Armadillo

Key Features

• Useful for algorithm development directly in C++, or quick conversion of research code into production environments; the syntax (API) is deliberately similar to Matlab • Can be used for machine learning, pattern recognition, signal processing, bioinformatics, statistics, econometrics, etc • Provides efficient classes for vectors, matrices and cubes, as well as 150+ associated functions (eg. contiguous and non-contiguous submatrix views) • Various matrix decompositions are provided through integration with LAPACK, or one of its high performance drop-in replacements (eg. multi-threaded Intel MKL, or AMD ACML, or OpenBLAS) • An automatic expression evaluator (via template meta-programming) combines several operations to increase efficiency • Integer, floating point and complex numbers are supported • The library is open-source software, distributed under a license useful in both open-source and proprietary contexts • Primarily developed at Data61 (Australia) by Conrad Sanderson, with contributions from around the world