• TNT Data Structures
  • C-style arrays
  • Fortran-style arrays
  • Sparse Matrices
  • Vector/Matrix
• TNT utilities
  • array I/O
  • math routines (hypot(), sign(), etc.)
  • Stopwatch class for timing measurements
• Libraries that utilize TNT
  • JAMA: a linear algebra library with QR, SVD, Cholesky and Eigenvector solvers.
  • old (pre 1.0) TNT routines for LU, QR, and Eigenvalue problems

TNT Data Structures

Vectors, Matrices, and multidimensional arrays form the basic data structures for scientific computing. TNT defines various interfaces for these. See the Documentation section for details.

• Numerical Arrays (pass-by-reference semantics)
  • C-style arrays:
    • TNT::Array1D
    • TNT::Array2D
    • TNT::Array3D

    accessed as A[i][j], with A[0][0] as the first element, stored in "row-major" storage order (i.e. right-most dimension varying fastest). This is useful when interfacing with codes written in C or using native "multidimensional" arrays of C/C++.

  • Fortran-style arrays:
    • TNT::Fortran_Array1D
    • TNT::Fortran_Array2D
    • TNT::Fortran_Array3D

    accessed as A(i,j), with A(1,1) as the first element, stored contiguous in memory in "column-major" storage order (i.e. left-most dimension varying fastest). This is useful when translating codes from Fortran by hand or via f2c().

• Sparse Matrices (pass-by-reference semantics)
  • TNT::Sparse_Matrix_CompRow

• Vector/Matrix (pass-by-value semantics)
  • TNT::Vector
  • TNT::Matrix

  [Note]: The Vector/Matrix classes have been superceded by the Array classes but are retained for backward compatibility.

• Utilities
  • array I/O
  • auxillary math routines, e.g. hypot(), abs(), sign()
  • Stopwatch class for timing measurements

Libraries that utilize TNT

• JAMA/C++: a translation of the Java Matrix Library, developed by the Mathworks and NIST, into C++
  • classical matrix linear algebra
  • LU
  • QR
  • SVD
  • Cholesky
  • Eigenvalue solver

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