Hi,
Can you please help me with this please?
What I am trying to do is call a vector from R function and used in the new
function
So I create 4 functions with these arguments
M11 <- function(TrainData,TestData,mdat,nsam) {
ls <- list()
I have few statments one of them is
vectx <- c(,1,2,3,4,5,6,6)
vectz <- c(12,34,5,6,78,9,90)
and then................
ls(vectx=vtecx,vectz=vectz)
return(ls)
}
Then I great an new function has the following arguments
get.m <- function(dat,asim,ModelFun,M){
Sim <- list()
modInd <- ModelFun(TrainData=dat,TestData=dat,mdat=dat,nsam=0.1) *# HERE IS
MY PROBLEM HOW CAN I JUST CALL vectx without fitting the ModelFun becasue as
you see in the bottom TrainData and Test are arguments used after
resampling. I dont want to use the main dat argument?*
if(M==11){
vecx <- modInd$vectx
px <- length(vecx) # ncol for X
nam <-colnames(dat[,vecx])
Asse <- matrix(NA,nrow=asim,ncol=px)
colnames(Asse) <- nam
}
for(i in 1:asim){
set.seed(i)
Samdat <- dat[sample(1:nrow(dat), nrow(dat), replace = TRUE), ]
TrSet <- Samdat[1:50,]
TeSet <- Samdat[51:75,]
}
Model<- ModelFun(TrainData=TrSet ,TestData=TeSet ,mdat=dat,nsam=i)
Y <- Model$Y
X <- Model$X
fit <- lm(Y~X)
return(fit)
}
--
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On Wed, Nov 7, 2012 at 3:31 PM, frespider <frespider at hotmail.com> wrote:> Hi, > > Can you please help me with this please? > > What I am trying to do is call a vector from R function and used in the new > function > > So I create 4 functions with these arguments > M11 <- function(TrainData,TestData,mdat,nsam) { > ls <- list() > I have few statments one of them is > vectx <- c(,1,2,3,4,5,6,6) > vectz <- c(12,34,5,6,78,9,90) > and then................ > ls(vectx=vtecx,vectz=vectz) > return(ls) > }This is not valid assignment to a list. In fact, I'm rather surprised it doesn't throw an error... Michael
On Wed, Nov 7, 2012 at 6:40 PM, Fares Said <frespider at hotmail.com> wrote:> Hi Michael, > > Can you explain more please why it want return an error? > > vectx and vectz just a vector of columns index I change them when ever is > required so I want use them at the begin of my get.m function before I do > the resampling. I only need these index and nothing else from that M11 > function nothing else. > > Can you help please? > >> From: michael.weylandt at gmail.com >> Date: Wed, 7 Nov 2012 18:28:38 +0000 >> Subject: Re: [R] Calling R object from R function >> To: frespider at hotmail.com >> CC: r-help at r-project.org >> >> On Wed, Nov 7, 2012 at 3:31 PM, frespider <frespider at hotmail.com> wrote: >> > Hi, >> > >> > Can you please help me with this please? >> > >> > What I am trying to do is call a vector from R function and used in the >> > new >> > function >> > >> > So I create 4 functions with these arguments >> > M11 <- function(TrainData,TestData,mdat,nsam) { >> > ls <- list() >> > I have few statments one of them is >> > vectx <- c(,1,2,3,4,5,6,6) >> > vectz <- c(12,34,5,6,78,9,90) >> > and then................ >> > ls(vectx=vtecx,vectz=vectz) >> > return(ls) >> > } >> >> This is not valid assignment to a list. In fact, I'm rather surprised >> it doesn't throw an error... >> >> MichaelHi Fares, A few points of etiquette: firstly, it's best to keep your posts on the list so others can help. If you want individual/private help, it's best to request it specifically or though a consulting arrangement. Secondly, your code is not reproducible: http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example -- nor is it entirely clear to me what it's trying to do. Please try to work up something reproducible and nicely commented. As to the error with ls() as you use it: ls <- list() ls(x = 5) # Gives an error. Note that the ls you create shadows the important function ls(). But even if you don't do that, there's an error because x = is not a parameter of ls(). Cheers, Michael
On Thu, Nov 8, 2012 at 2:44 PM, Fares Said <frespider at hotmail.com> wrote:> Hi Michael, > > you mentioned I can get help, can you give more details please.Hi Fares, I also asked that you keep our correspondance on the mailing list. Please do so. If you want private help, you can seek a local statistical consultancy, but free help is available here, if you follow protocol.> > I also edited the example to make productive.But I'm not using Nabble and neither are most of your other potential respondents: if you want to use an email help list, it's much better to use email. For instance, if we check the official R help archives -- https://stat.ethz.ch/pipermail/r-help/2012-November/328391.html -- you'll see your post wasn't changed. It's rather wretched that Nabble allows that, in my opinion, as it invalidates conversations.> > and you might tell me to create the M1 function on the get.m function but I > prefer not because I have 9 to ten function and they have lots statement and > I prefer to keep them separate >I've copied your Nabble post here: ------------------------------------------------------- a0=rep(1,40) a=rep(0:1,20) b=c(rep(1,20),rep(0,20)) c0=c(rep(0,12),rep(1,28)) c1=c(rep(1,5),rep(0,35)) c2=c(rep(1,8),rep(0,32)) c3=c(rep(1,23),rep(0,17)) c4=c(rep(1,6),rep(0,34)) x=matrix(cbind(a0,a,b,c0,c1,c2,c3,c4,rnorm(40)),nrow=40,ncol=9) Dat <- cbind(x,rnorm(40,2,30));colnames(Dat) <- c("a0","a","b","c0","c1","c2","c3","c4","c5","Y") M1 <- function(Trdat,Tedat,mdat,nsam,conv){ M1list <- NULL vectx <- c(1,4,6,7,9) vectz <- c(2,3,7,1,4,9) X <- Trdat[,vectx] Z <- Trdat[,vectz] Y <- Trdat[,ncol(Trdat)] TesX <- Tedat[,vectx] TesZ <- Tedat[,vectz] TesY <- Tedat[,ncol(Tedat)] Treig <- eigen(crossprod(X))$values if(any(abs(Treig) < conv))stop("In M1 the design matrix (X) is singular for simulation ",paste(nsam)) Comp <- c("nCol(X)"= ncol(X),"nCol(Z)"= ncol(Z),"Is length(Y)=nrow(X)"= length(Y)==nrow(X), "Is length(Y)=nrow(Z)"= length(Y)==nrow(Z)) M1list$vectx <- vectx M1list$vectz <- vectz M1list$X <- X M1list$Z <- Z M1list$Y <- Y M1list$TesX <- TesX M1list$TesZ <- TesZ M1list$TesY <- TesY M1list$Comp <- Comp return(M1list) } get.m <- function(dat,asim,ModelFun,M,conv){ Sim <- list() modInd <- ModelFun(Trdat=dat,Tedat=dat,mdat=dat,nsam=-1,conv=conv) # HERE WHERE I NEED HELP i only need to import vectx and vectz that is why I set Trdat=Tedat=dat if(M==1){ vecx <- modInd$vectx vecz <- modInd$vectz px <- length(vecx) pz <- length(vecz) pk <- length(modInd$Comp) nam <-colnames(dat[,vecx]) Asse <- matrix(NA,nrow=asim,ncol=px) Check <- matrix(NA,nrow=pk,ncol=asim) colnames(Check) <- paste("CheckIter",1:asim,sep="") } else { vecx <- modInd$vectx vecz <- modInd$vectz px <- length(vecx) pz <- length(vecz) pk <- length(modInd$Comp) nam <-colnames(dat[,vecx]) Asse <- matrix(NA,nrow=asim,ncol=px) Check <- matrix(NA,nrow=pk,ncol=asim) colnames(Check) <- paste("CheckIter",1:asim,sep="") } for(k in 1:asim){ cat("Iter #",paste(k),"\n") #=========================================================================================# Start Sampling code #=========================================================================================# Sample the Index for Train Set set.seed(k) Indx<-sample(1:nrow(dat),nrow(dat),replace=T) SamDat <- dat[Indx,] # Split Data set.seed(k) TrainInd <- sample(1:nrow(SamDat), trunc(2*length(1:nrow(SamDat))/3)) # Sample 2/3 of the data TrSet <- SamDat[TrainInd,] # Train data ######## Hold 1/3 of the data TeSet <- SamDat[-TrainInd,] # hold 1/3 of the data Trind <- ceiling((2*length(Indx))/3) Model <- ModelFun(Trdat=TrSet,Tedat=TeSet,mdat=dat,nsam=k,conv=conv) Y <- Model$Y X <- Model$X Z <- Model$Z TesX <- Model$TesX TesZ <- Model$TesZ TesY <- Model$TesY xnam <-colnames(X) znam <-colnames(Z) pc <- ncol(X) fmla <- as.formula(paste("Y ~",paste(xnam, collapse= "+"),"-1",sep="")) fitlm <- lm(formula=fmla,data = data.frame(cbind(X,Y))) ResiSqr <- (residuals(fitlm))*(residuals(fitlm)) Check[,k] <- Model$Comp Asse[k,1:pc] <- coef(fitlm) } Sim$Check <- Check Sim$Asse <- Asse return(Asse) } get.m(dat=Dat,asim=6,ModelFun=M1,M=1,conv=1e-4) ------------------------------------------------------ Your code is quite messy and difficult to follow: I'd write it as follows: # Initialize some data Dat <- cbind( a0 = rep(1, 40), a = rep(0:1, 20), b = rep(c(1,0), each = 20), c0=c(rep(0,12),rep(1,28)), c1=c(rep(1,5),rep(0,35)), c2=c(rep(1,8),rep(0,32)), c3=c(rep(1,23),rep(0,17)), c4=c(rep(1,6),rep(0,34)), Y = rnorm(40,2,30)) M1 <- function(Trdat,Tedat,mdat,nsam,conv){ vectx <- c(1,4,6,7,9) vectz <- c(2,3,7,1,4,9) X <- Trdat[,vectx] Z <- Trdat[,vectz] Y <- Trdat[,ncol(Trdat)] TesX <- Tedat[,vectx] TesZ <- Tedat[,vectz] TesY <- Tedat[,ncol(Tedat)] Treig <- eigen(crossprod(X))$values if(any(abs(Treig) < conv)) stop("In M1 the design matrix (X) is singular for simulation ", nsam) Comp <- c(`nCol(X)`= ncol(X),`nCol(Z)`= ncol(Z), `Is length(Y)=nrow(X)` = length(Y)==nrow(X), `Is length(Y)=nrow(Z)` = length(Y)==nrow(Z)) list(vectx = vectx, vectz = vectz, X = X, Z = Z, Y = Y, TesX = TesX, TesZ = TesZ, TesY = TesY, Comp = Comp) } with similar modifications throughout the rest of your code. Hopefully you find that easier to read: I certainly do. Now, it's still not entirely clear to me what you're asking: but perhaps global assignment and/or lexical scoping does what you want? Consider these tricks: ######################### add_magic_Z <- function(z){ Z <- z function(x) x + z } add_2 <- function(2) add_2(5) # 7 add_3 <- function(3) add_3(0) # 3 ########################## f <- function(x) { X <<- X + x return(x^2) } X <- -3 f(5) f(10) print(X) # increased by the `<<-` inside of f() ########################### The latter is considered bad programming practice however. Cheers, Michael
On Thu, Nov 8, 2012 at 4:57 PM, Fares Said <frespider at hotmail.com> wrote:> Hi Micheal, > > Please Can you tell me how I do that?How to do what? I wrote you a very long reply with many nouns.... I'll assume you mean keeping your reply on list: it's what I've done differently than you in each step of our communication up to now -- making sure that r-help at r-project.org is in the cc: field of your email. Depending on your mail client, this is as easy as hitting "reply all" instead of "reply." Michael Weylandt> > THanks > >> From: michael.weylandt at gmail.com >> Date: Thu, 8 Nov 2012 16:46:14 +0000 >> Subject: Re: [R] Calling R object from R function >> To: frespider at hotmail.com; r-help at r-project.org >> >> On Thu, Nov 8, 2012 at 2:44 PM, Fares Said <frespider at hotmail.com> wrote: >> > Hi Michael, >> > >> > you mentioned I can get help, can you give more details please. >> >> Hi Fares, >> >> I also asked that you keep our correspondance on the mailing list. >> Please do so. If you want private help, you can seek a local >> statistical consultancy, but free help is available here, if you >> follow protocol. >> >> > >> > I also edited the example to make productive. >> >> But I'm not using Nabble and neither are most of your other potential >> respondents: if you want to use an email help list, it's much better >> to use email. For instance, if we check the official R help archives >> -- https://stat.ethz.ch/pipermail/r-help/2012-November/328391.html -- >> you'll see your post wasn't changed. It's rather wretched that Nabble >> allows that, in my opinion, as it invalidates conversations. >> >> > >> > and you might tell me to create the M1 function on the get.m function >> > but I >> > prefer not because I have 9 to ten function and they have lots statement >> > and >> > I prefer to keep them separate >> > >> >> I've copied your Nabble post here: >> >> ------------------------------------------------------- >> >> a0=rep(1,40) >> a=rep(0:1,20) >> b=c(rep(1,20),rep(0,20)) >> c0=c(rep(0,12),rep(1,28)) >> c1=c(rep(1,5),rep(0,35)) >> c2=c(rep(1,8),rep(0,32)) >> c3=c(rep(1,23),rep(0,17)) >> c4=c(rep(1,6),rep(0,34)) >> x=matrix(cbind(a0,a,b,c0,c1,c2,c3,c4,rnorm(40)),nrow=40,ncol=9) >> Dat <- cbind(x,rnorm(40,2,30));colnames(Dat) <- >> c("a0","a","b","c0","c1","c2","c3","c4","c5","Y") >> >> M1 <- function(Trdat,Tedat,mdat,nsam,conv){ >> M1list <- NULL >> vectx <- c(1,4,6,7,9) >> vectz <- c(2,3,7,1,4,9) >> X <- Trdat[,vectx] >> Z <- Trdat[,vectz] >> Y <- Trdat[,ncol(Trdat)] >> TesX <- Tedat[,vectx] >> TesZ <- Tedat[,vectz] >> TesY <- Tedat[,ncol(Tedat)] >> Treig <- eigen(crossprod(X))$values >> if(any(abs(Treig) < conv))stop("In M1 the design matrix (X) is >> singular for simulation ",paste(nsam)) >> Comp <- c("nCol(X)"= ncol(X),"nCol(Z)"= ncol(Z),"Is >> length(Y)=nrow(X)"= length(Y)==nrow(X), >> "Is length(Y)=nrow(Z)"= length(Y)==nrow(Z)) >> >> M1list$vectx <- vectx >> M1list$vectz <- vectz >> M1list$X <- X >> M1list$Z <- Z >> M1list$Y <- Y >> M1list$TesX <- TesX >> M1list$TesZ <- TesZ >> M1list$TesY <- TesY >> M1list$Comp <- Comp >> return(M1list) >> } >> >> >> get.m <- function(dat,asim,ModelFun,M,conv){ >> Sim <- list() >> modInd <- ModelFun(Trdat=dat,Tedat=dat,mdat=dat,nsam=-1,conv=conv) # >> HERE WHERE I NEED HELP i only need to import vectx and vectz that is >> why I set Trdat=Tedat=dat >> if(M==1){ >> vecx <- modInd$vectx >> vecz <- modInd$vectz >> px <- length(vecx) >> pz <- length(vecz) >> pk <- length(modInd$Comp) >> nam <-colnames(dat[,vecx]) >> Asse <- matrix(NA,nrow=asim,ncol=px) >> Check <- matrix(NA,nrow=pk,ncol=asim) >> colnames(Check) <- paste("CheckIter",1:asim,sep="") >> } >> else { >> vecx <- modInd$vectx >> vecz <- modInd$vectz >> px <- length(vecx) >> pz <- length(vecz) >> pk <- length(modInd$Comp) >> nam <-colnames(dat[,vecx]) >> Asse <- matrix(NA,nrow=asim,ncol=px) >> Check <- matrix(NA,nrow=pk,ncol=asim) >> colnames(Check) <- paste("CheckIter",1:asim,sep="") >> } >> >> for(k in 1:asim){ >> cat("Iter #",paste(k),"\n") >> >> #=========================================================================================>> # Start Sampling code >> >> #=========================================================================================>> # Sample the Index for Train Set >> set.seed(k) >> Indx<-sample(1:nrow(dat),nrow(dat),replace=T) >> SamDat <- dat[Indx,] >> # Split Data >> set.seed(k) >> TrainInd <- sample(1:nrow(SamDat), trunc(2*length(1:nrow(SamDat))/3)) >> # Sample 2/3 of the data >> TrSet <- SamDat[TrainInd,] # Train data >> ######## Hold 1/3 of the data >> TeSet <- SamDat[-TrainInd,] # hold 1/3 of the data >> Trind <- ceiling((2*length(Indx))/3) >> Model <- ModelFun(Trdat=TrSet,Tedat=TeSet,mdat=dat,nsam=k,conv=conv) >> Y <- Model$Y >> X <- Model$X >> Z <- Model$Z >> TesX <- Model$TesX >> TesZ <- Model$TesZ >> TesY <- Model$TesY >> xnam <-colnames(X) >> znam <-colnames(Z) >> pc <- ncol(X) >> fmla <- as.formula(paste("Y ~",paste(xnam, collapse= "+"),"-1",sep="")) >> fitlm <- lm(formula=fmla,data = data.frame(cbind(X,Y))) >> ResiSqr <- (residuals(fitlm))*(residuals(fitlm)) >> Check[,k] <- Model$Comp >> Asse[k,1:pc] <- coef(fitlm) >> >> } >> Sim$Check <- Check >> Sim$Asse <- Asse >> return(Asse) >> } >> get.m(dat=Dat,asim=6,ModelFun=M1,M=1,conv=1e-4) >> >> ------------------------------------------------------ >> >> Your code is quite messy and difficult to follow: I'd write it as follows: >> >> # Initialize some data >> Dat <- cbind( >> a0 = rep(1, 40), >> a = rep(0:1, 20), >> b = rep(c(1,0), each = 20), >> c0=c(rep(0,12),rep(1,28)), >> c1=c(rep(1,5),rep(0,35)), >> c2=c(rep(1,8),rep(0,32)), >> c3=c(rep(1,23),rep(0,17)), >> c4=c(rep(1,6),rep(0,34)), >> Y = rnorm(40,2,30)) >> >> M1 <- function(Trdat,Tedat,mdat,nsam,conv){ >> vectx <- c(1,4,6,7,9) >> vectz <- c(2,3,7,1,4,9) >> >> X <- Trdat[,vectx] >> Z <- Trdat[,vectz] >> Y <- Trdat[,ncol(Trdat)] >> >> TesX <- Tedat[,vectx] >> TesZ <- Tedat[,vectz] >> TesY <- Tedat[,ncol(Tedat)] >> >> Treig <- eigen(crossprod(X))$values >> >> if(any(abs(Treig) < conv)) >> stop("In M1 the design matrix (X) is singular for simulation ", nsam) >> >> Comp <- c(`nCol(X)`= ncol(X),`nCol(Z)`= ncol(Z), >> `Is length(Y)=nrow(X)` = length(Y)==nrow(X), >> `Is length(Y)=nrow(Z)` = length(Y)==nrow(Z)) >> >> list(vectx = vectx, >> vectz = vectz, >> X = X, Z = Z, Y = Y, >> TesX = TesX, TesZ = TesZ, >> TesY = TesY, Comp = Comp) >> } >> >> with similar modifications throughout the rest of your code. Hopefully >> you find that easier to read: I certainly do. >> >> Now, it's still not entirely clear to me what you're asking: but >> perhaps global assignment and/or lexical scoping does what you want? >> >> Consider these tricks: >> >> ######################### >> add_magic_Z <- function(z){ >> Z <- z >> function(x) x + z >> } >> >> add_2 <- function(2) >> >> add_2(5) # 7 >> >> add_3 <- function(3) >> >> add_3(0) # 3 >> ########################## >> f <- function(x) { >> X <<- X + x >> return(x^2) >> } >> >> X <- -3 >> >> f(5) >> f(10) >> >> print(X) # increased by the `<<-` inside of f() >> ########################### >> >> The latter is considered bad programming practice however. >> >> Cheers, >> Michael
Hi,
I edit my post, Can you please help with this matter?
Hi,
Can you please help me with this please?
What I am trying to do is call a vector from R function and used in the new
function
# Initialize some data
Dat <- cbind(
a0 = rep(1, 40),
a = rep(0:1, 20),
b = rep(c(1,0), each = 20),
c0=c(rep(0,12),rep(1,28)),
c1=c(rep(1,5),rep(0,35)),
c2=c(rep(1,8),rep(0,32)),
c3=c(rep(1,23),rep(0,17)),
c4=c(rep(1,6),rep(0,34)),
Y = rnorm(40,2,30))
colnames(Dat) <-
c("a0","a","b","c0","c1","c2","c3","c4","c5","Y")
M1 <- function(Trdat,Tedat,mdat,nsam,conv){
vectx <- c(1,4,6,7,9)
vectz <- c(2,3,7,1,4,9)
X <- Trdat[,vectx]
Z <- Trdat[,vectz]
Y <- Trdat[,ncol(Trdat)]
TesX <- Tedat[,vectx]
TesZ <- Tedat[,vectz]
TesY <- Tedat[,ncol(Tedat)]
Treig <- eigen(crossprod(X))$values
if(any(abs(Treig) < conv))
stop("In M1 the design matrix (X) is singular for simulation
",
nsam)
Comp <- c("nCol(X)"= ncol(X),"nCol(Z)"= ncol(Z),"Is
length(Y)=nrow(X)"length(Y)==nrow(X),
"Is length(Y)=nrow(Z)"= length(Y)==nrow(Z))
list(vectx = vectx,
vectz = vectz,
X = X, Z = Z, Y = Y,
TesX = TesX, TesZ = TesZ,
TesY = TesY, Comp = Comp)
}
get.m <- function(dat,asim,ModelFun,M,conv){
Sim <- list()
modInd <- ModelFun(Trdat=dat,Tedat=dat,mdat=dat,nsam=-1,conv=conv) # HERE
WHERE I NEED HELP i only need to import vectx and vectz that is why I set
Trdat=Tedat=dat
if(M==1){
vecx <- modInd$vectx
vecz <- modInd$vectz
px <- length(vecx)
pz <- length(vecz)
pk <- length(modInd$Comp)
nam <-colnames(dat[,vecx])
Asse <- matrix(NA,nrow=asim,ncol=px)
Check <- matrix(NA,nrow=pk,ncol=asim)
colnames(Check) <- paste("CheckIter",1:asim,sep="")
}
else {
vecx <- modInd$vectx
vecz <- modInd$vectz
px <- length(vecx)
pz <- length(vecz)
pk <- length(modInd$Comp)
nam <-colnames(dat[,vecx])
Asse <- matrix(NA,nrow=asim,ncol=px)
Check <- matrix(NA,nrow=pk,ncol=asim)
colnames(Check) <- paste("CheckIter",1:asim,sep="")
}
for(k in 1:asim){
cat("Iter #",paste(k),"\n")
#=========================================================================================#
Start Sampling code
#=========================================================================================#
Sample the Index for Train Set
set.seed(k)
Indx<-sample(1:nrow(dat),nrow(dat),replace=T)
SamDat <- dat[Indx,]
# Split Data
set.seed(k)
TrainInd <- sample(1:nrow(SamDat), trunc(2*length(1:nrow(SamDat))/3)) #
Sample 2/3 of the data
TrSet <- SamDat[TrainInd,] # Train data
######## Hold 1/3 of the data
TeSet <- SamDat[-TrainInd,] # hold 1/3 of the data
Trind <- ceiling((2*length(Indx))/3)
Model <- ModelFun(Trdat=TrSet,Tedat=TeSet,mdat=dat,nsam=k,conv=conv)
Y <- Model$Y
X <- Model$X
Z <- Model$Z
TesX <- Model$TesX
TesZ <- Model$TesZ
TesY <- Model$TesY
xnam <-colnames(X)
znam <-colnames(Z)
pc <- ncol(X)
fmla <- as.formula(paste("Y ~",paste(xnam, collapse=
"+"),"-1",sep=""))
fitlm <- lm(formula=fmla,data = data.frame(cbind(X,Y)))
ResiSqr <- (residuals(fitlm))*(residuals(fitlm))
Check[,k] <- Model$Comp
Asse[k,1:pc] <- coef(fitlm)
}
Sim$Check <- Check
Sim$Asse <- Asse
return(Asse)
}
get.m(dat=Dat,asim=6,ModelFun=M1,M=1,conv=1e-4)
--
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