armadillo-code | Armadillo : fast C library for linear algebra

by metablaster C++ Version: Current License: Non-SPDX

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kandi X-RAY | armadillo-code Summary

armadillo-code is a C++ library. armadillo-code has no bugs, it has no vulnerabilities and it has low support. However armadillo-code has a Non-SPDX License. You can download it from GitLab.

Armadillo is a high quality C++ library for linear algebra and scientific computing, aiming towards a good balance between speed and ease of use. It's useful for algorithm development directly in C++, and/or quick conversion of research code into production environments. It has high-level syntax and functionality which is deliberately similar to Matlab. The library provides efficient classes for vectors, matrices and cubes, as well as 200+ associated functions covering essential and advanced functionality for data processing and manipulation of matrices. Various matrix decompositions are provided through integration with LAPACK, or one of its high performance drop-in replacements (eg. OpenBLAS, Intel MKL, Apple Accelerate framework, etc). A sophisticated expression evaluator (via C++ template meta-programming) automatically combines several operations (at compile time) to increase speed and efficiency. The library can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc.

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armadillo-code has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

armadillo-code has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of armadillo-code is current.

Quality

armadillo-code has no bugs reported.

Security

armadillo-code has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

armadillo-code has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

armadillo-code releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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armadillo-code Key Features

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armadillo-code Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install armadillo-code

The installation is comprised of 3 steps:.
Step 1: Copy the entire "include" folder to a convenient location and tell your compiler to use that location for header files (in addition to the locations it uses already). Alternatively, you can use the "include" folder directly.
Step 2: Modify "include/armadillo_bits/config.hpp" to indicate which libraries are currently available on your system. For example, if you have LAPACK, BLAS (or OpenBLAS), ARPACK and SuperLU present, uncomment the following lines: #define ARMA_USE_LAPACK #define ARMA_USE_BLAS #define ARMA_USE_ARPACK #define ARMA_USE_SUPERLU If you don't need sparse matrices, don't worry about ARPACK or SuperLU.
Step 3: Configure your compiler to link with LAPACK and BLAS (and optionally ARPACK and SuperLU).

Support

Armadillo can use OpenBLAS or Intel Math Kernel Library (MKL) as high-speed replacements for BLAS and LAPACK. In essence this involves linking with the replacement libraries instead of BLAS and LAPACK.

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