Path to this page:
./
math/armadillo,
C++ linear algebra library
Branch: CURRENT,
Version: 12.6.7,
Package name: armadillo-12.6.7,
Maintainer: baconArmadillo is an open-source C++ linear algebra library (matrix maths) aiming
towards a good balance between speed and ease of use. Integer, floating point
and complex numbers are supported, as well as a subset of trigonometric and
statistics functions.
Master sites:
Filesize: 6653.379 KB
Version history: (Expand)
- (2023-12-19) Package added to pkgsrc.se, version armadillo-12.6.7 (created)
CVS history: (Expand)
2024-08-25 08:19:21 by Thomas Klausner | Files touched by this commit (575) |
Log message:
*: replace CMAKE_ARGS with CMAKE_CONFIGURE_ARGS
|
2023-12-19 13:28:50 by Dr. Thomas Orgis | Files touched by this commit (6) |
Log message:
math/armadillo: C++ linear algebra library
longer form:
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
Provides high-level syntax and functionality deliberately similar
to Matlab
Useful for algorithm development directly in C++, or quick conversion
of research code into production environments
Provides efficient classes for vectors, matrices and cubes; dense and
sparse matrices are supported
Integer, floating point and complex numbers are supported
A sophisticated expression evaluator (based on template meta-programming)
automatically combines several operations to increase speed and efficiency
Dynamic evaluation automatically chooses optimal code paths based on
detected matrix structures
Various matrix decompositions (eigen, SVD, QR, etc) are provided
through integration with LAPACK, or one of its high performance drop-in
replacements (eg. MKL or OpenBLAS)
Can automatically use OpenMP multi-threading (parallelisation) to speed
up computationally expensive operations
Distributed under the permissive Apache 2.0 license, useful for both
open-source and proprietary (closed-source) software
Can be used for machine learning, pattern recognition, computer vision,
signal processing, bioinformatics, statistics, finance, etc
|