Installation

Prerequisites

The Trees module uses the MPI-based OpenBTMixing Python package (See [1] and [2]). Before installing Taweret, please prepare your system as indicated in the OpenBTMixing installation documentation.

It is important to note that pip maintains a cache of previously built wheels. Therefore a new Taweret installation may be faulty if OpenBTMixing was installed using a previously cached wheel that was built with an MPI installation that is different from or incompatible with the current MPI installation. To determine if pip has an OpenBTMixing wheel cached, inspect the output of

python -m pip cache list

If an OpenBTMixing wheel is present, consider removing it prior to installing Taweret with a command such as

python -m pip cache remove openbtmixing

Otherwise, the list of dependences is as short as possible to keep the installation process streamlined and allow for minimal, clean installations; however, if a user would like to run the Jupyter notebooks in the associated Jupyter Book, dependences for the notebooks will need to be installed in the relevant environment. These dependences are located in the Jupyter notebooks, and hence can be quickly installed by running the import cell at the top of each notebook.

The bilby sampler comes with the ability to use a suite of samplers---in the case of Taweret, we also have not listed all samplers as dependences. However, the user can (and should) install any samplers that they wish to use and bilby will be able to use them through its wrapper in the Taweret package.

OpenBT References

OpenBT Repository (https://bitbucket.org/mpratola/openbt/src/master/).
OpenBT Repository with Model Mixing (https://github.com/jcyannotty/OpenBT).

Windows Users

While in the past Taweret was known to work with Windows 10 using an appropriately configured Ubuntu 20.04 Windows Subsystem for Linux (WSL) build, it is presently tested only using macOS and Ubuntu installations. Windows users that would like to see if Taweret will work for them might find these instructions useful for helping to keep their Ubuntu WSL up to date, or to install additional features like X support.

Standard Installation

Taweret is available via pip install

pip install Taweret

If you prefer to use conda to setup your Python environment, 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, checkout the desired commit (ideally the latest tagged release), and install Taweret into your Python environment in developer or editable mode from the clone by running

pip install -e .

Testing

A Taweret installation can be tested directly by executing

>>> import Taweret
>>> Taweret.__version__
>>> Taweret.test()

The version output should be consistent with the version of the release that was installed or the commit that was used to install from your local clone.