RFlat2DMatrix.hxx

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#ifndef ROOT_INTERNAL_ML_RFLAT2DMATRIX
#define ROOT_INTERNAL_ML_RFLAT2DMATRIX
 
#include <utility>
#include <cassert>
 
#include "ROOT/RVec.hxx"
 
namespace ROOT::Experimental::Internal::ML {
/// \brief Wrapper around ROOT::RVec<float> representing a 2D matrix
///
/// The storage is flattened row-major: index(row, col) == row * cols + col.
struct RFlat2DMatrix {
   ROOT::RVecF fRVec;
   std::size_t fRows{0};
   std::size_t fCols{0};
 
   RFlat2DMatrix() = default;
 
   RFlat2DMatrix(std::size_t rows, std::size_t cols) { Resize(rows, cols); }
 
   float *GetData() { return fRVec.data(); }
 
   const float *GetData() const { return fRVec.data(); }
 
   // Used in the pythonization
   std::pair<std::size_t, std::size_t> GetShape() const { return {fRows, fCols}; }
 
   std::size_t GetRows() const { return fRows; }
 
   std::size_t GetCols() const { return fCols; }
 
   std::size_t GetSize() const { return fRVec.size(); }
 
   void Resize(std::size_t rows, std::size_t cols)
   {
      fRows = rows;
      fCols = cols;
      fRVec.resize(rows * cols);
   }
 
   void Reshape(std::size_t rows, std::size_t cols)
   {
      // We don't reallocate: require matching sizes
      assert(rows * cols == fRVec.size());
      fRows = rows;
      fCols = cols;
   }
 
   float &operator[](std::size_t i) { return fRVec[i]; }
 
   const float &operator[](std::size_t i) const { return fRVec[i]; }
};
 
} // namespace ROOT::Experimental::Internal::ML
#endif // ROOT_INTERNAL_ML_RFLAT2DMATRIX