similar to: Easy 'apply' question

Dear list, I'm writing a function to re-grid a data set from finer to coarser resolutions in R as follows (I use this function with sapply/apply): gridResize <- function(startVec = stop("What's your input vector"), to = stop("Missing 'to': How long do you want the fnial vector to be?")){ from <- length(startVec) shortVec<-numeric() tics <- from*to

Greetings, My goal is to create a Markov transition matrix (probability of moving from one state to another) with the 'highest traffic' portion of the matrix occupying the top-left section. Consider the following sample: inputData <- c( c(5, 3, 1, 6, 7), c(9, 7, 3, 10, 11), c(1, 2, 3, 4, 5), c(2, 4, 6, 8, 10), c(9, 5, 2, 1, 1) ) MAT <- matrix(inputData,

Hi everybody, I noticed a strange behavior when using loops versus apply() on a data frame. The example below "explicitly" computes a distance matrix given a dataset. When the dataset is a matrix, everything works fine. But when the dataset is a data.frame, the dist.for function written using nested loops will take a lot longer than the dist.apply ######## USING FOR ####### dist.for

OK. Another amateur question. I have a list with attributes on pine trees, like the stem's location, a logical value set to T if it's alive, some parameters for growth, diameter, etc. The tree list has another list in it which is a new data type for me. I want to make a new list that retains all the live trees. That is where Living == T. Here's the summary of the list: >

Hello R community, I need to do some aggregation based on the test data below. The below code works ok, but when its applied to my real data which includes over 9,000 records the process runs for over an hour. I know there is a more efficient way of doing this. I want to Sum the below data's volumes where FNODE and TNODE match, i.e. FNODE=1 and TNODE =20 -> Volume=100 ,

Another solution is to only save the parts of the model object that interest you. As long as they don't include the formula (which is what drags along the environment it was created in), you will save space. E.g., tfun2 <- function(subset) { junk <- 1:1e6 list(subset=subset, lm(Sepal.Length ~ Sepal.Width, data=iris, subset=subset)$coef) } saveSize(tfun2(1:4)) #[1] 152 Bill

I have a list (length 750), each element containing a vector of unique strings (unique gene ids), with length up to ~40 (median 15). I want to compile a matrix of all possible triplets and their frequency within gene elements. Using combn and a lot of looping, I am accomplishing this but it is VERY slow. I've tried to figure out a way to vectorize this, using "match" and

Buenas noches grupo. Saludos cordiales. He seguido en la búsqueda de una forma que me permita realizar la comparación de dos documentos pertenecientes a los años 2005 y 2013, y que pueda representar finalmente con wordcloud y con una table en la que las columnas sean los años de cada informe "2005" y "2013", y las filas sean las palabras con la frecuencia de cada una de ellas

I have a very long list that I'd like to subset based on a logical value within each element. Example below. I'd like to get just those list elements for further study whose $sig.cor slot is TRUE. In this example, I'd only want element [[2]]. Should be simple, I know. How can I do this? Thanks, Mark > gene.pair.tf.lst [[1]] [[1]]$gene.pair [1] "Lgals1:Pxmp2"

Hi R, Getting a strange result using ?apply. Please look into the below codes: > d=data.frame(a=c(1,2,3),b=c("A","B","C"),c=c(TRUE,FALSE,FALSE),d=c(T,F,F )) > class(d[,1]) [1] "numeric" > class(d[,2]) [1] "factor" > class(d[,3]) [1] "logical" > class(d[,4]) [1] "logical" >

Folks, i thought it should be straightforward but after a few hours poking around, I decided it's best to post my question on this list. I have a data frame consisting of a (large) number of date columns, which are read in from a csv file as character string. I want to convert them to Date type. Following is an example, where the first column is of integer type, while the rest are type

Full_Name: simon wood Version: 2.2.0 (and lower) OS: linux/windows Submission from: (NULL) (86.135.153.59) I think that the documentation for the `specials' attribute of a `terms.object' is not quite right: specials: If the 'specials' argument was given to 'terms.formula' there is a 'specials' attribute, a list of vectors indicating the terms

Hello, What is the best way of solving this problem? answer <- ifelse(tf=TRUE, i * 5, previous answer) where as an initial condition tf[1] <- TRUE For example if, tf <- c(T,F,F,F,T,T,F) over i = 1 to 7 then the output of the function will be answer = 5 5 5 5 25 30 30 Thank you. Phil,

Hi all, I am trying to filter the element of a df that start with "TF", like this: alfa = c(123221,"TF13124",41243,"TF1234",32414,"TF13124","TF14333",2134123,"TF1234") beta =

Hi, I'm writing a function that needs the input names (as characterstrings) as part of the output. With deparse(substitute( ) ) that works fine, until I replace all zeros with 0.001 (log is calculated at some time): tf <- function(input) { input[input==0] <- 0.001 ; deparse(substitute(input)) } myguess <- 42 tf(myguess) # not "myguess", but "42" Now when

What is puppet doing here? Nov 17 00:02:01 gumby yum: Installed: tf-starterkit-tfel0-1.0-1.tf.noarch Nov 17 00:02:01 gumby puppetd[720]: (//Node[gumby.fr.xxx.com]/Starterkit::Setup[tfel0]/Package[tf-starterkit-tfel0]/ensure) created Nov 17 00:02:07 gumby yum: Installed: tf-jboss-server-4.2.3.GA-1.tf.noarch Nov 17 00:02:07 gumby puppetd[720]:

>>>>> Martin Maechler <maechler at stat.math.ethz.ch> >>>>> on Tue, 1 May 2018 16:14:43 +0200 writes: >>>>> G?bor Cs?rdi <csardi.gabor at gmail.com> >>>>> on Tue, 1 May 2018 12:05:32 +0000 writes: >> This is a not too old R-devel on Linux, it already fails >> in R 3.4.4, and on macOS as well.

Dear R users, please can you help me understand the behaviour of abline using function lm. I'm trying to learn linearity over groups. So I make three groups with 10 values each: test=data.frame(cbind( l=c(rnorm(10,0,30),rnorm(10,100,30),rnorm(10,200,30)), t = c(rep(0,10), rep(1,10), rep(2,10)) )) when I do: plot(test$l~test$t) abline(lm(test$l~test$t)) the abline is a straight line

Hola, Acabo de calcular tf-idf y me surge una duda. ¿Habría un valor de idf o tf-idf que se considerara como umbral para establecer que una palabra es muy común o no? Los valores de idf en mis datos van entre 0 y 3.78 y los de tf-idf ente 0 y 0.07. Un saludo El Mar, 28 de Abril de 2020, 12:53, Carlos Ortega escribió: > Hola, > Yo de primeras los quitaría para qué otros topics aparecen.

According to the Assembly language reference: "In LLVM, opaque types can eventually be resolved to any type (not just a structure type)." But the only way I can think of to do so is to give it a type name, then later redeclare the name. But that gives an error: %TO = type opaque %TF = type i32 ( %TO* ) %TO = type %TF gives: $ llvm-as types1.ll llvm-as: types1.ll:3:1: error: