similar to: assigning vector or matrix sparsely (for use with mclapply)

On 11/27/24 08:30, Sorkin, John wrote: > I am an old, long time SAS programmer. I need to produce R code that processes a dataframe in a manner that is equivalent to that produced by using a by statement in SAS and an if first.day statement and a retain statement: > > I want to take data (olddata) that looks like this > ID Day > 1 1 > 1 1 > 1 2 > 1 2 > 1 3 > 1 3 >

Hi, This is my code (my data is attached): library(languageR) library(rms) library(party) OLDDATA <- read.csv("/Users/Abigail/Documents/OldData250412.csv") OLDDATA$YD <- factor(OLDDATA$YD, label=c("Yes", "No"))? OLDDATA$ND <- factor(OLDDATA$ND, label=c("Yes", "No"))? attach(OLDDATA) defaults <- cbind(YD, ND) set.seed(47) data.controls

?s 16:30 de 27/11/2024, Sorkin, John escreveu: > I am an old, long time SAS programmer. I need to produce R code that processes a dataframe in a manner that is equivalent to that produced by using a by statement in SAS and an if first.day statement and a retain statement: > > I want to take data (olddata) that looks like this > ID Day > 1 1 > 1 1 > 1 2 > 1 2 > 1 3 >

Rui: "f these two, diff is faster. But of all the solutions posted so far, Ben Bolker's is the fastest." But the explicit version of diff is still considerably faster: > D <- c(rep(1,10),rep(2,6),rep(3,2)) > microbenchmark(c(1L,diff(D)), times = 1000L) Unit: microseconds expr min lq mean median uq max neval c(1L, diff(D)) 3.075 3.198 3.34396

Was wondering when this would be suggested. But the question was about getting the final dataframe... newdta <- olddta newdta$FirstDay <- ave(newdata$date, newdata$ID, FUN = \(x) x[1L]) On November 27, 2024 11:13:49 AM PST, Rui Barradas <ruipbarradas at sapo.pt> wrote: >?s 16:30 de 27/11/2024, Sorkin, John escreveu: >> I am an old, long time SAS programmer. I need to

Dear R help folks, First my apologizes for sending several related questions to the list server. I am trying to learn how to manipulate data in R . . . and am having difficulty getting my program to work. I greatly appreciate the help and support list member give! I am trying to write a program that will run through a data frame organized by ID and for the first line of each new group of data

I am an old, long time SAS programmer. I need to produce R code that processes a dataframe in a manner that is equivalent to that produced by using a by statement in SAS and an if first.day statement and a retain statement: I want to take data (olddata) that looks like this ID Day 1 1 1 1 1 2 1 2 1 3 1 3 1 4 1 4 1 5 1 5 2 5 2 5 2 5 2 6 2 6 2 6 3 10 3 10 and make it look like this: (withing each

Check out the dplyr package, specifically the mutate function. # Create new column based on existing column value df <- df %>% mutate(FirstDay = if(ID = 2, 5)) df Repeat as needed to capture all of the day/firstday combinations you want to account for. Like everything else in R, there are probably at least a dozen other ways to do this, between base R and all of the library packages

Hi I have just moved our 400 TB HPC storage from lustre to gluster. It is part of a research institute and users have very small files to big files ( few KB to 20GB) . Our setup consists of 5 servers, each with 96TB RAID 6 disks. All servers are connected through 10G ethernet but not all clients. Gluster volumes are distributed without any replication. There are approximately 80 million files in

Isn't anything in a data frame that is not explicitly numeric a *factor*? -Greg > -----Original Message----- > From: Peter Dalgaard BSA [mailto:p.dalgaard@biostat.ku.dk] > Sent: Friday, December 07, 2001 5:32 PM > To: Erich Neuwirth > Cc: r-devel@stat.math.ethz.ch > Subject: Re: [Rd] question > > > Erich Neuwirth

Can you please provide more details about your volume configuration and the version of gluster that you are using? Regards, Vijay On Fri, Jun 9, 2017 at 5:35 PM, mohammad kashif <kashif.alig at gmail.com> wrote: > Hi > > I have just moved our 400 TB HPC storage from lustre to gluster. It is > part of a research institute and users have very small files to big files > ( few

Hi Vijay Thanks for your quick response. I am using gluster 3.8.11 on Centos 7 servers glusterfs-3.8.11-1.el7.x86_64 clients are centos 6 but I tested with a centos 7 client as well and results didn't change gluster volume info Volume Name: atlasglust Type: Distribute Volume ID: fbf0ebb8-deab-4388-9d8a-f722618a624b Status: Started Snapshot Count: 0 Number of Bricks: 5 Transport-type: tcp

Hi, sorry, I'm an idiot.. and I know I'm missing something stupid.. I thought if we solve an underdetermine system with QR, my soln is: min ||x|| (L2 sense) such that Ax = b then say i have: > w <- matrix(c(1, 5), ncol=2) > sw = 2 > qrW = qr(t(w) %*% w) > qr.coef(qrW, t(w) %*% sw) [,1] [1,] 2 [2,] NA but we also have soln (0, 2/5) which obviously has a

Hi, We have outdated SOA information in our samba DNS. We used to have a DC1, and it is no more, however it's listed in our SOA records on both remaining DC's. I think this is not correct. I am under the impression that in order to get full failover support, all DC's need to have listed themselves as SOA. This is also what google tells me:

Hi Vijay I have enabled client profiling and used this script https://github.com/bengland2/gluster-profile-analysis/blob/master/gvp-client.sh to extract data. I am attaching output files. I don't have any reference data to compare with my output. Hopefully you can make some sense out of it. On Sat, Jun 10, 2017 at 10:47 AM, Vijay Bellur <vbellur at redhat.com> wrote: > Would it be

I've been using mclapply and have encountered situations where it gives errors or returns incorrect results. Here's a minimal example, which gives the error on R 2.15.2 on Mac and Linux: library(parallel) f <- function(x) NULL mclapply(1, f, mc.preschedule = FALSE, mc.cores = 1) # Error in sum(sapply(res, inherits, "try-error")) : # invalid 'type' (list) of argument

for the googleable r-help archives, I thought I would post what I wrote into my .Rprofile to automatically set some system information. the most relevant aspect is the determination of mc.cores. this is useful when users want to use the parallel package options(uname= system("uname", intern=TRUE)) options(os= if (getOption("uname")=="Darwin") "osx"

Would it be possible for you to turn on client profiling and then run du? Instructions for turning on client profiling can be found at [1]. Providing the client profile information can help us figure out where the latency could be stemming from. Regards, Vijay [1] https://gluster.readthedocs.io/en/latest/Administrator%20Guide/Performance%20Testing/#client-side-profiling On Fri, Jun 9, 2017 at

dear R readers---I thought I would post the following snippet of R code that makes by() like operations easier and faster on multicore machines for R novices and amateurs. I hope it helps some. YMMV. feel free to ignore. PS: I wish R had a POD-like documentation system for end users that are not writing full libraries. because it does not, I did not provide documentation ala '?mc.by'.

Dear members, I am using arfima in an mclapply construction (from the parallel package): Browse[2]> LYG <- mclapply(LYGH, FUN = arfima, mc.cores = detectCores()) ^C Browse[2]> LYG <- mclapply(LYGH[1:10], FUN = arfima, mc.cores = detectCores()) ^C Browse[2]> LYG <- mclapply(LYGH[1:2], FUN = arfima, mc.cores = detectCores()) ^C You can see that I am