similar to: Extract

Thank you and sorry for the confusion. The desired result should have 8 variables as a comma separated in each line. The string variable is considered as one variable. The output of your script is wfine for me. Thank you! On Fri, Jul 19, 2024 at 1:00?PM Ebert,Timothy Aaron <tebert at ufl.edu> wrote: > > The desired result is odd. > 1) It looks like the string is duplicated in

Thank you Jeff and Bert for your help! The components of the string could be nixed (i.e, numeric, character or date). Once that is splitted it would be easy for me to format it accordingly. On Fri, Jul 19, 2024 at 2:10?PM Bert Gunter <bgunter.4567 at gmail.com> wrote: > > I did not look closely at the solutions that you were offered, but > note that you did not specify in your

Val: I wanted to add here a base R solution to your problem that I realize you can happily ignore. However, in the course of puzzling over how to do it using the R native pipe syntax ("|>") , I learned some new stuff that I thought others might find useful, and it seemed sensible to keep the code with this thread for comparison. I want to acknowledge that in the course of my labor,

Thank you Bert! However, the last line of the script. dat |> names() |> _[4:8] <- paste0("s", 1:5) is giving me an error as shown below Error: pipe placeholder can only be used as a named argument Thank you! On Sat, Jul 20, 2024 at 7:41?PM Bert Gunter <bgunter.4567 at gmail.com> wrote: > > Val: > I wanted to add here a base R solution to your problem that I

I did not look closely at the solutions that you were offered, but note that you did not specify in your post whether the numbers in your string were to be character or numeric variables after they are broken out into their own columns. I believe that they are character in the solutions, but you should check this. If you want them as numeric, e.g., for further processing, you will need to convert

We can use read.table for a base R solution string <- read.table(text = dat$string, fill = TRUE, header = FALSE, na.strings = "") names(string) <- paste0("S", seq_along(string)) cbind(dat[-3], string) On Fri, Jul 19, 2024 at 12:52?PM Val <valkremk at gmail.com> wrote: > > Hi All, > > I want to extract new variables from a string and add it to the

The desired result is odd. 1) It looks like the string is duplicated in the desired result. The first line of data has "15, xc, Ab", and the desired result has "15, xc, Ab, 15, xc, Ab" 2) The example has S1 through S5, but the desired result has data for eight variables in the first line (not five). 3) The desired result has a different number of variables for each line. 4)

Nice! -- Let read.table do the work of handling the NA's. However, even simpler is to use the 'colnames' argument of read.table() for the column names no? string <- read.table(text = dat$string, fill = TRUE, header = FALSE, na.strings = "", col.names = paste0("s", 1:5)) dat <- cbind(dat, string) -- Bert On Sun, Jul 21, 2024 at 10:16?AM Gabor

Fixing col.names=paste0("S", 1:5) assumes that there will be 5 columns and we may not want to do that. If there are only 3 fields in string, at the most, we may wish to generate only 3 columns. On Sun, Jul 21, 2024 at 2:20?PM Bert Gunter <bgunter.4567 at gmail.com> wrote: > > Nice! -- Let read.table do the work of handling the NA's. > However, even simpler is to use

Base R. Regarding code improvements: 1. Personally I find (\(...) ...)() notation hard to read (although by placing (\(x), the body and )() on 3 separate lines it can be improved somewhat). Instead let us use a named function. The name of the function can also serve to self document the code. 2. The use of dat both at the start of the pipeline and then again within a later step of the pipeline

As always, good point. Here's a piped version of your code for those who are pipe afficianados. As I'm not very skilled with pipes, it might certainly be improved. dat <- dat$string |> read.table( text = _, fill = TRUE, header = FALSE, na.strings = "") |> (\(x)'names<-'(x,paste0("s", seq_along(x))))() |>

Thanks. I found this to be quite informative and a nice example of how useful R-Help can be as a resource for R users. Best, Bert On Mon, Jul 22, 2024 at 4:50?AM Gabor Grothendieck <ggrothendieck at gmail.com> wrote: > > Base R. Regarding code improvements: > > 1. Personally I find (\(...) ...)() notation hard to read (although by > placing (\(x), the body and )() on 3

I am confused when trying the function survfit. my question is: what does the survival curve given by plot.survfit mean? is it the survival curve with different covariates at different points? or just the baseline survival curve? for example, I run the following code and get the survival curve #### library(survival) fit<-coxph(Surv(futime,fustat)~resid.ds+rx+ecog.ps,data=ovarian)

Using R, I would like to find out which Samples (S1, S2, S3, S4, S5) fulfill the following criteria:contain minimally one value (x, y or z) bigger than 4. Any ideas? Thanks, Alex. > data Sample x y z 1 S1 -0.3 5.3 2.5 2 S2 0.4 0.2 -1.2 3 S3 1.2 -0.6 3.2 4 S4 4.3 0.7 5.7 5 S5 2.4 4.3 2.3

Hi Jean-Marc, Thanks a lot for reviewing this huge assembly function! silk_warped_autocorrelation_FIX_c()'s kernel part is for( n = 0; n < length; n++ ) { tmp1_QS = silk_LSHIFT32( (opus_int32)input[ n ], QS ); /* Loop over allpass sections */ for( i = 0; i < order; i++ ) { /* Output of allpass section */ tmp2_QS = silk_SMLAWB(

This is a great idea. But the order (psEncC->shapingLPCOrder) can be configured to 12, 14, 16, 20 and 24 according to complexity parameter. It's hard to get a universal function to handle all these orders efficiently. Any suggestions? Thanks, Linfeng On Mon, Feb 6, 2017 at 12:40 PM, Jean-Marc Valin <jmvalin at jmvalin.ca> wrote: > Hi Linfeng, > > On 06/02/17 02:51 PM,

Hi all, i had a replica 2 gluster 3.12 between S1 and S2 (1 brick per node) geo-replicated to S5 where both S1 and S2 were visible in the geo-replication status and S2 "active" while S1 "passive". I had to replace S1 with S3, so I did an "add-brick replica 3 S3" and then "remove-brick replica 2 S1". Now I have again a replica 2 gluster between S3 and S2

Hi Jean-Marc, Thanks for your suggestions. Will get back to you once we have some updates. Linfeng On Mon, Feb 6, 2017 at 5:47 PM, Jean-Marc Valin <jmvalin at jmvalin.ca> wrote: > Hi Linfeng, > > On 06/02/17 07:18 PM, Linfeng Zhang wrote: > > This is a great idea. But the order (psEncC->shapingLPCOrder) can be > > configured to 12, 14, 16, 20 and 24 according to

Sorry to bother you kind folks again with my questions. I am trying to learn as much as I can about all this, and I will admit that I don't have the proper background, but I hope that someone can at least point me in the correct direction. I have created a test matrix for what I want to do: s1 s2 s3 s4 s5 s1 10 5 0 8 7 s2 5 10 0 0 5 s3 0 0 10 0 0 s4 8 0 0 10 0 s5 7

I attached a new patch with small cleanup (disassembly is identical as the last patch). We have done the same internal testing as usual. Also, attached 2 failed temporary versions which try to reduce code size (just for code review reference purpose). The new patch of silk_warped_autocorrelation_FIX_neon() has a code size of 3,228 bytes (with gcc). smaller_slower.c has a code size of 2,304