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https://github.com/oie-mines-paristech/lca_algebraic
Layer over brightway2 for algebraic definition of parametric models and super fast computation of LCA
https://github.com/oie-mines-paristech/lca_algebraic
brightway2 foreground-activities lca lca-algebraic monte-carlo numpy symbolic-expressions
Last synced: 8 days ago
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Layer over brightway2 for algebraic definition of parametric models and super fast computation of LCA
- Host: GitHub
- URL: https://github.com/oie-mines-paristech/lca_algebraic
- Owner: oie-mines-paristech
- License: bsd-2-clause
- Created: 2020-03-30T14:53:35.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-10-10T14:34:09.000Z (29 days ago)
- Last Synced: 2024-10-29T22:30:57.260Z (10 days ago)
- Topics: brightway2, foreground-activities, lca, lca-algebraic, monte-carlo, numpy, symbolic-expressions
- Language: Jupyter Notebook
- Size: 16.2 MB
- Stars: 38
- Watchers: 7
- Forks: 18
- Open Issues: 29
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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- open-sustainable-technology - lca_algebraic - This library is a small layer above brightway2, designed for the definition of parametric inventories with fast computation of LCA impacts, suitable for monte-carlo analyis. (Industrial Ecology / Life Cycle Assessment)
README
# Introduction
This library is a layer above [**brightway2**](https://brightway.dev/) 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](https://www.sympy.org/en/index.html) 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](https://pypi.org/project/lca-algebraic/)
## 1) Setup separate environement
First create a python environment, with **Python** [>=3.9] :
**With Conda (or [mamba](https://mamba.readthedocs.io/en/latest/index.html))**
```bash
conda create -n lca python==3.10
conda activate lca
```
**With virtual env**
```bash
python3.10 -m venv .venv
source .venv/bin/activate
```
## 2) Install lca_algebraic
> pip install lca_algebraic
## 3) [Optional] Install Jupyter & Activity Browser
You may also install Jupyter and [Activity Browser](https://github.com/LCA-ActivityBrowser/activity-browser) on the same
environment.
**Jupyter** :
> pip install jupyter
**Activity Browser** can only be installed via conda/mamba. Note that it can also be installed on a separate Python env and will
still be able to access and browse the projects created programmatically with *lca_algebraic* / *Brightway*.
> conda install activity-browser
# Licence & Copyright
This library has been developed by [OIE - MinesParistech](http://www.oie.mines-paristech.fr), for the project [*INCER-ACV*](https://librairie.ademe.fr/energies-renouvelables-reseaux-et-stockage/4448-incer-acv.html),
lead by [ADEME](https://www.ademe.fr/).
It is distributed under the [BSD License](./LICENSE)
# Mailing list
Please register to this dedicated mailing list to discuss the evolutions of this library and be informed of future releases :
[[email protected]](https://groupes.minesparis.psl.eu/wws/subscribe/lca_algebraic)
# Documentation
Full documentation and example notebooks are [hosted on **readthedocs**](https://lca-algebraic.readthedocs.io/)