Description:

Armadillo is a template C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. The API is similar to MATLAB.

Provides efficient classes for vectors, matrices and cubes, as well as many functions which operate on the classes (eg. contiguous and non-contiguous submatrix views)

Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided via an optional integration with LAPACK, or one of its high performance drop-in replacements (eg. Intel MKL, AMD ACML, or OpenBLAS).

A delayed evaluation approach is employed (at compile time) to combine several operations into one and reduce (or eliminate) the need for temporaries. This is automatically accomplished through recursive templates and template meta-programming.

Useful for conversion of research code into production environments, or if C++ has been decided as the language of choice, due to speed and/or integration capabilities.

Distributed under a license that is useful in both open-source and commercial/proprietary contexts.

Primarily developed at NICTA (Australia) by Conrad Sanderson, with contributions from around the world.

Changes to previous version:

• faster norm() and normalise() when using Intel MKL, ATLAS or OpenBLAS
• faster handling of compound expressions by join_rows() and join_cols()
• added Schur decomposition: schur()
• added .each_slice() for repeated matrix operations on each slice of a cube
• expanded join_slices() to handle joining cubes with matrices
• expanded .each_col() and .each_row() to handle out-of-place operations
• stricter handling of matrix objects by hist() and histc()
• Cube class now delays allocation of .slice() related structures until needed

BibTeX Entry: Download

Supported Operating Systems: Linux, Windows, Unix, Mac Os X

Data Formats: Ascii, Binary, Hdf, Csv

Tags: Matlab, Matrix Library, Atlas, Lapack, Linear Algebra, Templates

Archive: download here

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