Index: trunk/MagicSoft/Mars/mjtrain/MJTrainSeparation.cc
===================================================================
--- trunk/MagicSoft/Mars/mjtrain/MJTrainSeparation.cc	(revision 7672)
+++ trunk/MagicSoft/Mars/mjtrain/MJTrainSeparation.cc	(revision 7673)
@@ -386,5 +386,5 @@
     const Double_t N = num;                        //[#]
 
-    *fLog << "Events produced by MC inside the production area:         " << num << endl;
+    *fLog << "Events produced by MC inside the production area:         " << TMath::Nint(num) << endl;
 
     // This correponds to an observation time T [s]
@@ -398,10 +398,10 @@
 
     *fLog << "Events measured per second effective on time:             " << r << "Hz" << endl;
-    *fLog << "Total effective on time:                                  " << data/r  << endl;
+    *fLog << "Total effective on time:                                  " << data/r  << "s" << endl;
 
     // this yields a number of n events to be read for training
     const Double_t n = r*T;                        //[#]
 
-    *fLog << "Events to be read from the data sample:                   " << n    << endl;
+    *fLog << "Events to be read from the data sample:                   " << TMath::Nint(n) << endl;
     *fLog << "Events available in data sample:                          " << data << endl;
 
@@ -421,5 +421,5 @@
         on  = TMath::Nint(nummc*data/n);
         off = TMath::Nint(data);
-        *fLog << "Not enough data events available... scaling by " << data/n << endl;
+        *fLog << warn << "Not enough data events available... scaling by " << data/n << endl;
     }
     else
@@ -529,6 +529,6 @@
         return kFALSE;
 
-    const Int_t numgammas = train.GetNumRows();
-    if (numgammas==0)
+    const Int_t numgammastrn = train.GetNumRows();
+    if (numgammastrn==0)
     {
         *fLog << err << "ERROR - No gammas available for training... aborting." << endl;
@@ -544,6 +544,6 @@
         return kFALSE;
 
-    const Int_t numbackgrnd = train.GetNumRows()-numgammas;
-    if (numbackgrnd==0)
+    const Int_t numbackgrndtrn = train.GetNumRows()-numgammastrn;
+    if (numbackgrndtrn==0)
     {
         *fLog << err << "ERROR - No background available for training... aborting." << endl;
@@ -583,5 +583,5 @@
 
     *fLog << all;
-    fLog->Separator();
+    fLog->Separator("The forest was tested with...");
 
     *fLog << "Training method:" << endl;
@@ -589,10 +589,10 @@
     *fLog << endl;
     *fLog << "Events used for training:"   << endl;
-    *fLog << " * Gammas:     " << numgammas   << endl;
-    *fLog << " * Background: " << numbackgrnd << endl;
+    *fLog << " * Gammas:     " << numgammastrn   << endl;
+    *fLog << " * Background: " << numbackgrndtrn << endl;
     *fLog << endl;
     *fLog << "Gamma/Background ratio:" << endl;
     *fLog << " * Requested:  " << (float)fNumTrainOn/fNumTrainOff << endl;
-    *fLog << " * Result:     " << (float)numgammas/numbackgrnd << endl;
+    *fLog << " * Result:     " << (float)numgammastrn/numbackgrndtrn << endl;
 
     if (!fDataSetTest.IsValid())
@@ -684,4 +684,18 @@
         return kFALSE;
 
+    *fLog << all;
+    fLog->Separator("The forest was tested with...");
+
+    const Double_t numgammastst   = h32.GetHist().GetEntries();
+    const Double_t numbackgrndtst = h31.GetHist().GetEntries();
+
+    *fLog << "Events used for test:"   << endl;
+    *fLog << " * Gammas:     " << numgammastst   << endl;
+    *fLog << " * Background: " << numbackgrndtst << endl;
+    *fLog << endl;
+    *fLog << "Gamma/Background ratio:" << endl;
+    *fLog << " * Requested:  " << (float)fNumTestOn/fNumTestOff << endl;
+    *fLog << " * Result:     " << (float)numgammastst/numbackgrndtst << endl;
+
     return kTRUE;
 }