lapply - R: sequentially applying an arbitrarty list of functions with arguments to a matrix -

lapply - R: sequentially applying an arbitrarty list of functions with arguments to a matrix -

i have list of filtering functions f1,f2,f3,f4,.... take matrix m , number of options input , homecoming subset of rows of matrix output. able define in orderly way meta-filtering function settings metaf1, metaf2, metaf3,... specify sequential application of specified nr of filtering functions, e.g. first f2 , f3, using given options each. store these filtering settings in list of class "metafiltering", , have function apply filtering steps specified in given metafiltering object. thought able in way allow filtering settings stored , applied in orderly way. how accomplish in elegant way in r? or there perhaps other convenient methods accomplish this?

edit: give example, have matrix

m=replicate(10, rnorm(20))

and filtering functions (these examples, mine more complicated :-) )

f1=function(m,opt1,opt2) { return(m[(m[,2]>opt1)&(m[,1]>opt2),]) } f2=function(m,opt1) { return(m[(m[,3]>opt1),]) }

and have defined next metafiltering settings of specific class specify 2 functions have applied sequentially matrix m

metafilterfuncs=list(fun1=f1(opt1=0.1,opt2=0.2),fun2=f2(opt1=0.5)) class("metafilterfuncs")="metafiltering"

the question have how apply filtering steps of arbitrary metafiltering function object given matrix m using specified functions , settings?

you can :

you define sort of functions pieplines give priority each function.

pipelines <- c(f1=100,f2=300,f3=200)

i define 3 dummy functions here test:

f1 <- function(m,a) m + f2 <- function(m,b) m + b f3 <- function(m,c) m + c

for each function , store argument in list :

args <- list(f1=c(a=1),f2=c(b=2),f3=c(c=3))

then apply functions :

m <- matrix(1:2,ncol=2) (func in names(pipelines[order(pipelines)])) { m <- do.call(func,list(m,args[[func]])) }

r lapply