Tensorflow Scientific

Introduction

TensorFlow Scientific (TFS) is a Python library built on TensorFlow for scientific computing. TensorFlow Scientific contains modules for integration, ODE solvers and other tasks common in science and engineering and a sub package on quantum mechanics.

Installation

Stable Builds

To install the latest version, run the following:

pip install tensorflow-scientific

Note: tensorflow==2.0.0-beta0 will be installed with the package if you don't have it.

To use TensorFlow Scientific:

import tensorflow as tf
import tensorflow_scientific as tfs

Installing from Source

WORK IN PROGRESS

You can also install from source. This requires the Bazel build system.

git clone https://github.com/mukeshmithrakumar/scientific.git
cd addons

# This script links project with TensorFlow dependency
./configure.sh

bazel build build_pip_pkg
bazel-bin/build_pip_pkg artifacts

pip install artifacts/tensorflow_scientific-*.whl

Subpackages

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tfs.integrate

• tfs.integrate.odeint
• tfs.integrate.odeint_fixed

tfs.solvers

WORK IN PROGRESS

tfs.quantum

WORK IN PROGRESS

Examples

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WORK IN PROGRESS

Upcoming Releases

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🔥 0.3.0 Developer Alpha

• tfs.solvers
• support for linux build
• install via conda
• examples on tfs.integrate
• examples on tfs.solvers

🔥 0.4.0 Developer Alpha

• tfs.quantum
• examples on tfs.quantum

FAQ

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Q1. How do I contribute?

TF-Scientific is a community led open source project. As such, the project depends on public contributions, bug-fixes, and documentation. Please see contribution guidelines for a guide on how to contribute. This project adheres to TensorFlow's code of conduct. By participating, you are expected to uphold this code.