elicito 0.5.1

A Python package for learning prior distributions based on expert knowledge

Expert prior elicitation method

A Python package for learning prior distributions based on expert knowledge

Key info :

PyPI :

Tests :

Other info :

Status

• prototype: the project is just starting up and the code is all prototype

Full documentation can be found at: elicito.readthedocs.io. We recommend reading the docs there because the internal documentation links don't render correctly on GitHub's viewer.

Installation

Our package depends on TensorFlow and thus all its requirements. Specifically, for Windows the Microsoft Visual C++ Redistributable for VisualStudio needs to be installed. See install tensorflow

As an application

If you want to use Expert prior elicitation method as an application, then we recommend using the 'locked' version of the package. This version pins the version of all dependencies too, which reduces the chance of installation issues because of breaking updates to dependencies.

The locked version of Expert prior elicitation method can be installed with

pip install 'elicito[locked]'

As a library

If you want to use Expert prior elicitation method as a library, for example you want to use it as a dependency in another package/application that you're building, then we recommend installing the package with the commands below. This method provides the loosest pins possible of all dependencies. This gives you, the package/application developer, as much freedom as possible to set the versions of different packages. However, the tradeoff with this freedom is that you may install incompatible versions of Expert prior elicitation method's dependencies (we cannot test all combinations of dependencies, particularly ones which haven't been released yet!). Hence, you may run into installation issues. If you believe these are because of a problem in Expert prior elicitation method, please raise an issue.

The (non-locked) version of Expert prior elicitation method can be installed with

pip install elicito

Additional dependencies can be installed using

# To add plotting dependencies
pip install 'elicito[plots]'

# To add all optional dependencies
pip install 'elicito[full]'

For developers

For development, we rely on uv for all our dependency management. To get started, you will need to make sure that uv is installed (instructions here (we found that the self-managed install was best, particularly for upgrading uv later).

For all of our work, we use our Makefile. You can read the instructions out and run the commands by hand if you wish, but we generally discourage this because it can be error prone. In order to create your environment, run make virtual-environment.

If there are any issues, the messages from the Makefile should guide you through. If not, please raise an issue in the issue tracker.

For the rest of our developer docs, please see [development][development].

Original template

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