Getting and setting dim and dimorder
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.
## 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
x |
a ff object |
value |
an appropriate integer vector |
... |
further arguments (not used) |
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.
names returns a character vector (or NULL)
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[]).
Jens Oehlschlägel
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.