similar to: Couldn't (and shouldn't) is.unsorted() be faster?

Hi, I've read ?is.unsorted and searched. Have found a few items but nothing close, yet. Is the following expected? > is.unsorted(data.frame(1:2)) [1] FALSE > is.unsorted(data.frame(2:1)) [1] FALSE > is.unsorted(data.frame(1:2,3:4)) [1] TRUE > is.unsorted(data.frame(2:1,4:3)) [1] TRUE IIUC, is.unsorted is intended for atomic vectors only (description of x in ?is.unsorted). Indeed

Hi, In the man page for is.unsorted(): Value: A length-one logical value. All objects of length 0 or 1 are sorted: the result will be ?NA? for objects of length 2 or more except for atomic vectors and objects with a class (where the ?>=? or ?>? method is used to compare ?x[i]? with ?x[i-1]? for ?i? in ?2:length(x)?). This contains many incorrect

I believe the performance of isUnsorted() in sort.c could be improved by calling REAL() once (outside of the for loop), rather than calling it twice inside the loop. As an aside, it is implemented in the faster way in doSort() (sort.c line 401). The example below shows the performance improvement for a vectors of double of moving REAL() outside the for loop. # example as implemented in

I've just realized that it could be handy to have a 'decreasing' argument in 'is.unsorted'. And I'm cheekily hoping someone else will implement it. It is easy enough to work around (with 'rev'), but would be less hassle with an argument. The case I have in mind uses 'is.unsorted' in 'stopifnot'. Pat -- Patrick Burns pburns at pburns.seanet.com

Dear Rdevelopers The background for this email is that I was helping a PhD student to improve the speed of her R code. I suggested to replace calls like t(AA)%*% BB by crossprod(AA,BB) since I expected this to be faster. The surprising result to me was that this change actually made her code slower. > ## Examples : > > AA <- matrix(rnorm(3000*1000),3000,1000) > BB <-

https://bugzilla.samba.org/show_bug.cgi?id=7861 Summary: documentation: files-frombehaves badly on unsorted input Product: rsync Version: 3.0.5 Platform: x64 OS/Version: Linux Status: NEW Severity: minor Priority: P3 Component: core AssignedTo: wayned at samba.org ReportedBy: rlpowell at

write.table with large data frames takes quite a long time > system.time({ + write.table(df, '/tmp/dftest.txt', row.names=FALSE) + }, gcFirst=TRUE) user system elapsed 97.302 1.532 98.837 A reason is because dimnames is always called, causing 'anonymous' row names to be created as character vectors. Avoiding this in src/library/utils, along the lines of Index:

Hi R-helpers, Does anyone know why adding which() makes the select call more efficient than just using logical selection in a dataframe? Doesn't which() technically add another conversion/function call on top of the logical selection? Here is a reproducible example with a slight difference in timing. # Surrogate data - the timing here isn't interesting urltext <-

Hello all, The following line of code includes a right-to-left language text, yet the R graphics engine displays it from left to right. One problem this causes is when there are parenthesis in the test, here is a basic example? plot(1:10, main = "שלום (טקסט)") Is there a way to make sure the text is displayed from right to left? Many thanks for any suggestions, Tal

> -----Original Message----- > From: Prof Brian Ripley [mailto:ripley@stats.ox.ac.uk] > Sent: Wednesday, April 27, 2005 1:13 AM > To: Vadim Ogranovich > Cc: Luke Tierney; r-devel@stat.math.ethz.ch > Subject: Re: [Rd] RE: [R] when can we expect Prof Tierney's > compiled R? > > On Tue, 26 Apr 2005, Vadim Ogranovich wrote: > ... > > The arithmetic shows

Full_Name: Alessandra Iacobucci Version: 2.5.1 OS: Mac OS X 10.4.11 Submission from: (NULL) (193.48.71.92) Hi, I am making some intensive simulations for the testing of a Population Monte Carlo algorithm. This involves also a study of the CPU times in two different case. What I am trying to measure is the "real" CPU time, the one which is independent on the %CPU. I'm using the

Hi, I'm trying to write a general-purpose "lexicon" class and associated methods for storing and accessing information about large numbers of specific words (e.g., their frequencies in different genres). Crucial to making such a class practically useful is to get hashing working correctly so that information about specific words can be accessed quickly. But I've never really

Hi, Encouraged by a tip from Simon Urbanek I tried to use the S3 machinery to write a faster version of the data.frame class. This quickly hits a snag: the "[.default"(x, i) for some reason cares about the dimensionality of x. In the end there is a full transcript of my R session. It includes the motivation for writing the class and the problems I have encountered. As a result I see

Hi all, This must be such a beginner''s problem, but I can''t figure it out. I''m pulling two integers out of a database, and i want to divide one value with the other, but i keep getting an error about operating on strings. Here''s the code - low_freq = unsorted.last.freq high_freq = unsorted.first.freq divider = high_freq / low_freq In my view, if i display

Hello, The problem I'm working now requires to operate on big matrices. I've noticed that there are some packages that allows to run some commands in parallel. I've tried snow and NetWorkSpaces, without much success (they are far more slower that the normal functions) My problem is very simple, it doesn't require any communication between parallel tasks; only that it divides

Hi, I have a 5x731 array A, and I want to compute the sums of the columns. Currently I do: apply(A, 2, sum) But it turns out, this is slow: 70% of my CPU time is spent here, even though there are many complicated steps in my computation. Is there a faster way? Thanks, Martin

This creates a named vector of length nx, then repeatedly draws a single sample from it. lkup <- function(nx, m=10000L) { tbl <- seq_len(nx) names(tbl) <- as.character(tbl) v <- sample(names(tbl), m, replace=TRUE) system.time(for(k in v) tbl[k], gcFirst=TRUE) } There is an abrupt performance degredation at nx=1000 > lkup(1000) user system elapsed 0.180

Dear friends, My dataset is like the following: x y mcpvalue 0.4603578 0.6247629 1.001 0.4603715 0.6247788 1.001 0.4603852 0.6247948 1.001 0.4110561 0.5664841 0.995 The x and y variables are unsorted. I use the function image(x,y,mcpvalue) to generate a plot, but the error is that "increasing 'x' and

Hi, I am experiencing a long delay when using dataframes inside loops and was wordering if this is a bug or not. Example code: > st <- rep(1,100000) > ed <- rep(2,100000) > for(i in 1:length(st)) st[i] <- ed[i] # works fine > df <- data.frame(start=st,end=ed) > for(i in 1:dim(df)[1]) df[i,1] <- df[i,2] #takes for ever R: R 2.0.0 (2004-10-04) OS: Linux, Fedora Core 2

hi all If I wanna get the total number of lines in a big file without reading the file's content into R as matrix or data frame, any methods or functions? thanks in advance. Regards