similar to: fft and wavenumber

I have a matrix named "spec" (see below), it is a 6x3 matrix, and each element of spec is a list. For example, spec[1,"wavenumber"] is a list, and it contains 1876 numeric numbers and NAs. I want to replace the NAs to zero, but don't know how to change it, the difficulty may be all the elements are of the class list, so it is hard to change. Thank you for your help!

Hi all, I've been trying to run a model using R2winBUGS, and recurrently I get the message: "Error in FUN(X[[3L]], ...) : invalid to change the storage mode of a factor" My model is the following: sink("GLMM_Poisson.txt") cat(" model{ mu~dnorm(0,0.01) beta1~dnorm(-1,1) for(j in 1:nsite){ alpha[j]~dnorm(mu.alpha,tau.alpha) } mu.alpha~dnorm(0,0.01)

Dear Dovecot-Admins, I've set up a pair of Dovecot Servers, please find config of server one attached. They are configured to replicate changes over a tcp connection using port 12345, set up as described in http://wiki2.dovecot.org/Replication article page. Adding the user postboxes to replication using "doveadm replicator add '*' " syncs the mailboxes as expected.

I am interested in running the SARA scanning product and it was indicated that to run it effectively that certain SAMBA products should be obtained as well (see email below)Could you let me know which products are needed for running SARA, and if they can be freely obtained form the SAMBA site? Thanks, paul relevant email: -----Original Message----- From: Bob Todd [mailto:toddr@arc.com] Sent:

Hi Sarah, the loop vectorizer runs not on the C code but on LLVM IR this c code was lowered to. Before the loop vectorizer runs many other optimization change the shape of this IR. You can see in the LLVM IR you referenced below, a preceding LLVM IR transformation has change your loop from: > for(int k=20;k<50;k++) > dataY[k] = dataY[k-1]; to > int a = d[19]; >

Dear all, I have one Model (M3) fitted using the lme package, and I have checked the correlation structure of within-group errors using plot(ACF (M3,maxLag=10),alpha=0.05) But now I am not sure how to interpret this plot for the empirical autocorrelation function. The problem is that I am used to see/interpret diagrams in which all the autocorrelation Lags, except lag-1, are inside the

ioemu: fix SDL mouse events processing - GetRelativeMouseState always returns the last position, so when the polling loop gets several mouse events in one go, we would send useless ''no move'' events. - So as to make sure we don''t miss any mouse click / double click, we should not use GetRelativeMouseState() to get the button state, but keep records of the button

Notice that the code you provided, for globals and stack allocations, at least, is semantically equivalent to: int a = d[19]; for(int k = 20; k < 50; k++) dataY[k] = a; Like so, the load you see missing was redundant, probably hoisted by GVN/PRE and replaced with "%.pre". H. On Sun, Nov 3, 2013 at 11:26 AM, Sara Elshobaky <sara.elshobaky at gmail.com>wrote: >

Thank you so much to Mark and Gabor for their codes (please see below). Now I solved my problem : ) Best, Jorge # --------- Mark's code res=sapply(colnames(dx), function(.colname) { if (.colname %in% colnames(dy)) dy[,.colname] else {numeric(nrow(dy))} }) res # --------- Gabor's code res=as.matrix(replace(as.data.frame(0 * dx), colnames(dy), dy)) # If dx were a data frame

Actually what I meant in my original loop, that there is a dependency between every two consecutive iterations. So, how the loop vectorizer says 'we can vectorize this loop'? for(int k=20;k<50;k++) dataY[k] = dataY[k-1]; From: Henrique Santos [mailto:henrique.nazare.santos at gmail.com] Sent: Sunday, November 03, 2013 4:28 PM To: Sara Elshobaky Cc: <llvmdev at

I am trying to add 2 stdev error bars to lattice type plots: panel.ebar<-function(x,y,dy=NULL,...) { panel.xyplot(x,y,...) panel.segments(x,y-dy,x,y+dy,...) } Then: xyplot(y~x|fc,data=dat,dy=dat$dy,panel=panel.ebar) This adds error bars but they are not conditioned on the factor fc. xyplot(y+I(y-dy)+I(y+dy)~x|fc,data=dat) This produces 3 series of points in different colors, conditioned

I want to implement the following algorithm in R: I want to split my data, use a t test to compare both means of the groups to see if they significantly differ from each other. If this is a yes (p < alpha) I want to split again (into 4 groups) and do the same procedure twice, and stop otherwise (here the problem arises). As a final result I would have different groups of data. I made some

Lets say I have the following data frame. df = data.frame(word = c("David", "James", "Sara", "Jamie", "Jon")) df I was trying to place brackets , [ ] , around each string. I'll be exporting it with write.table and quotes=FALSE, so it will eventually look like: [David] [James] [Sara] .... Can anyone help with this task? I'd like to

So, what is the use of the profile passes in LLVM? Also, does llvm detect hot blocks of code for recompilation? On Mon, Oct 7, 2013 at 4:44 PM, Amara Emerson <amara.emerson at arm.com> wrote: > No, the JIT does not do any profile guided optimizations for any > architecture. It just uses the static compilation components before loading > the object into memory and running its own

When legend() is used with the angle argument as follows, not only the boxes beside the legend text, but also the whole legend box is filled with shading lines. I think this is not intended: plot(1:10) legend(8, 4, c("A", "B"), angle=c(10, 80), fill=NULL, density=20) I'd suggest as a fix (legend.R of R-1.5.0): 25c25 < rect2 <- function(left, top, dx, dy,

Buenas tardes, Solicito por favor ayuda con este error: Error: OutOfMemoryError (Java): Java heap space Estoy trabajando con matrices de grandes dimensiones y el programa no logra completarse porque dice le falta memoria. Gracias [unnamed] Sara Suarez Zapata Estudiante en práctica - Unidad Gestion Bolsa de Energia. Tel: (574) 380 61 18 Correo: sara.suarez en

Dear R users, I'm working with 2 data sets which look like (for example) dx and dy in the next code: # Seed set.seed(4) # First data frame dx=matrix(rnorm(6*5),ncol=6) colnames(dx)=LETTERS[1:6] # Second data frame dy=matrix(rnorm(3*5),ncol=3) colnames(dy)=c('A','C','E') As you will notice, some columns in both data sets have the same names. At the end, what I need

Hi! I've successfully installed tinc on Solaris 8 x86. Everything seem to work ok except for one thing, I get 5kb/s transfer rates over a 100mbit TP connection. Is this a known problem or have I made some mistakes? My setup is really simple: anna(Win XP - Tinc 1.0.2 using the Win32-TAP driver) <=> LAN <=> sara (Solaris 8 x86 - Tinc 1.0.2 using the TUN/TAP 1.1 driver, OpenSSL

Hi I'm using kronecker() with a matrix and a vector. I'm interested in the column names that kronecker() returns: > a <- matrix(1:9,3,3) > rownames(a) <- letters[1:3] > colnames(a) <- LETTERS[1:3] > b <- c(x=1,y=2) > kronecker(a,b,make.dimnames=TRUE) A: B: C: a:x 1 4 7 a:y 2 8 14 b:x 2 5 8 b:y 4 10 16 c:x 3 6 9 c:y 6 12 18 > The

Hello, You know, I always worry about the precision and the float constants... and there is a large lookup table in the floor1.c ... and I figure out a way to keep the code size and speed, but to improve the precision at this lookup table. (the difference is small, but audible) Here is the modifications in the floor1.c: tatic unsigned long FLOOR_fromdB_LOOKUP[256]={