similar to: Loop vectorization and unsafe floating point math

Hi R-helpers I would like to plot some planes which are perpendicular to the x-y plane, such as x=y. Is there a way to do this in wireframe? I realize that I am not plotting a function of x, y since there are infinite number of z's that satisfy the above relation.... Hmm... Somewhat related, I would also like to plot a line in 3 d space... Finally, if you are feeling really brave, I

I am trying to use lme to fit a mixed effects model to get the same results as when using the following SAS code: proc mixed; class refseqid probeid probeno end; model expression=end logpgc / ddfm=satterth; random probeno probeid / subject=refseqid type=cs; lsmeans end / diff cl; run; There are 3 genes (refseqid) which is the large grouping factor, with 2 probeids nested within each refseqid,

Hi. If I have a vector, v_1, and another vector of positive integers, i_1, the same length as v_1, then rep(v_1,i_1) will repeat v_i[j] exactly i_1[j] times, like so: >rep(c(1,2,3),c(3,2,1)) [1] 1 1 1 2 2 3 > I'd like to do the same sort of thing where I replace v_1 with a matrix, and the jth row of the matrix is repeated i_1 times. Obviously, I could do this with for loops, like

Hello, Great to see the new metafor package for meta-analysis. I would like to perform a meta-analysis in which I initially calculate the intercept of the model with a nested random-effects structure. In lme, this would be model<- lme(v3~1, random=~1|species/study, weights = varFixed(~Wt), method = "REML") where multiple effects sizes are measured for some studies and more than

I am trying to use lme to fit a mixed effects model to get the same results as when using the following SAS code: proc mixed; class refseqid probeid probeno end; model expression=end logpgc / ddfm=satterth; random probeno probeid / subject=refseqid type=cs; lsmeans end / diff cl; run; There are 3 genes (refseqid) which is the large grouping factor, with 2 probeids nested within each refseqid,

Hello! In the example below the Reduce() function by default assigns "a" to be the last accumulated value and "b" to be the current value in "x". I could not find this documented anywhere as the default settings for the Reduce() function. Does any sort of documentation for this behavior exist? x <- c(0,0,0,0,0,1,0,0,0,5,0,0,0,7,0,0,0,8,5,10)

Dear R Gurus: I read somewhere that functions are considered vectors. Is this true, please? thanks Edna Bell

Hello all, Is there a way in R to compute the multivariate normal density of every pair of entries in a vector efficiently instead of using for loop? For example Suppose I have a vector a=c(v_1,...,v_p)=c(0.5343909, -0.7784353, -0.0568370, 1.8772838, -1.3183407, 0.8227418,...) I want to compute density(v_i, v_j) for every pair of entries (i,j) (i!=j) in a. The joint bivariate distribution

Hello, I m trying to set vector width using #pragma clang loop vectorize_width(32) but i m getting width 8 for the following kernel; #define M 128 #define N 128 #define SQRT_FUN(x) sqrtf(x) int main(int argc, char** argv) { /* Variable declaration/allocation. */ double float_n = (double)N; double data[N*M]; double corr[M*M]; double mean[M]; double stddev[M]; uint32_t

Am Mi., 2. Okt. 2019 um 07:08 Uhr schrieb Florian Hahn via llvm-dev <llvm-dev at lists.llvm.org>: > The other thing is that with the patch behaviour is slightly changed and we could get a diagnostic we didn't get before: > > warning: loop not vectorized: the optimizer was unable to > perform the requested transformation; the transformation might be disabled or >

Can I ask a small stat. related question here? Suppose I have two predictors for a time series processes and accuracy of predictor is measured from MSEs. My question is, if two predictors give same MSE then, necessarily they have to be identical? Can anyone provide me any counter example? Thanks. -- View this message in context:

Hi Michael and Florian, ( + llvm-dev for visibility) I would like to quickly follow up on "Pragma vectorize_width() implies vectorize(enable)", which got reverted with commit 858a1ae for 2 reasons, see also that revert commit message. Ignore the assert, that's been fixed now. The other thing is that with the patch behaviour is slightly changed and we could get a diagnostic we

Hi, I have a data-matrix: > PID sato hrs fim health 214 3 4.376430 6.582958 5 193 6 4.361825 3.138525 6 8441 6 4.205771 3.835886 7 7525 6 4.284489 3.245139 6 6806 7 4.168926 2.821833 7 5682 7 1.788707 1.212653 7 5225 6 1.651463 1.436980 7 4845 6 1.692710 1.267359 4 4552 5 1.686448 1.220539 6

below. Dan ___________________________________________________________________________ Dan Yocum | Phone: (630) 840-8525 Linux/Unix System Administrator | Fax: (630) 840-6345 Computing Division OSS/FSS | email: yocum@fnal.gov .~. L Fermi National Accelerator Lab | WWW: www-oss.fnal.gov/~yocum/ /V\ I P.O. Box 500 |

Dear All, Thank you for the replies to my first thread here: http://r.789695.n4.nabble.com/global-optimisation-with-inequality-constraints-td3799258.html. So far the best result is achieved via a penalised objective function. This was suggested by someone on this list privately. I am still looking into some of the options mentioned in the original thread, but I have been advised that there may

Hi, everybody. I am working processing EEG data from 1000 pacients. I have a specific syntax to perform the Spectral Analysis and a loop to analyse all subjects. each subject data are in separate folders (P1, P2 P3...) My question is: in some cases, some errors can appear in one subject. I want to know if is possible to jump to the next subject and perform the same syntax , exibiting an error

I'm not compiling it to x86. Should loop optimizer something independent of the target? If so, should the vectorized code on IR level? On Aug 12, 2016 11:39 AM, "Daniel Berlin" <dberlin at dberlin.org> wrote: > cat > test.c > > #define SIZE 128 > > void bar(int *restrict A, int* restrict B,int K) { > > #pragma clang loop vectorize(enable)

Hi Daniel, I increased the size of your test to be 128 but -stats still shows no loop optimized... Xiaochu On Aug 12, 2016 11:11 AM, "Daniel Berlin" <dberlin at dberlin.org> wrote: > It's not possible to know that A and B don't alias in this example. It's > almost certainly not profitable to add a runtime check given the size of > the loop. > > >

Hi Andrey, Thanks. I found even when loop vectorizer and SLP vectorizer are enabled, my simple test still not get optimized. I also tried clang pragma in my test to force vectorization. What do you think is the problem? Test: #define SIZE 8 void bar(int *A, int* B,int K) { #pragma clang loop vectorize(enable) vectorize_width(2) unroll_count(8) for (int i = 0; i < SIZE; ++i) A[i]

Hi -- I have found a bug in an HPC code where llvm is vectorizing a loop on Skylake that has an obvious recurrence. I derived a small test case based on the original benchmark below: /*****************************************************************/ static void __attribute__ ((always_inline)) one( const int *restrict in, const int *const end, const unsigned shift, int *const restrict index,