Installation

Taweret is available via pip install

pip install Taweret

If you prefer to use conda for your package management, you can still pip install Taweret, but be sure to conda install pip first, so you conda environment knows where to look.

Alternative Installation

Alternatively, you can clone the repository <https://github.com/bandframework/Taweret.git>. Open cloning, the dependencies for Taweret dependencies by running the command

pip install -e .

From here, you can run the notebooks, for example, in CodeSpaces.

Prerequisites

The Trees module depends on OpenMPI. Please ensure OpenMPI is installed with shared/built libraries prior to using the Trees module.

Windows Users

The Trees module is a Python interface for a C++ backend. For Mac OS/X and Linux users, the compiled libraries are installed as a dependency with Taweret. This module is developed as a part of the Open Bayesian Trees Project (OpenBT). See references [1] and [2] for details. The package relies on OpenMPI thus Windows users must use Windows subsytem for linux in order to use the Trees module. Further installation instructions are listed below.

OpenBT will run within the Windows 10 Windows Subsystem for Linux (WSL) environment. For instructions on installing WSL, please see (https://ubuntu.com/wsl). We recommend installing the Ubuntu 20.04 WSL build. There are also instructions (https://wiki.ubuntu.com/WSL?action=subscribe&_ga=2.237944261.411635877.1601405226-783048612.1601405226#Installing_Packages_on_Ubuntu) on keeping your Ubuntu WSL up to date, or installing additional features like X support. Once you have installed the WSL Ubuntu layer, start the WSL Ubuntu shell from the start menu and then you can begin working with Taweret.

OpenBT References

  1. OpenBT Repository (https://bitbucket.org/mpratola/openbt/src/master/).

  2. OpenBR Repository with Model Mixing (https://github.com/jcyannotty/OpenBT).