similar to: vectorizing a function

Why when I assign 0 to an element of an integer vector does the type change to numeric? Here is a particularly perplexing example: > v <- 0:10 > v [1] 0 1 2 3 4 5 6 7 8 9 10 > class(v) [1] "integer" > v[1] <- 0 > class(v) [1] "numeric" #!! > -- View this message in context:

Why when I assign 0 to an element of an integer vector does the type change to numeric? Here is a particularly perplexing example: > v <- 0:10 > v [1] 0 1 2 3 4 5 6 7 8 9 10 > class(v) [1] "integer" > v[1] <- 0 > class(v) [1] "numeric" #!! > -- View this message in context:

I'd like to write some objects (eg arrays) to a log file. cat() flattens them out. I'd like them formatted as in 'print' but print only writes to stdout. Is there a simple way to achieve this result? Thanks -- View this message in context: http://www.nabble.com/print%28%29-to-file--tp24397445p24397445.html Sent from the R help mailing list archive at Nabble.com.

Suppose I have an n-diml array A and I want to extract the first "row" -- ie all elements A[1, ...] Interactively if I know 'n' I can write A[1,,,,,] with (n-1) commas. How do I do the same more generally, eg in a script? (I can think of doing this by converting A to a vector then extracting the approp elements then reshaping it to an array, but I wonder if there isn't a

I've asked about custom sorting before and it appears that -- in terms of a user-defined order -- it can only be done either by defining a custom class or using various tricks with "order" Just wondering if anyone has a clever way to order "vintages" of the form 2002, 2003H1, 2003H2, 2004, 2005Q1, 2005Q2, etc some have H1 or H2, some have Q1,Q2,Q3,Q4, some are just plain

When I do dev.new(), the resulting window comes to the front and grabs the focus. Is there a way to prevent this so I can continue working in other windows while the graphics are being produced? Thanks -- View this message in context: http://www.nabble.com/X-window-graphics----preventing-window-coming-to-front--tp24167763p24167763.html Sent from the R help mailing list archive at Nabble.com.

Hello Folks, I'm trying to vectorize a loop that processes rows of a dataframe. It involves lots of conditionals, such as "If column 10 == 3, and if column 3 is True, and both column 5 and 6 are False, then set column 4 to True". So, for example, any ideas about vectorizing the following? df = data.frame( list(a=c(1,2,3,4),

Dear Members, I work on a simulaton experiment but it has an bottleneck. It's quite fast because of R and vectorizing, but it has a very slow for loop. The adjacent element of a vector (in terms of index number) depends conditionally on the former value of itself. Like a simple cumulating function (eg. cumsum) but with condition. Let's show me an example: a_vec = rnorm(100) b_vec = rep(0,

Dear all, I would really appreciate if somebody can help me to understand what does the phrase "Vectorize your function" mean? And what is the job of Vectorize() function in doing that? I have read many threads where experts suggest to Vectorize the function, which will speed up entire calculation (and more elegant ofcourse.) I used to think that vectorizing function means, to create a

Hi -- I have found a bug in an HPC code where llvm is vectorizing a loop on Skylake that has an obvious recurrence. I derived a small test case based on the original benchmark below: /*****************************************************************/ static void __attribute__ ((always_inline)) one( const int *restrict in, const int *const end, const unsigned shift, int *const restrict index,

Hi, I have a list of numbers (classified as a list) that contains integer(0) empty vectors. How do I convert those integer(0) into NAs? Thanks [[alternative HTML version deleted]]

What is the simplest way to extract a matched subexpression? Eg. in perl you can do "hello world" =~ m/hello (.*)/ which would return 1(true) and set $1 to the matched subexpression "world". -- View this message in context: http://n4.nabble.com/regular-expression-submatch-tp1459146p1459146.html Sent from the R help mailing list archive at Nabble.com.

When operating in daemon mode, will rsync check to see which file is newer and decide which direction to transfer based on that? Example, We have 2 terminal servers, A and B. I want users to be able to work on either server and have their home directories on both stay in sync. If a user logs into server A and changes files, the server would know to transfer the file from A to B. If they log

Is it possible to vectorize anova over the output of a vectorized lm? I have a gene expression matrix with each row being a gene and columns for samples. There are several factors with interactions. I can get p values by looping over the matrix with lm and anova, but I would like to make this as computationally efficient as possible. I am able to vectorize the lm command, but when I try to use

Perhaps this is a common question but I haven't been able to find the answer. I have data with many factors, each taking many values. However, only relatively few combinations appear in the data, ie have nonzero counts, in other words the resulting table is sparse. Say we have 10 factors each with 10 levels. The result of table() would exceed the memory space (on a 32bit machine). Is there

Dear R-xperts I have just written a little hypergeometric function, included below [the hypergeometric function crops up when solving a common type of ODE]. It works fine on single values of the primary argument z, but vectorizing it is getting confusing. The best I have come up with so far just tests for z being longer than 1 and if so, uses sapply() recursively. This is fine, except that it

The situation is that I know there is a function and know approximately what the name is, and want to find the exact name. Is there a way of searching for near-matches (similar to unix apropos). For example, I know there is a function called something like allequal (or allequals or AllEquals or...). But ?allequal, etc, return nothing, only if I remember the name can I get help via ?all.equal.

Hi Hameeza, Aside from Ashutosh's patch..... When the vector width is that large, we can't keep vectorizing remainder like below. It'll be a huge code size if nothing else ---- hitting ITLB miss because of this is very bad, for example. VF=2048 // main vector loop VF=1024 // vectorized remainder 1 VF=512 // vectorized remainder 2 ... Vectorize remainder until trip count is

Greetings, Can anyone suggest me if we can vectorize the following problem effectively? I have two datasets, one dataset is portfolio of stocks returns on a historical basis and another dataset consist of a bunch of factors (again on a historical basis). I intend to compute a rolling n-day sensitivitiesfor each stock for each factor, so the output will be a data frame with

Hello, I m working on a hardware with very large vector width till v2048. Now when I vectorize using llvm default vectorizer maximum 2047 iterations are scalar remainder loop. These are not vectorized by llvm which increases the cost. However these should be vectorized using next available vector width I.e v1024, v512, v256, v128, v64, v32, v16, v8, v4..... The issue of scalar remainder loop has