong.

Here is a small example of creating an @R{} numeric vector in C code.
First we use the macros in @file{Rinternals.h}:

@example
@group
#include <R.h>
#include <Rinternals.h>

  SEXP ab;
    ....
  PROTECT(ab = allocVector(REALSXP, 2));
  REAL(ab)[0] = 123.45;
  REAL(ab)[1] = 67.89;
  UNPROTECT(1);
@end group
@end example

@noindent
and then those in @file{Rdefines.h}:

@example
@group
#include <R.h>
#include <Rdefines.h>

  SEXP ab;
    ....
  PROTECT(ab = NEW_NUMERIC(2));
  NUMERIC_POINTER(ab)[0] = 123.45;
  NUMERIC_POINTER(ab)[1] = 67.89;
  UNPROTECT(1);
@end group
@end example

Now, the reader may ask how the @R{} object could possibly get removed
during those manipulations, as it is just our C code that is running.
As it happens, we can do without the protection in this example, but in
general we do not know (nor want to know) what is hiding behind the @R{}
macros and functions we use, and any of them might cause memory to be
allocated, hence garbage collection and hence our object @code{ab} to be
removed. It is usually wise to err on the side of caution and assume
that any of the @R{} macros and functions might remove the object.

In some cases it is necessary to keep better track of whether protection
is really needed.  Be particularly aware of situations where a large
number of objects are generated.  The pointer protection stack has a
fixed size (default 10,000) and can become full.  It is not a good idea
then to just @code{PROTECT} everything in sight and @code{UNPROTECT}
several thousand objects at the end. It will almost invariably be
possible to either assign the objects as part of another object (which
automatically protects them) or unprotect them immediately after use.

Protection is not needed for objects which @R{} already knows are in
use.  In particular, this applies to function arguments.

There is a less-used macro @code{UNPROTECT_PTR(@var{s})} that unprotects
the object pointed to by the @code{SEXP} @var{s}, even if it is not the
top item on the pointer protection stack. This is rarely needed outside
the parser (the @R{} sources have one example, in
@file{src/main/plot3d.c}).
@findex UNPROTECT_PTR

Sometimes an object is changed (for example duplicated, coerced or
grown) yet the current value needs to be protected.  For these cases
@code{PROTECT_WITH_INDEX} saves an index of the protection location that
can be used to replace the protected value using @code{REPROTECT}.
@findex PROTECT_WITH_INDEX
@findex REPROTECT
For example (from the internal code for @code{optim})

@example
    PROTECT_INDEX ipx;

    ....
    PROTECT_WITH_INDEX(s = eval(OS->R_fcall, OS->R_env), &ipx);
    REPROTECT(s = coerceVector(s, REALSXP), ipx);
@end example


@node Allocating storage, Details of R types, Garbage Collection, Handling R objects in C
@subsection Allocating storage
@cindex Allocating storage

For many purposes it is sufficient to allocate @R{} objects and
manipulate those.  There are quite a few @code{alloc@var{Xxx}} functions
defined in @file{Rinternals.h}---you may want to explore them.  These
allocate @R{} objects of various types, and for the standard vector
types there are equivalent @code{NEW_@var{XXX}} macros defined in
@file{Rdefines.h}.

If storage is required for C objects during the calculations this is
best allocating by calling @code{R_alloc}; @pxref{Memory allocation}.
All of these memory allocation routines do their own error-checking, so
the programmer may assume that they will raise an error and not return
if the memory cannot be allocated.

@node Details of R types, Attributes, Allocating storage, Handling R objects in C
@subsection Details of R types
@cindex Details of R types

Users of the @file{Rinternals.h} macros will need to know how the @R{}
types are known internally: if the @file{Rdefines.h} macros are used
then S4-compatible names are used.

The different @R{} data types are represented in C by @dfn{SEXPTYPE}.
Some of these are familiar from @R{} and some are internal data types.
The usual @R{} object modes are given in the table.

@quotation
@multitable {SEXPTYPE} {numeric with storage mode integer integer}
@headitem SEXPTYPE @tab @R{} equivalent
@item @code{REALSXP}  @tab numeric with storage mode @code{double}
@item @code{INTSXP}   @tab integer
@item @code{CPLXSXP}  @tab complex
@item @code{LGLSXP}   @tab logical
@item @code{STRSXP}   @tab character
@item @code{VECSXP}   @tab list (generic vector)
@item @code{LISTSXP}  @tab ``dotted-pair'' list
@item @code{DOTSXP}   @tab a @samp{@dots{}} object
@item @code{NILSXP}   @tab NULL
@item @code{SYMSXP}   @tab name/symbol
@item @code{CLOSXP}   @tab function or function closure
@item @code{ENVSXP}   @tab environment
@end multitable
@end quotation

@noindent
Among the important internal @code{SEXPTYPE}s are @code{LANGSXP},
@code{CHARSXP}, @code{PROMSXP}, etc.  (@strong{Note}: although it is
possible to return objects of internal types, it is unsafe to do so as
assumptions are made about how they are handled which may be violated at
user-level evaluation.)  More details are given in @ref{R Internal
Structures, , R Internal Structures, R-ints, R Internals}.

Unless you are very sure about the type of the arguments, the code
should check the data types.  Sometimes it may also be necessary to
check data types of objects created by evaluating an @R{} expression in
the C code.  You can use functions like @code{isReal}, @code{isInteger}
and @code{isString} to do type checking.  See the header file
@file{Rinternals.h} for definitions of other such functions.  All of
these take a @code{SEXP} as argument and return 1 or 0 to indicate
@var{TRUE} or @var{FALSE}.  Once again there are two ways to do this,
and @file{Rdefines.h} has macros such as @code{IS_NUMERIC}.

What happens if the @code{SEXP} is not of the correct type?  Sometimes
you have no other option except to generate an error.  You can use the
function @code{error} for this.  It is usually better to coerce the
object to the correct type.  For example, if you find that an
@code{SEXP} is of the type @code{INTEGER}, but you need a @code{REAL}
object, you can change the type by using, equivalently,

@example
PROTECT(@var{newSexp} = coerceVector(@var{oldSexp}, REALSXP));
@end example

@noindent
or

@example
PROTECT(@var{newSexp} = AS_NUMERIC(@var{oldSexp}));
@end example

@noindent
Protection is needed as a new @emph{object} is created; the object
formerly pointed to by the @code{SEXP} is still protected but now
unused.

All the coercion functions do their own error-checking, and generate
@code{NA}s with a warning or stop with an error as appropriate.

Note that these coercion functions are @emph{not} the same as calling
@code{as.numeric} (and so on) in @R{} code, as they do not dispatch on
the class of the object.  Thus it is normally preferable to do the
coercion in the calling @R{} code.

So far we have only seen how to create and coerce @R{} objects from C
code, and how to extract the numeric data from numeric @R{} vectors.
These can suffice to take us a long way in interfacing @R{} objects to
numerical algorithms, but we may need to know a little more to create
useful return objects.

@node Attributes, Classes, Details of R types, Handling R objects in C
@subsection Attributes
@cindex Attributes

Many @R{} objects have attributes: some of the most useful are classes
and the @code{dim} and @code{dimnames} that mark objects as matrices or
arrays.  It can also be helpful to work with the @code{names} attribute
of vectors.

To illustrate this, let us write code to take the outer product of two
vectors (which @code{outer} and @code{%o%} already do).  As usual the
@R{} code is simple

@example
out <- function(x, y)
@{
   storage.mode(x) <- storage.mode(y) <- "double"
   .Call("out", x, y)
@}
@end example

@noindent
where we expect @code{x} and @code{y} to be numeric vectors (possibly
integer), possibly with names.  This time we do the coercion in the
calling @R{} code.

C code to do the computations is

@example
@group
#include <R.h>
#include <Rinternals.h>

SEXP out(SEXP x, SEXP y)
@{
  int i, j, nx, ny;
  double tmp, *rx = REAL(x), *ry = REAL(y), *rans;
  SEXP ans;

  nx = length(x); ny = length(y);
  PROTECT(ans = allocMatrix(REALSXP, nx, ny));
  rans = REAL(ans);
  for(i = 0; i < nx; i++) @{
    tmp = rx[i];
    for(j = 0; j < ny; j++)
      rans[i + nx*j] = tmp * ry[j];
  @}
  UNPROTECT(1);
  return(ans);
@}
@end group
@end example

@noindent
Note the way @code{REAL} is used: as it is a function call it can be
considerably faster to store the result and index that.

However, we would like to set the @code{dimnames} of the result.
Although @code{allocMatrix} provides a short cut, we will show how to
set the @code{dim} attribute directly.

@example
#include <R.h>
#include <Rinternals.h>

@group
SEXP out(SEXP x, SEXP y)
@{
  R_len_t i, j, nx, ny;
  double tmp, *rx = REAL(x), *ry = REAL(y), *rans;
  SEXP ans, dim, dimnames;
@end group

@group
  nx = length(x); ny = length(y);
  PROTECT(ans = allocVector(REALSXP, nx*ny));
  rans = REAL(ans);
  for(i = 0; i < nx; i++) @{
    tmp = rx[i];
    for(j = 0; j < ny; j++)
      rans[i + nx*j] = tmp * ry[j];
  @}
@end group

@group
  PROTECT(dim = allocVector(INTSXP, 2));
  INTEGER(dim)[0] = nx; INTEGER(dim)[1] = ny;
  setAttrib(ans, R_DimSymbol, dim);
@end group

@group
  PROTECT(dimnames = allocVector(VECSXP, 2));
  SET_VECTOR_ELT(dimnames, 0, getAttrib(x, R_NamesSymbol));
  SET_VECTOR_ELT(dimnames, 1, getAttrib(y, R_NamesSymbol));
  setAttrib(ans, R_DimNamesSymbol, dimnames);
@end group

@group
  UNPROTECT(3);
  return(ans);
@}
@end group
@end example

This example introduces several new features.  The @code{getAttrib} and
@code{setAttrib}
@findex getAttrib
@findex setAttrib
functions get and set individual attributes.  Their second argument is a
@code{SEXP} defining the name in the symbol table of the attribute we
want; these and many such symbols are defined in the header file
@file{Rinternals.h}.

There are shortcuts here too: the functions @code{namesgets},
@code{dimgets} and @code{dimnamesgets} are the internal versions of the
default methods of @code{names<-}, @code{dim<-} and @code{dimnames<-}
(for vectors and arrays), and there are functions such as
@code{GetMatrixDimnames} and @code{GetArrayDimnames}.

What happens if we want to add an attribute that is not pre-defined? We
need to add a symbol for it @emph{via} a call to
@findex install
@code{install}.  Suppose for illustration we wanted to add an attribute
@code{"version"} with value @code{3.0}.  We could use

@example
@group
  SEXP version;
  PROTECT(version = allocVector(REALSXP, 1));
  REAL(version)[0] = 3.0;
  setAttrib(ans, install("version"), version);
  UNPROTECT(1);
@end group
@end example

Using @code{install} when it is not needed is harmless and provides a
simple way to retrieve the symbol from the symbol table if it is already
installed.

@node Classes, Handling lists, Attributes, Handling R objects in C
@subsection Classes
@cindex Classes

In @R{} the (S3) class is just the attribute named @code{"class"} so it
can be handled as such, but there is a shortcut @code{classgets}.
Suppose we want to give the return value in our example the class
@code{"mat"}.  We can use

@example
@group
#include <R.h>
#include <Rdefines.h>
    ....
  SEXP ans, dim, dimnames, class;
    ....
  PROTECT(class = allocVector(STRSXP, 1));
  SET_STRING_ELT(class, 0, mkChar("mat"));
  classgets(ans, class);
  UNPROTECT(4);
  return(ans);
@}
@end group
@end example

@noindent
As the value is a character vector, we have to know how to create that
from a C character array, which we do using the function
@code{mkChar}.

@node Handling lists, Handling character data, Classes, Handling R objects in C
@subsection Handling lists
@cindex Handling lists

Some care is needed with lists, as @R{} moved early on from using
LISP-like lists (now called ``pairlists'') to S-like generic vectors.
As a result, the appropriate test for an object of mode @code{list} is
@code{isNewList}, and we need @code{allocVector(VECSXP, @var{n}}) and
@emph{not} @code{allocList(@var{n})}.

List elements can be retrieved or set by direct access to the elements
of the generic vector.  Suppose we have a list object

@example
a <- list(f=1, g=2, h=3)
@end example

@noindent
Then we can access @code{a$g} as @code{a[[2]]} by

@example
@group
  double g;
    ....
  g = REAL(VECTOR_ELT(a, 1))[0];
@end group
@end example

This can rapidly become tedious, and the following function (based on
one in package @pkg{stats}) is very useful:

@example
@group
/* get the list element named str, or return NULL */

SEXP getListElement(SEXP list, const char *str)
@{
  SEXP elmt = R_NilValue, names = getAttrib(list, R_NamesSymbol);
  int i;
@end group

@group
  for (i = 0; i < length(list); i++)
    if(strcmp(CHAR(STRING_ELT(names, i)), str) == 0) @{
      elmt = VECTOR_ELT(list, i);
      break;
    @}
  return elmt;
@}
@end group
@end example

@noindent
and enables us to say

@example
@group
  double g;
  g = REAL(getListElement(a, "g"))[0];
@end group
@end example

@node Handling character data, Finding and setting variables, Handling lists, Handling R objects in C
@subsection Handling character data
@cindex handling character data

R character vectors are stored as @code{STRSXP}s, a vector type like
@code{VECSXP} where every element is of type @code{CHARSXP}.  The
@code{CHARSXP} elements of @code{STRSXP}s are accessed using
@code{STRING_ELT} and @code{SET_STRING_ELT}.

@code{CHARSXP}s are read-only objects and must never be modified.  In
particular, the C-style string contained in a @code{CHARSXP} should be
treated as read-only and for this reason the @code{CHAR} function used
to access the character data of a @code{CHARSXP} returns @code{(const
char *)} (this also allows compilers to issue warnings about improper
use).  Since @code{CHARSXP}s are immutable, the same @code{CHARSXP} can
be shared by any @code{STRSXP} needing an element representing the same
string. @R{} maintains a global cache of @code{CHARSXP}s so that there
is only ever one @code{CHARSXP} representing a given string in memory.

@findex mkChar
@findex mkCharLen
You can obtain a @code{CHARSXP} by calling @code{mkChar} and providing a
nul-terminated C-style string.  This function will return a pre-existing
@code{CHARSXP} if one with a matching string already exists, otherwise
it will create a new one and add it to the cache before returning it to
you.   The variant @code{mkCharLen} can be used to create a
@code{CHARSXP} from part of a buffer and will ensure null-termination.

Currently, it is still possible to create @code{CHARSXP}s using
@code{allocVector}; @code{CHARSXP}s created in this way will not be
captured by the global @code{CHARSXP} cache and this should be avoided.
In the future, all @code{CHARSXP}s will be captured by the cache and
this will allow further optimizations, for example, replacing calls to
@code{strcmp} with pointer comparisons.  A helper macro,
@code{CallocCharBuf}, can be used to obtain a temporary character buffer
for in-place string manipulation: this memory must be released using
@code{Free}.

@node Finding and setting variables, Some convenience functions, Handling character data, Handling R objects in C
@subsection Finding and setting variables
@cindex Finding variables
@cindex Setting variables

It will be usual that all the @R{} objects needed in our C computations
are passed as arguments to @code{.Call} or @code{.External}, but it is
possible to find the values of @R{} objects from within the C given
their names.  The following code is the equivalent of @code{get(name,
envir = rho)}.

@example
@group
SEXP getvar(SEXP name, SEXP rho)
@{
  SEXP ans;

  if(!isString(name) || length(name) != 1)
    error("name is not a single string");
  if(!isEnvironment(rho))
    error("rho should be an environment");
  ans = findVar(install(CHAR(STRING_ELT(name, 0))), rho);
  Rprintf("first value is %f\n", REAL(ans)[0]);
  return(R_NilValue);
@}
@end group
@end example

The main work is done by
@findex findVar
@code{findVar}, but to use it we need to install @code{name} as a name
in the symbol table.  As we wanted the value for internal use, we return
@code{NULL}.

Similar functions with syntax

@example
@group
void defineVar(SEXP symbol, SEXP value, SEXP rho)
void setVar(SEXP symbol, SEXP value, SEXP rho)
@end group
@end example
@findex defineVar
@findex setVar

@noindent
can be used to assign values to @R{} variables.  @code{defineVar}
creates a new binding or changes the value of an existing binding in the
specified environment frame; it is the analogue of @code{assign(symbol,
value, envir = rho, inherits = FALSE)}, but unlike @code{assign},
@code{defineVar} does not make a copy of the object
@code{value}.@footnote{You can assign a @emph{copy} of the object in the
environment frame @code{rho} using @code{defineVar(symbol,
duplicate(value), rho)}).}  @code{setVar} searches for an existing
binding for @code{symbol} in @code{rho} or its enclosing environments.
If a binding is found, its value is changed to @code{value}.  Otherwise,
a new binding with the specified value is created in the global
environment.  This corresponds to @code{assign(symbol, value, envir =
rho, inherits = TRUE)}.

@node Some convenience functions, Named objects and copying, Finding and setting variables, Handling R objects in C
@subsection Some convenience functions

Some operations are done so frequently that there are convenience
functions to handle them. (All these are provided via the header file
@file{Rinternals.h}.)

Suppose we wanted to pass a single logical
argument @code{ignore_quotes}: we could use

@example
    int ign;

    ign = asLogical(ignore_quotes);
    if(ign == NA_LOGICAL) error("'ignore_quotes' must be TRUE or FALSE");
@end example

@noindent
which will do any coercion needed (at least from a vector argument), and
return @code{NA_LOGICAL} if the value passed was @code{NA} or coercion
failed.  There are also @code{asInteger}, @code{asReal} and
@code{asComplex}.  The function @code{asChar} returns a @code{CHARSXP}.
All of these functions ignore any elements of an input vector after the
first.

To return a length-one real vector we can use

@example
    double x;

    ...
    return ScalarReal(x);
@end example

@noindent
and there are versions of this for all the atomic vector types (those for
a length-one character vector being @code{ScalarString} with argument a
@code{CHARSXP} and @code{mkString} with argument @code{const char *}).

Some of the @code{is@var{XXXX}} functions differ from their apparent
@R{}-level counterparts: for example @code{isVector} is true for any
atomic vector type (@code{isVectorAtomic}) and for lists and expressions
(@code{isVectorList}) (with no check on attributes).  @code{isMatrix} is
a test of a length-2 @code{"dim"} attribute.

There are a series of small macros/functions to help construct pairlists
and language objects (whose internal structures just differ by
@code{SEXPTYPE}).  Function @code{CONS(u, v)} is the basic building
block: is constructs a pairlist from @code{u} followed by @code{v}
(which is a pairlist or @code{R_NilValue}).  @code{LCONS} is a variant
that constructs a language object.  Functions @code{list1} to
@code{list5} construct a pairlist from one to five items, and
@code{lang1} to @code{lang6} do the same for a language object (a
function to call plus zero to five arguments).  Functions @code{elt} and
@code{lastElt} find the @var{i}th element and the last element of a
pairlist, and @code{nthcdr} returns a pointer to the @var{n}th position
in the pairlist (whose @code{CAR} is the @var{n}th item).

Functions @code{str2type} and @code{type2str} map @R{}
length-one character strings to and from @code{SEXPTYPE} numbers, and
@code{type2char} maps numbers to C character strings.

@comment Want to encourage use of some of the more stable and useful R_*
@comment and Rf_* functions:
@menu
* Semi-internal convenience functions::
@end menu

@node Semi-internal convenience functions,  , Some convenience functions, Some convenience functions
@subsubsection Semi-internal convenience functions

There is quite a collection of functions that may be used in your C code
@emph{if} you are willing to adapt to rare ``API'' changes.
These typically contain ``work horses'' of @R{} counterparts.

Functions @code{any_duplicated} and @code{any_duplicated3} are fast
versions of @R{}'s @code{any(duplicated(.))}.

Function @code{R_compute_identical} corresponds to @R{}'s @code{identical} function.


@node Named objects and copying,  , Some convenience functions, Handling R objects in C
@subsection Named objects and copying
@findex duplicate
@cindex Copying objects

When assignments are done in @R{} such as

@example
x <- 1:10
y <- x
@end example

@noindent
the named object is not necessarily copied, so after those two
assignments @code{y} and @code{x} are bound to the same @code{SEXPREC}
(the structure a @code{SEXP} points to).  This means that any code which
alters one of them has to make a copy before modifying the copy if the
usual @R{} semantics are to apply.  Note that whereas @code{.C} and
@code{.Fortran} do copy their arguments (unless the dangerous @code{dup
= FALSE} is used), @code{.Call} and @code{.External} do not.  So
@code{duplicate} is commonly called on arguments to @code{.Call} before
modifying them.

However, at least some of this copying is unneeded.  In the first
assignment shown, @code{x <- 1:10}, @R{} first creates an object with
value @code{1:10} and then assigns it to @code{x} but if @code{x} is
modified no copy is necessary as the temporary object with value
@code{1:10} cannot be referred to again.  @R{} distinguishes between
named and unnamed objects @emph{via} a field in a @code{SEXPREC} that
can be accessed @emph{via} the macros @code{NAMED} and @code{SET_NAMED}.  This
can take values

@table @code
@item 0
The object is not bound to any symbol
@item 1
The object has been bound to exactly one symbol
@item 2
The object has potentially been bound to two or more symbols, and one
should act as if another variable is currently bound to this value.
@end table

@noindent
Note the past tenses: @R{} does not do full reference counting and there
may currently be fewer bindings.

It is safe to modify the value of any @code{SEXP} for which
@code{NAMED(foo)} is zero, and if @code{NAMED(foo)} is two, the value
should be duplicated (@emph{via} a call to @code{duplicate}) before any
modification.  Note that it is the responsibility of the author of the
code making the modification to do the duplication, even if it is
@code{x} whose value is being modified after @code{y <- x}.

The case @code{NAMED(foo) == 1} allows some optimization, but it can be
ignored (and duplication done whenever @code{NAMED(foo) > 0}).  (This
optimization is not currently usable in user code.)  It is intended
for use within assignment functions.  Suppose we used

@example
x <- 1:10
foo(x) <- 3
@end example

@noindent
which is computed as

@example
x <- 1:10
x <- "foo<-"(x, 3)
@end example

@noindent
Then inside @code{"foo<-"} the object pointing to the current value of
@code{x} will have @code{NAMED(foo)} as one, and it would be safe to
modify it as the only symbol bound to it is @code{x} and that will be
rebound immediately.  (Provided the remaining code in @code{"foo<-"}
make no reference to @code{x}, and no one is going to attempt a direct
call such as @code{y <- "foo<-"(x)}.)

Currently all arguments to a @code{.Call} call will have @code{NAMED}
set to 2, and so users must assume that they need to be duplicated
before alteration.

@node Interface functions .Call and .External, Evaluating R expressions from C, Handling R objects in C, System and foreign language interfaces
@section Interface functions @code{.Call} and @code{.External}
@cindex Interfaces to compiled code

In this section we consider the details of the @R{}/C interfaces.

These two interfaces have almost the same functionality. @code{.Call} is
based on the interface of the same name in @Sl{} version 4, and
@code{.External} is based on @code{.Internal}.  @code{.External} is more
complex but allows a variable number of arguments.

@menu
* Calling .Call::
* Calling .External::
* Missing and special values::
@end menu

@node Calling .Call, Calling .External, Interface functions .Call and .External, Interface functions .Call and .External
@subsection Calling @code{.Call}

@findex .Call

Let us convert our finite convolution example to use @code{.Call}, first
using the @file{Rdefines.h} macros.  The calling function in @R{} is

@example
conv <- function(a, b) .Call("convolve2", a, b)
@end example

@noindent
which could hardly be simpler, but as we shall see all the type checking
must be transferred to the C code, which is

@example
@group
#include <R.h>
#include <Rdefines.h>

SEXP convolve2(SEXP a, SEXP b)
@{
  int i, j, na, nb, nab;
  double *xa, *xb, *xab;
  SEXP ab;

  PROTECT(a = AS_NUMERIC(a));
  PROTECT(b = AS_NUMERIC(b));
  na = LENGTH(a); nb = LENGTH(b); nab = na + nb - 1;
  PROTECT(ab = NEW_NUMERIC(nab));
  xa = NUMERIC_POINTER(a); xb = NUMERIC_POINTER(b);
  xab = NUMERIC_POINTER(ab);
  for(i = 0; i < nab; i++) xab[i] = 0.0;
  for(i = 0; i < na; i++)
    for(j = 0; j < nb; j++) xab[i + j] += xa[i] * xb[j];
  UNPROTECT(3);
  return(ab);
@}
@end group
@end example

Note that unlike the macros in @Sl{} version 4, the @R{} versions of
these macros do check that coercion can be done and raise an error if it
fails.  They will raise warnings if missing values are introduced by
coercion.  Although we illustrate doing the coercion in the C code here,
it often is simpler to do the necessary coercions in the @R{} code.

Now for the version in @R{}-internal style.  Only the C code changes.

@example
@group
#include <R.h>
#include <Rinternals.h>

SEXP convolve2(SEXP a, SEXP b)
@{
  R_len_t i, j, na, nb, nab;
  double *xa, *xb, *xab;
  SEXP ab;

  PROTECT(a = coerceVector(a, REALSXP));
  PROTECT(b = coerceVector(b, REALSXP));
  na = length(a); nb = length(b); nab = na + nb - 1;
  PROTECT(ab = allocVector(REALSXP, nab));
  xa = REAL(a); xb = REAL(b);
  xab = REAL(ab);
  for(i = 0; i < nab; i++) xab[i] = 0.0;
  for(i = 0; i < na; i++)
    for(j = 0; j < nb; j++) xab[i + j] += xa[i] * xb[j];
  UNPROTECT(3);
  return(ab);
@}
@end group
@end example

@noindent
This is called in exactly the same way.

@node Calling .External, Missing and special values, Calling .Call, Interface functions .Call and .External
@subsection Calling @code{.External}

@findex .External

We can use the same example to illustrate @code{.External}.  The @R{}
code changes only by replacing @code{.Call} by @code{.External}

@example
conv <- function(a, b) .External("convolveE", a, b)
@end example

@noindent
but the main change is how the arguments are passed to the C code, this
time as a single SEXP.  The only change to the C code is how we handle
the arguments.

@example
@group
#include <R.h>
#include <Rinternals.h>

SEXP convolveE(SEXP args)
@{
  int i, j, na, nb, nab;
  double *xa, *xb, *xab;
  SEXP a, b, ab;

  PROTECT(a = coerceVector(CADR(args), REALSXP));
  PROTECT(b = coerceVector(CADDR(args), REALSXP));
    ...
@}
@end group
@end example

@noindent
Once again we do not need to protect the arguments, as in the @R{} side
of the interface they are objects that are already in use.  The macros

@example
@group
  first = CADR(args);
  second = CADDR(args);
  third = CADDDR(args);
  fourth = CAD4R(args);
@end group
@end example

@noindent
provide convenient ways to access the first four arguments.  More
generally we can use the
@findex CAR
@findex CDR
@code{CDR} and @code{CAR} macros as in

@example
@group
  args = CDR(args); a = CAR(args);
  args = CDR(args); b = CAR(args);
@end group
@end example

@noindent
which clearly allows us to extract an unlimited number of arguments
(whereas @code{.Call} has a limit, albeit at 65 not a small one).

More usefully, the @code{.External} interface provides an easy way to
handle calls with a variable number of arguments, as @code{length(args)}
will give the number of arguments supplied (of which the first is
ignored).  We may need to know the names (`tags') given to the actual
arguments, which we can by using the @code{TAG} macro and using
something like the following example, that prints the names and the first
value of its arguments if they are vector types.

@example
@group
#include <R_ext/PrtUtil.h>

SEXP showArgs(SEXP args)
@{
  int i, nargs;
  Rcomplex cpl;
  const char *name;
  SEXP el;
@end group

@group
  args = CDR(args); /* skip 'name' */
  for(i = 0; args != R_NilValue; i++, args = CDR(args)) @{
    args = CDR(args);
    name = CHAR(PRINTNAME(TAG(args)));
    switch(TYPEOF(CAR(args))) @{
    case REALSXP:
      Rprintf("[%d] '%s' %f\n", i+1, name, REAL(CAR(args))[0]);
      break;
@end group
@group
    case LGLSXP:
    case INTSXP:
      Rprintf("[%d] '%s' %d\n", i+1, name, INTEGER(CAR(args))[0]);
      break;
@end group
@group
    case CPLXSXP:
      cpl = COMPLEX(CAR(args))[0];
      Rprintf("[%d] '%s' %f + %fi\n", i+1, name, cpl.r, cpl.i);
      break;
@end group
@group
    case STRSXP:
      Rprintf("[%d] '%s' %s\n", i+1, name,
             CHAR(STRING_ELT(CAR(args), 0)));
      break;
@end group
@group
    default:
      Rprintf("[%d] '%s' R type\n", i+1, name);
    @}
  @}
  return(R_NilValue);
@}
@end group
@end example

This can be called by the wrapper function

@example
showArgs <- function(...) .External("showArgs", ...)
@end example

@noindent
Note that this style of programming is convenient but not necessary, as
an alternative style is

@example
showArgs1 <- function(...) .Call("showArgs1", list(...))
@end example

@noindent
The (very similar) C code is in the scripts.

@node Missing and special values,  , Calling .External, Interface functions .Call and .External
@subsection Missing and special values
@cindex Missing values
@cindex IEEE special values

One piece of error-checking the @code{.C} call does (unless @code{NAOK}
is true) is to check for missing (@code{NA}) and @acronym{IEEE} special
values (@code{Inf}, @code{-Inf} and @code{NaN}) and give an error if any
are found.  With the @code{.Call} interface these will be passed to our
code.  In this example the special values are no problem, as
@acronym{IEEE} arithmetic will handle them correctly.  In the current
implementation this is also true of @code{NA} as it is a type of
@code{NaN}, but it is unwise to rely on such details.  Thus we will
re-write the code to handle @code{NA}s using macros defined in
@file{R_exts/Arith.h} included by @file{R.h}.

The code changes are the same in any of the versions of @code{convolve2}
or @code{convolveE}:

@example
@group
    ...
  for(i = 0; i < na; i++)
    for(j = 0; j < nb; j++)
        if(ISNA(xa[i]) || ISNA(xb[j]) || ISNA(xab[i + j]))
          xab[i + j] = NA_REAL;
        else
          xab[i + j] += xa[i] * xb[j];
    ...
@end group
@end example

@findex ISNA
@findex ISNAN

Note that the @code{ISNA} macro, and the similar macros @code{ISNAN}
(which checks for @code{NaN} or @code{NA}) and @code{R_FINITE} (which is
false for @code{NA} and all the special values), only apply to numeric
values of type @code{double}.  Missingness of integers, logicals and
character strings can be tested by equality to the constants
@code{NA_INTEGER}, @code{NA_LOGICAL} and @code{NA_STRING}.  These and
@code{NA_REAL} can be used to set elements of @R{} vectors to @code{NA}.

The constants @code{R_NaN}, @code{R_PosInf}, @code{R_NegInf} and
@code{R_NaReal} can be used to set @code{double}s to the special values.

@node Evaluating R expressions from C, Parsing R code from C, Interface functions .Call and .External, System and foreign language interfaces
@section Evaluating R expressions from C
@cindex Evaluating R expressions from C

We noted that the @code{call_R} interface could be used to evaluate @R{}
expressions from C code, but the current interfaces are much more
convenient to use.  The main function we will use is

@example
SEXP eval(SEXP expr, SEXP rho);
@end example

@noindent
the equivalent of the interpreted @R{} code @code{eval(expr, envir =
rho)}, although we can also make use of @code{findVar}, @code{defineVar}
and @code{findFun} (which restricts the search to functions).

To see how this might be applied, here is a simplified internal version
of @code{lapply} for expressions, used as

@example
@group
a <- list(a = 1:5, b = rnorm(10), test = runif(100))
.Call("lapply", a, quote(sum(x)), new.env())
@end group
@end example

@noindent
with C code

@example
@group
SEXP lapply(SEXP list, SEXP expr, SEXP rho)
@{
  R_len_t i, n = length(list);
  SEXP ans;

  if(!isNewList(list)) error("'list' must be a list");
  if(!isEnvironment(rho)) error("'rho' should be an environment");
  PROTECT(ans = allocVector(VECSXP, n));
  for(i = 0; i < n; i++) @{
    defineVar(install("x"), VECTOR_ELT(list, i), rho);
    SET_VECTOR_ELT(ans, i, eval(expr, rho));
  @}
  setAttrib(ans, R_NamesSymbol, getAttrib(list, R_NamesSymbol));
  UNPROTECT(1);
  return(ans);
@}
@end group
@end example

It would be closer to @code{lapply} if we could pass in a function
rather than an expression.  One way to do this is @emph{via} interpreted
@R{} code as in the next example, but it is possible (if somewhat
obscure) to do this in C code.  The following is based on the code in
@file{src/main/optimize.c}.

@example
@group
SEXP lapply2(SEXP list, SEXP fn, SEXP rho)
@{
  R_len_t i, n = length(list);
  SEXP R_fcall, ans;

  if(!isNewList(list)) error("'list' must be a list");
  if(!isFunction(fn)) error("'fn' must be a function");
  if(!isEnvironment(rho)) error("'rho' should be an environment");
  PROTECT(R_fcall = lang2(fn, R_NilValue));
  PROTECT(ans = allocVector(VECSXP, n));
  for(i = 0; i < n; i++) @{
    SETCADR(R_fcall, VECTOR_ELT(list, i));
    SET_VECTOR_ELT(ans, i, eval(R_fcall, rho));
  @}
  setAttrib(ans, R_NamesSymbol, getAttrib(list, R_NamesSymbol));
  UNPROTECT(2);
  return(ans);
@}
@end group
@end example

@noindent
used by

@example
.Call("lapply2", a, sum, new.env())
@end example

@noindent
Function @code{lang2} creates an executable pairlist of two elements, but
this will only be clear to those with a knowledge of a LISP-like
language.

As a more comprehensive example of constructing an @R{} call in C code
and evaluating, consider the following fragment of
@code{printAttributes} in @file{src/main/print.c}.

@example
    /* Need to construct a call to
       print(CAR(a), digits=digits)
       based on the R_print structure, then eval(call, env).
       See do_docall for the template for this sort of thing.
    */
    SEXP s, t;
    PROTECT(t = s = allocList(3));
    SET_TYPEOF(s, LANGSXP);
    SETCAR(t, install("print")); t = CDR(t);
    SETCAR(t,  CAR(a)); t = CDR(t);
    SETCAR(t, ScalarInteger(digits));
    SET_TAG(t, install("digits"));
    eval(s, env);
    UNPROTECT(1);
@end example

@noindent
At this point @code{CAR(a)} is the @R{} object to be printed, the
current attribute.  There are three steps: the call is constructed as
a pairlist of length 3, the list is filled in, and the expression
represented by the pairlist is evaluated.

A pairlist is quite distinct from a generic vector list, the only
user-visible form of list in @R{}.  A pairlist is a linked list (with
@code{CDR(t)} computing the next entry), with items (accessed by
@code{CAR(t)}) and names or tags (set by @code{SET_TAG}).  In this call
there are to be three items, a symbol (pointing to the function to be
called) and two argument values, the first unnamed and the second named.
Setting the type to @code{LANGSXP} makes this a call which can be evaluated.

@menu
* Zero-finding::
* Calculating numerical derivatives::
@end menu

@node Zero-finding, Calculating numerical derivatives, Evaluating R expressions from C, Evaluating R expressions from C
@subsection Zero-finding
@cindex Zero-finding

In this section we re-work the example of @code{call_S} in Becker,
Chambers & Wilks (1988) on finding a zero of a univariate function,
The @R{} code and an example are

@example
zero <- function(f, guesses, tol = 1e-7) @{
  f.check <- function(x) @{
    x <- f(x)
    if(!is.numeric(x)) stop("Need a numeric result")
    as.double(x)
  @}
  .Call("zero", body(f.check), as.double(guesses), as.double(tol),
        new.env())
@}

cube1 <- function(x) (x^2 + 1) * (x - 1.5)
zero(cube1, c(0, 5))
@end example

@noindent
where this time we do the coercion and error-checking in the @R{} code.
The C code is

@example
@group
SEXP mkans(double x)
@{
    SEXP ans;
    PROTECT(ans = allocVector(REALSXP, 1));
    REAL(ans)[0] = x;
    UNPROTECT(1);
    return ans;
@}
@end group

@group
double feval(double x, SEXP f, SEXP rho)
@{
    defineVar(install("x"), mkans(x), rho);
    return(REAL(eval(f, rho))[0]);
@}
@end group

@group
SEXP zero(SEXP f, SEXP guesses, SEXP stol, SEXP rho)
@{
    double x0 = REAL(guesses)[0], x1 = REAL(guesses)[1],
           tol = REAL(stol)[0];
    double f0, f1, fc, xc;
@end group

@group
    if(tol <= 0.0) error("non-positive tol value");
    f0 = feval(x0, f, rho); f1 = feval(x1, f, rho);
    if(f0 == 0.0) return mkans(x0);
    if(f1 == 0.0) return mkans(x1);
    if(f0*f1 > 0.0) error("x[0] and x[1] have the same sign");
@end group

@group
    for(;;) @{
        xc = 0.5*(x0+x1);
        if(fabs(x0-x1) < tol) return  mkans(xc);
        fc = feval(xc, f, rho);
        if(fc == 0) return  mkans(xc);
        if(f0*fc > 0.0) @{
            x0 = xc; f0 = fc;
        @} else @{
            x1 = xc; f1 = fc;
        @}
    @}
@}
@end group
@end example

@noindent
The C code is essentially unchanged from the @code{call_R} version, just
using a couple of functions to convert from @code{double} to @code{SEXP}
and to evaluate @code{f.check}.

@node Calculating numerical derivatives,  , Zero-finding, Evaluating R expressions from C
@subsection Calculating numerical derivatives
@cindex Numerical derivatives

We will use a longer example (by Saikat DebRoy) to illustrate the use of
evaluation and @code{.External}.  This calculates numerical derivatives,
something that could be done as effectively in interpreted @R{} code but
may be needed as part of a larger C calculation.

An interpreted @R{} version and an example are

@example
@group
numeric.deriv <- function(expr, theta, rho=sys.frame(sys.parent()))
@{
  eps <- sqrt(.Machine$double.eps)
  ans <- eval(substitute(expr), rho)
  grad <- matrix(,length(ans), length(theta),
                 dimnames=list(NULL, theta))
  for (i in seq_along(theta)) @{
    old <- get(theta[i], envir=rho)
    delta <- eps * min(1, abs(old))
    assign(theta[i], old+delta, envir=rho)
    ans1 <- eval(substitute(expr), rho)
    assign(theta[i], old, envir=rho)
    grad[, i] <- (ans1 - ans)/delta
  @}
  attr(ans, "gradient") <- grad
  ans
@}
omega <- 1:5; x <- 1; y <- 2
numeric.deriv(sin(omega*x*y), c("x", "y"))
@end group
@end example

@noindent
where @code{expr} is an expression, @code{theta} a character vector of
variable names and @code{rho} the environment to be used.

For the compiled version the call from @R{} will be

@example
.External("numeric_deriv", @var{expr}, @var{theta}, @var{rho})
@end example

@noindent
with example usage

@example
.External("numeric_deriv", quote(sin(omega*x*y)),
          c("x", "y"), .GlobalEnv)
@end example

@noindent
Note the need to quote the expression to stop it being evaluated.

Here is the complete C code which we will explain section by section.

@example
@group
#include <R.h> /* for DOUBLE_EPS */
#include <Rinternals.h>

SEXP numeric_deriv(SEXP args)
@{
  SEXP theta, expr, rho, ans, ans1, gradient, par, dimnames;
  double tt, xx, delta, eps = sqrt(DOUBLE_EPS), *rgr, *rans;
  int start, i, j;
@end group

@group
  expr = CADR(args);
  if(!isString(theta = CADDR(args)))
    error("theta should be of type character");
  if(!isEnvironment(rho = CADDDR(args)))
    error("rho should be an environment");
@end group

@group
  PROTECT(ans = coerceVector(eval(expr, rho), REALSXP));
  PROTECT(gradient = allocMatrix(REALSXP, LENGTH(ans), LENGTH(theta)));
  rgr = REAL(gradient); rans = REAL(ans);
@end group

@group
  for(i = 0, start = 0; i < LENGTH(theta); i++, start += LENGTH(ans)) @{
    PROTECT(par = findVar(install(CHAR(STRING_ELT(theta, i))), rho));
    tt = REAL(par)[0];
    xx = fabs(tt);
    delta = (xx < 1) ? eps : xx*eps;
    REAL(par)[0] += delta;
    PROTECT(ans1 = coerceVector(eval(expr, rho), REALSXP));
    for(j = 0; j < LENGTH(ans); j++)
      rgr[j + start] = (REAL(ans1)[j] - rans[j])/delta;
    REAL(par)[0] = tt;
    UNPROTECT(2); /* par, ans1 */
  @}
@end group

@group
  PROTECT(dimnames = allocVector(VECSXP, 2));
  SET_VECTOR_ELT(dimnames, 1,  theta);
  dimnamesgets(gradient, dimnames);
  setAttrib(ans, install("gradient"), gradient);
  UNPROTECT(3); /* ans  gradient  dimnames */
  return ans;
@}
@end group
@end example

The code to handle the arguments is

@example
@group
  expr = CADR(args);
  if(!isString(theta = CADDR(args)))
    error("theta should be of type character");
  if(!isEnvironment(rho = CADDDR(args)))
    error("rho should be an environment");
@end group
@end example

@noindent
Note that we check for correct types of @code{theta} and @code{rho} but
do not check the type of @code{expr}.  That is because @code{eval} can
handle many types of @R{} objects other than @code{EXPRSXP}.  There is
no useful coercion we can do, so we stop with an error message if the
arguments are not of the correct mode.

The first step in the code is to evaluate the expression in the
environment @code{rho}, by

@example
  PROTECT(ans = coerceVector(eval(expr, rho), REALSXP));
@end example

@noindent
We then allocate space for the calculated derivative by

@example
  PROTECT(gradient = allocMatrix(REALSXP, LENGTH(ans), LENGTH(theta)));
@end example

@noindent
The first argument to @code{allocMatrix} gives the @code{SEXPTYPE} of
the matrix: here we want it to be @code{REALSXP}.  The other two
arguments are the numbers of rows and columns.

@example
@group
  for(i = 0, start = 0; i < LENGTH(theta); i++, start += LENGTH(ans)) @{
    PROTECT(par = findVar(install(CHAR(STRING_ELT(theta, i))), rho));
@end group
@end example

@noindent
Here, we are entering a for loop.  We loop through each of the
variables.  In the @code{for} loop, we first create a symbol
corresponding to the @code{i}'th element of the @code{STRSXP}
@code{theta}.  Here, @code{STRING_ELT(theta, i)} accesses the
@code{i}'th element of the @code{STRSXP} @code{theta}.  Macro
@code{CHAR()} extracts the actual character
representation@footnote{@pxref{Character encoding issues} for why this
might not be what is required.} of it: it returns a pointer.  We then
install the name and use @code{findVar} to find its value.

@example
@group
    tt = REAL(par)[0];
    xx = fabs(tt);
    delta = (xx < 1) ? eps : xx*eps;
    REAL(par)[0] += delta;
    PROTECT(ans1 = coerceVector(eval(expr, rho), REALSXP));
@end group
@end example

@noindent
We first extract the real value of the parameter, then calculate
@code{delta}, the increment to be used for approximating the numerical
derivative.  Then we change the value stored in @code{par} (in
environment @code{rho}) by @code{delta} and evaluate @code{expr} in
environment @code{rho} again.  Because we are directly dealing with
original @R{} memory locations here, @R{} does the evaluation for the
changed parameter value.

@example
@group
    for(j = 0; j < LENGTH(ans); j++)
      rgr[j + start] = (REAL(ans1)[j] - rans[j])/delta;
    REAL(par)[0] = tt;
    UNPROTECT(2);
  @}
@end group
@end example

@noindent
Now, we compute the @code{i}'th column of the gradient matrix.  Note how
it is accessed: @R{} stores matrices by column (like FORTRAN).

@example
@group
  PROTECT(dimnames = allocVector(VECSXP, 2));
  SET_VECTOR_ELT(dimnames, 1, theta);
  dimnamesgets(gradient, dimnames);
  setAttrib(ans, install("gradient"), gradient);
  UNPROTECT(3);
  return ans;
@}
@end group
@end example

@noindent
First we add column names to the gradient matrix.  This is done by
allocating a list (a @code{VECSXP}) whose first element, the row names,
is @code{NULL} (the default) and the second element, the column names,
is set as @code{theta}.  This list is then assigned as the attribute
having the symbol @code{R_DimNamesSymbol}.  Finally we set the gradient
matrix as the gradient attribute of @code{ans}, unprotect the remaining
protected locations and return the answer @code{ans}.

@node Parsing R code from C, External pointers and weak references, Evaluating R expressions from C, System and foreign language interfaces
@section Parsing R code from C
@cindex Parsing R code from C

Suppose an @R{} extension want to accept an @R{} expression from the
user and evaluate it.  The previous section covered evaluation, but the
expression will be entered as text and needs to be parsed first.  A
small part of @R{}'s parse interface is declared in header file
@file{R_ext/Parse.h}@footnote{This is only guaranteed to show the
current interface: it is liable to change.}.

An example of the usage can be found in the (example) Windows package
@pkg{windlgs} included in the @R{} source tree.  The essential part is

@example
@group
#include <R.h>
#include <Rinternals.h>
#include <R_ext/Parse.h>

SEXP menu_ttest3()
@{
    char cmd[256];
    SEXP cmdSexp, cmdexpr, ans = R_NilValue;
    int i;
    ParseStatus status;
   ...
    if(done == 1) @{
        PROTECT(cmdSexp = allocVector(STRSXP, 1));
        SET_STRING_ELT(cmdSexp, 0, mkChar(cmd));
        cmdexpr = PROTECT(R_ParseVector(cmdSexp, -1, &status, R_NilValue));
        if (status != PARSE_OK) @{
            UNPROTECT(2);
            error("invalid call %s", cmd);
        @}
        /* Loop is needed here as EXPSEXP will be of length > 1 */
        for(i = 0; i < length(cmdexpr); i++)
            ans = eval(VECTOR_ELT(cmdexpr, i), R_GlobalEnv);
        UNPROTECT(2);
    @}
    return ans;
@}
@end group
@end example
@noindent
Note that a single line of text may give rise to more than one @R{}
expression.

@findex R_ParseVector
@code{R_ParseVector} is essentially the code used to implement
@code{parse(text=)} at @R{} level.  The first argument is a character
vector (corresponding to @code{text}) and the second the maximal number
of expressions to parse (corresponding to @code{n}).  The third argument
is a pointer to a variable of an enumeration type, and it is normal (as
@code{parse} does) to regard all values other than @code{PARSE_OK} as an
error.  Other values which might be returned are @code{PARSE_INCOMPLETE}
(an incomplete expression was found) and @code{PARSE_ERROR} (a syntax
error), in both cases the value returned being @code{R_NilValue}.
The fourth argument is a @code{srcfile} object or the @R{} @code{NULL}
object (as in the example above). In the former case a @code{srcref}
attribute would be attached to the result, containing a list of
@code{srcref} objects of the same length as the expression, to allow it to be
echoed with its original formatting.

@node External pointers and weak references, Vector accessor functions, Parsing R code from C, System and foreign language interfaces
@section External pointers and weak references

The @code{SEXPTYPE}s @code{EXTPTRSXP} and @code{WEAKREFSXP} can be
encountered at @R{} level, but are created in C code.

@cindex external pointer
External pointer @code{SEXP}s are intended to handle references to C
structures such as `handles', and are used for this purpose in package
@pkg{RODBC} for example.  They are unusual in their copying semantics in
that when an @R{} object is copied, the external pointer object is not
duplicated.  (For this reason external pointers should only be used as
part of an object with normal semantics, for example an attribute or an
element of a list.)

An external pointer is created by

@example
SEXP R_MakeExternalPtr(void *p, SEXP tag, SEXP prot);
@end example

@noindent
where @code{p} is the pointer (and hence this cannot portably be a
function pointer), and @code{tag} and @code{prot} are references to
ordinary @R{} objects which will remain in existence (be protected from
garbage collection) for the lifetime of the external pointer object.  A
useful convention is to use the @code{tag} field for some form of type
identification and the @code{prot} field for protecting the memory that
the external pointer represents, if that memory is allocated from the
@R{} heap.  Both @code{tag} and @code{prot} can be @code{R_NilValue},
and often are.

The elements of an external pointer can be accessed and set @emph{via}

@example
void *R_ExternalPtrAddr(SEXP s);
SEXP R_ExternalPtrTag(SEXP s);
SEXP R_ExternalPtrProtected(SEXP s);
void R_ClearExternalPtr(SEXP s);
void R_SetExternalPtrAddr(SEXP s, void *p);
void R_SetExternalPtrTag(SEXP s, SEXP tag);
void R_SetExternalPtrProtected(SEXP s, SEXP p);
@end example

@noindent
Clearing a pointer sets its value to the C @code{NULL} pointer.

@cindex finalizer
An external pointer object can have a @emph{finalizer}, a piece of code
to be run when the object is garbage collected.  This can be @R{} code
or C code, and the various interfaces are, respectively.

@example
void R_RegisterFinalizerEx(SEXP s, SEXP fun, Rboolean onexit);

typedef void (*R_CFinalizer_t)(SEXP);
void R_RegisterCFinalizerEx(SEXP s, R_CFinalizer_t fun, Rboolean onexit);
@end example

@noindent
The @R{} function indicated by @code{fun} should be a function of a
single argument, the object to be finalized.  @R{} does not perform a
garbage collection when shutting down, and the @code{onexit} argument of
the extended forms can be used to ask that the finalizer be run during a
normal shutdown of the @R{} session.  It is suggested that it is good
practice to clear the pointer on finalization.

The only @R{} level function for interacting with external pointers is
@code{reg.finalizer} which can be used to set a finalizer.

It is probably not a good idea to allow an external pointer to be
@code{save}d and then reloaded, but if this happens the pointer will be
set to the C @code{NULL} pointer.


@cindex weak reference
Weak references are used to allow the programmer to maintain information
on entities without preventing the garbage collection of the entities
once they become unreachable.

A weak reference contains a key and a value.  The value is reachable is
if it either reachable directly or @emph{via} weak references with reachable
keys.  Once a value is determined to be unreachable during garbage
collection, the key and value are set to @code{R_NilValue} and the
finalizer will be run later in the garbage collection.

Weak reference objects are created by one of

@example
SEXP R_MakeWeakRef(SEXP key, SEXP val, SEXP fin, Rboolean onexit);
SEXP R_MakeWeakRefC(SEXP key, SEXP val, R_CFinalizer_t fin,
                    Rboolean onexit);
@end example

@noindent
where the @R{} or C finalizer are specified in exactly the same way as
for an external pointer object (whose finalization interface is
implemented @emph{via} weak references).

The parts can be accessed @emph{via}

@example
SEXP R_WeakRefKey(SEXP w);
SEXP R_WeakRefValue(SEXP w);
void R_RunWeakRefFinalizer(SEXP w);
@end example

A toy example of the use of weak references can be found at
@uref{http://www.stat.uiowa.edu/~luke/R/references/weakfinex.html,
@code{www.@/stat.@/uiowa.@/edu/@/~luke/@/R/references/@/weakfinex.html}},
but that is used to add finalizers to external pointers which can now be
done more directly.  At the time of writing no @acronym{CRAN} or
Bioconductor package uses weak references.


@menu
* An external pointer example::
@end menu

@node An external pointer example,  , External pointers and weak references, External pointers and weak references
@subsection An example

Package @pkg{RODBC} uses external pointers to maintain its
@emph{channels}, connections to databases.  There can be several
connections open at once, and the status information for each is stored
in a C structure (pointed to by @code{this_handle}) in the code extract
below) that is returned @emph{via} an external pointer as part of the RODBC
`channel' (as the @code{"handle_ptr"} attribute).  The external pointer
is created by

@example
    SEXP ans, ptr;
    PROTECT(ans = allocVector(INTSXP, 1));
    ptr = R_MakeExternalPtr(thisHandle, install("RODBC_channel"), R_NilValue);
    PROTECT(ptr);
    R_RegisterCFinalizerEx(ptr, chanFinalizer, TRUE);
            ...
    /* return the channel no */
    INTEGER(ans)[0] = nChannels;
    /* and the connection string as an attribute */
    setAttrib(ans, install("connection.string"), constr);
    setAttrib(ans, install("handle_ptr"), ptr);
    UNPROTECT(3);
    return ans;
@end example

@noindent
Note the symbol given to identify the usage of the external pointer, and
the use of the finalizer.  Since the final argument when registering the
finalizer is @code{TRUE}, the finalizer will be run at the the of the
@R{} session (unless it crashes).  This is used to close and clean up
the connection to the database.  The finalizer code is simply

@example
static void chanFinalizer(SEXP ptr)
@{
    if(!R_ExternalPtrAddr(ptr)) return;
    inRODBCClose(R_ExternalPtrAddr(ptr));
    R_ClearExternalPtr(ptr); /* not really needed */
@}
@end example

@noindent
Clearing the pointer and checking for a @code{NULL} pointer avoids any
possibility of attempting to close an already-closed channel.

@R{}'s connections provide another example of using external pointers,
in that case purely to be able to use a finalizer to close and destroy the
connection if it is no longer is use.

@node Vector accessor functions, Character encoding issues, External pointers and weak references, System and foreign language interfaces
@section Vector accessor functions

The vector accessors like @code{REAL} and @code{INTEGER} and
@code{VECTOR_ELT} are @emph{functions} when used in @R{} extensions.
(For efficiency they are macros when used in the @R{} source code, apart
from @code{SET_STRING_ELT} and @code{SET_VECTOR_ELT} which are always
functions.)

The accessor functions check that they are being used on an appropriate
type of @code{SEXP}.

If efficiency is essential, the macro versions of the accessors can be
obtained by defining @samp{USE_RINTERNALS} before including
@file{Rinternals.h}.  If you find it necessary to do so, please do test
that your code compiled without @samp{USE_RINTERNALS} defined, as this
provides a stricter test that the accessors have been used correctly.

@node Character encoding issues,  , Vector accessor functions, System and foreign language interfaces
@section Character encoding issues

@findex translateChar
@findex translateCharUTF8
@code{CHARSXP}s can be marked as coming from a known encoding (Latin-1
or UTF-8).  This is mainly intended for human-readable output, and most
packages can just treat such @code{CHARSXP}s as a whole.  However, if
they need to be interpreted as characters or output at C level then it
would normally be correct to ensure that they are converted to the
encoding of the current locale: this can be done by accessing the data
in the @code{CHARSXP} by @code{translateChar} rather than by
@code{CHAR}.  If re-encoding is needed this allocates memory with
@code{R_alloc} which thus persists to the end of the
@code{.Call}/@code{.External} call unless @code{vmaxset} is used.

There is a similar function @code{translateCharUTF8} which converts to
UTF-8: this has the advantage that a faithful translation is almost
always possible (whereas only a few languages can be represented in the
encoding of the current locale unless that is UTF-8).

@findex getCharCE
@findex mkCharCE
There is a public interface to the encoding marked on @code{CHARXSXPs}
@emph{via}

@example
typedef enum @{CE_NATIVE, CE_UTF8, CE_LATIN1, CE_SYMBOL, CE_ANY@} cetype_t;
cetype_t getCharCE(SEXP);
SEXP mkCharCE(const char *, cetype_t);
@end example

@noindent
Only the @code{CE_UTF8} and @code{CE_LATIN1} are marked on
@code{CHARSXPs} (and so @code{Rf_getCharCE} will only return one of the
first three), and these should only be used on non-@acronym{ASCII}
strings.  Value @code{CE_SYMBOL} is used internally to indicate Adobe
Symbol encoding.  Value @code{CE_ANY} is used to indicate a character
string that will not need re-encoding -- this is used for character
strings known to be in @acronym{ASCII}, and can also be used as an input
parameter where the intention is that the string is treated as a series
of bytes.

Function

@findex reEnc
@example
const char *reEnc(const char *x, cetype_t ce_in, cetype_t ce_out,
                  int subst);
@end example

@noindent
can be used to re-encode character strings: like @code{translateChar} it
returns a string allocated by @code{R_alloc}.  This can translate from
@code{CE_SYMBOL} to @code{CE_UTF8}, but not conversely.  Argument
@code{subst} controls what to do with untranslatable characters or
invalid input: this is done byte-by-byte with @code{1} indicates to
output hex of the form @code{<a0>}, and @code{2} to replace by @code{.},
with any other value causing the byte to produce no output.

@findex mkCharLenCE
There is also

@example
SEXP mkCharLenCE(const char *, int, cetype_t);
@end example

@noindent
to create marked character strings of a given length.


@node The R API, Generic functions and methods, System and foreign language interfaces, Top
@chapter The R @acronym{API}: entry points for C code

@menu
* Memory allocation::
* Error handling::
* Random numbers::
* Missing and IEEE values::
* Printing::
* Calling C from FORTRAN and vice versa::
* Numerical analysis subroutines::
* Optimization::
* Integration::
* Utility functions::
* Re-encoding::
* Allowing interrupts::
* Platform and version information::
* Inlining C functions::
* Controlling visibility::
* Standalone Mathlib::
* Organization of header files::
@end menu

There are a large number of entry points in the @R{} executable/DLL that
can be called from C code (and some that can be called from FORTRAN
code).  Only those documented here are stable enough that they will only
be changed with considerable notice.

The recommended procedure to use these is to include the header file
@file{R.h} in your C code by

@example
#include <R.h>
@end example

@noindent
This will include several other header files from the directory
@file{@var{R_INCLUDE_DIR}/R_ext}, and there are other header files
there that can be included too, but many of the features they contain
should be regarded as undocumented and unstable.

An alternative is to include the header file @file{S.h}, which may be
useful when porting code from @Sl{}.  This includes rather less than
@file{R.h}, and has some extra compatibility definitions (for example
the @code{S_complex} type from @Sl{}).

The defines used for compatibility with @Sl{} sometimes causes
conflicts (notably with Windows headers), and the known
problematic defines can be removed by defining @code{STRICT_R_HEADERS}.

Most of these header files, including all those included by @file{R.h},
can be used from C++ code.  Some others need to be included within an
@code{extern "C"} declaration, and for clarity this is advisable for all
@R{} header files.

@quotation Note
Because @R{} re-maps many of its external names to avoid clashes with
user code, it is @emph{essential} to include the appropriate header
files when using these entry points.
@end quotation

This remapping can cause problems@footnote{Known problems are redefining
@code{error}, @code{length}, @code{vector} and @code{warning}}, and can
be eliminated by defining @code{R_NO_REMAP} and prepending @samp{Rf_} to
@emph{all} the function names used from @file{Rinternals.h} and
@file{R_ext/Error.h}.

We can classify the entry points as

@table @emph
@item API
Entry points which are documented in this manual and declared in an
installed header file.  These can be used in distributed packages and
will only be changed after deprecation.

@item public
Entry points declared in an installed header file that are exported
on all @R{} platforms but are not documented and subject to change
without notice.

@item private
Entry points that are used when building @R{} and exported on all @R{}
platforms but are not declared in the installed header files.
Do not use these in distributed code.

@item hidden
Entry points that are where possible (Windows and some modern Unix-alike
compilers/loaders when using @R{} as a shared library) not exported.
@end table

@node Memory allocation, Error handling, The R API, The R API
@section Memory allocation
@cindex Memory allocation from C

@menu
* Transient::
* User-controlled::
@end menu

There are two types of memory allocation available to the C programmer,
one in which @R{} manages the clean-up and the other in which user
has full control (and responsibility).

@node Transient, User-controlled, Memory allocation, Memory allocation
@subsection Transient storage allocation
@findex R_alloc
@findex S_alloc
@findex S_realloc
@findex vmaxget
@findex vmaxset

Here @R{} will reclaim the memory at the end of the call to @code{.C}.
Use

@example
char *R_alloc(size_t @var{n}, int @var{size})
@end example

@noindent
which allocates @var{n} units of @var{size} bytes each.  A typical usage
(from package @pkg{stats}) is

@example
x = (int *) R_alloc(nrows(merge)+2, sizeof(int));
@end example

@noindent
(@code{size_t} is defined in @file{stddef.h} which the header defining
@code{R_alloc} includes.)

There is a similar call, @code{S_alloc} (for compatibility with older
versions of @Sl{}) which zeroes the memory allocated,

@example
char *S_alloc(long @var{n}, int @var{size})
@end example

@noindent
and

@example
char *S_realloc(char *@var{p}, long @var{new}, long @var{old}, int @var{size})
@end example

@noindent
which changes the allocation size from @var{old} to @var{new} units, and
zeroes the additional units.

For compatibility with current versions of @Sl{}, header @file{S.h}
(only) defines wrapper macros equivalent to

@example
type* Salloc(long @var{n}, int @var{type})
type* Srealloc(char *@var{p}, long @var{new}, long @var{old}, int @var{type})
@end example

This memory is taken from the heap, and released at the end of the
@code{.C}, @code{.Call} or @code{.External} call.  Users can also manage
it, by noting the current position with a call to @code{vmaxget} and
clearing memory allocated subsequently by a call to @code{vmaxset}.
This is only recommended for experts.

Note that this memory will be freed on error or user interrupt
(if allowed: @pxref{Allowing interrupts}).

Note that although @var{n} is @code{long}, there are limits imposed by
@R{}'s internal allocation mechanism.  These will only come into play on
64-bit systems, where the current limit for @var{n} is just under 16Gb.

@node User-controlled,  , Transient, Memory allocation
@subsection User-controlled memory
@findex Calloc
@findex Realloc
@findex Free

The other form of memory allocation is an interface to @code{malloc},
the interface providing @R{} error handling.  This memory lasts until
freed by the user and is additional to the memory allocated for the @R{}
workspace.

The interface functions are

@example
@group
@var{type}* Calloc(size_t @var{n}, @var{type})
@var{type}* Realloc(@var{any} *@var{p}, size_t @var{n}, @var{type})
void Free(@var{any} *@var{p})
@end group
@end example

@noindent
providing analogues of @code{calloc}, @code{realloc} and @code{free}.
If there is an error during allocation it is handled by @R{}, so if
these routines return the memory has been successfully allocated or
freed.  @code{Free} will set the pointer @var{p} to @code{NULL}.  (Some
but not all versions of @Sl{} do so.)

Users should arrange to @code{Free} this memory when no longer needed,
including on error or user interrupt.  This can often be done most
conveniently from an @code{on.exit} action in the calling @R{} function
-- see @code{pwilcox} for an example.

Do not assume that memory allocated by @code{Calloc}/@code{Realloc}
comes from the same pool as used by @code{malloc}: in particular do not
use @code{free} or @code{strdup} with it.

These entry points need to be prefixed by @code{R_} if
@code{STRICT_R_HEADERS} has been defined.


@node Error handling, Random numbers, Memory allocation, The R API
@section Error handling
@cindex Error handling from C

The basic error handling routines are the equivalents of @code{stop} and
@code{warning} in @R{} code, and use the same interface.

@example
@group
void error(const char * @var{format}, ...);
void warning(const char * @var{format}, ...);
@end group
@end example

@noindent
These have the same call sequences as calls to @code{printf}, but in the
simplest case can be called with a single character string argument
giving the error message. (Don't do this if the string contains @samp{%}
or might otherwise be interpreted as a format.)

If @code{STRICT_R_HEADERS} is not defined there is also an
@Sl{}-compatibility interface which uses calls of the form

@example
@group
PROBLEM ...... ERROR
MESSAGE ...... WARN
PROBLEM ...... RECOVER(NULL_ENTRY)
MESSAGE ...... WARNING(NULL_ENTRY)
@end group
@end example

@noindent
the last two being the forms available in all @Sl{} versions.  Here
@samp{......} is a set of arguments to @code{printf}, so can be a string
or a format string followed by arguments separated by commas.

@menu
* Error handling from FORTRAN::
@end menu

@node Error handling from FORTRAN,  , Error handling, Error handling
@subsection Error handling from FORTRAN
@cindex Error handling from FORTRAN

There are two interface function provided to call @code{error} and
@code{warning} from FORTRAN code, in each case with a simple character
string argument.  They are defined as

@example
@group
subroutine rexit(@var{message})
subroutine rwarn(@var{message})
@end group
@end example

Messages of more than 255 characters are truncated, with a warning.


@node Random numbers, Missing and IEEE values, Error handling, The R API
@section Random number generation
@cindex Random numbers in C
@findex unif_rand
@findex norm_rand
@findex exp_rand
@findex GetRNGstate
@findex PutRNGstate
@findex .Random.seed
@findex seed_in
@findex seed_out

The interface to @R{}'s internal random number generation routines is

@example
@group
double unif_rand();
double norm_rand();
double exp_rand();
@end group
@end example

@noindent
giving one uniform, normal or exponential pseudo-random variate.
However, before these are used, the user must call

@example
GetRNGstate();
@end example

@noindent
and after all the required variates have been generated, call

@example
PutRNGstate();
@end example

@noindent
These essentially read in (or create) @code{.Random.seed} and write it
out after use.

File @file{S.h} defines @code{seed_in} and @code{seed_out} for
@Sl{}-compatibility rather than @code{GetRNGstate} and
@code{PutRNGstate}.  These take a @code{long *} argument which is
ignored.

The random number generator is private to @R{}; there is no way to
select the kind of RNG or set the seed except by evaluating calls to the
@R{} functions.

The C code behind @R{}'s @code{r@var{xxx}} functions can be accessed by
including the header file @file{Rmath.h}; @xref{Distribution
functions}.  Those calls generate a single variate and should also be
enclosed in calls to @code{GetRNGstate} and @code{PutRNGstate}.

@c MM: FIXME   void rmultinom() is different, returning a vector!

In addition, there is an interface (defined in header
@file{R_ext/Applic.h}) to the generation of random 2-dimensional tables
with given row and column totals using Patefield's algorithm.

@deftypefun void rcont2 (int* @var{nrow}, int* @var{ncol}, int* @var{nrowt}, int* @var{ncolt}, int* @var{ntotal}, double* @var{fact}, int* @var{jwork}, int* @var{matrix})
Here, @var{nrow} and @var{ncol} give the numbers @math{nr} and @math{nc}
of rows and columns and @var{nrowt} and @var{ncolt} the corresponding
row and column totals, respectively, @var{ntotal} gives the sum of the
row (or columns) totals, @var{jwork} is a workspace of length @math{nc},
and on output @var{matrix} a contains the @math{nr * nc} generated
random counts in the usual column-major order.
@end deftypefun

@node Missing and IEEE values, Printing, Random numbers, The R API
@section Missing and @acronym{IEEE} special values
@cindex Missing values
@cindex IEEE special values
@findex ISNA
@findex ISNAN
@findex R_FINITE
@findex R_IsNaN
@findex R_PosInf
@findex R_NegInf
@findex NA_REAL

A set of functions is provided to test for @code{NA}, @code{Inf},
@code{-Inf} and @code{NaN}.  These functions are accessed @emph{via} macros:

@example
@group
ISNA(@var{x})        @r{True for R's @code{NA} only}
ISNAN(@var{x})       @r{True for R's @code{NA} and @acronym{IEEE} @code{NaN}}
R_FINITE(@var{x})    @r{False for @code{Inf}, @code{-Inf}, @code{NA}, @code{NaN}}
@end group
@end example

@noindent
and @emph{via} function @code{R_IsNaN} which is true for @code{NaN} but not
@code{NA}.

Do use @code{R_FINITE} rather than @code{isfinite} or @code{finite}; the
latter is often mendacious and @code{isfinite} is only available on a
few platforms, on which @code{R_FINITE} is a macro expanding to
@code{isfinite}.

Currently in C code @code{ISNAN} is a macro calling @code{isnan}.
(Since this gives problems on some C++ systems, if the @R{} headers is
called from C++ code a function call is used.)

You can check for @code{Inf} or @code{-Inf} by testing equality to
@code{R_PosInf} or @code{R_NegInf}, and set (but not test) an @code{NA}
as @code{NA_REAL}.

All of the above apply to @emph{double} variables only.  For integer
variables there is a variable accessed by the macro @code{NA_INTEGER}
which can used to set or test for missingness.


@node Printing, Calling C from FORTRAN and vice versa, Missing and IEEE values, The R API
@section Printing
@cindex Printing from C
@findex Rprintf
@findex REprintf
@findex Rvprintf
@findex REvprintf

The most useful function for printing from a C routine compiled into
@R{} is @code{Rprintf}.  This is used in exactly the same way as
@code{printf}, but is guaranteed to write to @R{}'s output (which might
be a @acronym{GUI} console rather than a file).  It is wise to write
complete lines (including the @code{"\n"}) before returning to @R{}.
It is defined in @file{R_ext/Print.h}.

The function @code{REprintf} is similar but writes on the error stream
(@code{stderr}) which may or may not be different from the standard
output stream.  Functions @code{Rvprintf} and @code{REvprintf} are
analogues using the @code{vprintf} interface.

@menu
* Printing from FORTRAN::
@end menu

@node Printing from FORTRAN,  , Printing, Printing
@subsection Printing from FORTRAN
@cindex Printing from FORTRAN

On many systems FORTRAN @code{write} and @code{print} statements can be
used, but the output may not interleave well with that of C, and will be
invisible on @acronym{GUI} interfaces.  They are not portable and best
avoided.

Three subroutines are provided to ease the output of information from
FORTRAN code.

@example
@group
subroutine dblepr(@var{label}, @var{nchar}, @var{data}, @var{ndata})
subroutine realpr(@var{label}, @var{nchar}, @var{data}, @var{ndata})
subroutine intpr (@var{label}, @var{nchar}, @var{data}, @var{ndata})
@end group
@end example

@noindent
Here @var{label} is a character label of up to 255 characters,
@var{nchar} is its length (which can be @code{-1} if the whole label is
to be used), and @var{data} is an array of length at least @var{ndata}
of the appropriate type (@code{double precision}, @code{real} and
@code{integer} respectively).  These routines print the label on one
line and then print @var{data} as if it were an @R{} vector on
subsequent line(s).  They work with zero @var{ndata}, and so can be used
to print a label alone.

@node Calling C from FORTRAN and vice versa, Numerical analysis subroutines, Printing, The R API
@section Calling C from FORTRAN and vice versa
@cindex Calling C from FORTRAN and vice versa

Naming conventions for symbols generated by FORTRAN differ by platform:
it is not safe to assume that FORTRAN names appear to C with a trailing
underscore.  To help cover up the platform-specific differences there is
a set of macros that should be used.

@table @code
@item F77_SUB(@var{name})
to define a function in C to be called from FORTRAN
@item F77_NAME(@var{name})
to declare a FORTRAN routine in C before use
@item F77_CALL(@var{name})
to call a FORTRAN routine from C
@item F77_COMDECL(@var{name})
to declare a FORTRAN common block in C
@item F77_COM(@var{name})
to access a FORTRAN common block from C
@end table

On most current platforms these are all the same, but it is unwise to
rely on this.  Note that names with underscores are not legal in FORTRAN
77, and are not portably handled by the above macros.  (Also, all
FORTRAN names for use by @R{} are lower case, but this is not enforced
by the macros.)

For example, suppose we want to call R's normal random numbers from
FORTRAN.  We need a C wrapper along the lines of

@cindex Random numbers in FORTRAN
@example
@group
#include <R.h>

void F77_SUB(rndstart)(void) @{ GetRNGstate(); @}
void F77_SUB(rndend)(void) @{ PutRNGstate(); @}
double F77_SUB(normrnd)(void) @{ return norm_rand(); @}
@end group
@end example

@noindent
to be called from FORTRAN as in

@example
@group
      subroutine testit()
      double precision normrnd, x
      call rndstart()
      x = normrnd()
      call dblepr("X was", 5, x, 1)
      call rndend()
      end
@end group
@end example

@noindent
Note that this is not guaranteed to be portable, for the return
conventions might not be compatible between the C and FORTRAN compilers
used.  (Passing values @emph{via} arguments is safer.)

The standard packages, for example @pkg{stats}, are a rich source of
further examples.



@node Numerical analysis subroutines, Optimization, Calling C from FORTRAN and vice versa, The R API
@section Numerical analysis subroutines
@cindex Numerical analysis subroutines from C

@R{} contains a large number of mathematical functions for its own use,
for example numerical linear algebra computations and special functions.

The header files @file{R_ext/BLAS.h}, @file{R_ext/Lapack.h} and
@file{R_ext/Linpack.h} contains declarations of the BLAS, LAPACK and
LINPACK/EISPACK linear algebra functions included in @R{}.  These
are expressed as calls to FORTRAN subroutines, and they will also be
usable from users' FORTRAN code.  Although not part of the official
@acronym{API}, this set of subroutines is unlikely to change (but might
be supplemented).

The header file @file{Rmath.h} lists many other functions that are
available and documented in the following subsections. Many of these are
C interfaces to the code behind @R{} functions, so the @R{} function
documentation may give further details.

@menu
* Distribution functions::
* Mathematical functions::
* Numerical Utilities::
* Mathematical constants::
@end menu

@node Distribution functions, Mathematical functions, Numerical analysis subroutines, Numerical analysis subroutines
@subsection Distribution functions
@cindex  Distribution functions from C

The routines used to calculate densities, cumulative distribution
functions and quantile functions for the standard statistical
distributions are available as entry points.

The arguments for the entry points follow the pattern of those for the
normal distribution:

@example
@group
double dnorm(double @var{x}, double @var{mu}, double @var{sigma}, int @var{give_log});
double pnorm(double @var{x}, double @var{mu}, double @var{sigma}, int @var{lower_tail},
             int @var{give_log});
double qnorm(double @var{p}, double @var{mu}, double @var{sigma}, int @var{lower_tail},
             int @var{log_p});
double rnorm(double @var{mu}, double @var{sigma});
@end group
@end example

@noindent
That is, the first argument gives the position for the density and CDF
and probability for the quantile function, followed by the
distribution's parameters.  Argument @var{lower_tail} should be
@code{TRUE} (or @code{1}) for normal use, but can be @code{FALSE} (or
@code{0}) if the probability of the upper tail is desired or specified.

Finally, @var{give_log} should be non-zero if the result is required on
log scale, and @var{log_p} should be non-zero if @var{p} has been
specified on log scale.

Note that you directly get the cumulative (or ``integrated'')
@emph{hazard} function, @eqn{H(t) = - \log(1 - F(t)), H(t) = - log(1 -
F(t))}, by using

@example
- p@var{dist}(t, ..., /*lower_tail = */ FALSE, /* give_log = */ TRUE)
@end example

@noindent
or shorter (and more cryptic) @code{- p@var{dist}(t, ..., 0, 1)}.
@cindex cumulative hazard

The random-variate generation routine @code{rnorm} returns one normal
variate. @xref{Random numbers}, for the protocol in using the
random-variate routines.
@cindex Random numbers in C

Note that these argument sequences are (apart from the names and that
@code{rnorm} has no @var{n}) mainly the same as the corresponding @R{}
functions of the same name, so the documentation of the @R{} functions
can be used.  Note that the exponential and gamma distributions are
parametrized by @code{scale} rather than @code{rate}.


For reference, the following table gives the basic name (to be prefixed
by @samp{d}, @samp{p}, @samp{q} or @samp{r} apart from the exceptions
noted) and distribution-specific arguments for the complete set of
distributions.

@quotation
@multitable @columnfractions .28 .22 .30
@item beta @tab @code{beta} @tab @code{a}, @code{b}
@item non-central beta @tab @code{nbeta} @tab @code{a}, @code{b}, @code{ncp}
@c in R shape1, shape2, ncp
@item binomial @tab @code{binom} @tab @code{n}, @code{p}
@item Cauchy @tab @code{cauchy} @tab @code{location}, @code{scale}
@item chi-squared @tab @code{chisq} @tab @code{df}
@item non-central chi-squared @tab @code{nchisq} @tab @code{df}, @code{ncp}
@item exponential @tab @code{exp} @tab @code{scale} (and @strong{not} @code{rate})
@item F @tab @code{f} @tab @code{n1}, @code{n2}
@item non-central F @tab @code{nf} @tab @code{n1}, @code{n2}, @code{ncp}
@item gamma @tab @code{gamma} @tab @code{shape}, @code{scale}
@item geometric @tab @code{geom} @tab @code{p}
@item hypergeometric @tab @code{hyper} @tab @code{NR}, @code{NB}, @code{n}
@c in R m, n, k
@item logistic @tab @code{logis} @tab @code{location}, @code{scale}
@item lognormal @tab @code{lnorm} @tab @code{logmean}, @code{logsd}
@item negative binomial @tab @code{nbinom} @tab @code{size}, @code{prob}
@item normal @tab @code{norm} @tab @code{mu}, @code{sigma}
@item Poisson @tab @code{pois} @tab @code{lambda}
@item Student's t @tab @code{t} @tab @code{n}
@item non-central t @tab @code{nt} @tab @code{df}, @code{delta}
@item Studentized range @tab @code{tukey} (*) @tab @code{rr}, @code{cc}, @code{df}
@c in R nranges, nmeans, df
@item uniform @tab @code{unif} @tab @code{a}, @code{b}
@c in R min, max
@item Weibull @tab @code{weibull} @tab @code{shape}, @code{scale}
@item Wilcoxon rank sum @tab @code{wilcox} @tab @code{m}, @code{n}
@item Wilcoxon signed rank @tab @code{signrank} @tab @code{n}
@end multitable
@end quotation

@noindent
Entries marked with an asterisk only have @samp{p} and @samp{q}
functions available, and none of the non-central distributions have
@samp{r} functions.  After a call to @code{dwilcox}, @code{pwilcox} or
@code{qwilcox} the function @code{wilcox_free()} should be called, and
similarly for the signed rank functions.

@node Mathematical functions, Numerical Utilities, Distribution functions, Numerical analysis subroutines
@subsection Mathematical functions

@findex gammafn
@findex lgammafn
@findex digamma
@findex trigamma
@findex tetragamma
@findex pentagamma
@findex psigamma
@cindex Gamma function
@deftypefun double gammafn (double @var{x})
@deftypefunx double lgammafn (double @var{x})
@deftypefunx double digamma (double @var{x})
@deftypefunx double trigamma (double @var{x})
@deftypefunx double tetragamma (double @var{x})
@deftypefunx double pentagamma (double @var{x})
@deftypefunx double psigamma (double @var{x}, double @var{deriv})
The Gamma function, the natural logarithm of its absolute value and
first four derivatives and the n-th derivative of Psi, the digamma
function, which is the derivative of @code{lgammafn}. In other words,
@code{digamma(x)} is the same as @code{(psigamma(x,0)},
@code{trigamma(x) == psigamma(x,1)}, etc.
@end deftypefun

@findex beta
@findex lbeta
@cindex Beta function
@deftypefun double beta (double @var{a}, double @var{b})
@deftypefunx double lbeta (double @var{a}, double @var{b})
The (complete) Beta function and its natural logarithm.
@end deftypefun

@findex choose
@findex lchoose
@deftypefun double choose (double @var{n}, double @var{k})
@deftypefunx double lchoose (double @var{n}, double @var{k})
The number of combinations of @var{k} items chosen from from @var{n} and
the natural logarithm of its absolute value, generalized to arbitrary real
@var{n}.  @var{k} is rounded to the nearest integer (with a warning if
needed).
@end deftypefun

@findex bessel_i
@findex bessel_j
@findex bessel_k
@findex bessel_y
@cindex Bessel functions
@deftypefun double bessel_i (double @var{x}, double @var{nu}, double @var{expo})
@deftypefunx double bessel_j (double @var{x}, double @var{nu})
@deftypefunx double bessel_k (double @var{x}, double @var{nu}, double @var{expo})
@deftypefunx double bessel_y (double @var{x}, double @var{nu})
Bessel functions of types I, J, K and Y with index @var{nu}.  For
@code{bessel_i} and @code{bessel_k} there is the option to return
@w{exp(-@var{x}) I(@var{x}; @var{nu})} or @w{exp(@var{x}) K(@var{x};
@var{nu})} if @var{expo} is 2. (Use @code{@var{expo} == 1} for unscaled
values.)
@end deftypefun


@node Numerical Utilities, Mathematical constants, Mathematical functions, Numerical analysis subroutines
@subsection Numerical Utilities
There are a few other numerical utility functions available as entry points.


@deftypefun double R_pow (double @var{x}, double @var{y})
@deftypefunx double R_pow_di (double @var{x}, int @var{i})
@code{R_pow(@var{x}, @var{y})} and @code{R_pow_di(@var{x}, @var{i})}
compute @code{@var{x}^@var{y}} and @code{@var{x}^@var{i}}, respectively
using @code{R_FINITE} checks and returning the proper result (the same
as @R{}) for the cases where @var{x}, @var{y} or @var{i} are 0 or
missing or infinite or @code{NaN}.
@end deftypefun

@deftypefun double pythag (double @var{a}, double @var{b})
@code{pythag(@var{a}, @var{b})} computes @code{sqrt(@var{a}^2 +
@var{b}^2)} without overflow or destructive underflow: for example it
still works when both @var{a} and @var{b} are between @code{1e200} and
@code{1e300} (in @acronym{IEEE} double precision).
@end deftypefun

@deftypefun double log1p (double @var{x})
Computes @code{log(1 + @var{x})} (@emph{log 1 @b{p}lus x}), accurately
even for small @var{x}, i.e., @eqn{|x| \ll 1, |x| << 1}.

This may be provided by your platform, in which case it is not included
in @file{Rmath.h}, but is (probably) in @file{math.h} which
@file{Rmath.h} includes.
@end deftypefun

@deftypefun double log1pmx (double @var{x})
Computes @code{log(1 + @var{x}) - @var{x}} (@emph{log 1 @b{p}lus x @b{m}inus @b{x}}),
accurately even for small @var{x}, i.e., @eqn{|x| \ll 1, |x| << 1}.
@end deftypefun

@deftypefun double expm1 (double @var{x})
Computes @code{exp(@var{x}) - 1} (@emph{exp x @b{m}inus 1}), accurately
even for small @var{x}, i.e., @eqn{|x| \ll 1, |x| << 1}.

This may be provided by your platform, in which case it is not included
in @file{Rmath.h}, but is (probably) in @file{math.h} which
@file{Rmath.h} includes.
@end deftypefun

@deftypefun double lgamma1p (double @var{x})
Computes @code{log(gamma(@var{x} + 1))} (@emph{log(gamma(1 @b{p}lus x))}),
accurately even for small @var{x}, i.e., @eqn{0 < x < 0.5, 0 < x < 0.5}.
@end deftypefun

@deftypefun double logspace_add (double @var{logx}, double @var{logy})
@deftypefunx double logspace_sub (double @var{logx}, double @var{logy})
Compute the log of a sum or difference from logs of terms, i.e.,
``x + y'' as @code{log (exp(@var{logx}) + exp(@var{logy}))} and
``x - y'' as @code{log (exp(@var{logx}) - exp(@var{logy}))},
without causing overflows or throwing away too much accuracy.
@end deftypefun

@deftypefun int imax2 (int @var{x}, int @var{y})
@deftypefunx int imin2 (int @var{x}, int @var{y})
@deftypefunx double fmax2 (double @var{x}, double @var{y})
@deftypefunx double fmin2 (double @var{x}, double @var{y})
Return the larger (@code{max}) or smaller (@code{min}) of two integer or
double numbers, respectively.
@end deftypefun

@deftypefun double sign (double @var{x})
Compute the @emph{signum} function, where sign(@var{x}) is 1, 0, or
@math{-1}, when @var{x} is positive, 0, or negative, respectively.
@end deftypefun

@deftypefun double fsign (double @var{x}, double @var{y})
Performs ``transfer of sign'' and is defined as @eqn{|x| *
\hbox{sign}(y), |x| * sign(y)}.
@end deftypefun

@deftypefun double fprec (double @var{x}, double @var{digits})
Returns the value of @var{x} rounded to @var{digits} decimal digits
(after the decimal point).

This is the function used by @R{}'s @code{round()}.
@end deftypefun

@deftypefun double fround (double @var{x}, double @var{digits})
Returns the value of @var{x} rounded to @var{digits} @emph{significant}
decimal digits.

This is the function used by @R{}'s @code{signif()}.
@end deftypefun

@deftypefun double ftrunc (double @var{x})
Returns the value of @var{x} truncated (to an integer value) towards zero.
@end deftypefun

@node Mathematical constants,  , Numerical Utilities, Numerical analysis subroutines
@subsection Mathematical constants
@findex M_E
@findex M_PI
@c maybe not all into the index ...

@R{} has a set of commonly used mathematical constants encompassing
constants usually found @file{math.h} and contains further ones that are
used in statistical computations.  All these are defined to (at least)
30 digits accuracy in @file{Rmath.h}.  The following definitions
use @code{ln(x)} for the natural logarithm (@code{log(x)} in @R{}).

@quotation
@multitable {Name can be long}  {Definition (needs space)}  {0.123456789012345678 ...}
@headitem Name @tab Definition (@code{ln = log}) @tab round(@emph{value}, 7)
@c SVID & X/Open Constants -- names from Solaris math.h :
@item @code{M_E} @tab @math{e} @tab 2.7182818
@item @code{M_LOG2E} @tab log2(@math{e}) @tab 1.4426950
@item @code{M_LOG10E} @tab log10(@math{e}) @tab 0.4342945
@item @code{M_LN2} @tab ln(2) @tab 0.6931472
@item @code{M_LN10} @tab ln(10) @tab 2.3025851
@item @code{M_PI} @tab @eqn{\pi, pi}   @tab 3.1415927
@item @code{M_PI_2} @tab @eqn{\pi/2, pi/2} @tab 1.5707963
@item @code{M_PI_4} @tab @eqn{\pi/4, pi/4} @tab 0.7853982
@item @code{M_1_PI} @tab @eqn{1/\pi, 1/pi} @tab 0.3183099
@item @code{M_2_PI} @tab @eqn{2/\pi, 2/pi} @tab 0.6366198
@item @code{M_2_SQRTPI} @tab 2/sqrt(@eqn{\pi, pi}) @tab 1.1283792
@item @code{M_SQRT2} @tab sqrt(2) @tab 1.4142136
@item @code{M_SQRT1_2} @tab 1/sqrt(2) @tab 0.7071068
@c R-specific ones
@item @code{M_SQRT_3} @tab sqrt(3) @tab 1.7320508
@item @code{M_SQRT_32} @tab sqrt(32) @tab 5.6568542
@item @code{M_LOG10_2} @tab log10(2) @tab 0.3010300
@item @code{M_2PI} @tab @eqn{2\pi, 2*pi} @tab 6.2831853
@item @code{M_SQRT_PI} @tab sqrt(@eqn{\pi, pi}) @tab 1.7724539
@item @code{M_1_SQRT_2PI} @tab 1/sqrt(@eqn{2\pi, 2*pi}) @tab 0.3989423
@item @code{M_SQRT_2dPI} @tab sqrt(2/@eqn{\pi, pi}) @tab 0.7978846
@item @code{M_LN_SQRT_PI} @tab ln(sqrt(@eqn{\pi, pi})) @tab 0.5723649
@item @code{M_LN_SQRT_2PI} @tab ln(sqrt(@eqn{2\pi, 2*pi})) @tab 0.9189385
@item @code{M_LN_SQRT_PId2} @tab ln(sqrt(@eqn{\pi, pi}/2)) @tab 0.2257914
@end multitable
@end quotation

There are a set of constants (@code{PI}, @code{DOUBLE_EPS}) (and so on)
defined (unless @code{STRICT_R_HEADERS} is defined) in the included
header @file{R_ext/Constants.h}, mainly for compatibility with @Sl{}.

@findex TRUE
@findex FALSE
Further, the included header @file{R_ext/Boolean.h} has constants
@code{TRUE} and @code{FALSE = 0} of type @code{Rboolean} in order to
provide a way of using ``logical'' variables in C consistently.


@node Optimization, Integration, Numerical analysis subroutines, The R API
@section Optimization
@cindex optimization

The C code underlying @code{optim} can be accessed directly.  The user
needs to supply a function to compute the function to be minimized, of
the type

@example
typedef double optimfn(int n, double *par, void *ex);
@end example

@noindent
where the first argument is the number of parameters in the second
argument.  The third argument is a pointer passed down from the calling
routine, normally used to carry auxiliary information.

Some of the methods also require a gradient function

@example
typedef void optimgr(int n, double *par, double *gr, void *ex);
@end example

@noindent
which passes back the gradient in the @code{gr} argument.  No function
is provided for finite-differencing, nor for approximating the Hessian
at the result.

The interfaces (defined in header @file{R_ext/Applic.h}) are

@itemize @bullet
@item Nelder Mead:
@findex nmmin
@example
void nmmin(int n, double *xin, double *x, double *Fmin, optimfn fn,
           int *fail, double abstol, double intol, void *ex,
           double alpha, double beta, double gamma, int trace,
           int *fncount, int maxit);
@end example

@item BFGS:
@findex vmmin
@example
void vmmin(int n, double *x, double *Fmin,
           optimfn fn, optimgr gr, int maxit, int trace,
           int *mask, double abstol, double reltol, int nREPORT,
           void *ex, int *fncount, int *grcount, int *fail);
@end example

@item Conjugate gradients:
@findex cgmin
@example
void cgmin(int n, double *xin, double *x, double *Fmin,
           optimfn fn, optimgr gr, int *fail, double abstol,
           double intol, void *ex, int type, int trace,
           int *fncount, int *grcount, int maxit);
@end example

@item Limited-memory BFGS with bounds:
@findex lbfgsb
@example
void lbfgsb(int n, int lmm, double *x, double *lower,
            double *upper, int *nbd, double *Fmin, optimfn fn,
            optimgr gr, int *fail, void *ex, double factr,
            double pgtol, int *fncount, int *grcount,
            int maxit, char *msg, int trace, int nREPORT);
@end example

@item Simulated annealing:
@findex samin
@example
void samin(int n, double *x, double *Fmin, optimfn fn, int maxit,
           int tmax, double temp, int trace, void *ex);
@end example

@end itemize

@noindent
Many of the arguments are common to the various methods.  @code{n} is
the number of parameters, @code{x} or @code{xin} is the starting
parameters on entry and @code{x} the final parameters on exit, with
final value returned in @code{Fmin}.  Most of the other parameters can
be found from the help page for @code{optim}: see the source code
@file{src/appl/lbfgsb.c} for the values of @code{nbd}, which
specifies which bounds are to be used.


@node Integration, Utility functions, Optimization, The R API
@section Integration
@cindex integration

The C code underlying @code{integrate} can be accessed directly.  The
user needs to supply a @emph{vectorizing} C function to compute the
function to be integrated, of the type

@example
typedef void integr_fn(double *x, int n, void *ex);
@end example

@noindent
where @code{x[]} is both input and output and has length @code{n}, i.e.,
a C function, say @code{fn}, of type @code{integr_fn} must basically do
@code{for(i in 1:n) x[i] := f(x[i], ex)}.  The vectorization requirement
can be used to speed up the integrand instead of calling it @code{n}
times.  Note that in the current implementation built on QUADPACK,
@code{n} will be either 15 or 21.  The @code{ex} argument is a pointer
passed down from the calling routine, normally used to carry auxiliary
information.

There are interfaces (defined in header @file{R_ext/Applic.h}) for
definite and for indefinite integrals.  `Indefinite' means that at least
one of the integration boundaries is not finite.

@itemize @bullet
@item Finite:
@findex Rdqags
@example
void Rdqags(integr_fn f, void *ex, double *a, double *b,
            double *epsabs, double *epsrel,
            double *result, double *abserr, int *neval, int *ier,
            int *limit, int *lenw, int *last,
            int *iwork, double *work);
@end example

@item Indefinite:
@findex Rdqagi
@example
void Rdqagi(integr_fn f, void *ex, double *bound, int *inf,
            double *epsabs, double *epsrel,
            double *result, double *abserr, int *neval, int *ier,
            int *limit, int *lenw, int *last,
            int *iwork, double *work);
@end example

@end itemize

@noindent
Only the 3rd and 4th argument differ for the two integrators; for the
definite integral, using @code{Rdqags}, @code{a} and @code{b} are the
integration interval bounds, whereas for an indefinite integral, using
@code{Rdqagi}, @code{bound} is the finite bound of the integration (if
the integral is not doubly-infinite) and @code{inf} is a code indicating
the kind of integration range,

@table @code
@item inf = 1
      corresponds to (bound, +Inf),
@item inf = -1
      corresponds to (-Inf, bound),
@item inf = 2
      corresponds to (-Inf, +Inf),
@end table

@code{f} and @code{ex} define the integrand function, see above;
@code{epsabs} and @code{epsrel} specify the absolute and relative
accuracy requested, @code{result}, @code{abserr} and @code{last} are the
output components @code{value}, @code{abs.err} and @code{subdivisions}
of the @R{} function integrate, where @code{neval} gives the number of
integrand function evaluations, and the error code @code{ier} is
translated to @R{}'s @code{integrate() $ message}, look at that function
definition.  @code{limit} corresponds to @code{integrate(...,
subdivisions = *)}.  It seems you should always define the two work
arrays and the length of the second one as

@example
    lenw = 4 * limit;
    iwork =   (int *) R_alloc(limit, sizeof(int));
    work = (double *) R_alloc(lenw,  sizeof(double));
@end example

The comments in the source code in @file{src/appl/integrate.c} give
more details, particularly about reasons for failure (@code{ier >= 1}).


@node Utility functions, Re-encoding, Integration, The R API
@section Utility functions
@cindex Sort functions from C

@R{} has a fairly comprehensive set of sort routines which are made
available to users' C code.  These are declared in header file
@file{R_ext/Utils.h} (included by @file{R.h}) and include the following.

@deftypefun void R_isort (int* @var{x}, int @var{n})
@deftypefunx void R_rsort (double* @var{x}, int @var{n})
@deftypefunx void R_csort (Rcomplex* @var{x}, int @var{n})
@deftypefunx void rsort_with_index (double* @var{x}, int* @var{index}, int @var{n})
The first three sort integer, real (double) and complex data
respectively.  (Complex numbers are sorted by the real part first then
the imaginary part.)  @code{NA}s are sorted last.

@code{rsort_with_index} sorts on @var{x}, and applies the same
permutation to @var{index}.  @code{NA}s are sorted last.
@end deftypefun

@deftypefun void revsort (double* @var{x}, int* @var{index}, int @var{n})
Is similar to @code{rsort_with_index} but sorts into decreasing order,
and @code{NA}s are not handled.
@end deftypefun

@deftypefun void iPsort (int* @var{x}, int @var{n}, int @var{k})
@deftypefunx void rPsort (double* @var{x}, int @var{n}, int @var{k})
@deftypefunx void cPsort (Rcomplex* @var{x}, int @var{n}, int @var{k})
These all provide (very) partial sorting: they permute @var{x} so that
@code{@var{x}[@var{k}]} is in the correct place with smaller values to
the left, larger ones to the right.
@end deftypefun

@deftypefun  void R_qsort   (double *@var{v}, int @var{i}, int @var{j})
@deftypefunx void R_qsort_I (double *@var{v}, int *@var{I}, int @var{i}, int @var{j})
@deftypefunx void R_qsort_int   (int *@var{iv}, int @var{i}, int @var{j})
@deftypefunx void R_qsort_int_I (int *@var{iv}, int *@var{I}, int @var{i}, int @var{j})


These routines sort @code{@var{v}[@var{i}:@var{j}]} or
@code{@var{iv}[@var{i}:@var{j}]} (using 1-indexing, i.e.,
@code{@var{v}[1]} is the first element) calling the quicksort algorithm
as used by @R{}'s @code{sort(v, method = "quick")} and documented on the
help page for the @R{} function @code{sort}.  The @code{..._I()}
versions also return the @code{sort.index()} vector in @code{I}.  Note
that the ordering is @emph{not} stable, so tied values may be permuted.

Note that @code{NA}s are not handled (explicitly) and you should
use different sorting functions if @code{NA}s can be present.
@end deftypefun

@deftypefun subroutine qsort4 (double precision @var{v}, integer @var{indx}, integer @var{ii}, integer @var{jj})
@deftypefunx subroutine qsort3 (double precision @var{v}, integer @var{ii}, integer @var{jj})

The FORTRAN interface routines for sorting double precision vectors are
@code{qsort3} and @code{qsort4}, equivalent to @code{R_qsort} and
@code{R_qsort_I}, respectively.
@end deftypefun

@deftypefun void R_max_col (double* @var{matrix}, int* @var{nr}, int* @var{nc}, int* @var{maxes}, int* @var{ties_meth})
Given the @var{nr} by @var{nc} matrix @code{matrix} in column-major
(``FORTRAN'')
order, @code{R_max_col()} returns in @code{@var{maxes}[@var{i}-1]} the
column number of the maximal element in the @var{i}-th row (the same as
@R{}'s @code{max.col()} function).  In the case of ties (multiple maxima),
@code{*ties_meth} is an integer code in @code{1:3} determining the method:
1 = ``random'', 2 = ``first'' and 3 = ``last''.
See @R{}'s help page @code{?max.col}.
@end deftypefun

@deftypefun int findInterval (double* @var{xt}, int @var{n}, double @var{x}, Rboolean @var{rightmost_closed}, Rboolean @var{all_inside}, int @var{ilo}, int* @var{mflag})
Given the ordered vector @var{xt} of length @var{n}, return the interval
or index of @var{x} in @code{@var{xt}[]}, typically max(@math{i}; @eqn{1
\le i \le @var{n}, 1 <= i <= @var{n}} & @math{@var{xt}[i]} @eqn{\le, <=}
@var{x}) where we use 1-indexing as in @R{} and FORTRAN (but not C).  If
@var{rightmost_closed} is true, also returns @math{@var{n}-1} if @var{x}
equals @math{@var{xt}[@var{n}]}.  If @var{all_inside} is not 0, the
result is coerced to lie in @code{1:(@var{n}-1)} even when @var{x} is
outside the @var{xt}[] range.  On return, @code{*@var{mflag}} equals
@math{-1} if @var{x} < @var{xt}[1], @math{+1} if @var{x} >=
@var{xt}[@var{n}], and 0 otherwise.

The algorithm is particularly fast when @var{ilo} is set to the last
result of @code{findInterval()} and @var{x} is a value of a sequence which
is increasing or decreasing for subsequent calls.

There is also an @code{F77_CALL(interv)()} version of
@code{findInterval()} with the same arguments, but all pointers.
@end deftypefun

The following two functions do @emph{numerical} colorspace conversion from
HSV to RGB and back.  Note that all colours must be in [0,1].

@deftypefun void hsv2rgb (double @var{h}, double @var{s}, double @var{v}, double *@var{r}, double *@var{g}, double *@var{b})
@end deftypefun

@deftypefun void rgb2hsv (double @var{r}, double @var{g}, double @var{b}, double *@var{h}, double *@var{s}, double *@var{v})
@end deftypefun

A system-independent interface to produce the name of a temporary
file is provided as

@deftypefun {char *} R_tmpnam (const char *@var{prefix})
Return a pathname for a temporary file with name beginning with
@var{prefix}.  A @code{NULL} prefix is replaced by @code{""}.
@end deftypefun

@c ----

There is also the internal function used to expand file names in several
@R{} functions, and called directly by @code{path.expand}.

@deftypefun {const char *} R_ExpandFileName (const char *@var{fn})
Expand a path name @var{fn} by replacing a leading tilde by the user's
home directory (if defined).  The precise meaning is platform-specific;
it will usually be taken from the environment variable @env{HOME} if
this is defined.
@end deftypefun

@node Re-encoding, Allowing interrupts, Utility functions, The R API
@section Re-encoding

@R{} has its own C-level interface to the encoding conversion
capabilities provided by @code{iconv} because there are
incompatibilities between the declarations in different implementations
of @code{iconv}.

These are declared in header file @file{R_ext/Riconv.h}.

@deftypefun void *Riconv_open (const char *@var{to}, const char *@var{from})
@end deftypefun
Set up a pointer to an encoding object to be used to convert between two
encodings: @code{""} indicates the current locale.

@deftypefun size_t Riconv (void *@var{cd}, const char **@var{inbuf}, size_t *@var{inbytesleft}, char  **@var{outbuf}, size_t *@var{outbytesleft})
@end deftypefun
Convert as much as possible of @code{inbuf} to @code{outbuf}.  Initially
the @code{int} variables indicate the number of bytes available in the
buffers, and they are updated (and the @code{char} pointers are updated
to point to the next free byte in the buffer).  The return value is the
number of characters converted, or @code{(size_t)-1} (beware:
@code{size_t} is usually an unsigned type).  It should be safe to assume
that an error condition sets @code{errno} to one of @code{E2BIG} (the
output buffer is full), @code{EILSEQ} (the input cannot be converted,
and might be invalid in the encoding specified) or @code{EINVAL} (the
input does not end with a complete multi-byte character).

@deftypefun int Riconv_close (void * @var{cd})
@end deftypefun
Free the resources of an encoding object.


@node Allowing interrupts, Platform and version information, Re-encoding, The R API
@section Allowing interrupts
@cindex Interrupts

No port of @R{} can be interrupted whilst running long computations in
compiled code, so programmers should make provision for the code to be
interrupted at suitable points by calling from C

@example
#include <R_ext/Utils.h>

void R_CheckUserInterrupt(void);
@end example

@noindent
and from FORTRAN

@example
subroutine rchkusr()
@end example

These check if the user has requested an interrupt, and if so branch to
@R{}'s error handling functions.

Note that it is possible that the code behind one of the entry points
defined here if called from your C or FORTRAN code could be interruptible
or generate an error and so not return to your code.


@node Platform and version information, Inlining C functions, Allowing interrupts, The R API
@section Platform and version information
@cindex Version information from C
@findex R_Version

The header files define @code{USING_R}, which can be used to test if
the code is indeed being used with @R{}.

Header file @file{Rconfig.h} (included by @file{R.h}) is used to define
platform-specific macros that are mainly for use in other header files.
The macro @code{WORDS_BIGENDIAN} is defined on big-endian systems
(e.g.@: @code{sparc-sun-solaris2.6}) and not on little-endian systems
(such as @code{i686} under Linux or Windows). It can be useful when
manipulating binary files.

Header file @file{Rversion.h} (@strong{not} included by @file{R.h})
defines a macro @code{R_VERSION} giving the version number encoded as an
integer, plus a macro @code{R_Version} to do the encoding.  This can be
used to test if the version of @R{} is late enough, or to include
back-compatibility features.  For protection against very old versions
of @R{} which did not have this macro, use a construction such as

@example
@group
#if defined(R_VERSION) && R_VERSION >= R_Version(1, 9, 0)
  ...
#endif
@end group
@end example

More detailed information is available in the macros @code{R_MAJOR},
@code{R_MINOR}, @code{R_YEAR}, @code{R_MONTH} and @code{R_DAY}: see the
header file @file{Rversion.h} for their format.  Note that the minor
version includes the patchlevel (as in @samp{9.0}).

@node Inlining C functions, Controlling visibility, Platform and version information, The R API
@section Inlining C functions
@findex R_INLINE

The C99 keyword @code{inline} is recognized by most compilers used to
build @R{} (all since @R{} 2.12.0) whereas others need @code{__inline__}
or do not support inlining.  Portable code can be written using the
macro @code{R_INLINE} (defined in file @file{Rconfig.h} included by
@file{R.h}), as for example from package @pkg{cluster}

@example
#include <R.h>

static R_INLINE int ind_2(int l, int j)
@{
...
@}
@end example

Be aware that using inlining with functions in more than one compilation
unit is almost impossible to do portably, see
@uref{http://www.greenend.org.uk/rjk/2003/03/inline.html}, so this usage
is for @code{static} functions as in the example.  All the @R{}
configure code has checked is that @code{R_INLINE} can be used in a
single C file with the compiler used to build @R{}.  We recommend that
packages making extensive use of inlining include their own configure
code.

@node Controlling visibility, Standalone Mathlib, Inlining C functions, The R API
@section Controlling visibility
@cindex Visibility

Header @file{R_ext/Visibility} has some definitions for controlling the
visibility of entry points.  These are only effective when
@samp{HAVE_VISIBILITY_ATTRIBUTE} is defined -- this is checked when @R{}
is configured and recorded in header @file{Rconfig.h} (included by
@file{R_ext/Visibility.h}).  It is generally defined on modern
Unix-alikes with a recent compiler (e.g.@: @code{gcc4}), but not
supported on Windows.  Minimizing the visibility of symbols in a shared
library will both speed up its loading (unlikely to be significant) and
reduce the possibility of linking to the wrong entry points of the same
name.

C/C++ entry points prefixed by @code{attribute_hidden} will not be
visible in the shared object.  There is no comparable mechanism for
FORTRAN entry points, but there is a more comprehensive scheme used by,
for example package @pkg{stats}.  Most compilers which allow control of
visibility will allow control of visibility for all symbols @emph{via} a flag,
and where known the flag is encapsulated in the macros
@samp{C_VISIBILITY} and @code{F77_VISIBILITY} for C and FORTRAN
compilers.  These are defined in @file{etc/Makeconf} and so available
for normal compilation of package code.  For example,
@file{src/Makevars} could include

@example
PKG_CFLAGS=$(C_VISIBILITY)
PKG_FFLAGS=$(F77_VISIBILITY)
@end example

This would end up with @strong{no} visible entry points, which would be
pointless.  However, the effect of the flags can be overridden by using
the @code{attribute_visible} prefix.  A shared object which registers
its entry points needs only for have one visible entry point, its
initializer, so for example package @pkg{stats} has

@example
void attribute_visible R_init_stats(DllInfo *dll)
@{
    R_registerRoutines(dll, CEntries, CallEntries, FortEntries, NULL);
    R_useDynamicSymbols(dll, FALSE);
...
@}
@end example

The visibility mechanism is not available on Windows, but there is an
equally effective way to control which entry points are visible, by
supplying a definitions file
@file{@var{pkgnme}/src/@var{pkgname}-win.def}: only entry points
listed in that file will be visible.  Again using @pkg{stats} as an
example, it has

@example
LIBRARY stats.dll
EXPORTS
 R_init_stats
@end example

@node Standalone Mathlib, Organization of header files, Controlling visibility, The R API
@section Using these functions in your own C code

It is possible to build @code{Mathlib}, the @R{} set of mathematical
functions documented in @file{Rmath.h}, as a standalone library
@file{libRmath} under both Unix-alikes and Windows.  (This includes the
functions documented in @ref{Numerical analysis subroutines} as from
that header file.)

The library is not built automatically when @R{} is installed, but can
be built in the directory @file{src/nmath/standalone} in the @R{}
sources: see the file @file{README} there.  To use the code in your own
C program include

@example
@group
#define MATHLIB_STANDALONE
#include <Rmath.h>
@end group
@end example

@noindent
and link against @samp{-lRmath} (and perhaps @samp{-lm}.  There is an
example file @file{test.c}.

A little care is needed to use the random-number routines. You will
need to supply the uniform random number generator

@example
double unif_rand(void)
@end example

@noindent
or use the one supplied (and with a dynamic library or DLL you will have
to use the one supplied, which is the Marsaglia-multicarry with an entry
points

@example
set_seed(unsigned int, unsigned int)
@end example

@noindent
to set its seeds and

@example
get_seed(unsigned int *, unsigned int *)
@end example

@noindent
to read the seeds).

@node Organization of header files,  , Standalone Mathlib, The R API
@section Organization of header files

The header files which @R{} installs are in directory
@file{@var{R_INCLUDE_DIR}} (default @file{@var{R_HOME}/include}).  This
currently includes

@quotation
@multitable @columnfractions 0.30 0.55
@item @file{R.h} @tab includes many other files
@item @file{S.h} @tab different version for code ported from @Sl{}
@item @file{Rinternals.h} @tab definitions for using @R{}'s internal
structures
@item @file{Rdefines.h} @tab macros for an @Sl{}-like interface to the
above
@item @file{Rmath.h} @tab standalone math library
@item @file{Rversion.h} @tab @R{} version information
@item @file{Rinterface.h} @tab for add-on front-ends (Unix-alikes only)
@item @file{Rembedded.h} @tab for add-on front-ends
@item @file{R_ext/Applic.h} @tab optimization and integration
@item @file{R_ext/BLAS.h} @tab C definitions for BLAS routines
@item @file{R_ext/Callbacks.h} @tab C (and R function) top-level task
handlers
@item @file{R_ext/GetX11Image.h} @tab X11Image interface used by package
@pkg{trkplot}
@item @file{R_ext/Lapack.h} @tab C definitions for some LAPACK routines
@item @file{R_ext/Linpack.h} @tab C definitions for some LINPACK
routines, not all of which are included in @R{}
@item @file{R_ext/Parse.h} @tab a small part of @R{}'s parse interface
@item @file{R_ext/RConvertors.h}
@item @file{R_ext/Rdynload.h} @tab needed to register compiled code in
packages
@item @file{R_ext/R-ftp-http.h} @tab interface to internal method of
@code{download.file}
@item @file{R_ext/Riconv.h} @tab interface to @code{iconv}
@item @file{R_ext/RStartup.h} @tab for add-on front-ends
@item @file{R_ext/Visibility.h} @tab definitions controlling visibility
@item @file{R_ext/eventloop.h} @tab for add-on front-ends and for
packages that need to share in the @R{} event loops (on all platforms)
@end multitable
@end quotation

The following headers are included by @file{R.h}:

@quotation
@multitable @columnfractions 0.30 0.55
@item @file{Rconfig.h} @tab configuration info that is made available
@item @file{R_ext/Arith.h} @tab handling for @code{NA}s, @code{NaN}s,
@code{Inf}/@code{-Inf}
@item @file{R_ext/Boolean.h} @tab @code{TRUE}/@code{FALSE} type
@item @file{R_ext/Complex.h} @tab C typedefs for @R{}'s @code{complex}
@item @file{R_ext/Constants.h} @tab constants
@item @file{R_ext/Error.h} @tab error handling
@item @file{R_ext/Memory.h} @tab memory allocation
@item @file{R_ext/Print.h} @tab @code{Rprintf} and variations.
@item @file{R_ext/Random.h} @tab random number generation
@item @file{R_ext/RS.h} @tab definitions common to @file{R.h} and
@file{S.h}, including @code{F77_CALL} etc.
@item @file{R_ext/Utils.h} @tab sorting and other utilities
@item @file{R_ext/libextern.h} @tab definitions for exports from
@file{R.dll} on Windows.
@end multitable
@end quotation

The graphics systems are exposed in headers
@file{R_ext/GraphicsEngine.h}, @file{R_ext/GraphicsDevice.h} (which it
includes) and @file{R_ext/QuartzDevice.h}.  Some entry points from the
@pkg{stats} package are in @file{R_ext/stats_package.h} (currently
related to the internals of @code{nls} and @code{nlminb}).


@node Generic functions and methods, Linking GUIs and other front-ends to R, The R API, Top
@chapter Generic functions and methods
@cindex Generic functions
@cindex Method functions

@R{} programmers will often want to add methods for existing generic
functions, and may want to add new generic functions or make existing
functions generic.  In this chapter we give guidelines for doing so,
with examples of the problems caused by not adhering to them.

This chapter only covers the `informal' class system copied from S3,
and not with the S4 (formal) methods of package @pkg{methods}.

The key function for methods is @code{NextMethod}, which dispatches the
next method.  It is quite typical for a method function to make a few
changes to its arguments, dispatch to the next method, receive the
results and modify them a little.  An example is

@example
@group
t.data.frame <- function(x)
@{
    x <- as.matrix(x)
    NextMethod("t")
@}
@end group
@end example

@noindent
Also consider @code{predict.glm}: it happens that in @R{} for historical
reasons it calls @code{predict.lm} directly, but in principle (and in S
originally and currently) it could use @code{NextMethod}.
(@code{NextMethod} seems under-used in the @R{} sources.  Do be aware
that there are S/R differences in this area, and the example above works
because there is a @emph{next} method, the default method, not that a
new method is selected when the class is changed.)

@emph{Any} method a programmer writes may be invoked from another method
by @code{NextMethod}, @emph{with the arguments appropriate to the
previous method}.  Further, the programmer cannot predict which method
@code{NextMethod} will pick (it might be one not yet dreamt of), and the
end user calling the generic needs to be able to pass arguments to the
next method.  For this to work

@quotation
@emph{A method must have all the arguments of the generic, including
@code{@dots{}} if the generic does.}
@end quotation

It is a grave misunderstanding to think that a method needs only to
accept the arguments it needs.  The original S version of
@code{predict.lm} did not have a @code{@dots{}} argument, although
@code{predict} did.  It soon became clear that @code{predict.glm} needed
an argument @code{dispersion} to handle over-dispersion.  As
@code{predict.lm} had neither a @code{dispersion} nor a @code{@dots{}}
argument, @code{NextMethod} could no longer be used.  (The legacy, two
direct calls to @code{predict.lm}, lives on in @code{predict.glm} in
@R{}, which is based on the workaround for S3 written by Venables &
Ripley.)

Further, the user is entitled to use positional matching when calling
the generic, and the arguments to a method called by @code{UseMethod}
are those of the call to the generic.  Thus

@quotation
@emph{A method must have arguments in exactly the same order as the
generic.}
@end quotation

@noindent
To see the scale of this problem, consider the generic function
@code{scale}, defined as

@example
@group
scale <- function (x, center = TRUE, scale = TRUE)
    UseMethod("scale")
@end group
@end example

@noindent
Suppose an unthinking package writer created methods such as

@example
scale.foo <- function(x, scale = FALSE, ...) @{ @}
@end example

@noindent
Then for @code{x} of class @code{"foo"} the calls

@example
@group
scale(x, , TRUE)
scale(x, scale = TRUE)
@end group
@end example

@noindent
would do most likely do different things, to the justifiable
consternation of the end user.

To add a further twist, which default is used when a user calls
@code{scale(x)} in our example?  What if

@example
scale.bar <- function(x, center, scale = TRUE) NextMethod("scale")
@end example

@noindent
and @code{x} has class @code{c("bar", "foo")}?  It is the default
specified in the method that is used, but the default
specified in the generic may be the one the user sees.
This leads to the recommendation:

@quotation
@emph{If the generic specifies defaults, all methods should use the same defaults.}
@end quotation

@noindent
An easy way to follow these recommendations is to always keep generics
simple, e.g.

@example
scale <- function(x, ...) UseMethod("scale")
@end example

Only add parameters and defaults to the generic if they make sense in
all possible methods implementing it.

@menu
* Adding new generics::
@end menu

@node Adding new generics,  , Generic functions and methods, Generic functions and methods
@section Adding new generics

When creating a new generic function, bear in mind that its argument
list will be the maximal set of arguments for methods, including those
written elsewhere years later.  So choosing a good set of arguments may
well be an important design issue, and there need to be good arguments
@emph{not} to include a @code{@dots{}} argument.

If a @code{@dots{}} argument is supplied, some thought should be given
to its position in the argument sequence.  Arguments which follow
@code{@dots{}} must be named in calls to the function, and they must be
named in full (partial matching is suppressed after @code{@dots{}}).
Formal arguments before @code{@dots{}} can be partially matched, and so
may `swallow' actual arguments intended for @code{@dots{}}.  Although it
is commonplace to make the @code{@dots{}} argument the last one, that is
not always the right choice.

Sometimes package writers want to make generic a function in the base
package, and request a change in @R{}.  This may be justifiable, but
making a function generic with the old definition as the default method
does have a small performance cost.  It is never necessary, as a package
can take over a function in the base package and make it generic by

@example
@group
foo <- function(object, ...) UseMethod("foo")
foo.default <- base::foo
@end group
@end example

@noindent
(If the thus defined default method needs a @samp{...} added to its
argument list, one can e.g.@: use @code{formals(foo.default) <-
c(formals(foo.default), alist(... = ))}.)

The same idea can be applied for functions in other packages with name spaces.

@node Linking GUIs and other front-ends to R, Function and variable index, Generic functions and methods, Top
@chapter Linking GUIs and other front-ends to R

There are a number of ways to build front-ends to @R{}: we take this to
mean a GUI or other application that has the ability to submit commands
to @R{} and perhaps to receive results back (not necessarily in a text
format).  There are other routes besides those described here, for
example the package @pkg{Rserve} (from @acronym{CRAN}, see also
@uref{http://www.rforge.net/Rserve/}) and connections to Java in
@samp{SJava} (see @uref{http://www.omegahat.org/RSJava/} and @samp{JRI},
part of the @pkg{rJava} package on @acronym{CRAN}).

@menu
* Embedding R under Unix-alikes::
* Embedding R under Windows::
@end menu

@node Embedding R under Unix-alikes, Embedding R under Windows, Linking GUIs and other front-ends to R, Linking GUIs and other front-ends to R
@section Embedding R under Unix-alikes

@R{} can be built as a shared library@footnote{In the parlance of Mac OS
X this is a @emph{dynamic} library, and is the normal way to build @R{}
on that platform.} if configured with @option{--enable-R-shlib}.  This
shared library can be used to run @R{} from alternative front-end
programs.  We will assume this has been done for the rest of this
section.  Also, it can be built as a static library if configured with
@option{--enable-R-static-lib}, and this can be used in a very similar
way.

The command-line @R{} front-end, @file{@var{R_HOME}/bin/exec/R} is one
such example, and the former @acronym{GNOME} (see package @pkg{gnomeGUI}
on @acronym{CRAN}'s @samp{Archive} area) and Mac OS X consoles are
others.  The source for @file{@var{R_HOME}/bin/exec/R} is in file
@file{src/main/Rmain.c} and is very simple

@example
int Rf_initialize_R(int ac, char **av); /* in ../unix/system.c */
void Rf_mainloop();                     /* in main.c */

extern int R_running_as_main_program;   /* in ../unix/system.c */

int main(int ac, char **av)
@{
    R_running_as_main_program = 1;
    Rf_initialize_R(ac, av);
    Rf_mainloop(); /* does not return */
    return 0;
@}
@end example

@noindent
indeed, misleadingly simple.  Remember that
@file{@var{R_HOME}/bin/exec/R} is run from a shell script
@file{@var{R_HOME}/bin/R} which sets up the environment for the
executable, and this is used for

@itemize @bullet
@item
Setting @env{R_HOME} and checking it is valid, as well as the path
@env{R_SHARE_DIR} and @env{R_DOC_DIR} to the installed @file{share} and
@file{doc} directory trees.  Also setting @env{R_ARCH} if needed.

@item
Setting @env{LD_LIBRARY_PATH} to include the directories used in linking
@R{}.  This is recorded as the default setting of
@env{R_LD_LIBRARY_PATH} in the shell script
@file{@var{R_HOME}/etc@var{R_ARCH}/ldpaths}.

@item
Processing some of the arguments, for example to run @R{} under a
debugger and to launch alternative front-ends to provide GUIs.
@end itemize

@noindent
The first two of these can be achieved for your front-end by running it
@emph{via} @command{R CMD}. So, for example

@example
R CMD /usr/local/lib/R/bin/exec/R
R CMD exec/R
@end example

@noindent
will both work in a standard @R{} installation. (@command{R CMD} looks
first for executables in @file{@var{R_HOME}/bin}.)  If you do not want
to run your front-end in this way, you need to ensure that @env{R_HOME}
is set and @env{LD_LIBRARY_PATH} is suitable.  (The latter might well
be, but modern Unix/Linux systems do not normally include
@file{/usr/local/lib} (@file{/usr/local/lib64} on some architectures),
and @R{} does look there for system components.)

The other senses in which this example is too simple are that all the
internal defaults are used and that control is handed over to the
@R{} main loop.  There are a number of small examples@footnote{but these
are not part of the automated test procedures and so little tested.} in the
@file{tests/Embedding} directory.  These make use of
@code{Rf_initEmbeddedR} in @file{src/main/Rembedded.c}, and essentially
use
@example
#include <Rembedded.h>

int main(int ac, char **av)
@{
    /* do some setup */
    Rf_initEmbeddedR(argc, argv);
    /* do some more setup */

    /* submit some code to R, which is done interactively via
        run_Rmainloop();

        A possible substitute for a pseudo-console is

        R_ReplDLLinit();
        while(R_ReplDLLdo1() > 0) @{
        /* add user actions here if desired */
       @}

     */
    Rf_endEmbeddedR(0);
    /* final tidying up after R is shutdown */
    return 0;
@}
@end example

@noindent
If you don't want to pass @R{} arguments, you can fake an @code{argv}
array, for example by

@example
    char *argv[]= @{"REmbeddedPostgres", "--silent"@};
    Rf_initEmbeddedR(sizeof(argv)/sizeof(argv[0]), argv);
@end example

However, to make a GUI we usually do want to run @code{run_Rmainloop}
after setting up various parts of @R{} to talk to our GUI, and arranging
for our GUI callbacks to be called during the @R{} mainloop.

One issue to watch is that on some platforms @code{Rf_initEmbeddedR} and
@code{Rf_endEmbeddedR} change the settings of the FPU (e.g.@: to allow
errors to be trapped and to set extended precision registers).

The standard code sets up a session temporary directory in the usual
way, @emph{unless} @code{R_TempDir} is set to a non-NULL value before
@code{Rf_initEmbeddedR} is called.  In that case the value is assumed to
contain an existing writable directory (no check is done), and it is not
cleaned up when @R{} is shut down.

@code{Rf_initEmbeddedR} sets @R{} to be in interactive mode: you can set
@code{R_Interactive} (defined in @file{Rinterface.h}) subsequently to
change this.

Note that @R{} expects to be run with the locale category
@samp{LC_NUMERIC} set to its default value of @code{C}, and so should
not be embedded into an application which changes that.

@menu
* Compiling against the R library::
* Setting R callbacks::
* Registering symbols::
* Meshing event loops::
* Threading issues::
@end menu

@node Compiling against the R library, Setting R callbacks, Embedding R under Unix-alikes, Embedding R under Unix-alikes
@subsection Compiling against the R library

Suitable flags to compile and link against the @R{} (shared or static)
library can be found by

@example
R CMD config --cppflags
R CMD config --ldflags
@end example

If @R{} is installed, @code{pkg-config} is available and
sub-architectures have not been used, alternatives for a shared @R{}
library are

@example
pkg-config --cflags libR
pkg-config --libs libR
@end example

@noindent
and for a static @R{} library

@example
pkg-config --cflags libR
pkg-config --libs --static libR
@end example

@node Setting R callbacks, Registering symbols, Compiling against the R library, Embedding R under Unix-alikes
@subsection Setting R callbacks

For Unix-alikes there is a public header file @file{Rinterface.h} that
makes it possible to change the standard callbacks used by @R{} in a
documented way.  This defines pointers (if @code{R_INTERFACE_PTRS} is
defined)

@example
extern void (*ptr_R_Suicide)(const char *);
extern void (*ptr_R_ShowMessage)(const char *);
extern int  (*ptr_R_ReadConsole)(const char *, unsigned char *, int, int);
extern void (*ptr_R_WriteConsole)(const char *, int);
extern void (*ptr_R_WriteConsoleEx)(const char *, int, int);
extern void (*ptr_R_ResetConsole)();
extern void (*ptr_R_FlushConsole)();
extern void (*ptr_R_ClearerrConsole)();
extern void (*ptr_R_Busy)(int);
extern void (*ptr_R_CleanUp)(SA_TYPE, int, int);
extern int  (*ptr_R_ShowFiles)(int, const char **, const char **,
                               const char *, Rboolean, const char *);
extern int  (*ptr_R_ChooseFile)(int, char *, int);
extern int  (*ptr_R_EditFile)(const char *);
extern void (*ptr_R_loadhistory)(SEXP, SEXP, SEXP, SEXP);
extern void (*ptr_R_savehistory)(SEXP, SEXP, SEXP, SEXP);
extern void (*ptr_R_addhistory)(SEXP, SEXP, SEXP, SEXP);
@end example

@noindent
which allow standard @R{} callbacks to be redirected to your GUI.  What
these do is generally documented in the file @file{src/unix/system.txt}.

@deftypefun void R_ShowMessage (char *@var{message})
This should display the message, which may have multiple lines:  it
should be brought to the user's attention immediately.
@end deftypefun

@deftypefun void R_Busy (int @var{which})
This function invokes actions (such as change of cursor) when @R{}
embarks on an extended computation (@code{@var{which}=1}) and when such
a state terminates (@code{@var{which}=0}).
@end deftypefun

@deftypefun int R_ReadConsole (const char *@var{prompt}, unsigned char *@var{buf}, @
  int @var{buflen}, int @var{hist})
@deftypefunx void R_WriteConsole (const char *@var{buf}, int @var{buflen})
@deftypefunx void R_WriteConsoleEx (const char *@var{buf}, int @var{buflen}, int @var{otype})
@deftypefunx void R_ResetConsole ()
@deftypefunx void R_FlushConsole ()
@deftypefunx void R_ClearErrConsole ()

These functions interact with a console.

@code{R_ReadConsole} prints the given prompt at the console and then
does a @code{gets(3)}--like operation, transferring up to @var{buflen}
characters into the buffer @var{buf}. The last two bytes should be
set to @samp{"\n\0"} to preserve sanity.  If @var{hist} is non-zero,
then the line should be added to any command history which is being
maintained.  The return value is 0 is no input is available and >0
otherwise.

@code{R_WriteConsoleEx} writes the given buffer to the console,
@var{otype} specifies the output type (regular output or
warning/error). Call to @code{R_WriteConsole(buf, buflen)} is equivalent
to @code{R_WriteConsoleEx(buf, buflen, 0)}. To ensure backward
compatibility of the callbacks, @code{ptr_R_WriteConsoleEx} is used only
if @code{ptr_R_WriteConsole} is set to @code{NULL}.  To ensure that
@code{stdout()} and @code{stderr()} connections point to the console,
set the corresponding files to @code{NULL} @emph{via}
@example
      R_Outputfile = NULL;
      R_Consolefile = NULL;
@end example

@code{R_ResetConsole} is called when the system is reset after an error.
@code{R_FlushConsole} is called to flush any pending output to the
system console.  @code{R_ClearerrConsole} clears any errors associated
with reading from the console.
@end deftypefun

@deftypefun int R_ShowFiles (int @var{nfile}, const char **@var{file}, @
  const char **@var{headers}, const char *@var{wtitle}, Rboolean @var{del}, @
  const char *@var{pager})

This function is used to display the contents of files.
@end deftypefun

@deftypefun int R_ChooseFile (int @var{new}, char *@var{buf}, @
  int @var{len})

Choose a file and return its name in @var{buf} of length @var{len}.
Return value is 0 for success, > 0 otherwise.
@end deftypefun

@deftypefun int R_EditFile (const char *@var{buf})
Send a file to an editor window.
@end deftypefun

@deftypefun SEXP R_loadhistory (SEXP, SEXP, SEXP, SEXP);
@deftypefunx SEXP R_savehistory (SEXP, SEXP, SEXP, SEXP);
@deftypefunx SEXP R_addhistory (SEXP, SEXP, SEXP, SEXP);

@code{.Internal} functions for @code{loadhistory}, @code{savehistory}
and @code{timestamp}: these are called after checking the number of
arguments.

If the console has no history mechanism these can be as
simple as

@example
SEXP R_loadhistory (SEXP call, SEXP op, SEXP args, SEXP env)
@{
    errorcall(call, "loadhistory is not implemented");
    return R_NilValue;
@}
SEXP R_savehistory (SEXP call, SEXP op , SEXP args, SEXP env)
@{
    errorcall(call, "savehistory is not implemented");
    return R_NilValue;
@}
SEXP R_addhistory (SEXP call, SEXP op , SEXP args, SEXP env)
@{
    return R_NilValue;
@}
@end example

The @code{R_addhistory} function should return silently if no history
mechanism is present, as a user may be calling @code{timestamp} purely
to write the time stamp to the console.
@end deftypefun

@deftypefun void R_Suicide (const char *@var{message})
This should abort @R{} as rapidly as possible, displaying the message.
A possible implementation is

@example
void R_Suicide (const char *message)
@{
    char  pp[1024];
    snprintf(pp, 1024, "Fatal error: %s\n", s);
    R_ShowMessage(pp);
    R_CleanUp(SA_SUICIDE, 2, 0);
@}
@end example
@end deftypefun

@deftypefun void R_CleanUp (SA_TYPE @var{saveact}, int @var{status}, @
  int @var{RunLast})

This function invokes any actions which occur at system termination.
It needs to be quite complex:

@example
#include <Rinterface.h>
#include <Rembedded.h>    /* for Rf_KillAllDevices */

void R_CleanUp (SA_TYPE saveact, int status, int RunLast)
@{
    if(saveact == SA_DEFAULT) saveact = SaveAction;
    if(saveact == SA_SAVEASK) @{
       /* ask what to do and set saveact */
    @}
    switch (saveact) @{
    case SA_SAVE:
        if(runLast) R_dot_Last();
        if(R_DirtyImage) R_SaveGlobalEnv();
        /* save the console history in R_HistoryFile */
        break;
    case SA_NOSAVE:
        if(runLast) R_dot_Last();
        break;
    case SA_SUICIDE:
    default:
        break;
    @}

    R_RunExitFinalizers();
    /* clean up after the editor e.g. CleanEd() */

    R_CleanTempDir();

    /* close all the graphics devices */
    if(saveact != SA_SUICIDE) Rf_KillAllDevices();
    fpu_setup(FALSE);

    exit(status);
@}
@end example
@end deftypefun

@node Registering symbols, Meshing event loops, Setting R callbacks, Embedding R under Unix-alikes
@subsection Registering symbols

An application embedding @R{} needs a different way of registering
symbols because it is not a dynamic library loaded by @R{} as would be
the case with a package.  Therefore @R{} reserves a special
@code{DllInfo} entry for the embedding application such that it can
register symbols to be used with @code{.C}, @code{.Call} etc.  This
entry can be obtained by calling @code{getEmbeddingDllInfo}, so a
typical use is

@example
DllInfo *info = R_getEmbeddingDllInfo();
R_registerRoutines(info, cMethods, callMethods, NULL, NULL);
@end example

The native routines defined by @code{cMethod} and @code{callMethods}
should be present in the embedding application.  See @ref{Registering
native routines} for details on registering symbols in general.


@node Meshing event loops, Threading issues, Registering symbols, Embedding R under Unix-alikes
@subsection Meshing event loops

One of the most difficult issues in interfacing @R{} to a front-end is
the handling of event loops, at least if a single thread is used.  @R{}
uses events and timers for

@itemize
@item
Running X11 windows such as the graphics device and data editor, and
interacting with them (e.g., using @code{locator()}).

@item
Supporting Tcl/Tk events for the @pkg{tcltk} package (for at least the
X11 version of Tk).

@item
Preparing input.

@item
Timing operations, for example for profiling @R{} code and
@code{Sys.sleep()}.

@item
Interrupts, where permitted.
@end itemize

@noindent
Specifically, the Unix-alike command-line version of @R{} runs separate
event loops for

@itemize
@item
Preparing input at the console command-line, in file
@file{src/unix/sys-unix.c}.

@item
Waiting for a response from a socket in the internal functions
underlying FTP and HTTP transfers in @code{download.file()} and for
direct socket access, in files
@file{src/@/modules/@/internet/@/nanoftp.c},
@file{src/@/modules/@/internet/@/nanohttp.c} and
@file{src/@/modules/@/internet/@/Rsock.c}

@item
Mouse and window events when displaying the X11-based dataentry window,
in file @file{src/modules/X11/dataentry.c}.  This is regarded as
@emph{modal}, and no other events are serviced whilst it is active.
@end itemize

There is a protocol for adding event handlers to the first two types of
event loops, using types and functions declared in the header
@file{R_ext/eventloop.h} and described in comments in file
@file{src/unix/sys-std.c}.  It is possible to add (or remove) an input
handler for events on a particular file descriptor, or to set a polling
interval (@emph{via} @code{R_wait_usec}) and a function to be called
periodically @emph{via} @code{R_PolledEvents}: the polling mechanism is used by
the @pkg{tcltk} package.

An alternative front-end needs both to make provision for other @R{}
events whilst waiting for input, and to ensure that it is not frozen out
during events of the second type.  This is not handled very well in the
existing examples.  The GNOME front-end can run a own handler for polled
events by setting

@example
extern int (*R_timeout_handler)();
extern long R_timeout_val;

      if (R_timeout_handler && R_timeout_val)
          gtk_timeout_add(R_timeout_val, R_timeout_handler, NULL);
      gtk_main ();
@end example

@noindent
whilst it is waiting for console input.  This obviously handles events
for Gtk windows (such as the graphics device in the @pkg{gtkDevice}
package), but not X11 events (such as the @code{X11()} device) or for
other event handlers that might have been registered with @R{}.  It does
not attempt to keep itself alive whilst @R{} is waiting on sockets.  The
ability to add a polled handler as @code{R_timeout_handler} is used by
the @pkg{tcltk} package.


@node Threading issues,  , Meshing event loops, Embedding R under Unix-alikes
@subsection Threading issues

Embedded @R{} is designed to be run in the main thread, and all the
testing is done in that context.  There is a potential issue with the
stack-checking mechanism where threads are involved.  This uses two
variables declared in @file{Rinterface.h} (if @code{CSTACK_DEFNS} is
defined) as

@example
extern uintptr_t R_CStackLimit; /* C stack limit */
extern uintptr_t R_CStackStart; /* Initial stack address */
@end example

@noindent
Note that @code{uintptr_t} is a C99 type for which a substitute is
defined in @R{}, so your code needs to define @code{HAVE_UINTPTR_T}
appropriately.

These will be set@footnote{at least on platforms where the values are
available, that is having @code{getrlimit} and on Linux or having
@code{sysctl} supporting @code{KERN_USRSTACK}, including FreeBSD and
Mac OS X.} when @code{Rf_initialize_R} is called, to values appropriate to
the main thread.  Stack-checking can be disabled by setting
@code{R_CStackLimit = (uintptr_t)-1}, but it is better to if possible
set appropriate values.  (What these are and how to determine them are
OS-specific, and the stack size limit may differ for secondary threads.
If you have a choice of stack size, at least 8Mb is recommended.)

You may also want to consider how signals are handled: @R{} sets signal
handlers for several signals, including @code{SIGINT}, @code{SIGSEGV},
@code{SIGPIPE}, @code{SIGUSR1} and @code{SIGUSR2}, but these can all be
suppressed by setting the variable @code{R_SignalHandlers} (declared in
@file{Rinterface.h}) to @code{0}.


@node Embedding R under Windows,  , Embedding R under Unix-alikes, Linking GUIs and other front-ends to R
@section Embedding R under Windows

All Windows interfaces to @R{} call entry points in the DLL
@file{R.dll}, directly or indirectly.  Simpler applications may find it
easier to use the indirect route @emph{via} @acronym{(D)COM}.

@menu
* Using (D)COM::
* Calling R.dll directly::
* Finding R_HOME::
@end menu

@node Using (D)COM, Calling R.dll directly, Embedding R under Windows, Embedding R under Windows
@subsection Using (D)COM

@acronym{(D)COM} is a standard Windows mechanism used for communication
between Windows applications.  One application (here @R{}) is run as COM
server which offers services to clients, here the front-end calling
application.  The services are described in a `Type Library' and are
(more or less) language-independent, so the calling application can be
written in C or C++ or Visual Basic or Perl or Python and so on.
The `D' in (D)COM refers to `distributed', as the client and server can
be running on different machines.

The basic @R{} distribution is not a (D)COM server, but two addons are
currently available that interface directly with @R{} and provide a
(D)COM server:
@itemize
@item
There is a (D)COM server called @code{StatConnector} written by Thomas
Baier available on @acronym{CRAN}
(@uref{http://@/cran.r-project.org/@/other-software.html}) which works
with package @pkg{rscproxy} to support transfer of data to and from @R{}
and remote execution of R commands, as well as embedding of an @R{}
graphics window.  The @pkg{rcom} package on @acronym{CRAN} provides a
(D)COM server in a running @R{} session.

@item
Another (D)COM server, @code{RDCOMServer}, is available from
@uref{http://www.omegahat.org/}. Its philosophy is discussed in
@uref{http://www.omegahat.org/RDCOMServer/Docs/Paradigm.html} and is
very different from the purpose of this section.
@end itemize
@node Calling R.dll directly, Finding R_HOME, Using (D)COM, Embedding R under Windows
@subsection Calling R.dll directly

The @code{R} DLL is mainly written in C and has @code{_cdecl} entry
points.  Calling it directly will be tricky except from C code (or C++
with a little care).

There is a version of the Unix-alike interface calling

@example
int Rf_initEmbeddedR(int ac, char **av);
void Rf_endEmbeddedR(int fatal);
@end example

@noindent
which is an entry point in @file{R.dll}.  Examples of its use (and a
suitable @file{Makefile.win}) can be found in the @file{tests/Embedding}
directory of the sources.  You may need to ensure that
@file{@var{R_HOME}/bin} is in your @env{PATH} so the @R{} DLLs are found.

Examples of calling @file{R.dll} directly are provided in the directory
@file{src/@/gnuwin32/@/front-ends}, including a simple command-line
front end @file{rtest.c} whose code is

@smallexample
#define Win32
#include <windows.h>
#include <stdio.h>
#include <Rversion.h>
#define LibExtern __declspec(dllimport) extern
#include <Rembedded.h>
#include <R_ext/RStartup.h>
/* for askok and askyesnocancel */
#include <graphapp.h>

/* for signal-handling code */
#include <psignal.h>

/* simple input, simple output */

/* This version blocks all events: a real one needs to call ProcessEvents
   frequently. See rterm.c and ../system.c for one approach using
   a separate thread for input.
*/
int myReadConsole(const char *prompt, char *buf, int len, int addtohistory)
@{
    fputs(prompt, stdout);
    fflush(stdout);
    if(fgets(buf, len, stdin)) return 1; else return 0;
@}

void myWriteConsole(const char *buf, int len)
@{
    printf("%s", buf);
@}

void myCallBack(void)
@{
    /* called during i/o, eval, graphics in ProcessEvents */
@}

void myBusy(int which)
@{
    /* set a busy cursor ... if which = 1, unset if which = 0 */
@}

static void my_onintr(int sig) @{ UserBreak = 1; @}

int main (int argc, char **argv)
@{
    structRstart rp;
    Rstart Rp = &rp;
    char Rversion[25], *RHome;

    sprintf(Rversion, "%s.%s", R_MAJOR, R_MINOR);
    if(strcmp(getDLLVersion(), Rversion) != 0) @{
        fprintf(stderr, "Error: R.DLL version does not match\n");
        exit(1);
    @}

    R_setStartTime();
    R_DefParams(Rp);
    if((RHome = get_R_HOME()) == NULL) @{
         fprintf(stderr, "R_HOME must be set in the environment or Registry\n");
         exit(1);
    @}
    Rp->rhome = RHome;
    Rp->home = getRUser();
    Rp->CharacterMode = LinkDLL;
    Rp->ReadConsole = myReadConsole;
    Rp->WriteConsole = myWriteConsole;
    Rp->CallBack = myCallBack;
    Rp->ShowMessage = askok;
    Rp->YesNoCancel = askyesnocancel;
    Rp->Busy = myBusy;

    Rp->R_Quiet = TRUE;        /* Default is FALSE */
    Rp->R_Interactive = FALSE; /* Default is TRUE */
    Rp->RestoreAction = SA_RESTORE;
    Rp->SaveAction = SA_NOSAVE;
    R_SetParams(Rp);
    R_set_command_line_arguments(argc, argv);

    FlushConsoleInputBuffer(GetStdHandle(STD_INPUT_HANDLE));

    signal(SIGBREAK, my_onintr);
    GA_initapp(0, 0);
    readconsolecfg();
    setup_Rmainloop();
#ifdef SIMPLE_CASE
    run_Rmainloop();
#else
    R_ReplDLLinit();
    while(R_ReplDLLdo1() > 0) @{
/* add user actions here if desired */
    @}
/* only get here on EOF (not q()) */
#endif
    Rf_endEmbeddedR(0);
    return 0;
@}
@end smallexample

The ideas are

@itemize
@item
Check that the front-end and the linked @file{R.dll} match -- other
front-ends may allow a looser match.

@item
Find and set the @R{} home directory and the user's home directory.  The
former may be available from the Windows Registry: it will be in
@code{HKEY_LOCAL_MACHINE\Software\R-core\R\InstallPath} from an
administrative install and
@code{HKEY_CURRENT_USER\Software\R-core\R\InstallPath} otherwise, if
selected during installation (as it is by default).

@item
Define startup conditions and callbacks @emph{via} the @code{Rstart} structure.
@code{R_DefParams} sets the defaults, and @code{R_SetParams} sets
updated values.

@item
Record the command-line arguments used by
@code{R_set_command_line_arguments} for use by the @R{} function
@code{commandArgs()}.

@item
Set up the signal handler and the basic user interface.

@item
Run the main @R{} loop, possibly with our actions intermeshed.

@item
Arrange to clean up.
@end itemize

An underlying theme is the need to keep the GUI `alive', and this has
not been done in this example.  The @R{} callback @code{R_ProcessEvents}
needs to be called frequently to ensure that Windows events in @R{}
windows are handled expeditiously.  Conversely, @R{} needs to allow the
GUI code (which is running in the same process) to update itself as
needed -- two ways are provided to allow this:

@itemize
@item
@code{R_ProcessEvents} calls the callback registered by
@code{Rp->callback}.  A version of this is used to run package Tcl/Tk
for @pkg{tcltk} under Windows, for the code is

@example
void R_ProcessEvents(void)
@{
    while (peekevent()) doevent(); /* Windows events for GraphApp */
    if (UserBreak) @{ UserBreak = FALSE; onintr(); @}
    R_CallBackHook();
    if(R_tcldo) R_tcldo();
@}
@end example

@item
The mainloop can be split up to allow the calling application to take
some action after each line of input has been dealt with: see the
alternative code below @code{#ifdef SIMPLE_CASE}.
@end itemize

It may be that no @R{} GraphApp windows need to be considered, although
these include pagers, the @code{windows()} graphics device, the @R{}
data and script editors and various popups such as @code{choose.file()}
and @code{select.list()}.  It would be possible to replace all of these,
but it seems easier to allow GraphApp to handle most of them.

It is possible to run @R{} in a GUI in a single thread (as
@file{RGui.exe} shows) but it will normally be easier@footnote{An
attempt to use only threads in the late 1990s failed to work correctly
under Windows 95, the predominant version of Windows at that time.} to
use multiple threads.

Note that @R{}'s own front ends use a stack size of 10Mb, whereas MinGW
executables default to 2Mb, and Visual C++ ones to 1Mb.  The latter
stack sizes are too small for a number of @R{} applications, so
general-purpose front-ends should use a larger stack size.


@node Finding R_HOME,  , Calling R.dll directly, Embedding R under Windows
@subsection Finding R_HOME

Both applications which embed @R{} and those which use a @code{system}
call to invoke @R{} (as @command{Rscript.exe}, @command{Rterm.exe} or
@command{R.exe}) need to be able to find the @R{} @file{bin} directory.
The simplest way to do so is the ask the user to set an environment
variable @env{R_HOME} and use that, but naive users may be flummoxed as
to how to do so or what value to use.

The @R{} for Windows installers have for a long time allowed the value
of @code{R_HOME} to be recorded in the Windows Registry: this is
optional but selected by default.  @emph{Where} is it is recorded has
changed over the years to allow for multiple versions of @R{} to be
installed at once, and as from @R{} 2.11.0, to allow 32- and 64-bit
versions of @R{} to be installed on the same machine.

The basic Registry location is @code{Software\R-core\R}.  For an
administrative install this is under @code{HKEY_LOCAL_MACHINE} and on a
64-bit OS @code{HKEY_LOCAL_MACHINE\Software\R-core\R} is by default
redirected for a 32-bit application, so a 32-bit application will see
the information for the last 32-bit install, and a 64-bit application
that for the last 64-bit install.  For a personal install, the
information is under @code{HKEY_CURRENT_USER\Software\R-core\R} which is
seen by both 32-bit and 64-bit applications and so records the last
install of either architecture.  To circumvent this, as from @R{} 2.11.0
there are locations @code{Software\R-core\R32} and @code{Software\R-core\R64}
which always refer to one architecture.

When @R{} is installed and recording is not disabled then two string
values are written at that location for keys @code{InstallPath} and
@code{Current Version}, and these keys are removed when @R{} is
uninstalled.  To allow information about other installed versions to be
retained, there is also a key named something like @code{2.11.0} or
@code{2.11.0 patched} or @code{2.12.0 Pre-release} with a value for
@code{InstallPath}.

So a comprehensive algorithm to search to @code{R_HOME} is something
like

@itemize
@item
Decide which of personal or administrative installs should have
precedence.  There are arguments both ways: we find that with roaming
profiles that @code{HKEY_CURRENT_USER\Software} often gets reverted to
an earlier version.  Do the following for one or both of
@code{HKEY_CURRENT_USER} and @code{HKEY_LOCAL_MACHINE}.

@item
If the desired architecture is known, look in @code{Software\R-core\R32}
or @code{Software\R-core\R64}, and if that does not exist or the
architecture is immaterial, in @code{Software\R-core\R}.

@item
If key @code{InstallPath} exists then this is @code{R_HOME} (recorded
using backslashes).  If it does not, look for version-specific keys like
@code{2.11.0 alpha}, pick the latest (which is of itself a complicated
algorithm as @code{2.11.0 patched > 2.11.0 > 2.11.0 alpha > 2.8.1}) and
use its value for @code{InstallPath}.
@end itemize

Prior to @R{} 2.12.0 @file{R.dll} and the various front-end executables
are in @file{R_HOME\bin}, but this will not be so from @R{} 2.12.0, when
they are in @file{R_HOME\bin\i386} or @file{R_HOME\bin\x64}.  So you
need to arrange to look first in the architecture-specific subdirectory
and then in @file{R_HOME\bin}.

@node Function and variable index, Concept index, Linking GUIs and other front-ends to R, Top
@unnumbered Function and variable index

@printindex vr

@node Concept index,  , Function and variable index, Top
@unnumbered Concept index

@printindex cp

@bye

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@c mode: TeXinfo ***
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