similar to: [LLVMdev] Re: LLVMdev Digest, Vol 21, Issue 2

Sir, Given code like: > > X = add int Y, 1 > Z = mul int X, 17 while I iterate over the operands of the first instruction i want to print the variable x ,as well as the constant 1 and while i iterate over the second instruction i want to print variable x and constant 17. what should I do? thanking you, yours sincerely, anubham suresh TU-Darmstadt --- llvmdev-request at

Sir, I am using LLVM Compiler for my Maters Dissertation work. So I want to include one chapter on LLVM in my report. Can I copy some of the figures from your documentation which is available on the net and keep them in my work ? thanking you, yours sincerely, Suresh Anubham TU-Darmstadt Germany Anubham Suresh Measurement and Instrumentation Electrical Department IIT Roorkee Current

hi everyone, here i have a question: is there any chance in llvm intermediate representation to compare whether a operand (ie a value) is used as a user without iterating over all the instructions in a basic block. i will explain this with an example: i=p+4; j=i+p; in the above example i mean p,4,i,p which are on the RHS are operands and the terms i,j which are on the LHS are users. so what i

Sir, I am using the op_begin and op_end iterator for iterating over the operands as mentioned below. for (User::op_iterator operand=j->op_begin(),operand_end=j->op_end();operand!=operand_end;++operand){ Value *v=operand->get(); const Type *t=v->getType(); cerr<<endl<<" operand: "<<"[ "<<v->hasName()<<"

On Wed, 2006-02-15 at 04:29, anubham suresh wrote: > hi everyone, > here i have a question: > is there any chance in llvm intermediate > representation to compare whether a operand (ie a > value) is used as a user without iterating over all > the instructions in a basic block. > i will explain this with an example: > i=p+4; > j=i+p; > > in the above example i

R-help - I have this set of aggregated tables (sample data below via dput()). And I would like to have delayValue as the column variables with the "temp" (temp1, temp2, temp3) values as the row variables. However I would like to have the temp variables *aggregated into single rows* so that I have the frequency ("Freq" | counts) of each time each "delayValue" occurs

Let me explain the subject title, store provider is Hackey, he''s a NPC that sells items to my users. <h1>Welcome to Hackey''s!</h1> <h3>Catalog</h3> <table border="2" bordercolor="red"> <% for items in @items -%> <% temp12 = Item.find(items.item_id) -%> <tr><td><%= @temp12.name

Dear R users I am using KS test to compare two different distribution for the same variable (temperature) for two different time periods. H0: the two distributions are equal H1: the two distributions are different ks.test (temp12, temp22) Two-sample Kolmogorov-Smirnov test data: temp12 and temp22 D = 0.2047, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: In

Hi everyone I am new to R and have a question about missing values. I am trying to do a cluster analysis of monthly temperatures and my data are 14 columns with spatial coordinates (lat,lon) and 12 monthly values: /lat - lon - temp1 - //temp2 - temp3 - .... - //temp12/ If I omit missing values (my missing values are 99.00) with /mydata <- na.omit(mydata)/ every row with a

Problem: I am sorting through model selection process for first time and want to make sure that I have used glm, stepAIC, and update correctly. Something is strange because I get a different result between: 1) a glm of 12 predictor variables followed by a stepAIC where all interactions are considered and then an update to remove one specific interaction. vs. 2) entering all the terms

dear all, I am a student in cs college. I would like to know how to plot infinte number of genes after using the svm. the data set i have consists of x which is a matrix of 39 cancer patients [rows] and 2000 gene names [colmns]. each cell is the value of the gene for a particular patient. there are two types of cancer people representedas factor y. here is the code: library(e1071) #load

hi, I considered multivariate multiple regression for respons, predictor, each 5 dimension. on going process, through initb <- eigen(temp)$vectors[,1:3] temp <- vhalf%*%Kproduct(Ir,initb) (herein 'vhalf' is root for inverse of covariance matrix and 'Kproduct' is Kronecker product) and then process regression. However, I have tried using the

Hi, if I know the colnames x and y in the following example, I can easily to do lm. tmp <- data.frame(x=c(1,1.2),y=c(1,2)) lm(y ~ x, data=tmp) when the colnames are variable, what should I do? for example colnames(tmp)[1] <- paste("aa",1,sep="_") lm(y ~ paste("aa",1,sep="_"), data = tmp) it gives me error. [[alternative HTML version

I have a vaiable named NAM having value : 1,2,3,4,5,6,7,8,9. I want to make an indicator variable that will take value 1 if NAM=7 or NAM=8 or NAM=9. How can I do that? I usually do: Var001<- ifelse(NAM==7,1,0) for the simplest case. [[alternative HTML version deleted]]

Hi folks, I have a vaiable Y and an associated factor Z at several (13) levels. boxplot(Y~Z) produces a nice array of boxplots, one for each level of Z, and each duly labaelled with its level of Z. I would like to superpose on each boxplot the actual data points which it represents, i.e. do something conceptually (though not in real R) expressed as points(Y~Z) or points(Z,Y) It can

I'm working on a rather interesting consulting problem with a client. A number of physical variables are measured on a number of cricket bowlers in the performance of a delivery. An example variable might be a directional component of angular momentum for a particular joint measured at a large number (101) of equally spaced timepoints. Each bowler generates a (fairly smooth) curve for

R múltiple Estoy pensando en un problema que tendré que solucionar pero aún no comencé a escribirlo, por lo tanto no hay código en R como para compartir, sin embargo no tengo idea de cómo realizarlo desde R. El planteo es el siguiente: Los datos son en una cantidad necesaria para que el procesamiento estadístico demore (minutos, horas). Supongamos dos variables (serían más), la A y la B,

Estimado Jorge Velez Lo que usted dice tiene algo a mi pregunta, pero yo la formule mal. Voy a preguntar nuevamente con un ejemplo que tiene errores, pero es más próximo a lo que estoy pensando. Modelo (con error pero no importa) modelo <- muerte = edad + sexo + 1!causa Causa: infarto, infarto, súbita, muerte en tiroteo El modelo lineal, sobrevida, etc. corre sin inconvenientes (aunque

Dear useR's, I was comparing results for a logistic regression model between different library's. themodel formula is arranged as follows: response ~ (intercept) + value + group OR: glm( response ~ (intercept) + value + group , family=binomial(link='logit')) lrm( response ~ (intercept) + value + group ) ROC( from = response ~ (intercept) + value + group ,

Dear R developers and users: I have the following data, x is the response vaiable, nsample(individual) nested within trt, and subsample nested within nsample, I want to fit trt as fixed effect, and block, nsample(trt) as random effects using lme, is the following coding correct? dat$vgrp <- getGroups(dat, form = ~ 1|trt/nsample, level = 2) ge.lme1 <- lme(fixed=x~trt, data=dat,