https://github.com/juanjosegarciaripoll/tensor

C++ library for numerical arrays and tensor objects and operations with them, designed to allow Matlab-style programming.
https://github.com/juanjosegarciaripoll/tensor

Last synced: about 1 month ago
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C++ library for numerical arrays and tensor objects and operations with them, designed to allow Matlab-style programming.

• Host: GitHub
• URL: https://github.com/juanjosegarciaripoll/tensor
• Owner: juanjosegarciaripoll
• License: other
• Created: 2013-01-21T12:59:50.000Z (almost 12 years ago)
• Default Branch: master
• Last Pushed: 2023-06-07T19:43:56.000Z (over 1 year ago)
• Last Synced: 2024-08-03T23:24:38.640Z (5 months ago)
• Language: C
• Size: 3.82 MB
• Stars: 51
• Watchers: 10
• Forks: 15
• Open Issues: 15
• Metadata Files:
  • Readme: README
  • License: LICENSE

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• awesome-list - juanjosegarciaripoll/tensor - C++ library for numerical arrays and tensor objects and operations with them, designed to allow Matlab-style programming. (Linear Algebra / Statistics Toolkit / General Purpose Tensor Library)

README

        
DESCRIPTION

===========

This is a C++ library for numerical arrays and tensor objects and operations

with them, designed to allow Matlab-style programming. Some of the key features:

* Fundamental data structures

  - Arrays of indices

  - Multidimensional arrays of double precision, real and complex numbers

  - Sparse matrices of real and complex numbers

* Operations

  - Algebraic operations between tensors, matrices and numbers.

  - Contraction among tensors (a generalization of matrix multiplication).

  - Tensor reshaping, index permutation, enlarging and contracting.

* Linear algebra

  - Solving systems of linear equations

  - Matrix exponentiation

  - Eigenvalue problems

  - Few eigenvalues of sparse problems using Arpack

  - Singular value decompositions

* Fast Fourier Transforms (to be done)

The Tensor library is discussed in the libtensor Google Group, currently found

here https://groups.google.com/forum/#!forum/libtensor Go to this forum for

help in configuring and installing the library.

Bug reports should be submitted using the GitHub Issues interface.

  

BUILD AND INSTALL

=================

Follow these steps to prepare, configure, build and install this library:

1) If you have checked out the library using a version control system (git) then

   several files have to be rebuilt before moving any further. Open a terminal

   and enter

      ./autogen.sh

   This will use the autotools (autoconf, automake, libtool) to rebuild several

   files, such as Makefile.in, configure, files in the m4 directory, etc.

2) Configure the library. This process detects existing software and chooses

   one or more options, such as building statically linked or shared libraries,

   using the Google Test library, etc. The process involves again a terminal

   and typing something like

      ./configure --prefix=$HOME LIBS="..." CXXFLAGS="..."

   Here we are using --prefix=$HOME to tell the configuration program that the

   libraries are going to be installed in our home directory, under $HOME/lib

   and $HOME/include, and we are passing additional options ("...") such as a

   list of libraries that are needed (LIBS) and flags for the C++ compiler

   (See below)

3) Build, optionally check and install the library

      make

      make check # optional

      make install

PLATFORM SPECIFIC DETAILS

=========================

LINUX / *BSD / etc

------------------

   You will need some version of the LAPACK and BLAS libraries installed.

   Typically, with Debian systems there are the Atlas libraries. To tell

   the tensor library that you are going to use them pass the option

       LIBS="-llapack -lcblas -latlas"

   to the "configure" program listed above.

MAC OS X

--------

   The OS X operating system is shipped with an optimized version of the Atlas

   libraries that can be used by passing the option

       LIBS="-framework veclib"

   to "configure"

OPTIONAL COMPONENTS

===================

Testing

-------

   To test the library you will need the Google Test framework, which is

   available at

       http://code.google.com/p/googletest/

Documentation

-------------

   Documentation is built using the Doxygen package, which is available in

   most Linux-type software distributions

       http://www.stack.nl/~dimitri/doxygen/

   The documentation itself is built using the command "make doxygen-doc"

   after "make" and before "make install"