[R-sig-Geo] slow computation progress for calc function

[Bede-Fazekas Ákos]

Dear Sara,
Hm.. so sorry, I have no more idea...
Ákos

2019.06.25. 9:55 keltezéssel, Sara Shaeri írta:
> Dear Ákos,
> I tried it on a small partition of my data. However, the processing 
> time is the same :(. Any other suggestion?
>
> -------------------------
> *Sara Shaeri Karimi*
> PhD Candidate, Department of Environmental Sciences
> Faculty of Science and Engineering
> Macquarie University, NSW 2109 Australia
> /Researchgate <https://www.researchgate.net/profile/Sara_Shaeri>
> /
> /Linkedin <https://www.linkedin.com/in/sara-shaeri-karimi-94351433>/
>
>
>
>
>
>
>
>
> On Tuesday, June 25, 2019, 4:33:34 PM GMT+10, Bede-Fazekas Ákos 
> <bfalevlist using gmail.com> wrote:
>
>
> Dear Sara,
>
> it is faster if you first convert the integer vector to logical, and
> then run rle().
>
> set.seed(12345)
> random_sample <- sample.int(n = 10, size = 1e5, replace = TRUE) - 1
>
> original <- function(x){
>     y <- rle(x)
>     return(max(y$lengths[y$values == 0]))
> }
>
> faster <- function(x){
>     y <- rle(x == 0)
>     return(max(y$lengths[y$values]))
> }
>
> original(random_sample) == faster(random_sample)
>
> library(microbenchmark)
> microbenchmark(
>     original(random_sample),
>     faster(random_sample)
> )
>
> Hence, this may be faster:
> interflood <- clusterR(all_predictions, calc, args=list(function(x){y <-
> rle(as.numeric(x) == 0; return(max(y$lengths[y$values]))}))
>
> HTH,
> Ákos Bede-Fazekas
> Hungarian Academy of Sciences
>
> 2019.06.25. 3:32 keltezéssel, Sara Shaeri via R-sig-Geo írta:
> > Dear community,
> > I’m trying to use the Calc function in a raster stack (8000 binary 
> format rasters). Each raster covers 2,421,090 cells, as such, I’m 
> using parallel coding to make the most of the available cores for this 
> computation, however, this process is extremely slow on a 36 core and 
> 76 Gb RAM. How could I speed up the calculations? This is the code I’m 
> using:
> >
> > beginCluster(30)
> >
> > interflood <- clusterR(all_predictions, calc, 
> args=list(function(x){y <- rle(as.numeric(x));return(max( 
> y$lengths[y$values == 0]))}))
> >
> > endCluster()
> >
> >
> > RegardsSara
> >
> >
> > -------------------------
> > Sara Shaeri KarimiPhD Candidate, Department of Environmental 
> SciencesFaculty of Science and EngineeringMacquarie University, NSW 
> 2109 Australia
> > Researchgate
> > Linkedin
>
> >
> >
> >
> >
> >
> >
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