similar to: table of means/medians across bins used for a histogram

Hi I have data of the following form ID age member_FLAG 1 25 Y 2 36.75 N 3 75.5 N ......... ......... I want to get a histogram of this data showing distribution of member_flag in each age-bin i.e. how many values in each age bin have a member_flag of 'Y' and how many have 'N'. I was able to do the same using barplot2. However I also need similar

Hi I am looking for suitable packages in R that do regression analyses using least median squares method (or better). Additionally, I am also looking for packages that implement algorithms/methods for detecting outliers that can be discarded before doing the regression analyses. Although some websites refer to "lms" method under package "lps" in R, I am unable to find such a

Hi I am looking for a package that 1. reads in a phylogenetic tree in NEXUS format 2. given two members/nodes on the tree, can return the distance between the two using the tree. I came across the following packages on CRAN ouch, ape, apTreeShape, phylgr all of which seem to provide extensive range of functions for reading in a Nexus-format tree and performing phylogenetic analyses, tree

Hi I have a table that goes data cluster_ac clockrate age class 7337 0.9 0.001 alpha_proteins 7888 0.1 0.78 beta proteins etc The class column can have 7-8 different unique values While the clockrate and age columns are floats varying from 0 to 1. I wish to get the average clockrate across each of the classes for this data. I would appreciate your help

Hi I am new to R programming and am using subset to extract part of a data as follows names(dataset) = c("genome1","genome2","dist","score"); prunedrelatives <- subset(dataset, score < -5); However when I use unique to find the number of unique genomes now present in prunedrelatives I get results identical to calling unique(dataset$genome1) although

Hi Thanks much for the prompt response to my earlier enquiry on packages for regression analyses. Along the same topic(?), I have another question about which I could use some input. I am retreiving data from a MySQL database using RODBC. The table has many BLOB columns and each BLOB column has data in the format "id1 \t id2 \t measure \n id3 \t id4 \t measure...." (i.e. multiple rows

Hi I am trying to process tabular data as follows: Data in the input file is of the form genome1 genome2 tree-dist log10escore Genome1 and genome2 are alphabetic. Tree-dist and log10escore are numeric. I wish to extract only those rows from this table where the log10escore is less than -3. data <-read.table(filename); data$log10escore = data$log10escore[ data$log10escore < -3]; I

Hi I have a dataframe which has 3 columns of numeric data A,B,C each of which has been obtained independent of the other. We are trying to find out, which of A or B cause C i.e. We are hypothesising that C is the effect and either A or B, not both is the cause. i.e. A causes C and this cause-effect relationship explains B. The data for A contains more noise than that for B. We are working with

Hi I am a newbie to R and am using the lm function to fit my data. This optimization is to be performed for around 45000 files not all of which lend themselves to optimization. Some of these will and do crash. However, How do I ensure that the program simply goes to the next file in line without exiting the code with the error "Error in lm.fit(x, y, offset = offset, singular.ok =

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Hi I have a data frame with 40,000 rows and 4 columns, one of which is "class". For each row, the "class" column can be one of 10 possible NUMERIC values. I wish to substitute these numeric values with words/characters. For example, I wish to substitute all occurences of "5467" in the column "class" with "alpha", "7867" with

Hi all, I have investigated the compile-time overhead of "Polly Scop Detection" pass based on LNT testing results. This mail is to share some results I have found. (1) Analysis of "SCOP Detection Pass" for PolyBench (Attached file PolyBench_SCoPs.log) Experimental results show that the "SCOP Detection pass" does not lead to significant extra compile-time

On 06/29/2013 05:04 PM, Star Tan wrote: > Hi all, > > > > I have investigated the compile-time overhead of "Polly Scop Detection" pass based on LNT testing results. > This mail is to share some results I have found. > > > (1) Analysis of "SCOP Detection Pass" for PolyBench (Attached file PolyBench_SCoPs.log) > Experimental results show that the

>Great. Now we have two test cases we can work with. Can you >upload the LLVM-IR produced by clang -O0 (without Polly)? Since tramp3d-v4.ll is to large (19M with 267 thousand lines), I would focus on the oggenc benchmark at firat. I attached the oggenc.ll (LLVM-IR produced by clang -O0 without Polly), which compressed into the file oggenc.tgz. >2) Check why the Polly scop detection is

On 07/01/2013 06:51 AM, Star Tan wrote: >> Great. Now we have two test cases we can work with. Can you > >> upload the LLVM-IR produced by clang -O0 (without Polly)? > Since tramp3d-v4.ll is to large (19M with 267 thousand lines), I would focus on the oggenc benchmark at firat. > I attached the oggenc.ll (LLVM-IR produced by clang -O0 without Polly), which compressed into the

Perfect, thank you very much :) 2011/10/26 Tobias Grosser <tobias at grosser.es>: > On 10/24/2011 11:32 PM, Marcello Maggioni wrote: >> >> Strange , with --enable-shared (I use auto tool by the way ...) it gives: >> >> MacBook-Pro-di-Marcello:examples Kariddi$ ./compile_ex.sh >> not_so_simple_loop >> clang (LLVM option parsing): Unknown command line

>> (3) About detecting scop regions in bottom-up order. >> Detecting scop regions in bottom-up order can significantly speed up the scop detection pass. However, as I have discussed with Sebastian, detecting scops in bottom-up order and up-bottom order will lead to different results. As a result, we should not change the detection order. > >Sebastian had a patch for this. Does

Hi Everyone, So I've been working a little with mzxml files generated from proteomics data. The current packages available to read these are not sufficient for what I am doing and I would like to build my own. The trouble I am having is how do I read in an mzxml file without the available packages (like reading in a table). I've been searching through Google for a couple of days and am

Dear Community, I would like to summarize my work till date for GSoC 2016. Till the current phase of my project, I have mostly focused on developing the necessary infrastructure to use analysis results from Polly in LLVM. Initial plan as mentioned in the proposal: For the first month:- 1. Decouple ScopInfo pass from Polly’s pass chain and provide capability to create SCoP(Static

Mmm, this code seems to kill polly: #include <stdio.h> #include <stdlib.h> int main() { char *B; int i,j,k,h; const int x = 0, y=0; B = (char *)malloc(sizeof(char)*1024*1024); for (i = 1; i < 1024; i++) for (j = 1; j < 1024; j++) { if (i+j > 1000) B[j] = i; } printf("Random Value: %d", B[rand() % 1024*1024]); return 0; } running: opt