Thank you for the example. Based on my recent experiments, this solution
is the most efficient.
Cheers,
Jaroslav
On 2015-12-15 23:15, Simon Urbanek wrote:
> You can pass the entire df, example:
>
>> data(iris)
>> iris$sp = as.character(iris$Species)
>> o=.jarray(lapply(iris, .jarray))
>> .jcall(
You can pass the entire df, example:
> data(iris)
> iris$sp = as.character(iris$Species)
> o=.jarray(lapply(iris, .jarray))
> .jcall("C",,"df",o)
df, 6 variables
[0]: double[150]
[1]: double[150]
[2]: double[150]
[3]: double[150]
[4]: int[150]
[5]: String[150]
Java code:
public class C {
Dear all,
thank you for your hints. I would prefer to do not use Rserve as Dirk
mentioned.
@Simon
I have full control over the Java implementation - I can adapt the code
that I use for the communication R <-> Java.
> You can natively access structures on each side. The fastest way is to
> use
On Dec 6, 2015, at 12:36 PM, Ing. Jaroslav Kuchař
wrote:
> Dear all,
>
> in our ongoing project we use Java implementations of several
> algorithms. We also provide a “wrapper” implemented as an R package
> using rJava (https://github.com/jaroslav-kuchar/rCBA). Based on our
> recent experiments
On 6 December 2015 at 18:36, Ing. Jaroslav Kuchař wrote:
| in our ongoing project we use Java implementations of several
| algorithms. We also provide a “wrapper” implemented as an R package
| using rJava (https://github.com/jaroslav-kuchar/rCBA). Based on our
| recent experiments, the significant
