Key Features

• Define custom scoring profiles with:

  • Desirability functions for each objective

  • Aggregation algorithm selection

  • Optional weighting and importance factors

• Calculate individual desirability scores for each property

• Aggregate scores using the specified method

• Process data from various input formats (e.g., dictionaries, dataframes)

Use Cases

• Decision support systems

• Multi-criteria optimization

• Performance evaluation

• Product or candidate ranking

Installation

Create a dedicated Python environment for this package with your favorite environment manager.

conda create -n pumas python=3.9
conda activate pumas

• Option 1: Install the package from the github repository:

pip install git+ssh://git@github.com/syngenta/pumas.git@main

• Option 2: Install the package from the Python Package Index (PyPI):

pip install pumas

Installing optional dependencies

Extensions to Pumas, have conditional dependencies on a variety of third-party Python packages. All dependencies are installed

A full list of conditional dependencies can be found in Pumas’s pyproject.toml (stored related requirements text files).

pip install pumas[uncertainty]

pip install pumas[graphics]

Development Installation

When working on the development of this package, the developer wants to work directly on the source code while still using the packaged installation.

Please install the package in development mode, including all dependencies.

git clone git@github.com:syngenta/pumas.git
pip install -e pumas/[dev]