{"id":38656509,"url":"https://github.com/llamm-de/tensor_tools","last_synced_at":"2026-01-17T09:28:28.832Z","repository":{"id":56583052,"uuid":"263405783","full_name":"llamm-de/tensor_tools","owner":"llamm-de","description":"A modern Fortran library for tensor calculus","archived":false,"fork":false,"pushed_at":"2021-05-03T08:24:19.000Z","size":126,"stargazers_count":6,"open_issues_count":3,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-01-30T09:13:23.907Z","etag":null,"topics":["abaqus","feap","fortran","modernfortran","tensor","tensorcalculus","umat"],"latest_commit_sha":null,"homepage":"","language":"Fortran","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"lgpl-2.1","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/llamm-de.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-05-12T17:31:12.000Z","updated_at":"2023-10-11T10:59:18.000Z","dependencies_parsed_at":"2022-08-15T21:20:53.260Z","dependency_job_id":null,"html_url":"https://github.com/llamm-de/tensor_tools","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/llamm-de/tensor_tools","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llamm-de%2Ftensor_tools","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llamm-de%2Ftensor_tools/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llamm-de%2Ftensor_tools/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llamm-de%2Ftensor_tools/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/llamm-de","download_url":"https://codeload.github.com/llamm-de/tensor_tools/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/llamm-de%2Ftensor_tools/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28505560,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-17T06:57:29.758Z","status":"ssl_error","status_checked_at":"2026-01-17T06:56:03.931Z","response_time":85,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["abaqus","feap","fortran","modernfortran","tensor","tensorcalculus","umat"],"created_at":"2026-01-17T09:28:28.730Z","updated_at":"2026-01-17T09:28:28.808Z","avatar_url":"https://github.com/llamm-de.png","language":"Fortran","funding_links":[],"categories":[],"sub_categories":[],"readme":"# TensorTools\n[![Build Status](https://jenkins.llamm.de/buildStatus/icon?job=tensor_tools_2%2Fmaster)](https://jenkins.llamm.de/job/tensor_tools_2/job/master/)\n![](https://img.shields.io/badge/license-LGPL--V2.1-blue)\n\nA modern Fortran library for tensor calculus.\n\n## Getting started\nThe following instructions will give you a copy of the project up and running on your local machine.\nNotice, this library is only tested on Unix like operating systems (e.g. Linux, MacOs), Windows is not supported at the moment.\n\n### Download\nTo get the latest version of this package, you can easily clone this repository by using\n```\ngit clone https://github.com/llamm-de/tensor_tools.git\n```\n\n### Prerequisites \u0026 Dependencies\nThis package uses [CMake](https://cmake.org/) for the creation of build files. In order to build this package yourself, you would need to have CMake installed on your system.\n\nSome optional third party dependencies are:\n\n* [**pFUnit**](https://github.com/Goddard-Fortran-Ecosystem/pFUnit) (Optional) - To run the unit test for TensorTools\n* [**Doxygen**](https://www.doxygen.nl/) (Optional) - To automatically build the documentation of TensorTools\n* [**LAPACK**](http://www.netlib.org/lapack/) (Optional) - To use the more advanced and performance oriented algorithms in TensorTools\n\nThese dependencies are disabled by default. If you wish to use them, you can activate them by providing the options ```LIBTT_TESTS=ON```, ```LIBTT_LAPACK=ON``` and/or ```LIBTT_DOCS=ON``` when running CMake.\n\n### Build \u0026 Installation\nFirst create a build directory\n```\nmkdir build\n```\nwithin the directory you cloned TensorTools into. Next run Cmake to configure the build files, i.e.\n```\ncd build\ncmake -DCMAKE_INSTALL_PREFIX=\u003cpath/to/install/dir\u003e ..\n```\nHere, you have to specify the installation path explicitly. If you did not specify the path, the executable will be build into the build directory you just created. \n\nFinally you can compile and install TensorTools by calling\n```\nmake\n```\nCongratulations, now you should be able to include the installed library into your projects.\n\n### Include TensorTools into your project\nThere are various possibilities to include the tensor tools library into your own project. A few of them are listed below.\n\n#### Use CMake\nThe most easy way to include TensorTools to your poject is available if your project is build using CMake.\n\n#### Link against a static labrary\nAfter having build the static library as described above, you only have to tell your linker where to find the ```libtt.a``` file.\n\n#### Copy source files\nIf you do not want to care about setting up CMake or configuring your build link against a static library, you can also use the quick and dirty way by copying the source files directly into your projects source directory.\n\n## LAPACK routines\nTensorTools offers some advanced and/or computational efficient routines which are based on the LAPACK library for linear algebra. The build of these routines is disabled by default. If you want to use them, you would need to set the corresponding option when running CMake, e.g.\n```\ncmake -DLIBTT_LAPACK=ON ..\n```\n\n## Testing\nIf you want to run the tests for this framework, let CMake generate your build files and compile everything using\n```\ncmake -DLIBTT_TESTS=ON -DCMAKE_PREFIX_PATH=\u003cpath/to/pfunit/install/dir\u003e ..\nmake\n```\nNow you can run the tests by calling\n```\nctest\n```\nfrom the build directory.\n\n## Examples\nYou can find examples on the functionality of this library within the ```examples``` directory. To run an example, got to the directory of the desired example and run the prepared shell script, e.g.\n```\n./run_example.sh\n```\nThis will build and execute the desired example for you.\n\n## Documentation\nIf you want to create a documentation for this framework, let CMake generate your build files and compile everything using\n```\ncmake -DLIBTT_DOCS=ON ..\n```\nNow you can create the documentation by calling\n```\nmake docs\n```\nfrom the build directory.\n\n## Versioning\nWe use [SemVer](http://semver.org/) for versioning.\n\n## Contributing\nIf you wish to contribute to this project, feel free to report issues on GitHub or to even fork and open a pull request.\n\n### Main authors\n* [**Lukas Lamm**](https://www.llamm.de) - Just some random guy working with computers\n\n## License \u0026 Copyright\nThis project is licensed under the LGPL License - see the [LICENSE.md](LICENSE.md) file for details.\n\nCopyright © 2020 by Lukas Lamm\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fllamm-de%2Ftensor_tools","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fllamm-de%2Ftensor_tools","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fllamm-de%2Ftensor_tools/lists"}