similar to: if block and brackets

Hello getdata <- function(p){ fname <- NULL; dl <- list()#build the sturcture builddl <- function(q,s){ fname <<- c(fname,s) #where "s" is a string dl <<- list( dl, dt2) } list(names = fname, data = dl) } data <- getdata("c:\somepath") > data $names [1] "fname" $data $data[[1]] <--- since there is no [[1]] how can I stop

If we decide not to be legal, should we change the verify to reject it? What happens to the test cases that currently test this very situation (eg. Transforms/LoopVectorize/phi-hang.ll)? The change as suggested by Philip is: - Assert(InstsInThisBlock.count(Op) || DT.dominates(Op, U), + Assert((!isa<PHINode>(I) && InstsInThisBlock.count(Op)) || + DT.dominates(Op, U), +

HI: I need ideas on how to make this code shorter (maybe with a second loop?). The code as it is works, but in this case I only have 14 samples, but it will become insane with more, so I need a way to make it more automatic. The problem is that the output from ts1, ts2, and so on is a vector with more than one value, so I do not know how to solve this. Thanks Prenewbie The code is the

Hi Well, I am not an expert in this field so I cannot comment your approach. I wanted only to point out that building matrix your way is like scratching your left ear with right hand, especially in R. What if you want increase size of your matrix? E.g. you use function ProbUP once for row "0" and than for rows different from jmax (if I correctly understand your code). Use of any

Hi Petr, Many thanks for your response. Basically I want to create a probability matrix to be used in a trinomial tree going forward. This is the reason why I thought to build the matrix around 0 would be much more efficient. I need to loop through because the probabilities will depend on my node and is not always the same per row (e.g. if N> jmax, jmax being defined in another function) I

I want to populate the matrix prb through the function HWMProb <- function (a,j,dt) that encapsulates different functions (please see code below), using j= 0:2 for each j. It only populates prb if I specify each function independently in the global environment and then run the loop with the iF statement, as per below. for (j in 0:2) { if (j==0) { prb["0","1"] <-

Hi Eric I did not see any answer and frankly speaking I cannot provide you with canned help. AFAIK if a function is defined within another function (which is your case) it cannot be called directly so it is necessary to define it in global environment. > fff <- function(x) { + myf <- function(a) a+2 + myf(x)^2} > > fff(5) [1] 49 > myf(5) Error in myf(5) : could not find

Dear r-users, I would like to construct 3-day moving average for block maxima series. I tried this: bmthree <- lapply(split(dt, dt$Year), function(x) max(sapply(1:(nrow(x)-2), function(i) with(x, mean(Amount[i:(i+2)],na.rm=TRUE))))) bmthree and got the following output. $`1971` [1] 70.81667 $`1972` [1] 68.94553 $`1973` [1] 102.7236 $`1974` [1] 73.6625 $`1975` [1]

I've two data.tables as shown below: *** N = 10 A.DT <- data.table(a1 = c(rnorm(N,0,1)), a2 = NA)) B.DT <- data.table(b1 = c(rnorm(N,0,1)), b2 = 1:N) setkey(A.DT,a1) setkey(B.DT,b1) *** I tried to change my previous data.frame implementation to a data.table implementation by changing the for-loop as shown below: *** for (i in 1:nrow(B.DT)) { for (j in nrow(A.DT):1) { if

Hi R-users, I have this code to uniformise the data using gamma: > length(dp1) [1] 696 > dim(dp1) [1] 58 12 > dim(ahall) [1]  1 12 > dim(bhall) [1]  1 12 > trans_dt <- function(dt,a,b) + { n1 <- ncol(dt) +   n2 <- length(dt) +   trans  <- vector(mode='numeric', length=n2) +   dim(trans) <- dim(dt) +   for (i in 1:n1) +   {  dt[,i] <- as.vector(dt[,i])

I am trying to find a convenient way to control line colors when printing from a for loop using the lines command. Right now I have solved this by creating a colors vector that is refered to in the loop with index. However, the colors choosen here are just 1,2,3,4,5... I would like to get colors from the col = rainbow(x) that you can use in plot() and set the to be my number of lines (I think

Dear R-help community, My main goal of this message is to find a way of skipping a file of a month/year in a loop that does not exist (and making it's output into an data.out array would be NA) and moving onto the next year/month in the loop to carry on filling data.out with real precipitation data. The situation so far: I downloaded 50 years worth of GRIB data files from the NCEP data

Hello: I use R with MAC I have a simple data table, numeric and text columns, named dt. The table is imported through read.csv from a csv file. Row numbers are automatically assigned, header is set to TRUE. there are 599 rows and several columns. I am trying to plot using the stripchart command: one numeric variable (say dt$fnatg) vs a text column (say dt$pat). dt$pat contains one of 3 values:

Dear all, I am trying to plot KM curves with confidence bands with function survplot under package rms. However, the following codes do not seem to work. The KM curves are produced, but the confidence bands are not there. Any insights? Thanks in advance. library(rms) ########data generation############ n <- 1000 set.seed(731) age <- 50 + 12*rnorm(n) label(age) <- "Age"

Hi, I am having trouble using the ave function with a POSIXct object. For example: x<-Sys.time()+0:9*3600 dat<-data.frame(id=rep(c('a',' b','c'),each=10),dt=rep(x,3),i=rep(1:10,3)) dat # This is what I want to do: dat$time.elapsed<-unsplit(lapply(split(dat$dt,dat$id),function(x) x-x[1]),f=dat$id) dat # The above code does the trick, but from the standpoint of

Par evitar el warning.... > DT=data.table(col1=1:10) > DT[,col2:=diff(log(c(1,col1)))] > DT col1 col2 1: 1 0.0000000 2: 2 0.6931472 3: 3 0.4054651 4: 4 0.2876821 5: 5 0.2231436 6: 6 0.1823216 7: 7 0.1541507 8: 8 0.1335314 9: 9 0.1177830 10: 10 0.1053605 > ----- Mensaje original ----- De: "Carlos Ortega" <cof en

Dear List, (self-contained example + version info at the bottom) I'm having trouble producing a barplot using the functions in ggplot2. When I use the position="dodge" option, the bars are plotted but also a number of spurious markers. More specifically, a number of black dots are plotted in the graph that should not be there. This behaviour is not seen when calling the same

Hello All, I am trying to work on writing the following piece of (pseudo) code in an optimal fashion: ---------------------------------------------------- # Two data frames with some data a = data.frame(somedata) b = data.frame(somedata) for(i in 1:nrow(dt) { # Merge dates for a given date into a new data frame c = merge(a[a$dt==dt[i],),b[b$dt == dt[i],], by=c(some column)); }

Hi Jenny If you want a general solution I understand. However I just downloaded the file fine (as far as I can tell) so you are welcome to have a copy. I can email it to you if you want. I do not think your test for NA is valid. i.e if(test != "NA"){ } I think you should use if(is.na(test)){ } Or something similar. J --- John Seers Institute of Food Research Norwich

Hi there, I am confused about fucntion call. After defining a function, I called it within another function. dt<-cars; #a copy of R internal dataset "cars" created; dt$cat1<-ifelse(dt$speed<20,0,1); dt$ind<-ifelse(dt$speed<15,1,2); #group variable; freqtot <- function(data,var){ attach(data,warn.conflicts=FALSE) x1 <- data.frame(table(var))