search for: largely

Hello! I've tried for a while - but can't figure it out. I have data frame x: y=c("a","b","c","d","e") z=c("m","n","o","p","r") a=c(0,0,1,0,0) b=c(2,0,0,0,0) c=c(0,0,0,4,0) x<-data.frame(y,z,a,b,c,stringsAsFactors=F) str(x) Some of the values in columns a,b, and c are >0: I need to

Jul 13 08:19:15 hera dovecot: fstat 75 : Value too large for defined data type Jul 13 08:19:18 hera dovecot: fstat 75 : Value too large for defined data type Jul 13 08:19:20 hera dovecot: fstat 75 : Value too large for defined data type Jul 13 08:19:27 hera dovecot: fstat 75 : Value too large for defined data type Jul 13 08:19:27 hera dovecot: fstat 75 : Value too large for defined data type Jul

Dear list members: I am looking for an elegant (or efficient) way to accomplish the following: take a large boolean vector and fill the TRUE values with the values from a smaller boolean vector that has a length that is the number of TRUE values of the large vector. Example: large<- c(FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, TRUE, FALSE) small<- c(TRUE,

unique(x) will give you the distinct values in x. table(x) will give you the distrinct values and their frequencies as an array with dimnames. data.frame(table(x)) will give you a 2-column data.frame with the distinct values and their frequencies. > values <- c("Small", "Large", "Large", "Large") > unique(values) [1] "Small"

I can't find a lot of information about using structures directly as parameters, returns, and in registers. Is this fully supported on all platforms? Does it always convert to creating a hidden parameter when too large? For example (assume very.large is too big to fit in the target machine registers): define %very.large @get_struct() { %m1 = insertvalue %very.large undef, i32 10, 0 ...

I''m trying to boot a PV guest using the "old method" of passing kernel= and ramdisk= and it appears to work fine with a "small" initrd but not with a "large" one. (Small is 4MB, large is 154MB.) I''m sure both of the initrd''s are properly gzip''ed etc. Unpacked, the large one approaches 400M. By doing some kernel startup debugging,

Dear all, ftable produces a list of the frequencies of all occuring values. But how about the occuring values? How can I retrieve a list of occuring values? How can I retrieve a table with both the list of occuring values and their respective frequencies? Thank you in advance, Yours, Ferri

How big is a file that e2fsck considers it to be a large file? 814611 blocks used (42.79%) 0 bad blocks 1 large file <----- that Thanks John Nelson

Hi, I tried performing a complete copy of 17GB of filesystems over the WAN (0.8GB/hr) with the speed of 16Mbps. The filesystem consists of several large g-zipped files. These large g-zipped files have actually been zipped out of other sub-filesystems and directories. I noticed that while transferring a lists of large g-zipped files, rsync tends to take a much longer time to transfer those files

Hello, Do you know a R implemented normality test like the shapiro test but more suitable for large data set ? Thanks, _________________________________________________________________ Découvrez toutes les possibilités de communication avec vos proches [[alternative HTML version deleted]]

I am checking a file system (ext3) as shown below. It is actually a fresh file system, as I had deleted all partitions and created an ext3 file system. But when I run the check with the verbose option, it says I have one large file. Am I missing something here, or is it odd that I cannot find this large file it is reporting? I reviewed some documentation on ext3 file systems, and experimented

I'm trying to rsync a filesystem from a Solaris 7 server to a Solaris 8 server. I keep getting the following message when rsync attempts to update a particular file: write failed on leelab/NCBI_Data/GenBank/htg : Error 0 rsync error: error in file IO (code 11) at receiver.c(243) Received signal 16. (no core) rsync: connection unexpectedly closed (22672537 bytes read so far) rsync error:

As a new user of R, I'm wondering what the maximum matrix size is in R? I have a large data set consisting of 9000 people and want to be able to create large matrices involving these. Is R suitable for large data sets? Thanks Laura -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

Hi all, Recently I have installed a centOS 5.4 server to use as a home NAS server. I need to use large files (8GB minimum) inside of it to serve via iSCSI services. Which filesystem do you recommends me to reach maximum performance: xfs, ext3, ext4, gfs2 ....?? Thanks. -- CL Martinez carlopmart {at} gmail {d0t} com

Hello, I just had a meeting about a pilot project going on in our University, The project manager has done some research in the past year and concluded that Asterisk can not scale well to large user base like 10,000 users, thus Asterisk is not fit for large University environment. The project manager instead choosed sipX and said it scales well for large user base. I had an Asterisk running

Hi, I tried to compile rsync-2.5.2 on Solaris 5.7 Ultra-2 machine, 5.7 on Ultra-2 is running 64 bit, but, when I ran configure, it said no for largefile, I thought 2.5.2 will support large file? Is that true? Thanks, Jennifer

I'm experiencing strange behavior from my ext3 RAID5 array and my Fedora Core 2 system. Before I go crazy varying all sorts of tuning parameters, I thought some list subscribers might provide me with useful advice. The problematic array is: 3x Promise Technology Ultra 100 TX2 PCI cards 6x Maxtor 250GB IDE drives (one drive per cable) RAID level 5, 128Kb chunk size, EXT3: "mkfs -t ext3

When trying to installing Syslinux on a FAT32 drive formatted using Ridgecrop's Large FAT32 formatting tool [1], the installer will bail due to the minfatsize check, as there is an extra sector being used. This fix addresses that. [1] http://www.ridgecrop.demon.co.uk/index.htm?fat32format.htm -------------- next part --------------

I just ran this again and got this error: leelab/NCBI_Data_old/GenBank/htg write failed on leelab/NCBI_Data_old/GenBank/htg : Error 0 rsync error: error in file IO (code 11) at receiver.c(243) Received signal 16. (no core) rsync error: received SIGUSR1 or SIGINT (code 20) at rsync.c(229) The command I am running is: /usr/local/bin/rsync -auv --delete --rsh=/usr/bin/ssh lpgfs104:/share/group/*

Dear R community, I find R fantastic and use R whenever I can for my data analytic needs. Certain data sets, however, are so large that other tools seem to be needed to pre-process data such that it can be brought into R for further analysis. Questions I have for the many expert contributors on this list are: 1. How do others handle situations of large data sets (gigabytes, terabytes)