RMP
2009-Mar-30 05:37 UTC
[R] Problem in S4 object displaying from within a Java application using JRI
I am using JRI (Java R Interface) library in order to call R from within my
Java application. But since the "rmu1" and "rmu2" ,see the
following code,
are objects of type S4 once i run the application the value of Null will be
returned for both of them. On this regard, i would appreciate it if anyone
can tell me how i am going to display and/ or convert these objects to Java
objects or any other way to get the result from R. In order to make the
problem more concrete i have attached the entire Java code contain my R
program and the R program itself and its actual result run in isolation:
Java application:
import java.io.*;
import java.awt.Frame;
import java.awt.FileDialog;
import java.util.Enumeration;
import org.rosuda.JRI.Rengine;
import org.rosuda.JRI.REXP;
import org.rosuda.JRI.RList;
import org.rosuda.JRI.RVector;
import org.rosuda.JRI.RMainLoopCallbacks;
public class Main {
public static void main(String[] args) {
// just making sure we have the right version of everything
if (!Rengine.versionCheck()) {
System.err.println("** Version mismatch - Java files don't
match
library version.");
System.exit(1);
}
System.out.println("Creating Rengine (with arguments)");
// 1) we pass the arguments from the command line
// 2) we won't use the main loop at first, we'll start it later
// (that's the "false" as second argument)
// 3) the callbacks are implemented by the TextConsole class above
Rengine re = new Rengine(args, false, new TextConsole());
System.out.println("Rengine created, waiting for R");
// the engine creates R is a new thread, so we should wait until
it's ready
if (!re.waitForR()) {
System.out.println("Cannot load R");
return;
}
try {
re.eval("library(kappalab)", true);
re.eval("library(methods)", true);
re.eval("mu1 <- c(59.73, 27.94,89.67, 62.44)", true);
re.eval("mu2<- c(57.81, 72.67, 82.97, 62.44)", true);
re.eval("mu3<- c(45.66, 49.19, 53, 64.39)", true);
re.eval("mu4<- c(70.39, 80.41, 89.67, 80)", true);
re.eval("delta.C <- 1", true);
re.eval("Acp <- rbind (c(mu4,mu2,delta.C),
c(mu2,mu3,delta.C),
c(mu3,mu1,delta.C))", true);
re.eval("wt <- c(0.3,0.3,0.25,0.15)/1", true);
re.eval("delta.S <- 0.08", true);
re.eval("Asp <-rbind ( c(1,4,delta.S), c(2,4,delta.S),
c(1,3,delta.S), c(2,3,delta.S),c(3,4,delta.S),c(1,2,-delta.S),
c(2,1,-delta.S))", true);
re.eval("delta.I <- 0.08", true);
re.eval("Aii <- rbind (c(1,2,delta.I,1), c(1,3, delta.I,1),
c
(1,4, delta.I,1),c(2,3, delta.I,1), c(2,4, delta.I,1), c(3,4,delta.I,1))",
true);
re.eval("lp <- lin.prog.capa.ident (4, 2, A.Choquet.preorder
Acp, A.Shapley.preorder = Asp, A.interaction.interval = Aii)", true);
re.eval("mv<- mini.var.capa.ident (4, 2, A.Choquet.preorder
Acp, A.Shapley.preorder = Asp, A.interaction.interval = Aii)", true);
re.eval("rmu1<- lp$solution", true);
re.eval("rmu1", true);
re.eval("rmu2<- mv$solution", true);
re.eval("rmu2", true);
re.eval("rbind(c(mu1,weighted.mean(mu1,wt),
Choquet.integral(rmu1,mu1), Choquet.integral(rmu2,mu1)), c(mu2,
weighted.mean(mu2,wt), Choquet.integral(rmu1,mu2),
Choquet.integral(rmu2,mu2)), c(mu3, weighted.mean(mu3,wt),
Choquet.integral(rmu1,mu3), Choquet.integral(rmu2,mu3)),c(mu4,
weighted.mean(mu4,wt), Choquet.integral(rmu1,mu4),
Choquet.integral(rmu2,mu4)))", true);
re.eval("summary (rmu1)", true);
re.eval("summary (rmu2)", true);
} catch (Exception e) {
System.out.println("EX:" + e);
e.printStackTrace();
}
}
}
/*-------------------------------------------------------------------------*/
class TextConsole implements RMainLoopCallbacks {
public void rWriteConsole(Rengine re, String text, int oType) {
System.out.print(text);
}
public void rBusy(Rengine re, int which) {
System.out.println("rBusy(" + which + ")");
}
public String rReadConsole(Rengine re, String prompt, int addToHistory)
{
System.out.print(prompt);
try {
BufferedReader br = new BufferedReader(new
InputStreamReader(System.in));
String s = br.readLine();
return (s == null || s.length() == 0) ? s : s + "\n";
} catch (Exception e) {
System.out.println("jriReadConsole exception: " +
e.getMessage());
}
return null;
}
public void rShowMessage(Rengine re, String message) {
System.out.println("rShowMessage \"" + message +
"\"");
}
public String rChooseFile(Rengine re, int newFile) {
FileDialog fd = new FileDialog(new Frame(), (newFile == 0) ?
"Select
a file" : "Select a new file", (newFile == 0) ? FileDialog.LOAD :
FileDialog.SAVE);
fd.show();
String res = null;
if (fd.getDirectory() != null) {
res = fd.getDirectory();
}
if (fd.getFile() != null) {
res = (res == null) ? fd.getFile() : (res + fd.getFile());
}
return res;
}
public void rFlushConsole(Rengine re) {
}
public void rLoadHistory(Rengine re, String filename) {
}
public void rSaveHistory(Rengine re, String filename) {
}
}
R program embedded in above Java application, but run in isolation:
> local({pkg <- select.list(sort(.packages(all.available = TRUE)))
+ if(nchar(pkg)) library(pkg, character.only=TRUE)})
Loading required package: lpSolve
Loading required package: quadprog
Loading required package: kernlab> ## E-MUSEUM 6.11.08
> mu1 <- c(59.73, 27.94, 89.67, 62.44)
> mu2<- c(57.81, 72.67, 82.97, 62.44)
> mu3<- c(45.66, 49.19, 53, 64.39)
> mu4<- c(70.39, 80.41, 89.67, 80)
>
> ##preference threshold relative
> ## to the preorder of the alternatives
> delta.C <-1
>
> ##corresponding Choquet preorder constraint matrix
> Acp <- rbind (c(mu4,mu2,delta.C), c(mu2,mu3,delta.C),
c(mu3,mu1,delta.C))
>
>
> ## weight 1=0.3, 2=0.3, 3=0.25, 4=0.15
> ## Shapley preorder constraint matrix
> ## criteria 1,2 should have the same global importance
> ## criteria 3 is more important than criteria 4
>
> wt <- c(0.3,0.3,0.25,0.15)/1
> delta.S <- 0.08
>
> Asp <-rbind ( c(1,4,delta.S), c(2,4,delta.S), c(1,3,delta.S),
> c(2,3,delta.S),c(3,4,delta.S),c(1,2,-delta.S), c(2,1,-delta.S))
>
> ## an interaction preorder constraint matrix
> delta.I <- 0.08
> Aii <- rbind (c(1,2,delta.I,1), c(1,3, delta.I,1), c (1,4, delta.I,1),
+ + c(2,3, delta.I,1), c(2,4, delta.I,1),
c(3,4,delta.I,1))>
> lp <- lin.prog.capa.ident (4, 2, A.Choquet.preorder = Acp,
> A.Shapley.preorder = Asp, A.interaction.interval = Aii)
Success: the objective function is 0.0239992 >
>
> mv<- mini.var.capa.ident (4, 2, A.Choquet.preorder = Acp,
> A.Shapley.preorder = Asp, A.interaction.interval = Aii)
>
> rmu1<- lp$solution
> rmu1
Mobius.capacity
{} 0.000000
{1} 0.000001
{2} 0.000001
{3} 0.000001
{4} 0.000001
{1,2} 0.391998
{1,3} 0.183999
{1,4} 0.080000
{2,3} 0.183999
{2,4} 0.080000
{3,4} 0.080000>
> rmu2<- mv$solution
> unclass(rmu2)
<S4 Type Object>
attr(,"subsets")
[1] 0 1 2 4 8 3 5 9 6 10 12
attr(,"k")
[1] 2
attr(,"data")
[1] 0.00000000 0.18284810 0.19427815 0.08567053 0.02284810 0.08000000
[7] 0.08000000 0.08000000 0.11435513 0.08000000 0.08000000
attr(,"n")
[1] 4> rmu2
Mobius.capacity
{} 0.000000
{1} 0.182848
{2} 0.194278
{3} 0.085671
{4} 0.022848
{1,2} 0.080000
{1,3} 0.080000
{1,4} 0.080000
{2,3} 0.114355
{2,4} 0.080000
{3,4} 0.080000>
> rbind(c(mu1,weighted.mean(mu1,wt), Choquet.integral(rmu1,mu1),
> Choquet.integral(rmu2,mu1)), c(mu2, weighted.mean(mu2,wt),
> Choquet.integral(rmu1,mu2), Choquet.integral(rmu2,mu2)), c(mu3,
> weighted.mean(mu3,wt), Choquet.integral(rmu1,mu3),
> Choquet.integral(rmu2,mu3)),
+ c(mu4, weighted.mean(mu4,wt), Choquet.integral(rmu1,mu4),
Choquet.integral(rmu2,mu4)))
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 59.73 27.94 89.67 62.44 58.0845 39.09266 47.67584
[2,] 57.81 72.67 82.97 62.44 69.2525 61.28507 65.39835
[3,] 45.66 49.19 53.00 64.39 51.3635 47.17915 48.67584
[4,] 70.39 80.41 89.67 80.00 79.6575 73.77131 76.89140>
> summary (rmu1)
Shapley value :
1 2 3 4
0.3279994 0.3279994 0.2240002 0.1200010
Shapley interaction indices :
1 2 3 4
1 NA 0.3919976 0.1839992 0.08
2 0.3919976 NA 0.1839992 0.08
3 0.1839992 0.1839992 NA 0.08
4 0.0800000 0.0800000 0.0800000 NA
Orness :
0.2222233
Veto indices :
1 2 3 4
0.8471095 0.8471095 0.7546657 0.6622220
Favor indices :
1 2 3 4
0.2568897 0.2568897 0.2106679 0.1644460
Normalized variance :
0.2709092
Normalized entropy :
0.6586446> summary (rmu2)
Shapley value :
1 2 3 4
0.3028481 0.3314557 0.2228481 0.1428481
Shapley interaction indices :
1 2 3 4
1 NA 0.0800000 0.0800000 0.08
2 0.08 NA 0.1143551 0.08
3 0.08 0.1143551 NA 0.08
4 0.08 0.0800000 0.0800000 NA
Orness :
0.3571236
Veto indices :
1 2 3 4
0.6761999 0.6990889 0.6266838 0.5695332
Favor indices :
1 2 3 4
0.3942643 0.4095188 0.3371137 0.2875976
Normalized variance :
0.07842338
Normalized entropy :
0.9035183>
--
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