identifying when one element of a row has a positive number

Hi,

This problem seemed deceptively simple to me. ?After chasing a
considerable number of dead ends, I came up with fg(). ?It lacks the
elegance of Dennis' solution, but (particularly for large datasets),
it is substantially faster. ?I still feel like I'm missing something,
but....

###############################################
## Data
df1 <- data.frame(x = seq(1860,1950,by=10),
?y = seq(-290,-200,by=10), ANN = c(3,0,0,0,1,0,1,1,0,0),
?CTA = c(0,1,0,0,0,0,1,0,0,2), GLM = c(0,0,2,0,0,0,0,1,0,0))
## larger test dataset
dftest <- do.call("rbind", rep(list(df1), 100))


f <- function(x) ifelse(sum(x > 0) == 1L, names(which(x > 0)), NA)
g <- function(x) ifelse(sum(x > 0) == 2L, names(which(x == 0L)), NA)

fg <- function(dat) {
?cnames <- colnames(dat)
?dat <- dat > 0; z <- rowSums(dat)
?z1 <- z == 1L; z2 <- z == 2L; rm(z)
?output <- matrix(NA, nrow = nrow(dat), ncol = 2)
?output[z1, 1] <- apply(dat[z1, ], 1, function(x) cnames[x])
?output[z2, 2] <- apply(dat[z2, ], 1, function(x) cnames[!x])
?return(output)
}

## Compare times on larger dataset
system.time(cbind(apply(dftest[, 3:5], 1, f),
?apply(dftest[, 3:5], 1, g)))
system.time(fg(dftest[, 3:5]))

## compare times under repetitions
system.time(for (i in 1:100) cbind(apply(df1[, 3:5], 1, f),
?apply(df1[, 3:5], 1, g)))
system.time(for (i in 1:100) fg(df1[, 3:5]))
###############################################

Josh


On Thu, Jan 27, 2011 at 12:36 AM, Dennis Murphy <djmuser at gmail.com> wrote:

Hi:

Try this:

f <- function(x) ifelse(sum(x > 0) == 1L, names(which(x > 0)), NA)
g <- function(x) ifelse(sum(x > 0) == 2L, names(which(x == 0L)), NA)

apply(df1[, 3:5], 1, f)

?[1] "ANN" "CTA" "GLM" NA ? ?"ANN" NA ? ?NA ? ?NA ? ?NA ? ?"CTA"

apply(df1[, 3:5], 1, g)

?[1] NA ? ?NA ? ?NA ? ?NA ? ?NA ? ?NA ? ?"GLM" "CTA" NA ? ?NA

HTH,
Dennis

On Wed, Jan 26, 2011 at 9:36 PM, Daisy Englert Duursma <
daisy.duursma at gmail.com> wrote:

Hello,

I am not sure where to begin with this problem or what to search for
in r-help. I just don't know what to call this.

If I have 5 columns, the first 2 are the x,y, locations and the last
three are variables about those locations.

x<-seq(1860,1950,by=10)
y<-seq(-290,-200,by=10)
ANN<-c(3,0,0,0,1,0,1,1,0,0)
CTA<-c(0,1,0,0,0,0,1,0,0,2)
GLM<-c(0,0,2,0,0,0,0,1,0,0)
df1<-as.data.frame(cbind(x,y,ANN,CTA,GLM))

What I would like to produce is an additional column that tells when
only 1 of the three variables has a value greater than 0. I would like
this new column to give the name of the variable. Likewise, I would
like a column that tells one only one of the three variables for a
given row has a value of 0. For my example the new columns would be:

one_presence<-c("ANN","CTA","GLM","NA","ANN","NA","NA","NA","NA","CTA")
one_absence<-c("NA","NA","NA","NA","NA","NA","GLM","CTA","NA","NA")

The end result should look like

df2<-(cbind(df1,one_presence,one_absence))

I am sure I can do this with a loop or maybe grep but I am out of ideas.

Any help would be appreciated.

Cheers,
Daisy

--
Daisy Englert Duursma

Room E8C156
Dept. Biological Sciences
Macquarie University ?NSW ?2109
Australia

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--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/