.. SPDX-FileCopyrightText: 2026 Maria Höller, German Aerospace Center (DLR) .. .. SPDX-License-Identifier: GPL-3.0-or-later MOCA - Uncertainty in Life Cycle Assessment =========================================== Welcome to the documentation for MOCA, the Python package for uncertainty analysis in Life Cycle Assessment (LCA). This package offers: - Fast and parallelised Monte Carlo simulations for LCA - Easy integration with existing LCA workflows - Compatibility with `Brightway2 `_ databases and methods - Pre-processing to define default uncertainty distributions for LCA parameters .. grid:: 1 2 2 2 :gutter: 2 .. card:: Installation :link: installation :link-type: doc :class-card: sd-shadow-md sd-rounded-md sd-bg-light How to install and set up moca_uncertainty_lca. .. card:: Getting Started :link: tutorial :link-type: doc :class-card: sd-shadow-md sd-rounded-md sd-bg-light Step-by-step guide for new users. .. card:: Code Examples :link: examples :link-type: doc :class-card: sd-shadow-md sd-rounded-md sd-bg-light Practical examples and code snippets. .. card:: API Reference :link: api_reference :link-type: doc :class-card: sd-shadow-md sd-rounded-md sd-bg-light Full API documentation. .. .. card:: Activity Browser .. :link: activity_browser .. :link-type: doc .. :class-card: sd-shadow-md sd-rounded-md sd-bg-light .. Explore activities and results interactively. .. admonition:: Coming Soon Look forward to future updates that will include: - Post-processing tools for analysing and visualising results - Integration with the `Activity Browser `_ for an even more user-friendly experience .. note:: This documentation is a work in progress. Contributions and feedback are welcome! .. toctree:: :maxdepth: 2 :hidden: installation tutorial examples api_reference .. activity_browser