Attribute setting by reference

Function setattr sets a singe attribute and function setattributes sets a list of attributes.

getsetattr(x, which, value)

setattr(x, which, value)

setattributes(x, attributes)

Arguments

x

an R object

which

name of the attribute

value

value of the attribute, use NULL to remove this attribute

attributes

a named list of attribute values

Value

invisible(), we do not return the changed object to remind you of the fact that this function is called for its side-effect of changing its input object.

Details

The attributes of 'x' are changed in place without copying x. function setattributes does only change the named attributes, it does not delete the non-names attributes like attributes() does.

References

Writing R extensions – System and foreign language interfaces – Handling R objects in C – Attributes (Version 2.11.1 (2010-06-03 ) R Development)

See also

attr() unattr()

Author

Jens Oehlschlägel

Examples

  x <- as.single(runif(10))
  attr(x, "Csingle")
#> [1] TRUE

  f <- function(x) attr(x, "Csingle") <- NULL
  g <- function(x) setattr(x, "Csingle", NULL)

  f(x)
  x
#>  [1] 0.54460339 0.27859715 0.44670247 0.37151118 0.02806097 0.46598719
#>  [7] 0.39003139 0.02006522 0.37697093 0.55991284
#> attr(,"Csingle")
#> [1] TRUE
  g(x)
  x
#>  [1] 0.54460339 0.27859715 0.44670247 0.37151118 0.02806097 0.46598719
#>  [7] 0.39003139 0.02006522 0.37697093 0.55991284

 if (FALSE) { # \dontrun{

  # restart R
  library(bit)

  mysingle <- function(length = 0) {
    ret <- double(length)
    setattr(ret, "Csingle", TRUE)
    ret
  }

  # show that mysinge gives exactly the same result as single
  identical(single(10), mysingle(10))

  # look at the speedup and memory-savings of mysingle compared to single
  system.time(mysingle(1e7))
  memory.size(max=TRUE)
  system.time(single(1e7))
  memory.size(max=TRUE)

  # look at the memory limits
  # on my win32 machine the first line fails
  #   because of not enough RAM, the second works
  x <- single(1e8)
  x <- mysingle(1e8)

  # .g. performance with factors
  x <- rep(factor(letters), length.out=1e7)
  x[1:10]
  # look how fast one can do this
  system.time(setattr(x, "levels", rev(letters)))
  x[1:10]
  # look at the performance loss in time caused by the non-needed copying
  system.time(levels(x) <- letters)
  x[1:10]


  # restart R
  library(bit)

  simplefactor <- function(n) {
    factor(rep(1:2, length.out=n))
  }

  mysimplefactor <- function(n) {
    ret <- rep(1:2, length.out=n)
    setattr(ret, "levels", as.character(1:2))
    setattr(ret, "class", "factor")
    ret
  }

  identical(simplefactor(10), mysimplefactor(10))

  system.time(x <- mysimplefactor(1e7))
  memory.size(max=TRUE)
  system.time(setattr(x, "levels", c("a", "b")))
  memory.size(max=TRUE)
  x[1:4]
  memory.size(max=TRUE)
  rm(x)
  gc()

  system.time(x <- simplefactor(1e7))
  memory.size(max=TRUE)
  system.time(levels(x) <- c("x", "y"))
  memory.size(max=TRUE)
  x[1:4]
  memory.size(max=TRUE)
  rm(x)
  gc()

} # }