Any reason not to get it from RcppCore/Rcpp? History shows the fix was
pulled in: https://github.com/RcppCore/Rcpp/commits/master
On my end, I just installed Rcpp via
> install_github("RcppCore/Rcpp")
and then re-installed openxlsx from CRAN via
> install.packages("openxlsx")
The script I ha
Embedded link was <
https://github.com/RevolutionAnalytics/rmr2/blob/master/pkg/src/t-list.cpp>
On Mon, May 4, 2015 at 7:39 AM, Dirk Eddelbuettel wrote:
>
> On 3 May 2015 at 21:29, Antonio Piccolboni wrote:
> | Check here for something similar to Tim's solution that preallocates all
>
> Please
ur help, and if you're interested I could describe
> you in details the goals of this code (i guess it's not the purpose of tis
> list)
> I'll let you know!
>
> Pierre
>
>
> Jonathan Olmsted a écrit :
>
>
> Pierre,
>>
>> Have you used a to
Pierre,
Have you used a tool like Valgrind? There is a bit of a learning curve, but
it is exceedingly useful.
A few comments:
1) For cases likes this gctortute(TRUE) in your R script helps those “for
enough iterations in a loop…” bugs to present quickly. With gctorture(TRUE)
I’m producing the cr
Hi, Martin.
> 1) Is there a way to see the source file of the "final" cpp-file? (I mean
> is it possible to see how the //-lines are replaced and what soureCpp does?)
>
The code generation that happens behind the scenes can be made explicit
with
sourceCpp(file = "crossp.cpp", verbose = TRUE)
James,
My attempt at marginal usefulness (compared to DE and JJE's comments) would
be to offer some code examples that I've got using OpenMP--based
parallelism. There are examples in the gallery, of course. But I've got a
number of others for euclidean distance and one for an EM algorithm. If you
I just wanted to jump in here.
Mark, I'm going to email you off the list to chat about a Gallery post. It
looks like we wanted to know roughly the same thing at roughly the same
time.
For this email, I just wanted to allay fears amongst the helpers that their
help in the last week on this topic w
Finally, some closure...
Romain, as you sensed, I did not *really* need linking. Of course, I did
not realize that earlier. You were completely right to point in the
direction of registering functions. And, while I wish this was some new
feature, it's been in R for a *long* time. How the answer co
Dirk and Romain (in the order listed in the file mentioned below),
Intellectual property rights confuse the heck out of me so I wanted to ask
explicitly before stepping on any toes. Rcpp is GPL-2. However, the
Makevars in the ./src/ directory don't necessarily carry the same license
header as your
s later with hopefully some positive results.
> >
> > Best
> >
> > Simon
> >
> > On Sep 12, 2013, at 5:47 PM, Jonathan Olmsted
> wrote:
> >
> >> Any idea where that is coming from? It isn't coming from the Rcpp
> Makevars or from
Any idea where that is coming from? It isn't coming from the Rcpp Makevars
or from a default Macports installation (as best as I can tell). I just did
an clean install of R from a clean Macports and then installed Rcpp from
within R.
g++ -dynamiclib -Wl,-headerpad_max_install_names -undefined dyna
n, NJ 08544
t: 609.258.6202
f: 609.258.1110
jolms...@princeton.edu
http://about.me/olmjo
-
On Thu, Aug 1, 2013 at 11:31 AM, Jonathan Olmsted wrote:
> Just my quick thoughts:
>
> Bayesian MCMC is what brought me to Rc
Just my quick thoughts:
Bayesian MCMC is what brought me to Rcpp. So, I have always found those
examples the most compelling. This is precisely because good R coding can't
improve performance on these problems and the gain in computational
performance really justified the development cost as oppos
Rcpp. Multiple C++ functions are created,
only some are exposed to R.
It seems like you'd probably do something similar.
-Jonathan
> | On Thu, May 16, 2013 at 8:11 PM, Dirk Eddelbuettel
> wrote:
> |
> |
> | On 16 May 2013 at 14:49, Jonathan Olmsted wrote:
> |
Several things.
Xiao, Dirk's code gives me a segfault immediately and reliably.
All, when I do this whole song and dance using the "old"
Rcpp/inline/cxxfunction approach, I don't have any issues. One obvious
difference you can see (like was mentioned) in the generated code (visibile
using verbose
Ditto Kevin's comment. I segfault no matter what.
> sessionInfo()
R version 2.15.3 (2013-03-01)
Platform: x86_64-apple-darwin12.3.0/x86_64 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datase
Yup. Progress was waiting on finalizing behavior of sample().
Current status is visible here:
https://github.com/olmjo/rcpp-gallery/blob/gh-pages/src/2013-03-19-using-the-Rcpp-based-sample-implementation.Rmd
-Jonathan
-
J.P
Jeff and List,
I was interested in the same fairly recently. The full shebang is here <
http://www.rochester.edu/college/gradstudents/jolmsted/blog/2012/08/22/rcpp-rng-performance/>.
I, unlike you, found some difference between the various approaches.
If I had to guess why we come up with differe
Liu,
A couple of initial reactions. The location of the R.h header is platform
dependent. On what platform are you working? You can always just paste the
output of the R function "sessionInfo()".
Next, the Rcpp team strongly recommends using an "inline"-based approach
where possible and an R pack
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