Apologies, I was using top = 0.0001
I had looked at browser and did show notconverged = NA. But I couldn't
understand why it worked for one and not the other?
On Friday, 23 December 2011, jim holtman <jholt...@gmail.com> wrote:
> Does this look similar to the error you are getting:
>
>> while(NA == TRUE) 1
> Error in while (NA == TRUE) 1 : missing value where TRUE/FALSE needed
>
> SO 'notconverged' is probably equal to NA. BTW, what is the value of
> 'tol'; I do not see it defined. So when computing 'notconverged' you
> have generated an NA. You can test it to see if this is true.
>
> You can use the following command:
>
> options(error=utils::recover)
>
> and then learn how to use the 'browser' to examine variables when the
> error occurs.
>
> On Fri, Dec 23, 2011 at 5:44 AM, Michael Pearmain
> <michael.pearm...@gmail.com> wrote:
>> Merry Xmas to all,
>>
>> I am writing a function and curiously this runs sometimes on one data set
>> and fails on another and i cannot figure out why.
>> Any help much appreciated.
>>
>> If i run the code below with
>> data <- iris[ ,1:4]
>> The code runs fine, but if i run on a large dataset i get the following
>> error (showing data structures as matrix is large)
>>
>>> str(cluster.data)
>> num [1:9985, 1:811] 0 0 0 0 0 0 0 0 0 0 ...
>> - attr(*, "dimnames")=List of 2
>> ..$ : NULL
>> ..$ : chr [1:811] "1073949105" "1073930585" "1073843224" "1073792624"
...
>> #(This is intended to be chr)
>>> str(iris)
>> 'data.frame': 150 obs. of 5 variables:
>> $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
>> $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
>> $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
>> $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
>> $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1
1 1
>> 1 1 1 ...
>>> str(as.matrix(iris[,1:4]))
>> num [1:150, 1:4] 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
>> - attr(*, "dimnames")=List of 2
>> ..$ : NULL
>> ..$ : chr [1:4] "Sepal.Length" "Sepal.Width" "Petal.Length"
"Petal.Width"
>>
>> n.cols <- ncol(data)
>> n.rows <- nrow(data)
>> X <- as.matrix(data)
>> stepsize <- 0.05
>> c1 <- (2 * pi) ** (n.cols / 2)
>> c2 <- n.rows * (smoothing ** (n.cols + 2))
>> c3 <- n.rows * (smoothing ** n.cols)
>>
>> Kexp <- function(sqs){
>> return (exp((-1 * sqs) / (2 * smoothing ** 2)))
>> }
>>
>> FindGradient <- function(x){
>> XmY <- t(x - t(X))
>> sqsum <- rowSums(XmY * XmY)
>> K <- sapply(sqsum, Kexp)
>> dens <- ((c1 * c3) ** -1) * sum(K)
>> grad <- -1 * ((c1 * c2) ** -1) * colSums(K * XmY)
>> return (list(gradient = grad,
>> density = dens))
>> }
>>
>> attractors <- matrix(0, n.rows, n.cols)
>> densities <- matrix(0, n.rows)
>>
>>
>>> density.attractors <-
>> sapply(rep(1:n.rows), function(i) {
>> notconverged <- TRUE
>> # For each row loop through and find the attractor and density
value.
>> x <- (X[i, ])
>> iters <- as.integer(1)
>> # Run gradient ascent for each point to obtain x*
>> while(notconverged == TRUE) {
>> find.gradient <- FindGradient(x)
>> next.x <- x + stepsize * find.gradient$gradient
>> change <- sqrt(sum((next.x - x) * (next.x - x)))
>> notconverged <- ifelse(change > tol, TRUE, FALSE)
>> x <- next.x
>> iters <- iters + 1
>> }
>>
>> # store the attractor and density value
>> return(c(densities[i, ] <- find.gradient$density,
>> attractors[i, ] <- x))
>> })
>>
>> Error in while (notconverged == TRUE) { :
>> missing value where TRUE/FALSE needed
>>>
>>
>> Any help would be great
>>
>> Mike
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>
>
> --
> Jim Holtman
> Data Munger Guru
>
> What is the problem that you are trying to solve?
> Tell me what you want to do, not how you want to do it.
>
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