intelligently using the ellipsis in an R function -


i had function signature this:

myfunction=function(class="class",v1='y',v2='y',dfparam=df){

where df dataframe , assumed there attribute called class in df. wanted make more general can accept variety of dataframes, df, not 1 has attribute called class. added in classname parameter , classvalue parameter replace class parameter. also, want allow unlimited arguments v1, v2, v3 etc. , using elipsis this: 

myfunctiongeneral = function(classname="class", classvalue="democrat", dfparam=df, ...){   arguments <- list(...)

prior using elipsis, had line used arguments follows:

x_bool=dfparam$v1==v1 & dfparam$v2==v2

i started out doing this:

x_bool=dfparam[,2]==arguments[1] & dfparam[,3]==arguments[2]

but want unlimited number of possible paremeters in elipsis. need expand statement somehow unraveling ellipsis. here example:

install.packages("vcd") library(vcd) data(arthritis) aar=arthritis[,-c(1,4)]   myfunctiongeneral=function(classname="class",classvalue="democrat",dfparam=df, ...){    dfparam$names<-rownames(dfparam)   arguments<-list(...)     dfparamdroppedclass=dfparam[,-1]   #x_bool=dfparam[,2]==arguments[1] & dfparam[,3]==arguments[2]    x_bool=do.call(all, map("==", dfparamdroppedclass, arguments))     x=dfparam[x_bool,]   }

this should illustrate principle:

arguments <- list(1, 2, 3) params <- list(1, 2, 3) do.call(all, map("==", arguments, params)) #[1] true  params <- list(1, 2, 4) do.call(all, map("==", arguments, params)) #[1] false

all equivalent arbitrary number of &, , map iterates == on 2 lists.

edit: apparently data.frame has more 1 observation. can't use all, need use reduce in reduce("&", map("==", arguments, params)). example:

myfunctiongeneral=function(classname="class",classvalue="democrat",dfparam=df, ...){    dfparam$names<-rownames(dfparam)   arguments<-list(...)    dfparamdroppedclass=dfparam[, -c(1, 4)]   #x_bool=dfparam[,2]==arguments[1] & dfparam[,3]==arguments[2]    x_bool=reduce("&", map("==", dfparamdroppedclass, arguments))    dfparam[x_bool,]       }  myfunctiongeneral('treatment','placebo',aar,'male','marked') #   treatment  sex improved names #4    treated male   marked     4 #5    treated male   marked     5 #6    treated male   marked     6 #8    treated male   marked     8 #14   treated male   marked    14 #52   placebo male   marked    52

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