Sorry, I got some new error:
Error in cut.default(i, breaks) : 'breaks' are not unique
>>>traceback()
20: stop("'breaks' are not unique")
19: cut.default(i, breaks)
18: cut(i, breaks)
17: split.default(i, cut(i, breaks))
16: split(i, cut(i, breaks))
15: structure(split(i, cut(i, breaks)), names = NULL)
14: splitIndices(length(x), ncl)
13: lapply(splitIndices(length(x), ncl), function(i) x[i])
12: splitList(x, length(cl))
11: staticClusterApply(cl, fun, length(x), argfun)
10: clusterApply(cl, splitList(x, length(cl)), lapply, fun, ...)
9: lapply(args, enquote)
8: do.call("fun", lapply(args, enquote))
7: docall(c, clusterApply(cl, splitList(x, length(cl)), lapply,
fun, ...))
6: parLapply(cl, as.list(X), FUN, ...)
5: parSapply(cl, eff, pow_error) at testing.R#5
4: eval(expr, envir, enclos)
3: eval(ei, envir)
2: withVisible(eval(ei, envir))
1: source("testing.R")
The sequential run was ok.
Best regards,
Kaiyin ZHONG
------------------------------
FMB, Erasmus MC
k.zh...@erasmusmc.nl
kindlych...@gmail.com
On Mon, Apr 29, 2013 at 8:26 PM, Duncan Murdoch <murdoch.dun...@gmail.com>wrote:
> On 29/04/2013 2:16 PM, Kaiyin Zhong (Victor Chung) wrote:
>
>> Hi, Uwe.
>>
>> I still don't get how this can be done correctly. Here is what I tried.
>>
>> In the file funcs.R, define these functions:
>>
>> library('modeest')
>> x = vector(length=500)
>> x = sapply(x, function(i) i=sample(c(1,0), 1))
>> pastK = function(n, x, k) {
>> if (n>k) { return(x[(n-k):(n-1)]) }
>> else {return(NA)}
>> }
>> predR = function(x, k) {
>> pastList = lapply(1:length(x), function(n) pastK(n, x, k))
>> pred = sapply(pastList, function(v) mfv(v)[1])
>> ratio = sum(pred==x, na.rm=T)/(length(pred) - sum(is.na(pred)))
>> }
>>
>>
>>
>> Then do the following:
>>
>> library('snow')
>> cl = makeCluster(rep('localhost', 12), 'SOCK')
>> clusterSetupRNG(cl)
>> clusterEvalQ(cl, 'source("funcs.R")')
>>
>
> The expression being evaluated there is a string,
>
> 'source("funcs.R")'
>
> You want an expression, e.g.
>
> clusterEvalQ(cl, source("funcs.R"))
>
> Duncan Murdoch
>
>
> testK = function() {
>> k = seq(3, 25, 2)
>> r = parSapply(cl, k, function(i) predR(x, i))
>> print(r)
>> }
>> testK()
>> stopCluster(cl)
>>
>>
>> The error still pops up:
>>
>> Error in checkForRemoteErrors(val) :
>> 12 nodes produced errors; first error: could not find function "predR"
>>
>>
>>
>>
>>
>> Best regards,
>>
>> Kaiyin ZHONG
>> ------------------------------
>> FMB, Erasmus MC
>> k.zh...@erasmusmc.nl
>> kindlych...@gmail.com
>>
>>
>> On Tue, Apr 23, 2013 at 3:44 PM, Uwe Ligges <
>> lig...@statistik.tu-dortmund.**de <lig...@statistik.tu-dortmund.de>
>> > wrote:
>>
>> >
>> >
>> > On 23.04.2013 15:00, Kaiyin Zhong (Victor Chung) wrote:
>> >
>> >> Thanks for the reply.
>> >>
>> >> How can i make the functions known to all nodes?
>> >>
>> >
>> > See ?clusterEvalQ
>> >
>> > you may also want to try the parallel packages.
>> >
>> > Best,
>> > Uwe Ligges
>> >
>> >
>> >
>> >
>> >> Best regards,
>> >>
>> >> Kaiyin ZHONG
>> >> ------------------------------****----------------------------**--**
>>
>> >> ------------
>> >> FMB, Erasmus MC
>> >> k.zh...@erasmusmc.nl <mailto:k.zh...@erasmusmc.nl>
>> >> kindlych...@gmail.com <mailto:kindlych...@gmail.com>
>> >>
>> >>
>> >>
>> >> On Tue, Apr 23, 2013 at 2:43 PM, Uwe Ligges
>> >> <lig...@statistik.tu-dortmund.****de <lig...@statistik.tu-dortmund.**
>> de <lig...@statistik.tu-dortmund.de>>
>> >> <mailto:lig...@statistik.tu-****dortmund.de <http://dortmund.de><
>> ligges@statistik.**tu-dortmund.de <lig...@statistik.tu-dortmund.de>>>>
>>
>> >> wrote:
>> >>
>> >>
>> >>
>> >> On 18.04.2013 11:11, Kaiyin Zhong (Victor Chung) wrote:
>> >>
>> >> Here is the code, assuming 8 cores in the cpu.
>> >>
>> >> library('modeest')
>> >> library('snow')
>> >>
>> >> cl = makeCluster(rep('localhost', 8), 'SOCK')
>> >> x = vector(length=50)
>> >> x = sapply(x, function(i) i=sample(c(1,0), 1))
>> >>
>> >> pastK = function(n, x, k) {
>> >> if (n>k) { return(x[(n-k):(n-1)]) }
>> >> else {return(NA)}
>> >> }
>> >>
>> >> predR = function(x, k) {
>> >> pastList = lapply(1:length(x), function(n) pastK(n, x,
>> k))
>> >> pred = sapply(pastList, function(v) mfv(v)[1])
>> >> ratio = sum(pred==x, na.rm=T)/(length(pred) - sum(is.na
>> >> <http://is.na>(pred)))
>> >>
>> >> }
>> >>
>> >> testK = function() {
>> >> k = seq(3, 25, 2)
>> >> r = parSapply(cl, k, function(i) predR(x, i))
>> >> # r = sapply(k, function(i) predR(x, i))
>> >> }
>> >>
>> >> r = testK()
>> >> stopCluster(cl)
>> >>
>> >> Here is the error:
>> >> Error in checkForRemoteErrors(val) :
>> >> 8 nodes produced errors; first error: could not find
>> >> function "predR"
>> >>
>> >>
>> >>
>> >> predR is not yet known on all nodes, just on the master. You have
>> to
>> >> tell the nodes about the definition first.
>> >>
>> >> Best,
>> >> Uwe Ligges
>> >>
>> >>
>> >>
>> >>
>> >>
>> >>
>> >> Best regards,
>> >>
>> >> Kaiyin ZHONG
>> >> ------------------------------
>> >>
>> >> FMB, Erasmus MC
>> >> k.zh...@erasmusmc.nl <mailto:k.zh...@erasmusmc.nl>
>> >> kindlych...@gmail.com <mailto:kindlych...@gmail.com>
>> >>
>> >> [[alternative HTML version deleted]]
>> >>
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