{"id":14970777,"url":"https://github.com/mukeshmithrakumar/scientific","last_synced_at":"2025-10-26T13:31:19.566Z","repository":{"id":35003812,"uuid":"192016048","full_name":"mukeshmithrakumar/scientific","owner":"mukeshmithrakumar","description":"TensorFlow scientific is a library for scientific 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align=\"center\"\u003e\u003cimg width=\"90%\" src=\"https://raw.githubusercontent.com/mukeshmithrakumar/scientific/master/logo/tfs.png\" /\u003e\u003c/p\u003e\n\n\u003ch1 id=\"TensorflowScientific\" align=\"center\" \u003eTensorflow Scientific\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"https://www.tensorflow.org/beta\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Tensorflow-2.0-orange.svg\" alt=\"Tensorflow 2.0\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://travis-ci.com/mukeshmithrakumar/scientific.svg?branch=master\"\u003e\n    \u003cimg src=\"https://travis-ci.com/mukeshmithrakumar/scientific.svg?branch=master\" alt=\"Build Status\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://pypi.org/project/tensorflow-scientific/\"\u003e\n    \u003cimg src=\"https://badge.fury.io/py/tensorflow-scientific.svg\" alt=\"PyPI Status Badge\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://pypi.python.org/pypi/tensorflow-scientific/\"\u003e\n    \u003cimg src=\"https://img.shields.io/pypi/pyversions/tensorflow-scientific.svg\" alt=\"PyPI pyversions\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://www.codacy.com/app/mukesh_4/scientific?utm_source=github.com\u0026amp;utm_medium=referral\u0026amp;utm_content=mukeshmithrakumar/scientific\u0026amp;utm_campaign=Badge_Grade\"\u003e\u003cimg src=\"https://api.codacy.com/project/badge/Grade/eb5acb88325245e9b7265da0c4f11db8\"/\u003e\n    \u003c/a\u003e\n    \u003ca href='https://coveralls.io/github/mukeshmithrakumar/scientific?branch=master'\u003e\u003cimg src='https://coveralls.io/repos/github/mukeshmithrakumar/scientific/badge.svg?branch=master' alt='Coverage Status'/\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n\n\u003ch2 align=\"center\"\u003eIntroduction\u003c/h2\u003e\n\nTensorFlow Scientific (TFS) is a Python library built on TensorFlow for scientific computing.\nTensorFlow Scientific contains modules for integration, ODE solvers and other tasks common in science and engineering and a sub package on quantum mechanics.\n\n\n\u003ch2 align=\"center\"\u003eInstallation\u003c/h2\u003e\n\n#### Stable Builds\n\nTo install the latest version, run the following:\n\n```\npip install tensorflow-scientific\n```\n\n**Note:** [`tensorflow==2.0.0-beta0`](https://www.tensorflow.org/beta) will be installed with the package if you don't have it.\n\nTo use TensorFlow Scientific:\n\n```python\nimport tensorflow as tf\nimport tensorflow_scientific as tfs\n```\n\n#### Installing from Source\n\n**WORK IN PROGRESS**\n\nYou can also install from source. This requires the [Bazel](\nhttps://bazel.build/) build system.\n\n```\ngit clone https://github.com/mukeshmithrakumar/scientific.git\ncd addons\n\n# This script links project with TensorFlow dependency\n./configure.sh\n\nbazel build build_pip_pkg\nbazel-bin/build_pip_pkg artifacts\n\npip install artifacts/tensorflow_scientific-*.whl\n```\n\n\n\u003ch2 align=\"center\"\u003eSubpackages\u003c/h2\u003e\n\u003cp align=\"right\"\u003e\u003ca href=\"#TensorflowScientific\"\u003e\u003csup\u003e▴ Back to top\u003c/sup\u003e\u003c/a\u003e\u003c/p\u003e\n\n[tfs.integrate](tensorflow_scientific/integrate/README.md)\n\n- tfs.integrate.odeint\n- tfs.integrate.odeint_fixed\n\n[tfs.solvers](tensorflow_scientific/solvers/README.md)\n\n**WORK IN PROGRESS**\n\n[tfs.quantum](tensorflow_scientific/quantum/README.md)\n\n**WORK IN PROGRESS**\n\n\n\u003ch2 align=\"center\"\u003eExamples\u003c/h2\u003e\n\u003cp align=\"right\"\u003e\u003ca href=\"#TensorflowScientific\"\u003e\u003csup\u003e▴ Back to top\u003c/sup\u003e\u003c/a\u003e\u003c/p\u003e\n\n**WORK IN PROGRESS**\n\n\n\u003ch2 align=\"center\"\u003eUpcoming Releases\u003c/h2\u003e\n\u003cp align=\"right\"\u003e\u003ca href=\"#TensorflowScientific\"\u003e\u003csup\u003e▴ Back to top\u003c/sup\u003e\u003c/a\u003e\u003c/p\u003e\n\n:fire: 0.3.0 Developer Alpha\n\n- tfs.solvers\n- support for linux build\n- install via conda\n- examples on tfs.integrate\n- examples on tfs.solvers\n\n:fire: 0.4.0 Developer Alpha\n\n- tfs.quantum\n- examples on tfs.quantum\n\n\n\u003ch2 align=\"center\"\u003eFAQ\u003c/h2\u003e\n\u003cp align=\"right\"\u003e\u003ca href=\"#TensorflowScientific\"\u003e\u003csup\u003e▴ Back to top\u003c/sup\u003e\u003c/a\u003e\u003c/p\u003e\n\nQ1. How do I contribute?\n\nTF-Scientific is a community led open source project. As such, the project\ndepends on public contributions, bug-fixes, and documentation. Please\nsee [contribution guidelines](CONTRIBUTING.md) for a guide on how to\ncontribute. This project adheres to [TensorFlow's code of conduct](CODE_OF_CONDUCT.md).\nBy participating, you are expected to uphold this code.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmukeshmithrakumar%2Fscientific","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmukeshmithrakumar%2Fscientific","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmukeshmithrakumar%2Fscientific/lists"}