% File src/library/base/man/identical.Rd
% Part of the R package, http://www.R-project.org
% Copyright 2001-2010 R Core Development Team
% Distributed under GPL 2 or later

\name{identical}
\alias{identical}
\title{Test Objects for Exact Equality}
\description{
  The safe and reliable way to test two objects for being
  \emph{exactly} equal.  It returns \code{TRUE} in this case,
  \code{FALSE} in every other case.
}
\usage{
identical(x, y, num.eq = TRUE, single.NA = TRUE, attrib.as.set = TRUE)
}
\arguments{
  \item{x, y}{any \R objects.}
  \item{num.eq}{logical indicating if (\code{\link{double}} and
    \code{\link{complex}} non-\code{\link{NA}}) numbers should be
    compared using \code{\link{==}} (\sQuote{equal}), or by bitwise
    comparison. The latter (non-default) differentiates between
    \code{-0} and \code{+0}.}
  \item{single.NA}{logical indicating if there is conceptually just one numeric
    \code{\link{NA}} and one \code{\link{NaN}};  \code{single.NA = FALSE}
    differentiates bit patterns.}
  \item{attrib.as.set}{logical indicating if \code{\link{attributes}} of
    \code{x} and \code{y} should be treated as \emph{unordered} tagged
    pairlists (\dQuote{sets}); this currently also applies to
    \code{\link{slot}}s of S4 objects.  It may well be too strict to set
    \code{attrib.as.set = FALSE}.
  }
}
\details{
  A call to \code{identical} is the way to test exact equality in
  \code{if} and \code{while} statements, as well as in logical
  expressions that use \code{&&} or \code{||}.  In all these
  applications you need to be assured of getting a single logical
  value.

  Users often use the comparison operators, such as \code{==} or
  \code{!=}, in these situations.  It looks natural, but it is not what
  these operators are designed to do in R.  They return an object like
  the arguments.  If you expected \code{x} and \code{y} to be of length
  1, but it happened that one of them wasn't, you will \emph{not} get a
  single \code{FALSE}.  Similarly, if one of the arguments is \code{NA},
  the result is also \code{NA}.  In either case, the expression
  \code{if(x == y)....} won't work as expected.

  The function \code{all.equal} is also sometimes used to test equality
  this way, but was intended for something different:  it allows for
  small differences in numeric results.

  The computations in \code{identical} are also reliable and usually
  fast.  There should never be an error.  The only known way to kill
  \code{identical} is by having an invalid pointer at the C level,
  generating a memory fault.  It will usually find inequality quickly.
  Checking equality for two large, complicated objects can take longer
  if the objects are identical or nearly so, but represent completely
  independent copies.  For most applications, however, the computational cost
  should be negligible.

  If \code{single.NA} is true, as by default, \code{identical} sees
  \code{\link{NaN}} as different from \code{\link{NA_real_}}, but all
  \code{NaN}s are equal (and all \code{NA} of the same type are equal).
  
  Character strings are regarded as identical if they are in different
  marked encodings but would agree when translated to UTF-8.
  
  If \code{attrib.as.set} is true, as by default, comparison of
  attributes view them as a set (and not a vector, so order is not
  tested).

  Note that \code{identical(x,y, FALSE,FALSE,FALSE)} pickily tests for
  very exact equality.
}
\value{
  A single logical value, \code{TRUE} or \code{FALSE}, never \code{NA}
  and never anything other than a single value.
}
\author{John Chambers and R Core}

\references{
  Chambers, J. M. (1998)
  \emph{Programming with Data. A Guide to the S Language}.
  Springer.
}
\seealso{
  \code{\link{all.equal}} for descriptions of how two objects differ;
  \link{Comparison} for operators that generate elementwise comparisons.
  \code{\link{isTRUE}} is a simple wrapper based on \code{identical}.
}
\examples{
identical(1, NULL) ## FALSE -- don't try this with ==
identical(1, 1.)   ## TRUE in R (both are stored as doubles)
identical(1, as.integer(1)) ## FALSE, stored as different types

x <- 1.0; y <- 0.99999999999
## how to test for object equality allowing for numeric fuzz :
(E <- all.equal(x,y))
isTRUE(E) # which is simply defined to just use
identical(TRUE, E)
## If all.equal thinks the objects are different, it returns a
## character string, and the above expression evaluates to FALSE

## even for unusual R objects :
identical(.GlobalEnv, environment())

### ------- Pickyness Flags : -----------------------------

## the infamous example:
identical(0., -0.) # TRUE, i.e. not differentiated
identical(0., -0., num.eq = FALSE)
## similar:
identical(NaN, -NaN) # TRUE
identical(NaN, -NaN, single.NA=FALSE) # differ on bit-level
\dontshow{
m0 <- m <- structure(cbind(I=1, a=1:3), foo = "bar", class = "matrix")
attributes(m0) <- rev(attributes(m))
names(attributes(m0)) # 'dim' remains first, interestingly...

stopifnot(identical(0, -0),     !identical(0, -0, num.eq=FALSE),
          identical(NaN, -NaN), !identical(NaN, -NaN, single.NA=FALSE),
          identical(m, m0),     !identical(m, m0, attrib.as.set=FALSE) )
}
}
\keyword{ programming }
\keyword{ logic }
\keyword{ iteration }
