similar to: get the enclosing function name

Hi, I would like to extract the last row of each group in a data frame. The data frame is as follows Name Value A 1 A 2 A 3 B 4 B 8 C 2 D 3 I would like to get a data frame as Name Value A 3 B 8 C 2 D 3 Thank you for your suggestions in advance Jeff

Hi, I have a a vector and a data frame with two columns vec = c("C", "A", "B") dataDF = data.frame(A1 = c("B", "A", "C"), A2 = c(1,2,3)) I would like to sort the data frame by column A1 such that the order of elements in A1 is as the same as in vec. After the ordering, the data frame would be A1 A2 C

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process1(X) ... process2(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types. I would like to pass g1, g2, g3 and their arguments to f and g1,

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process(X) ... process(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types.

Hi, I wonder how to have R automatically print stack trace produced by traceback upon errors during interactive uses. I tried the suggestions on http://old.nabble.com/Automatically-execute-traceback-when-execution-of-script-causes-error--td22368483.html#a22368775 and used options(error = recover) options(showErrorCalls = T) It just produces an extra message like "recover called

Hi, I currently combine multiple processed data (data frame) into a list and save the list as ".rda" using the save command. When new data come, I load the rda file, process the new data into a data frame, append the data frame to the end of the list, and save the whole list to the disk. The loading and saving steps are quite time consuming. Since I don't need to change the old data

Hi, I have a data set similar to the following State Gender Quantity TX Male 1 NY Female 2 TX Male 3 NY Female 4 I need to calculate cumulative sum of the quantity by State and Gender. The expected output is State Gender Quantity CumQuantity TX Male 1 1 TX Male 3 4 NY Female 2 2 NY Female 4 6 I highly appreciate if someone can give me some hints on solving that in R. Hao -- View this

Hi, I wonder what is a better way to organize a lot of R source files. I have a lot of utility functions written and store them in several source files (e.g util1.R, util2.R,..utilN.R). I also have a master file in which the source command is used to load all the util.R files. When I need to use the utility functions in a new project, I create a new R file (e.g main.R) in which I

Hi, I have two questions on using the ff package and wonder if anyone who used ff can share some thoughts. I need to save a matrix as a memory-mapped file and load it back later. To save the matrix, I use mat = matrix(1:20, 4, 5) matFF = ff(mat, dim=dim(mat), filename="~/a.mat", overwrite=TRUE, dimnames = dimnames(mat)) To load it back, I use matFF2 = ff(vmode = "double",

Hi, I would like to save a few dynamically created objects to disk. The following is the basic flow of the code segment for(i = 1:10) { m = i:5 save(m, file = ...) ## ??? } To distinguish different objects to be saved, I would like to save m as m1, m2, m3 ..., to file /home/data/m1, /home/data/m2, home/data/m3, ... I tried a couple of methods on translating between object names and

Hi, I have a vector with lots of NAs. e.g. vec = c(NA, NA, 2, NA, NA, 5, NA, 6, NA) > vec [1] NA NA 2 NA NA 5 NA 6 NA I would like to replace NAs with their immediately previous non NA number. After replacement, the above vector will become > vec [1] 0 0 2 2 2 5 5 6 6. I understand how to do that with a loop but the actual vector is very long and the loop takes too much time in R.

Hi, I have multiple responses y1, y2, .., yn, and would like to do linear regression for each of them with x1, x2, ..., xm. Instead of doing regression n times, it it possible to do it all at once? I tried lm(y1+y2 ~ x1 + x2 + x3) and lm added y1 y2 and then did the regression. thanks Jeff

Hi, I wonder how to write a function that remembers its state across its calls. For example, I would like to compute the average of the pass three values the function has seen f(1) # NA f(2) # NA f(3) # 2 f(4) # 3 This would require f to keep track of the values it has seen. In other languages like c++ or java it is easy to do by having a member variable. I am not sure how to do similar

Try to close the file on the first nfs client before reopening it on the second nfs client. NFS has something called "close-to-open cache consistency". This means that two clients which have the same nfs file open, cannot rely on seeing the updates from the respective other client. If one clients closes, and the other client opens thereafter, it should see the changes. If you want

The `examples' section says plot.mlm # to see how the "NotYetImplemented" # reference is made automagically ^ Best, Torsten

Hi, I wonder anyone knows what causes the error message "select: bad file descriptor" in the multicore package. This error sometimes occurs and sometimes doesn't. I couldn't find any documentation on this error about this package. thanks Jeff

Hi, I am writing a function in C that is meant to be called by R. In the C function, I used a gsl function gsl_stats_mean. The code is as simple as below void gsl(double *m, int *dim){ int r, c; r = dim[0]; c = dim[1]; double mean = gsl_stats_mean(&m[0], 1, r); Rprintf("mean = %f\n", mean); } The C code is succesfully compiled and the output is as follows. $ R CMD SHLIB

Hi, I have C code to produce a lot of matrices to be analyzed. As these matrices are large (> 1000*10000) and are a lot (> 1000), I am thinking about how to pass them from C to R effectively. Would you think about the following solution? In R, I create a wrapper function passDataFromCToR = function(row, col) { mat = matrix(0, row, col) .C("passDataFromCToR",mat)[[1]] }

Hi All, I want to enclose with() in a function mean_on_element. Obviously, it is not working. The problem is how to specify the element name with a function body. Does anybody have any suggestion? Thanks! > data=list(x=1:10) > with(data, mean(x)) [1] 5.5 > > mean_on_element=function(data, elem_name) { + with(data, mean(elem_name)) + } > mean_on_element(data, 'x') [1] NA

Dear all, I am planning to use nlme library for analysis of experiments in semiconductor industry. Currently I am using "lm" but plan to move to "lme" to handle within wafer / wafer-to-wafer and lot-to-lot variation correctly. So far everything is working well, but I have a fundamentel question: NLME offers "maximum likelihood" and "restricted maximum