Armadillo (C++ library)

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Armadillo C++ Library
Stable release 4.000 / January 5, 2014 (2014-01-05)
Written in C++
Operating system Cross-platform
Available in English
Type Software library
License open source (MPL)
Website arma.sourceforge.net

Armadillo is a linear algebra software library for C++. It aims to provide an efficient and streamlined base calculations, while at the same time having a straightforward and easy to use interface. Its intended target users are scientists and engineers.

It supports integer, floating point (single and double precision), complex numbers, and a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with Linear Algebra PACKage (LAPACK) and Automatically Tuned Linear Algebra Software (ATLAS) libraries.[1] High performance LAPACK replacement libraries such as Math Kernel Library (MKL) and AMD Core Math Library (ACML) can also be used.

The library employs a delayed evaluation approach (during compile time) to combine several operations into one and reduce (or eliminate) the need for temporaries. Where applicable, the order of operations is optimised. Delayed evaluation and optimisation are achieved through template metaprogramming.

Due to its approach, Armadillo is related to the Boost Basic Linear Algebra Subprograms (uBLAS) library, but has a more accessible syntax. Further, as Armadillo has an efficient wrapper of ATLAS and LAPACK functions, it provides machine-dependent optimisations and functions not present in uBLAS.

It is open source software distributed under the Mozilla Public License, making it useful for developing both open source and proprietary software. The project is supported by the NICTA research centre in Australia and is hosted by SourceForge.

Example

Here is a trivial example demonstrating Armadillo functionality:

#include <iostream>
#include <armadillo>
 
using namespace std;
using namespace arma;
 
int main()
{
  vec b;
  b << 2.0 << 5.0 << 2.0;
 
  // endr represents the end of a row
  // in a matrix
  mat A;
  A << 1.0 << 2.0 << endr
    << 2.0 << 3.0 << endr
    << 1.0 << 3.0 << endr;
 
  cout << "Least squares solution:" << endl;
  cout << solve(A,b) << endl;
 
  return 0;
}

See also

References

External links

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