 
  
 
 This tutorial illustrates the basic features of the RTensor class, RTensor is a std::vector-like container with additional shape information. 
The class serves as an interface in C++ between multi-dimensional data and the algorithm such as in machine learning workflows. The interface is similar to Numpy arrays and provides a subset of the functionality.
 
 
{
   
 
   
 
   
 
   
   auto x3 = 
x.Reshape({2, 2}).
Slice({{0, 2}, {0, 1}});
 
 
   
   float data[] = {5, 6, 7, 8};
 
 
   
   auto data2 = std::make_shared<std::vector<float>>(4);
 
   }
 
   cout << z << endl;
}
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
Option_t Option_t TPoint TPoint const char x2
T Slice(const T &histo, std::vector< Int_t > &args)
Creates a sliced copy of the given histogram.
 
{ { 0, 0 } { 0, 0 } }
{ 1, 2, 3, 4 }
{ 1, 3 }
{ { 5, 6 } { 7, 8 } }
{ { 9, 10 } { 11, 12 } }
- Date
- December 2018 
- Author
- Stefan Wunsch 
Definition in file tmva001_RTensor.C.