similar to: Fast ave for sorted data?

Hi all, Basically, I have data in the format of (up to 1 gig in size) text files containing stuff like: F34060F81000F28055F8A000F2E05EF8F000F34 (...) The data is basically strings denoting hex values (9 = 9, A = 10, B = 11, ...) organised in fixed, small blocks. What I want to do is to read in a specified segment of the string, break it up into blocks, and convert it into a vector of integers

Hi, Is there any way to load workspaces (e.g. stuff from save.image) from the command line? I'm on Linux, and would find this very helpful. I'm guessing this functionality can be duplicated with a skillful bash script to rename the particular file to .RData (and then back once R terminates), but I'm wondering if there's a better way. Zhou Fang

Hi, Okay, I have a n x p matrix X, which I know is not full rank. In particular, there may be linear dependencies amongst the columns (but not that many). What is a fast way of finding a linearly independent subset of the columns of X that will span the column space of X, in R? If it helps, I have the QR decomposition of the original X 'for free'. I know that it's possible to do this

Okay, someone explain this behaviour to me: Browse[1]> replace(rep(0, 4000), temp1[12] , temp2[12])[3925] [1] 0.4462404 Browse[1]> temp1[12] [1] 3926 Browse[1]> temp2[12] [1] 0.4462404 Browse[1]> replace(rep(0, 4000), 3926 , temp2[12])[3925] [1] 0 For some reason, R seems to shift indices along when doing this replacement. Has anyone encountered this bug before? It seems to crop up

Hi, Possibly a dumb question, but I wonder if anyone can help me with this. What I want to do, essentially, is to loop over all ordered subsets of a given size of a certain set. Ultimately, the idea is to find the subset that maximises a certain value. The set in question is likely large (the subset size is likely small, though), so things like combn don't seem to be a good solution. The

hi, all: i want to add a function in xen. in the function i need to call the "printk" to display the values of some variables. i found the definition of printk() in file "xen-3.1.0-src\xen\include\xen\lib.h ": extern void printk(const char *format, ...) __attribute__ ((format (printf, 1, 2))); who can tell me the location of printk()? thanks in advance. 2008-04-26

> ----- Original Message ----- >> Hi all, >> My recent commit r187027 fixed a simple oversight of forgetting to >> check for __ppc__ (only checking __powerpc__), which broke my >> powerpc-apple-darwin8 stage1 tests, since the system gcc only >> provided >> __ppc__. I was wondering if this justifies using simpler macros like >> >> #define

Hi, I've made a research about how to compare two regression line slopes (of y versus x for 2 groups, "group" being a factor ) using R. I knew the method based on the following statement : t = (b1 - b2) / sb1,b2 where b1 and b2 are the two slope coefficients and sb1,b2 the pooled standard error of the slope (b) which can be calculated in R this way: > df1 <-

Hi, Thanks for the quick reply again. > On Thu, Dec 15, 2011 at 1:17 PM, David Fang <fang at csl.cornell.edu> wrote: >> Hi, >> >> I've bootstrapped llvm/clang from svn-trunk on powerpc-darwin8 (g++-4.0.1), and >> have the following test results to share. >> Summary below, full log at: >>

Hi, > ----- Original Message ----- >>> ----- Original Message ----- >>>> Hi all, >>>> My recent commit r187027 fixed a simple oversight of forgetting >>>> to >>>> check for __ppc__ (only checking __powerpc__), which broke my >>>> powerpc-apple-darwin8 stage1 tests, since the system gcc only >>>> provided

----- Original Message ----- > > ----- Original Message ----- > >> Hi all, > >> My recent commit r187027 fixed a simple oversight of forgetting > >> to > >> check for __ppc__ (only checking __powerpc__), which broke my > >> powerpc-apple-darwin8 stage1 tests, since the system gcc only > >> provided > >> __ppc__. I was

Hi, For anyone who might be interested, I've thrown together a little page to track my builds of llvm and clang, both release 3.0 and svn-trunk, on powerpc-darwin8. http://www.csl.cornell.edu/~fang/sw/llvm/ I'll update the list of logs each time I svn-update and build. It's nowhere as nice as a real buildbot page, but it's better than nothing. 3.0 still has over 20 test

Hello Tobias, Thank you for the suggestion! Aditya also mentioned this. I will look into it. Best regards, Ruijie Ruijie Fang Email: ruijief at princeton.edu On Tue, Jun 2, 2020 at 12:48 PM Tobias Hieta <tobias at plexapp.com> wrote: > Hello Ruijie, > > One other workload that would be interesting to test might be clang > itself. Building clang with PGO information is a

>> These results have far fewer failures than svn-trunk, and are also >> comparable to bootstrapping with gcc-4.6.2, summarized here: >> http://paste.lisp.org/display/126363 >> (Unfortunately, I no longer have the whole build/test log for the gcc46 bootstrap.) >> This consistency between different bootstraps of the release gives me >> some hope that g++-4.0.1 is

18.01.2012, 02:46, "David Fang" <fang at csl.cornell.edu>: > Hi, >          For anyone who might be interested, I've thrown together a little > page to track my builds of llvm and clang, both release 3.0 and > svn-trunk, on powerpc-darwin8. > > http://www.csl.cornell.edu/~fang/sw/llvm/ > > I'll update the list of logs each time I svn-update and

Hi all, My recent commit r187027 fixed a simple oversight of forgetting to check for __ppc__ (only checking __powerpc__), which broke my powerpc-apple-darwin8 stage1 tests, since the system gcc only provided __ppc__. I was wondering if this justifies using simpler macros like #define LLVM_PPC (defined(__ppc__) || defined(__powerpc__) ...) #define LLVM_PPC64 (defined(__ppc64__) ||

On Wed, Jan 18, 2012 at 10:51:38PM +0400, Konstantin Tokarev wrote: > > > 18.01.2012, 02:46, "David Fang" <fang at csl.cornell.edu>: > > Hi, > > ?????????For anyone who might be interested, I've thrown together a little > > page to track my builds of llvm and clang, both release 3.0 and > > svn-trunk, on powerpc-darwin8. > > > >

On Thu, Dec 15, 2011 at 1:17 PM, David Fang <fang at csl.cornell.edu> wrote: > Hi, > > I've bootstrapped llvm/clang from svn-trunk on powerpc-darwin8 (g++-4.0.1), and > have the following test results to share. > Summary below, full log at: > http://www.csl.cornell.edu/~fang/sw/llvm/r146586-powerpc-darwin8-results.txt > > The only edits required were those I

Hi, Should be a quickie: I want to make a datafile in R for plotting in gnuplot (which has friendlier 3D plotting options, as far as I can tell). So, I want to create a file with contents along the lines of #File begins 0 0 10 0 13 10 0.2 2 10 1 0 10.12 1 1 5 1 2 10 2 0 10 2 1 1 2 2 10 It's probably fairly easy to write the space-separated numbers with write.table, sink, or similar. But

Hi, I try to use lm to fit a linear model with 600k rows and 70 attributes. But I can't even load the data into the R environment. The error message says the vector memory is used up. Is there anyone having experience with large datasets in R? (I bet) Please advise. thanks, Yun-Fang [[alternative HTML version deleted]]