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o_bouldjedri
Hi every one I am working on shiny app using bnlearn for Bayesian networks and using r studio I get a fatal error and when I use R GUI I get this error

** caught segfault ***

address 0xfffffffc0fcd6248, cause 'memory not mapped' Traceback: 1:
.Call("mappred", node = node, fitted = fitted, data = data, n =
as.integer(n), from = from, prob = prob, debug = debug) 2:
map.prediction(node = node, fitted = object, data = data, n =
extra.args$n, from = extra.args$from, prob = prob, debug = debug) 3:
predict.bn.fit(values10$fitted, input$targetvariables, combn2, prob =
TRUE, method = "bayes-lw") 4: predict(values10$fitted,
input$targetvariables, combn2, prob = TRUE, method = "bayes-lw") 5:
t(attr(predict(values10$fitted, input$targetvariables, combn2, prob =
TRUE, method = "bayes-lw"), "prob")) 6: observeEventHandler(...) 7:
..stacktraceon..(observeEventHandler(...)) 8: handlerFunc() 9:
..stacktraceon..(expr) 10: contextFunc() 11: env$runWith(self, func)
12: withReactiveDomain(.domain, { env <- .getReactiveEnvironment()
.graphEnterContext(id) on.exit(.graphExitContext(id), add = TRUE)
env$runWith(self, func)}). ......


I tried to get the latest version of R and rstudio but it still happens

is it my computer memory that is small ?? or something else

thanks in advance



best regards

        [[alternative HTML version deleted]]

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David Winsemius

> On Jun 15, 2017, at 3:05 PM, oussama bouldjedri <[hidden email]> wrote:
>
> Hi every one I am working on shiny app using bnlearn for Bayesian networks and using r studio I get a fatal error and when I use R GUI I get this error
>
> ** caught segfault ***
>
> address 0xfffffffc0fcd6248, cause 'memory not mapped' Traceback: 1:
> .Call("mappred", node = node, fitted = fitted, data = data, n =
> as.integer(n), from = from, prob = prob, debug = debug) 2:
> map.prediction(node = node, fitted = object, data = data, n =
> extra.args$n, from = extra.args$from, prob = prob, debug = debug) 3:
> predict.bn.fit(values10$fitted, input$targetvariables, combn2, prob =
> TRUE, method = "bayes-lw") 4: predict(values10$fitted,
> input$targetvariables, combn2, prob = TRUE, method = "bayes-lw") 5:
> t(attr(predict(values10$fitted, input$targetvariables, combn2, prob =
> TRUE, method = "bayes-lw"), "prob")) 6: observeEventHandler(...) 7:
> ..stacktraceon..(observeEventHandler(...)) 8: handlerFunc() 9:
> ..stacktraceon..(expr) 10: contextFunc() 11: env$runWith(self, func)
> 12: withReactiveDomain(.domain, { env <- .getReactiveEnvironment()
> .graphEnterContext(id) on.exit(.graphExitContext(id), add = TRUE)
> env$runWith(self, func)}). ......
>
>
> I tried to get the latest version of R and rstudio but it still happens
>
> is it my computer memory that is small ?? or something else

As I already told you on SO, you should send a reproducible example to the maintainer.

>
> thanks in advance
>
>
>
> best regards
>
> [[alternative HTML version deleted]]

I did not suggest cross-posting to Rhelp, but if you are going to do so in the future, could you please read the posting guide and set up your email client to post in plain text?

(I doubt this error is due to RStudio or R. Shiny ... perhaps. "bnlearn" ... most probably.)

>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> 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.

David Winsemius
Alameda, CA, USA

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
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.
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