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Armadillo is a high quality linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use
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Provides high-level syntax and functionality deliberately similar to Matlab
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Useful for algorithm development directly in C++, or quick conversion of research code into production environments
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Provides efficient classes for vectors, matrices and cubes; dense and sparse matrices are supported
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Integer, floating point and complex numbers are supported
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A sophisticated expression evaluator (based on template meta-programming) automatically combines several operations to increase speed and efficiency
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Dynamic evaluation automatically chooses optimal code paths based on detected matrix structures
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Matrix decompositions (eigen, SVD, Cholesky, etc) are provided through
integration with LAPACK,
or one of its high performance drop-in replacements
(eg. MKL or OpenBLAS)
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Can automatically use OpenMP multi-threading (parallelisation) to speed up computationally expensive operations
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Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software
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Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc
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download latest version | git repo | browse documentation
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