Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
benchmark
docs
src
test
.gitignore
.travis.yml
LICENSE.md
README.md
REQUIRE
appveyor.yml

README.md

ContMechTensors

Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.

Note : This package is deprecated: Development continues at: https://github.com/KristofferC/Tensors.jl

Documentation Build Status

Introduction

This Julia package provides fast operations with symmetric and non-symmetric tensors of order 1, 2 and 4. The Tensors are allocated on the stack which means that there is no need to preallocate output results for performance. Unicode infix operators are provided such that the tensor expression in the source code is similar to the one written with mathematical notation. When possible, symmetry of tensors is exploited for better performance. Supports Automatic Differentiation to easily compute first and second order derivatives of tensorial functions.

Installation

The package is registered in METADATA.jl and so can be installed with Pkg.add.

julia> Pkg.add("ContMechTensors")

Documentation

  • STABLEmost recently tagged version of the documentation.
  • LATESTin-development version of the documentation.

Project Status

The package is tested against Julia 0.5, and 0.6-dev on Linux, OS X, and Windows.

Contributing and Questions

Contributions are very welcome, as are feature requests and suggestions. Please open an issue if you encounter any problems.