search for: merges

With the ATI bug I was hitting earlier fixed, only my btrfs partition continues to show high cpu usage for some operations. Rsync, git pull, git checkout and svn up are typicall operations which trigger the high cpu usage. As an example, this perf report is from using git checkout to change to a new branch; the change needed to checkout 208 files out of about 1600 total files. du(1) reports

Well for a long time now my wine menu entry in gnome has been gone. Most threads I read all say to fine the <deleted> tag in .config/menus/applications.menu but mine doesn't have it.

So I needed to merge 17 .csv files, and did so by brute force, but I might need to do so again. Anyone have suggestions for a for loop that might do the below for me (where a:r are separate .csv files) ab<-merge(a,b,all=TRUE) cd<-merge(c,d,all=TRUE) ef<-merge(e,f,all=TRUE) gh<-merge(g,h,all=TRUE) ij<-merge(i,j,all=TRUE) kl<-merge(k,l,all=TRUE) no<-merge(m,n,all=TRUE)

...courage people to make reasonable separate commits to master which are sensible (reviewable, buildable, etc) in isolation. And, to make it so the history is more easily understandable to humans. It's not only that we don't want merge commits -- we actually don't really want people doing merges, in general. But, here we actually *do* have a merge, because flang was developed externally. This is an exceptional circumstance (and I'm sure we'll have a few more). Using a merge commit in this circumstance makes it easier for humans looking at history to understand what's going on...

Hello, I am attempting to merge 8 different data sets into a "grand merge" data set; all their variable names are common except for the the gas measured. However, when I did a quick stat summary comparison of merged data with unmerged data, it turned out that R mysteriously duplicated thousands of values in the merged set and I have no idea why. I've not had this problem with merge

Hi, all. Last week I posted some code for extracting subtrees of trees in hclust format. Petra Steiner quickly found an example for which the code breaks, and sent it to me. The problem seems to be that I had not considered the possibility of trees with unlabeled nodes. In the new version of f.make.subtree (below), I steal some code from plot.hclust to assign labels if there are none. That

Hi, I have some protein array data, each array in a separate text file. So I read them in and try to combine them into a single data frame by using merge(). see code below (If you download the attached data files into a specific folder, the code below should work): fls<-list.files("C:\\folder_of_download",full.names=T) ## get file names prot<-list() ## a list to contain

...atthias Braun via llvm-dev <llvm-dev at lists.llvm.org> writes: > - Even in the long term I would vote to stay with linear history, I > see little benefits in having "correct" origin information of a commit > that the merging model provides. We often revert entire feature merges when problem arise. It's much easier to do in a merging workflow because you have a single commit to revert. In the end I don't really care which model LLVM uses. I just want to provide as much working knowledge as I can based on experience doing exactly this kind of SVN->git transiti...

Hello, My problem is that I would like to merge multiple files with a common column but merge accepts only two data.frames to merge. In the real situation, I have 26 different data.frames with a common column. I can of course use merge many times (see below) but what would be more sophisticated solution? For loop? Any ideas? DF1 <- data.frame(var1 = letters[1:5], a = rnorm(5)) DF2 <-

Hi, As part of the migration of LLVM's source code to github, we need to update our developer policy with instructions about how to interact with the new git repository. There are a lot of different topics we will need to discuss, but I would like to start by initiating a discussion about our merge commit policy. Should we: 1. Disallow merge commits and enforce a linear history by

Hello, everyone I have a piece of code that looks like this: mrets <- merge(mrets, BMM.SR=apply(mrets, 1, MyFunc, ret="BMM.AV120", stdev="BMM.SD120")) mrets <- merge(mrets, GM1.SR=apply(mrets, 1, MyFunc, ret="GM1.AV120", stdev="GM1.SD120")) mrets <- merge(mrets, IYC.SR=apply(mrets, 1, MyFunc, ret="IYC.AV120",

Hi everyone, I'm currently working on a new function merging optimization that is more general than the current LLVM function merging optimization that works only on identical functions. I would like to know if the community has any interest in having a more powerful function merging optimization. ---- More Details ---- Up until now, I have been focusing on the quality of the code

Hi All, I am looking into merging 3 data sets I know how to do that by merging data1 with data2 and then merging the result with data 3. I was wondering if it can be done all at once so I tried, M<-merge(data1,data2,data3, by=?ID?) It does not work! Any ideas? -- View this message in context: http://www.nabble.com/merging-3-data-sets-at-once-tp17658873p17658873.html Sent from the R help

Actually I have collected some pointer information in the form [ p -> a,c ]. Now suppose at some node I have information as [p->a,c]. Now i want to find a merge node above this node where this information is actually geting merged. So if I get a merge node above this, I can check in its predecessors if their out has only [p->a] or [p->c] and if not so then I will look for the next

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I'd like to be able to cut dendrograms at a height I specify and then plot the resulting subtrees. I wanted to use the dendrogram object for this purpose because there doesn't seem to be a canned way to cut a hclust object and get a list of hclust objects, but there is a function (cut) that does that for dendrograms. The problem I'm having is that when I plot a dendrogram, I

I've downloaded the "data.table" package from CRAN and R-Forge and still can't utilize merge.data.table for faster merges. How do I make this function visible? > install.packages("data.table",repos="http://R-Forge.R-project.org") trying URL 'http://R-Forge.R-project.org/src/contrib/data.table_1.5.1.tar.gz' Content type 'application/x-gzip' length 616492 bytes (602 Kb) opened URL...

ambika at cse.iitb.ac.in wrote: > Actually I have collected some pointer information in the form [ p -> a,c > ]. Now suppose at some node I have information as [p->a,c]. Now i want to > find a merge node above this node where this information is actually > geting merged. > So if I get a merge node above this, I can check in its predecessors if > their out has only [p->a]

Hello, I merged my test commit successfully. (./utils/release/merge.sh --proj llvm --rev 46043 -srcdir ../llvm/) ... D46043 as "Merging r46043" https://reviews.llvm.org/rL330799 But I have issues with other patch - https://reviews.llvm.org/D45418 I ran ./utils/release/merge.sh --proj llvm --rev 45418 -srcdir ../llvm/ # Updating tree Updating '.': At revision 330799. #

Hello I have two data frames, SNP4 and SNP1: > head(SNP4) Animal Marker Y 3213 194073197 P1001 0.021088 1295 194073197 P1002 0.021088 915 194073197 P1004 0.021088 2833 194073197 P1005 0.021088 1487 194073197 P1006 0.021088 1885 194073197 P1007 0.021088 > head(SNP1) Animal Marker x 3213 194073197 P1001 2 1295 194073197 P1002 1 915 194073197