similar to: Accessing data via url

Hi, I've got a problem with a function trying to return 2 data frames in a list. The code is as follow: function(x) { # code.... MyList<- list("a"=df.a,"b"=df.b) return(MyList) } and I got the following message: Error in list_to_dataframe(res, attr(.data, "split_labels")) : Results must be all atomic, or all data frames At first instance I thought it

Hi everyone, I have to fetch about 300 to 500 zipped archives from a remote ftp server. Each of the archive is about 1Mb. I know I can get it done by using download.file() in R, but I am curious that is there a faster way to do this using RCurl. For example, are there some parameters that I can set so that the connection does not need to be rebuilt....etc. A even simpler question is, how can I

I have a data set of individual trees and the plots that they are in: Tree Plot 56749 1 63494 1 87375 1 37494 2 92753 3 34847 3 38747 4 etc... So each plot is represented once for every individual that occurrs in it. Plots get different numbers of rows because there can be a different number of individuals in each plot. I want to make a data frame that consists of one

Hi, I am new to R and am using the ctree() function to do customer segmentation. I am using the following code to generate the tree: treedata$Response<-factor(treedata$Conversion) fit<-ctree(Response ~ .,controls=ctree_control(mincriterion=0.99,maxdepth=4),data=treedata) plot(fit) print(fit) The variable "Response" above equals 1 if the customer responded to an offering and

> datafilename="E:/my documents/r/sex/bysex1.csv" > data.sex=read.table(datafilename,header=T) > data.sex y.sex.age.region.c.n 1 1980,F,A,N,-18.15,13.61 2 1980,F,A,N,-18.61,13.04 3 1980,F,A,N,-18.81,12.32 4 1990,F,A,N,-21.12,11.7 5 1990,F,A,N,-20.77,11.58 6 1990,F,A,N,-21.6,13.34 7 1990,F,A,N,-21.78,12.6 > model.anova<-aov(c~age*sex,data=data.sex)

Hi, I am trying to reconcile anova table in R (summary(lm)) with individual t.test. datafilename="http://personality-project.org/R/datasets/R.appendix1.data" data.ex1=read.table(datafilename,header=T) #read the data into a table summary(lm(Alertness~Dosage,data=data.ex1)) gives: Call: lm(formula = Alertness ~ Dosage, data = data.ex1) Residuals:    Min     1Q Median     3Q    Max

(Resending after removing llvmdev at cs.uiuc.edu and using llvm-dev at lists.llvm.org) On Mon, Dec 7, 2015 at 3:08 PM, Easwaran Raman <eraman at google.com> wrote: > Hi Philip, > > Is there any update on this? I've been sending patches to get rid of the > callee hotness based inline hints from the frontend and move the logic to > the inliner. The next step is to use

On Thu, Dec 10, 2015 at 4:51 PM, Philip Reames <listmail at philipreames.com> wrote: > > > On 12/10/2015 04:29 PM, Xinliang David Li wrote: >> >> On Thu, Dec 10, 2015 at 4:00 PM, Philip Reames >> <listmail at philipreames.com> wrote: >>> >>> Given I didn't get any response to my original query, I chose not to >>> invest

Hi all, To implement more profile-guided optimizations, we’d like to use ProfileSummaryInfo (PSI) and BlockFrequencyInfo (BFI) from more passes of various types, under the new pass manager. The following is what we came up with. Would appreciate feedback. Thanks. Issue It’s not obvious (to me) how to best do this, given that we cannot request an outer-scope analysis result from an inner-scope

On 3/4/19 10:49 PM, Hiroshi Yamauchi wrote: > > > On Mon, Mar 4, 2019 at 10:55 AM Hiroshi Yamauchi <yamauchi at google.com > <mailto:yamauchi at google.com>> wrote: > > > > On Sat, Mar 2, 2019 at 12:58 AM Fedor Sergeev > <fedor.sergeev at azul.com <mailto:fedor.sergeev at azul.com>> wrote: > > > > On 3/2/19 2:38 AM,

On Sat, Mar 2, 2019 at 12:58 AM Fedor Sergeev <fedor.sergeev at azul.com> wrote: > > > On 3/2/19 2:38 AM, Hiroshi Yamauchi wrote: > > Here's a sketch of the proposed approach for just one pass (but imagine > more) > > https://reviews.llvm.org/D58845 > > On Fri, Mar 1, 2019 at 12:54 PM Fedor Sergeev via llvm-dev < > llvm-dev at lists.llvm.org>

Here's a sketch of the proposed approach for just one pass (but imagine more) https://reviews.llvm.org/D58845 On Fri, Mar 1, 2019 at 12:54 PM Fedor Sergeev via llvm-dev < llvm-dev at lists.llvm.org> wrote: > On 2/28/19 12:47 AM, Hiroshi Yamauchi via llvm-dev wrote: > > Hi all, > > To implement more profile-guided optimizations, we’d like to use > ProfileSummaryInfo

Overall seems fine to me. On 3/11/19 8:12 PM, Hiroshi Yamauchi wrote: > Here's a revised approach based on the discussion: > > - Cache PSI right after the profile summary in the IR is written in > the pass pipeline. This would avoid the need to insert > RequireAnalysisPass for PSI before each non-module pass that needs it. > PSI can be technically invalidated but unlikely

On Thu, Dec 10, 2015 at 4:00 PM, Philip Reames <listmail at philipreames.com> wrote: > Given I didn't get any response to my original query, I chose not to invest > time in this at the time. I am unlikely to get time for this in the near > future. > > On 12/07/2015 03:13 PM, Easwaran Raman wrote: > > (Resending after removing llvmdev at cs.uiuc.edu and using >

Hi, we got the following assert: assert(!Working[0].isLoopHeader() && "entry block is a loop header"); [in BlockFrequencyInfoImpl<BT>::tryToComputeMassInFunction(), BlockFrequencyInfoImpl.h] on a Hexagon target - the entry block is a loop header. Has someone seen this assert on other targets? What would be a preferable way to fix it: - extend BlockFrequency pass to

> On 2015-Jun-04, at 12:45, Duncan P. N. Exon Smith <dexonsmith at apple.com> wrote: > >> On 2015-Jun-04, at 12:28, Ivan Baev <ibaev at codeaurora.org> wrote: >> >> Hi, we got the following assert: >> >> assert(!Working[0].isLoopHeader() && "entry block is a loop header"); >> >> [in

On 3/14/19 2:04 AM, Hiroshi Yamauchi wrote: > > > On Wed, Mar 13, 2019 at 2:37 PM Fedor Sergeev <fedor.sergeev at azul.com > <mailto:fedor.sergeev at azul.com>> wrote: > >> >> - Add a new proxy ModuleAnalysisManagerLoopProxy for a loop pass >> to be able to get to the ModuleAnalysisManager in one step and >> PSI through it. >

Hi there, I checked google for aov. usually one uses summary to see whether the p-value is small. but I want to put aov in my script. how can I get the p-value, (0.1115, 0.6665, 0.6665 in the following example)? thanks YU > datafilename="http://personality-project.org/r/datasets/R.appendix2.data" > data.example2=read.table(datafilename,header=T) > aov.ex2 =

Hey, I am trying to use the BlockFrequencyInfoWrapperPass to obtain hotness information in my LLVM pass. Attached is a minimal example of code which creates a SIGSEGV. The pass calls AU.addRequired<BlockFrequencyInfoWrapperPass>(); in getAnalysisUsage(..). The problem exists with changed and unchanged IR. The binary is instrumented like this: clang input.bc -fprofile-generate -o

Dear all I am a newbie to R and I would appreciate it very much if someone can give me some advice on this. Please note that I am not a programmer so some of the questions might sound really stupid. I would like to compute McDonald's omega calculation using R, I'm aware I can use the omega function in the psych package. But I'm really not sure how to do it. I have read these two