[tutorials] Rename TMVA to Machine Learning category.

Inside the current TMVA category of tutorials,
there are not only the tmva tutorials but for example
also RBatchGenerator tutorials. Hence, new Machine
Learning category will be the entry point to all the
related tutorials.
Paths to files were changed across all of the ROOT
repository as well.

bindings/pyroot/pythonizations/python/ROOT/JsMVA/OutputTransformer.py

@@ -300,7 +300,7 @@ def __transformOneGroup(self, firstLine):
                         self.iterLines.next()
                         lineIter.next()
                     tmp_str += "<td><b>" + WelcomeHeader.group(1) + "</b></td></tr>"
-                    tmp_str += "<tr><td><img src='https://rawgit.com/root-project/root/master/tutorials/tmva/tmva_logo.svg' width='100%' /><br />"
+                    tmp_str += "<tr><td><img src='https://rawgit.com/root-project/root/master/tutorials/machine_learning/tmva_logo.svg' width='100%' /><br />"
                     tmp_str += "<center><b>" + EndWelcome.group(1) + "</b></center></td></tr>"
                 else:
                     lmatch = re.match(r"\s*(<\w+>\s*)*\s*:\s*(.*)", nextline)

documentation/tmva/UsersGuide/TMVAdef.tex

@@ -245,5 +245,5 @@
 \newcommand{\IHessiankmone}{\ensuremath{\Hessian^{-1(k-1)}}\xspace}
 
 % TMVA constants
-\newcommand\TmvaTutorialDir{\code{$ROOTSYS/tutorials/tmva/test}~}
-\newcommand\TmvaKerasTutorialDir{\code{$ROOTSYS/tutorials/tmva/test/keras}~}
+\newcommand\TmvaTutorialDir{\code{$ROOTSYS/tutorials/machine_learning/test}~}
+\newcommand\TmvaKerasTutorialDir{\code{$ROOTSYS/tutorials/machine_learning/test/keras}~}

documentation/tmva/UsersGuide/UsingTMVAQuickStart.tex

@@ -81,8 +81,8 @@ \subsection{Running the example}
 to ROOT's macro search path:
 \begin{codeexample}
 \begin{tmvacode}
-> root -l $ROOTSYS/tutorials/tmva/TMVAClassification.C
-> echo "Unix.*.Root.MacroPath: $ROOTSYS/tutorials/tmva" >> ~/.rootrc
+> root -l $ROOTSYS/tutorials/machine_learning/TMVAClassification.C
+> echo "Unix.*.Root.MacroPath: $ROOTSYS/tutorials/machine_learning" >> ~/.rootrc
 > root -l TMVAClassification.C
 \end{tmvacode}
 \caption[.]{\codeexampleCaptionSize Running the example \code{TMVAClassification.C}.}
@@ -91,7 +91,7 @@ \subsection{Running the example}
 It is also possible to explicitly select the MVA methods to be processed:
 \begin{codeexample}
 \begin{tmvacode}
-> root -l '$ROOTSYS/tutorials/tmva/TMVAClassification.C("Fisher","BDT")'
+> root -l '$ROOTSYS/tutorials/machine_learning/TMVAClassification.C("Fisher","BDT")'
 \end{tmvacode}
 \caption[.]{\codeexampleCaptionSize Running the example \code{TMVAClassification.C} and processing only the Fisher and BDTclassifier. Multiple classifiers are separated by commas. The others macros can be called accordingly.}
 \end{codeexample}

tmva/doc/README

@@ -16,7 +16,7 @@ copying of 'evaluation macros' necessary anymore !
 
 All the evaluation macros are now part of the TMVA library libTMVA.so
 
-Example scripts of how to run TMVA are available in $ROOTSYS/tutorials/tmva/
+Example scripts of how to run TMVA are available in $ROOTSYS/tutorials/machine_learning/
 !!!!!
 
 After 2013 TMVA was completely integrated into ROOT and is now released as part of it.
@@ -31,7 +31,7 @@ System requirements:
 ========================================================================================
 Getting Started:
 ----------------
-  Example scripts of how to run TMVA are availabe in $ROOTSYS/tutorials/tmva/
+  Example scripts of how to run TMVA are availabe in $ROOTSYS/tutorials/machine_learning/
 
   please simply copy one of those scripts to you 'work' directory
 

tmva/pymva/test/testPyAdaBoostMulticlass.C

@@ -16,7 +16,7 @@ int testPyAdaBoostMulticlass(){
    TString fname = "./tmva_example_multiple_background.root";
    if (gSystem->AccessPathName(fname)){  // file does not exist in local directory
       std::cout << "Create multiclass test data..." << std::endl;
-      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/tmva/createData.C";
+      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/machine_learning/createData.C";
       gROOT->ProcessLine(TString::Format(".L %s",createDataMacro.Data()));
       gROOT->ProcessLine("create_MultipleBackground(200)");
       std::cout << "Created " << fname << " for tests of the multiclass features" << std::endl;

tmva/pymva/test/testPyGTBMulticlass.C

@@ -16,7 +16,7 @@ int testPyGTBMulticlass(){
    TString fname = "./tmva_example_multiple_background.root";
    if (gSystem->AccessPathName(fname)){  // file does not exist in local directory
       std::cout << "Create multiclass test data..." << std::endl;
-      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/tmva/createData.C";
+      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/machine_learning/createData.C";
       gROOT->ProcessLine(TString::Format(".L %s",createDataMacro.Data()));
       gROOT->ProcessLine("create_MultipleBackground(200)");
       std::cout << "Created " << fname << " for tests of the multiclass features" << std::endl;

tmva/pymva/test/testPyKerasMulticlass.C

@@ -27,7 +27,7 @@ int testPyKerasMulticlass(){
    TString fname = "./tmva_example_multiple_background.root";
    if (gSystem->AccessPathName(fname)){  // file does not exist in local directory
       std::cout << "Create multiclass test data..." << std::endl;
-      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/tmva/createData.C";
+      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/machine_learning/createData.C";
       gROOT->ProcessLine(TString::Format(".L %s",createDataMacro.Data()));
       gROOT->ProcessLine("create_MultipleBackground(200)");
       std::cout << "Created " << fname << " for tests of the multiclass features" << std::endl;

tmva/pymva/test/testPyRandomForestMulticlass.C

@@ -16,7 +16,7 @@ int testPyRandomForestMulticlass(){
    TString fname = "./tmva_example_multiple_background.root";
    if (gSystem->AccessPathName(fname)){  // file does not exist in local directory
       std::cout << "Create multiclass test data..." << std::endl;
-      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/tmva/createData.C";
+      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/machine_learning/createData.C";
       gROOT->ProcessLine(TString::Format(".L %s",createDataMacro.Data()));
       gROOT->ProcessLine("create_MultipleBackground(200)");
       std::cout << "Created " << fname << " for tests of the multiclass features" << std::endl;

tmva/pymva/test/testPyTorchMulticlass.C

@@ -17,7 +17,7 @@ int testPyTorchMulticlass(){
    TString fname = "./tmva_example_multiple_background.root";
    if (gSystem->AccessPathName(fname)){  // file does not exist in local directory
       std::cout << "Create multiclass test data..." << std::endl;
-      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/tmva/createData.C";
+      TString createDataMacro = TString(gROOT->GetTutorialsDir()) + "/machine_learning/createData.C";
       gROOT->ProcessLine(TString::Format(".L %s",createDataMacro.Data()));
       gROOT->ProcessLine("create_MultipleBackground(200)");
       std::cout << "Created " << fname << " for tests of the multiclass features" << std::endl;

tmva/sofie/README.md

@@ -148,13 +148,13 @@ The above operators are supported for tensors of the following types:
 ## Additional Links
 
 - **Tutorials**
-    - [TMVA_SOFIE_Inference](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_Inference.py)
-    - [TMVA_SOFIE_Keras](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_Keras.C)
-    - [TMVA_SOFIE_Keras_HiggsModel](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_Keras_HiggsModel.C)
-    - [TMVA_SOFIE_ONNX](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_ONNX.C)
-    - [TMVA_SOFIE_PyTorch](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_PyTorch.C)
-    - [TMVA_SOFIE_RDataFrame](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_RDataFrame.C)
-    - [TMVA_SOFIE_RDataFrame](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_RDataFrame.py)
-    - [TMVA_SOFIE_RDataFrame_JIT](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_RDataFrame_JIT.C)
-    - [TMVA_SOFIE_RSofieReader](https://github.com/root-project/root/blob/master/tutorials/tmva/TMVA_SOFIE_RSofieReader.C)
+    - [TMVA_SOFIE_Inference](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_Inference.py)
+    - [TMVA_SOFIE_Keras](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_Keras.C)
+    - [TMVA_SOFIE_Keras_HiggsModel](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_Keras_HiggsModel.C)
+    - [TMVA_SOFIE_ONNX](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_ONNX.C)
+    - [TMVA_SOFIE_PyTorch](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_PyTorch.C)
+    - [TMVA_SOFIE_RDataFrame](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.C)
+    - [TMVA_SOFIE_RDataFrame](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.py)
+    - [TMVA_SOFIE_RDataFrame_JIT](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_RDataFrame_JIT.C)
+    - [TMVA_SOFIE_RSofieReader](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_RSofieReader.C)
 

tmva/tmvagui/src/tmvaglob.cxx

@@ -252,9 +252,9 @@ void TMVA::TMVAGlob::imgconv( TCanvas* c, const TString & fname )
 TImage * TMVA::TMVAGlob::findImage(const char * imageName)
 {
    // looks for the image in tutorialpath
-   //TString tutorialPath = "$ROOTSYS/tutorials/tmva"; // look for the image in here
+   //TString tutorialPath = "$ROOTSYS/tutorials/machine_learning"; // look for the image in here
    TString tutorialPath = getenv ("ROOTSYS");
-   tutorialPath+="/tutorials/tmva";
+   tutorialPath+="/tutorials/machine_learning";
    TImage *img = nullptr;
    TString fullName = TString::Format("%s/%s", tutorialPath.Data(), imageName);
    Bool_t fileFound = ! gSystem->AccessPathName(fullName);