Changeset 7693 for trunk/MagicSoft/Mars/mranforest/MRanTree.cc

Timestamp:

05/05/06 07:46:50 (19 years ago)

Author:

tbretz

Message:

*** empty log message ***

File:

• trunk/MagicSoft/Mars/mranforest/MRanTree.cc (modified) (16 diffs)

trunk/MagicSoft/Mars/mranforest/MRanTree.cc

@@ -38 +38 @@
 #include <TRandom.h>
 
+#include "MArrayI.h"
+#include "MArrayF.h"
+
 #include "MLog.h"
 #include "MLogManip.h"
@@ -95 +98 @@
 }
 
-void MRanTree::GrowTree(TMatrix *mat, const TArrayF &hadtrue, const TArrayI &idclass,
-                        TArrayI &datasort, const TArrayI &datarang, TArrayF &tclasspop,
-                        float &mean, float &square, TArrayI &jinbag, const TArrayF &winbag,
+void MRanTree::GrowTree(TMatrix *mat, const MArrayF &hadtrue, const MArrayI &idclass,
+                        MArrayI &datasort, const MArrayI &datarang, MArrayF &tclasspop,
+                        const Float_t &mean, const Float_t &square, const MArrayI &jinbag, const MArrayF &winbag,
                         const int nclass)
 {
@@ -110 +113 @@
     for (Int_t n=0;n<numdata;n++) if(jinbag[n]==1) ninbag++;
 
-    TArrayI bestsplit(nrnodes);      bestsplit.Reset(0);
-    TArrayI bestsplitnext(nrnodes);  bestsplitnext.Reset(0);
-
-    fBestVar.Set(nrnodes);    fBestVar.Reset(0);
-    fTreeMap1.Set(nrnodes);   fTreeMap1.Reset(0);
-    fTreeMap2.Set(nrnodes);   fTreeMap2.Reset(0);
-    fBestSplit.Set(nrnodes);  fBestSplit.Reset(0);
-    fGiniDec.Set(numdim);     fGiniDec.Reset(0);
+    MArrayI bestsplit(nrnodes);
+    MArrayI bestsplitnext(nrnodes);
+
+    fBestVar.Set(nrnodes);    fBestVar.Reset();
+    fTreeMap1.Set(nrnodes);   fTreeMap1.Reset();
+    fTreeMap2.Set(nrnodes);   fTreeMap2.Reset();
+    fBestSplit.Set(nrnodes);  fBestSplit.Reset();
+    fGiniDec.Set(numdim);     fGiniDec.Reset();
 
 
@@ -139 +142 @@
         const Int_t &msp =fBestVar[k];
 
-        fBestSplit[k]  = (*mat)(bsp, msp);
-        fBestSplit[k] += (*mat)(bspn,msp);
-        fBestSplit[k] /= 2.;
+        fBestSplit[k] = ((*mat)(bsp, msp)+(*mat)(bspn,msp))/2;
     }
 
@@ -151 +152 @@
 }
 
-int MRanTree::FindBestSplitGini(const TArrayI &datasort,const TArrayI &datarang,
-                                const TArrayF &hadtrue,const TArrayI &idclass,
-                                Int_t ndstart,Int_t ndend, TArrayF &tclasspop,
-                                float &mean, float &square, Int_t &msplit,
-                                Float_t &decsplit,Int_t &nbest, const TArrayF &winbag,
+int MRanTree::FindBestSplitGini(const MArrayI &datasort,const MArrayI &datarang,
+                                const MArrayF &hadtrue,const MArrayI &idclass,
+                                Int_t ndstart,Int_t ndend, const MArrayF &tclasspop,
+                                const Float_t &mean, const Float_t &square, Int_t &msplit,
+                                Float_t &decsplit,Int_t &nbest, const MArrayF &winbag,
                                 const int nclass)
 {
@@ -161 +162 @@
     const Int_t numdata = (nrnodes-1)/2;
     const Int_t mdim = fGiniDec.GetSize();
-
-    TArrayF wr(nclass); wr.Reset(0);// right node
 
     // For the best split, msplit is the index of the variable (e.g Hillas par.,
@@ -202 +201 @@
         Double_t rld=0;
 
-        TArrayF wl(nclass); wl.Reset(0.);// left node //nclass
-        wr = tclasspop;
+        MArrayF wl(nclass); // left node //nclass
+        MArrayF wr(tclasspop);  // right node//nclass
 
         Double_t critvar=-1.0e20;
@@ -230 +229 @@
             const Double_t crit=(rln/rld)+(rrn/rrd);
 
-
             if (crit<=critvar) continue;
 
@@ -249 +247 @@
 }
 
-int MRanTree::FindBestSplitSigma(const TArrayI &datasort,const TArrayI &datarang,
-                                 const TArrayF &hadtrue, const TArrayI &idclass,
-                                 Int_t ndstart,Int_t ndend, TArrayF &tclasspop,
-                                 float &mean, float &square, Int_t &msplit,
-                                 Float_t &decsplit,Int_t &nbest, const TArrayF &winbag,
+int MRanTree::FindBestSplitSigma(const MArrayI &datasort,const MArrayI &datarang,
+                                 const MArrayF &hadtrue, const MArrayI &idclass,
+                                 Int_t ndstart,Int_t ndend, const MArrayF &tclasspop,
+                                 const Float_t &mean, const Float_t &square, Int_t &msplit,
+                                 Float_t &decsplit,Int_t &nbest, const MArrayF &winbag,
                                  const int nclass)
 {
@@ -259 +257 @@
     const Int_t numdata = (nrnodes-1)/2;
     const Int_t mdim = fGiniDec.GetSize();
-
-    float wr=0;// right node
 
     // For the best split, msplit is the index of the variable (e.g Hillas par., zenith angle ,...)
@@ -300 +296 @@
     for (Int_t mt=0; mt<fNumTry; mt++)
     {
-        const Int_t mvar=Int_t(gRandom->Rndm()*mdim);
+        const Int_t mvar= gRandom->Integer(mdim);
         const Int_t mn  = mvar*numdata;
 
         Double_t rrn=0, rrd=0, rln=0, rld=0;
-        Double_t esumr=0, esuml=0, e2sumr=0,e2suml=0;
-
-        esumr =mean;
-        e2sumr=square;
-        esuml =0;
-        e2suml=0;
+
+        Double_t esumr =mean;
+        Double_t e2sumr=square;
+        Double_t esuml =0;
+        Double_t e2suml=0;
 
         float wl=0.;// left node
-        wr = tclasspop[0];
+        float wr=tclasspop[0]; // right node
 
         Double_t critvar=critmin;
@@ -400 +395 @@
 }
 
-void MRanTree::MoveData(TArrayI &datasort,Int_t ndstart, Int_t ndend,
-                        TArrayI &idmove,TArrayI &ncase,Int_t msplit,
+void MRanTree::MoveData(MArrayI &datasort,Int_t ndstart, Int_t ndend,
+                        MArrayI &idmove,MArrayI &ncase,Int_t msplit,
                         Int_t nbest,Int_t &ndendl)
 {
@@ -410 +405 @@
     const Int_t mdim    = fGiniDec.GetSize();
 
-    TArrayI tdatasort(numdata); tdatasort.Reset(0);
+    MArrayI tdatasort(numdata);
 
     // compute idmove = indicator of case nos. going left
@@ -448 +443 @@
 }
 
-void MRanTree::BuildTree(TArrayI &datasort,const TArrayI &datarang, const TArrayF &hadtrue,
-                         const TArrayI &idclass, TArrayI &bestsplit, TArrayI &bestsplitnext,
-                         TArrayF &tclasspop, float &tmean, float &tsquare, const TArrayF &winbag,
+void MRanTree::BuildTree(MArrayI &datasort,const MArrayI &datarang, const MArrayF &hadtrue,
+                         const MArrayI &idclass, MArrayI &bestsplit, MArrayI &bestsplitnext,
+                         MArrayF &tclasspop, const Float_t &tmean, const Float_t &tsquare, const MArrayF &winbag,
                          Int_t ninbag, const int nclass)
 {
@@ -470 +465 @@
     const Int_t numdata = (nrnodes-1)/2;
 
-    TArrayI nodepop(nrnodes);     nodepop.Reset(0);
-    TArrayI nodestart(nrnodes);   nodestart.Reset(0);
-    TArrayI parent(nrnodes);      parent.Reset(0);
-
-    TArrayI ncase(numdata);       ncase.Reset(0);
-    TArrayI idmove(numdata);      idmove.Reset(0);
-    TArrayI iv(mdim);             iv.Reset(0);
-
-    TArrayF classpop(nrnodes*nclass);  classpop.Reset(0.);//nclass
-    TArrayI nodestatus(nrnodes);       nodestatus.Reset(0);
+    MArrayI nodepop(nrnodes);
+    MArrayI nodestart(nrnodes);
+    MArrayI parent(nrnodes);
+
+    MArrayI ncase(numdata);
+    MArrayI idmove(numdata);
+    MArrayI iv(mdim);
+
+    MArrayF classpop(nrnodes*nclass);//nclass
+    MArrayI nodestatus(nrnodes);
 
     for (Int_t j=0;j<nclass;j++)
         classpop[j*nrnodes+0]=tclasspop[j];
 
-    TArrayF mean(nrnodes);   mean.Reset(0.);
-    TArrayF square(nrnodes); square.Reset(0.);
+    MArrayF mean(nrnodes);
+    MArrayF square(nrnodes);
 
     mean[0]=tmean;
@@ -509 +504 @@
               tclasspop[j]=classpop[j*nrnodes+kbuild];
 
-          tmean=mean[kbuild];
-          tsquare=square[kbuild];
-
           Int_t msplit, nbest;
           Float_t decsplit=0;
 
-          if ((*this.*FindBestSplit)(datasort,datarang,hadtrue,idclass,ndstart,
-                                     ndend, tclasspop,tmean, tsquare,msplit,decsplit,
+          if ((this->*FindBestSplit)(datasort,datarang,hadtrue,idclass,ndstart,
+                                     ndend, tclasspop,mean[kbuild],square[kbuild],msplit,decsplit,
                                      nbest,winbag,nclass))
           {