Le 12/05/10 01:44, Davor Cubranic a écrit :
I think x, y, and weights are in my case not necessarily SEXPs, but can be
(i.e., some of them are pure Armadillo colvecs, while others are created from a
NumericVector without copying its contents).
Davor
sure, but wrap makes SEXP, when you do _
On 11 May 2010 at 16:41, Davor Cubranic wrote:
| No, sadly. I still get a segfault if any of the variables 'x', 'y', or
'weights' below are 'wrap'ped.
Now that we've come this far -- do you want to try 0.8.0 will should hit CRAN
tomorrow?
Early bird versions are at http://dirk.eddelbuettel/co
I think x, y, and weights are in my case not necessarily SEXPs, but can be
(i.e., some of them are pure Armadillo colvecs, while others are created from a
NumericVector without copying its contents).
Davor
On 2010-05-11, at 1:25 PM, Romain Francois wrote:
>
> Thanks for letting us know of th
No, sadly. I still get a segfault if any of the variables 'x', 'y', or
'weights' below are 'wrap'ped.
Davor
On 2010-05-11, at 1:30 PM, Dirk Eddelbuettel wrote:
>
> On 11 May 2010 at 13:17, Davor Cubranic wrote:
> | Hmm, once I stopped using 'wrap' and just passed Armadillo objects using
> 'N
On 11 May 2010 at 13:17, Davor Cubranic wrote:
| Hmm, once I stopped using 'wrap' and just passed Armadillo objects using
'Named', I'm able to run unit tests with no errors.
|
| I.e., I now use:
|
| List data = List::create(_["x"] = x,
| _["y"] = y);
| const Numeric
Thanks for letting us know of the problem ... and the solution
Not sure what the problem is. The _["x"] = is intended for implicit
calls to wrap, but it should not trouble you if you make them explicit.
maybe we did not handle properly the special case where the rhs is
already a SEXP.
Will
Hmm, once I stopped using 'wrap' and just passed Armadillo objects using
'Named', I'm able to run unit tests with no errors.
I.e., I now use:
List data = List::create(_["x"] = x,
_["y"] = y);
const NumericVector out_r = predict_fn(loess_fn(formula_fn("y~x"),
Can anyone tell me about issues I have to look out for when dealing with Rcpp
Functions and passing Armadillo objects as arguments? I'm getting "not
compatible with INTSXP" and segfault errors when calling the following Rcpp
equivalent of R's 'predict(loess(y~x, weights=w, span=span))'. The erro
