similar to: printing levels as tuples

Hi, I need to map words in a document back to there original word id''s in my database. For example, if I had the sentence "I eat food" and I was searching for "food" I would obviously get the document back as a result. For my particular problem I need to not only get the document id but also the id of the match. Suppose my original sentence was actually

Hi, this seems like a strange question, but in R is there a function that can handle vectors containing factors inside lists/tuples? Or is there some other approach/functions I can use? Like for example V1 "{"Harry","Brown")" "{"Brown","Harry")" I want to use these variables in a machine learning setting, And don't want to convert

Hi all, Does anyone uses astDB for a large amount of data, in special for implementing black lists with millions of numbers (i'd like about 2 or 3 million)? That would be held in memory right? Is this (memory consumption) the only problem I could face? Att. Gabriel -------------- next part -------------- An HTML attachment was scrubbed... URL:

JID Pri S Owner Number Pages Dials TTS Status 58 123 S root 008675533661 0:2 4:12 02:12 No carrier detected Here is the asterisk output: [Mar 28 01:54:00] NOTICE[16753]: chan_iax2.c:6025 update_registry: Restricting registration for peer 'iaxmodem' to 60 seconds (requested 50) -- ast_get_srv: SRV lookup for '_sip._udp.voipuser.org' mapped to host

I'd like to control my namespace thoroughly, separated by task. Is there a way, in R session, to introduce namespaces for tasks dynamically and switch them as needed? Or, is there a combination of load/save workspace steps which can facilitate this? Cheers, Alexy

I get tables with millions of rows. For plotting to a screen-size jpg, obviously just about 1000 points are enough. Instead of feeding plot() the original millions of rows, I'd rather shrink the original dataframe, using some kind of the following interpolation: -- split dataframe into chunks of N rows each, e.g. 1000 rows each -- compute average for each column -- issue one new row

Is there an R analog of the Unix command uniq -c: http://en.wikipedia.org/wiki/Uniq Given an array x, uniq -c replaces each contiguous subsequence of identical numbers with a tuple (count, number). E.g. $ cat > usample 10 10 9 8 8 7 7 7 6 3 1 1 1 0 $ uniq -c usample 2 10 1 9 2 8 3 7 1 6 1 3 3 1 1 0 Cheers, Alexy

Greetings -- in order to write back to SQL databases, one needs to create a dataframe with values. I can get column names of an existing table with sqlColumns. Say I have a vector of values (if they're all the same type), or a list (if different). How do I create a dataframe with column names given by my sqlColumns? To make it concrete, how do we make a dataframe A B C 1 2 3

I'm growing a large dataframe by composing new rows and then doing row <- compute.new.row.somehow(...) d <- rbind(d,row) Is this a fast/preferred way? Cheers, Alexy

What are idioms for taking a head or a tail of a vector, either up to an index, or from an index to the end? Also -- is it necessary to use length(v) to refer to the last element? E.g., Python has v[:3] # indices 0,1,2 v[3:] # indices 3,4,... v[-1] # the last element of v v[:-1] # all but last Cheers, Alexy

I've had a very long file written out by R with write.table, with fields of time values, converted from POSIXlt as.numeric. Among 2.5 million values, very few had 6 trailing zeroes, and those were output in scientific notation as in the subject. Is this the default behavior for long integers, and how can it be turned off (with all digits for any integer field in write.table)? This

Greetings -- I have a dataframe a with one element a vector, time, of POSIXct values. What's a good way to split the data frame into periods of a$time, e.g. days, and apply a function, e.g. mean, to some other column of the dataframe, e.g. a$value? Cheers, Alexy

Using wk <- with(d, split(word, kind)), I get the following class table: wk$`1` [1] "a" "bra" ... # (*) wk$`10` "ca" "dabra" ... Now I need to export it in the following format: class num_members examples 1 23 a bra ... 10 4 ca dabra For each class C such as `1`, I need to print the

I want to produce a dataframe with integer columns for elements of string pairs: pairs <- c("10 21","23 45") pairs.split <- lapply(pairs,function(x)strsplit(x," ")) pdf <- as.data.frame(pairs.split) names(pdf) <- c("p","q") -- at this point things look good, except the columns are factors, as I didn't change the default

I've used to have a script with a barplot command it in, preceded by a png: png(graph.file,height=H,width=W) barplot(t,names.arg=breaks[2:(length(t)+1)],tck=gridlines) -- worked before R 2.6.2. When I tried it in R 2.6.2, which I have for a while but didn't run with that script, it complained, the margins too large, and I've googled the messages from our list where neither

Hi, this is an RFC for optional, named parameter tuples for intrinsics. The proposed syntax is: %z = call @llvm.some.intrinsic(%a, %b) optional_tuple(%x, %y, %z) where from the perspective of the call site %x, %y and %z are simply additional parameters. Optional parameter tuples would be very useful for constrained fp intrinsics and vector predication. Some examples: ; Default fpenv fadd

I have a setup that looks roughly like: # cat smb.conf [global] security = ads workgroup = company realm = internal.company.com password server = 192.168.1.2 netbios name = server server string = Samba Server name resolve order = wins bcast username map = /etc/samba/smbusers map to guest = Bad User invalid

Every time I have to prefix a dataframe column inside the indexing brackets with the dataframe name, e.g. df[df$colname==value,] -- I am wondering, why isn't there an R scoping rule that search starts with the dataframe names, as if we'd said with(df, df[colname==value,]) -- wouldn't that be a reasonable default to prepend to the name search path? Cheers, Alexy

Sometimes I'm iterating over a list where names are keys into another data structure, e.g. a related list. Then I can't use lapply as it does [[]] and loses the name. Then I do something like this: do.one <- function(ldf) { # list-dataframe item key <- names(ldf) meat <- ldf[[1]] mydf <- some.df[[key]] # related data structure r.df <-

I found there's a very good functional set of operations in R, such as apply family, Hadley Wickham's lovely plyr, etc. There's even a Reduce (a.k.a. fold). Now I wonder how can we do pattern-matching? E.g., now I split dimensions like this: m <- dim(V)[1] # R n <- dim(V)[2] # still R While even Matlab allows for [m,n] = size(V) % MATLAB! Ideally I'd be able to