search for: cond3

Hi everyone, I'm having some trouble with my ifelse statements. I'm trying to put 12 conditions within 3 groups. Here is the code I have so far: dat$cond <- ifelse(test = dat$cond == "cond1" | dat$cond == "cond2" | dat$cond == "cond3" dat$cond == "cond4" yes = "Uniform" no = ifelse(test = dat$cond == "cond5" | dat$cond == "cond6") | dat$cond == "cond7" dat$cond == "cond8" yes = "Biased Low"...

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Estimada comunidad, tengo el siguiente problema: 1. tengo un data.frame con varias columnas, algunas numericas, otras son variables categoricas 2. necesito hacer un calculo simple sobre este data.frame (un promedio ponderado de los valores de la columna 7), pero solo para las filas que cumplan ciertos criterios 3. en ocasiones ninguna de las filas

Hi, I've been working on a Blackfin backend (llvm-3.6.0) based on the previous one that was removed in llvm-3.1. llc generates codes like this: 29 p1 = r2; 30 r5 = [p1]; 31 p1 = r2; 32 r6 = [p1 + 4]; 33 r5 = r6 + r5; 34 r6 = [p0 + -4]; 35 r5 *= r6; 36 p1 = r2; 37 r6 = [p1 + 8]; 38 p1 = r2; p1 and r2 are in different register classes. A p*

Hi all, suppose there is a vector y with rownames: > y cond1 cond2 cond3 cond4 78.952 87.308 86.490 74.040 how can I easily plot this vector using the rownames? plot(y) gives me a plot with a x-axis from 1 to 4 in 0.5 steps, also plot(rownames(y), y) and plot(y ~ rownames(y) don't work. I know I can build a x-axis with axis(1, ...), but in this case I need a cha...

Dear R users, I have a matrix a and a classification vector b such that > str(a) num [1:50, 1:800000] and > str(b) Factor w/ 3 levels "cond1","cond2","cond3" I'd like to do an anova on all 800000 columns and record the F statistic for each test; I currently do this using f.stat.vec <- numeric(length(a[1,]) for (i in 1:length(a[1,]) { f.test.frame <- data.frame(nums = a[,i], cond = b) aov.vox <- aov(nums ~ cond, data = f.test.fr...

...veryone, > >I'm having some trouble with my ifelse statements. > >I'm trying to put 12 conditions within 3 groups. Here is the code I >have so >far: > >dat$cond <- ifelse(test = dat$cond == "cond1" | dat$cond == "cond2" | >dat$cond == "cond3" dat$cond == "cond4" > yes = "Uniform" > no = ifelse(test = dat$cond == "cond5" | dat$cond == >"cond6") | dat$cond == "cond7" dat$cond == "cond8" > yes = "Biased L...

Hi: I have a large dataset mydata, of 1000 rows and 1000 columns. The rows have gene names and columns have condition names (cond1, cond2, cond3, etc). mydata<- read.table(file="c:/file1.mtx", header=TRUE, sep="") I applied PCA as follows: data_after_pca<- prcomp(mydata, retx=TRUE, center=TRUE, scale.=TRUE); Now i get 1000 PCs and i choose first three PCs and make a new data frame new_data_frame<- cbind(dat...

...r %tmp = load i32* %cond.addr ; <i32> [#uses=1] %tobool = icmp ne i32 %tmp, 0 ; <i1> [#uses=1] %tmp1 = load i32* %a.addr ; <i32> [#uses=1] %tmp2 = load i32* %b.addr ; <i32> [#uses=1] %cond3 = select i1 %tobool, i32 %tmp1, i32 %tmp2 ; <i32> [#uses=1] store i32 %cond3, i32* %retval %0 = load i32* %retval ; <i32> [#uses=1] ret i32 %0 } define i32 @main() nounwind { entry: %retval = alloca i32 ; <i32*> [#uses=3...

...4 D 2 5 D 3 6 E 1 1 E 2 4 E 3 6 Now I wanted to extract the x of those groups where condition 2 and condition 3 do both exist. In this example that would be groups A, D and E and the extracted pairs e.g.: cond2 cond3 4 6.5 5 6 4 6 (I need this for a wilcoxon test) I would be happy if one could give me a hint, probably its very simple... Thanks Stefan Grosse

...%cond.addr ; <i32> [#uses=1] > %tobool = icmp ne i32 %tmp, 0 ; <i1> [#uses=1] > %tmp1 = load i32* %a.addr ; <i32> [#uses=1] > %tmp2 = load i32* %b.addr ; <i32> [#uses=1] > %cond3 = select i1 %tobool, i32 %tmp1, i32 %tmp2 ; <i32> [#uses=1] > store i32 %cond3, i32* %retval > %0 = load i32* %retval ; <i32> [#uses=1] > ret i32 %0 > } > > define i32 @main() nounwind { > entry: > %retval = alloca i32...

Dear R users, I have a data where I desire to subset according to certain conditions. However, the script is very messy as there are about 30 distinct conditions. (i.e. same script but with different conditions) I would like to make a user defined function so that I can input the desired conditions and just get the results accordingly. Below is an arbitrary data set & sample statements

...the Anova and get the model object (the data are at https://docs.google.com/open?id=0B6-m45Jvl3ZmOVFTYVpZYV9sUUk). data <- as.matrix( read.table( file="EEGpriming.txt", header=T, sep="\t") ) Condition <- c( rep("Cond1", 6), rep("Cond2", 6), rep("Cond3", 6) ) Region <- factor( rep( c("la", "ma", "ra", "lp", "mp", "rp"), 3 ) ) library(car) model.Anova <- Anova( lm(eeg ~ 1), idata=data.frame(Condition, Region), idesign=~Condition*Region ) ) I'm now trying to do post-hoc c...

Dear Rxperts! I was wondering if it is possible to write a function which can take in argument of a subset or condition.. Of course, I am aware of the alternate methods like coplot, par.plot, xyplot etc... I am specifically interested in using conditions/subsets with "plot".. A simple fragmented example is shown here.. pltit <- function(y,x,dat,dat1,dat2,sbst) { plot(y~x, data=dat,

Hi friends, I have a matrix with following format. group var1 var2 .......varN c1 group1 1.2399 1.4990....-1.4829 c2 group4 0.8989 0.7849.....1.8933 ... ... c100 group10 ..... I want to draw a profile plot of each condition c1 to c100, which rows in above matrix and each line representing a row should be uniquely colored according to the group(1 to 10). I think this is simple task

Hi Sean, Thank you for reminding me. It looks like it get lost among tons of emails and other tasks. I’ll check if the code size issues still exist. Thanks, Evgeny Astigeevich From: Sean Fertile <sd.fertile at gmail.com> Date: Monday, 29 January 2018 at 19:52 To: Florian Hahn <Florian.Hahn at arm.com> Cc: Evgeny Astigeevich <Evgeny.Astigeevich at arm.com>, Graham Yiu <gyiu

Hello All, This conversations seems to have fizzled out and I would like to try to revive it. My intention is to pick up where Graham left off with enabling partial-inlining by default. On Sat, Dec 9, 2017 at 7:47 AM, Florian Hahn via llvm-dev < llvm-dev at lists.llvm.org> wrote: > Hi, > > On 13/11/2017 14:47, Evgeny Astigeevich via llvm-dev wrote: > >> Hi Graham,

...se1: %gep2 = getelementptr i32* %a, i32 2 %val2 = load i32* %gep2 %cond2 = icmp ugt i32 %val2, 2 br i1 %cond2, label %then2, label %else2, !prof !0 then2: call void @error(i32 %i, i32 1, i32 %b) br label %else2 else2: %gep3 = getelementptr i32* %a, i32 3 %val3 = load i32* %gep3 %cond3 = icmp ugt i32 %val3, 3 br i1 %cond3, label %then3, label %else3, !prof !0 then3: call void @error(i32 %i, i32 1, i32 %b) br label %else3 else3: %gep4 = getelementptr i32* %a, i32 4 %val4 = load i32* %gep4 %cond4 = icmp ugt i32 %val4, 4 br i1 %cond4, label %then4, label %else4, !pro...

On Tue, Oct 18, 2011 at 6:58 PM, Jakob Stoklund Olesen <stoklund at 2pi.dk>wrote: > > On Oct 18, 2011, at 5:22 PM, Chandler Carruth wrote: > > As for why it should be an IR pass, mostly because once the selection dag >> runs through the code, we can never recover all of the freedom we have at >> the IR level. To start with, splicing MBBs around requires known about

Hello everyone, I am running a mixed effects model where I have two fixed factors, one with 2 levels and one with 4, and their interaction. Let's say these are my factors and their levels: FirstFactor: 1, 2 SecondFactor: A, B, C, D For the interaction, I am interested in the four two-way comparisons, not the two four-way comparisons. In other words, I want to test whether 1A is

...step.     3) Vector code generation support for inner loop with multiple exits       for (i=0;i<N;i++){ // vectorize here       // branches may be here       if (cond(1)) {         // branches may be here         while (cond1(i)){           .           if (cond2) break;           .           if (cond3) break;           .         }         // branches may be here       }       // branch may be here     }   ============================ Future Work beyond this RFC: ============================   * Outer loop auto-vectorization legality analysis   * Outer loop auto-vectorization cost model   * Cost...