dim.ff: Getting and setting dim and dimorder

In ff: Memory-Efficient Storage of Large Data on Disk and Fast Access Functions

Getting and setting dim and dimorder

Description

Assigning dim to an ff_vector changes it to an ff_array. Beyond that dimorder can be assigned to change from column-major order to row-major order or generalizations for higher order ff_array.

Usage

  ## S3 method for class 'ff'
dim(x)
  ## S3 method for class 'ffdf'
dim(x)
  ## S3 replacement method for class 'ff'
dim(x) <- value
  ## S3 replacement method for class 'ffdf'
dim(x) <- value
   dimorder(x, ...)
   dimorder(x, ...) <- value
  ## Default S3 method:
dimorder(x, ...)
  ## S3 method for class 'ff_array'
dimorder(x, ...)
  ## S3 method for class 'ffdf'
dimorder(x, ...)
  ## S3 replacement method for class 'ff_array'
dimorder(x, ...) <- value
  ## S3 replacement method for class 'ffdf'
dimorder(x, ...) <- value  # just here to catch forbidden assignments

Arguments

x	a ff object
value	an appropriate integer vector
...	further arguments (not used)

Details

dim and dimorder are virtual attributes. Thus two copies of an R ff object can point to the same file but interpret it differently. dim has the usual meaning, dimorder defines the dimension order of storage, i.e. c(1,2) corresponds to R's standard column-major order, c(1,2) corresponds to row-major order, and for higher dimensional arrays dimorder can also be used. Standard dimorder is seq_along(dim(x)).
For ffdf dim returns the number of rows and virtual columns. With dim<-.ffdf only the number of rows can be changed. For convenience you can assign NA to the number of columns.
For ffdf the dimorder returns non-standard dimorder if any of its columns contains a ff object with non-standard dimorder (see dimorderStandard) An even higher level of virtualization is available using virtual windows, see vw.

Value

names returns a character vector (or NULL)

Note

x[] returns a matrix like x[,] and thus respects dimorder, while x[i:j] returns a vector and simply returns elements in the stored order. Check the corresponding example twice, in order to make sure you understand that for non-standard dimorder x[seq_along(x)] is not the same as as.vector(x[]).

Author(s)

Jens Oehlschlägel

See Also

dim, dimnames.ff_array, dimorderStandard, vw, virtual

Examples

  x <- ff(1:12, dim=c(3,4), dimorder=c(2:1))
  y <- x
  dim(y) <- c(4,3)
  dimorder(y) <- c(1:2)
  x
  y
  x[]
  y[]
  x[,bydim=c(2,1)]
  y[,bydim=c(2,1)]

  message("NOTE that x[] like x[,] returns a matrix (respects dimorder),")
  message("while x[1:12] returns a vector IN STORAGE ORDER")
  message("check the following examples twice to make sure you understand this")
  x[,]
  x[]
  as.vector(x[])
  x[1:12]
  rm(x,y); gc()

  
  ## Not run: 
    message("some performance comparison between different dimorders")
    n <- 100
    m <- 100000
    a <- ff(1L,dim=c(n,m))
    b <- ff(1L,dim=c(n,m), dimorder=2:1)
    system.time(lapply(1:n, function(i)sum(a[i,])))
    system.time(lapply(1:n, function(i)sum(b[i,])))
    system.time(lapply(1:n, function(i){i<-(i-1)*(m/n)+1; sum(a[,i:(i+m/n-1)])}))
    system.time(lapply(1:n, function(i){i<-(i-1)*(m/n)+1; sum(b[,i:(i+m/n-1)])}))
    rm(a,b); gc()
  
## End(Not run)

ff documentation built on Feb. 16, 2023, 7:48 p.m.