lca-algebraic 1.1

This library provides a layer above brightway2 for defining parametric models and running super fast LCA for monte carlo analysis.

Introduction

This library is a layer above brightway2 designed for the definition of parametric inventories with fast computation of LCA impacts, suitable for monte-carlo / global sensitivity analysis

It integrates the magic of Sympy in order to write parametric formulas as regular Python expressions.

lca-algebraic provides a set of helper functions for :

• compact & human readable definition of activities :
  • search background (tech and biosphere) activities
  • create new foreground activities with parametrized amounts
  • parametrize / update existing background activities (extending the class Activity)
• Definition of parameters
• Fast computation of LCAs
• Computation of monte carlo method and global sensitivity analysis (Sobol indices)

Installation

We don't provide conda package anymore.

This packages is available via pip /pypi

1) Setup separate environement

First create a python environment, with Python [>=3.9] :

With Conda (or mamba)

conda env create -n lca python==3.10
conda activate lca

With virtual env

python3.10 -m venv .venv
source .venv/bin/activate

2) Install lca_algebraic

pip install lca_algebraic

Licence & Copyright

This library has been developed by OIE - MinesParistech, for the project INCER-ACV, lead by ADEME.

It is distributed under the BSD License

Documentation

Full documentation and example notebooks are hosted on readthedocs