Metadata-Version: 2.4
Name: probabilistic_library
Version: 26.1.1
Summary: Package which provides probabilistic methods
Author: Deltares
Author-email: Deltares <d-prob-support@deltares.nl>
License: LGPL-3.0
Project-URL: Homepage, https://deltares.github.io/ProbabilisticLibrary/
Project-URL: Documentation, https://github.com/Deltares/ProbabilisticLibrary/tree/master/docs
Project-URL: Repository, https://github.com/Deltares/ProbabilisticLibrary
Project-URL: issues, https://github.com/Deltares/ProbabilisticLibrary/issues
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: matplotlib
Dynamic: author
Dynamic: requires-python

[![Python 3.11](https://img.shields.io/badge/Python-3.11-blue.svg)](https://www.python.org/downloads/release/python-31110/) 
[![C++][c++-image]][c++standard]
[![docs2](https://github.com/Deltares/ProbabilisticLibrary/actions/workflows/docs.yml/badge.svg)](https://github.com/Deltares/ProbabilisticLibrary/actions/workflows/docs.yml)

[c++-image]: https://img.shields.io/badge/C++-20-blue.svg?style=flat&logo=c%2B%2B
[c++standard]: https://isocpp.org/std/the-standard

# Probabilistic Library

This is the Probabilistic Library of Deltares.
The library provides a set of routines that enable reliability, uncertainty, and sensitivity analyses.

## Scientific background

The scientific background of the library can be found here:
[scientific_background.pdf](https://github.com/Deltares/ProbabilisticLibrary/releases/download/26.1.1/scientific_background.pdf)

## Python wrapper

A description of the Python classes is given here:
[API documentation](https://deltares.github.io/ProbabilisticLibrary/api_reference/index.html)

## Tutorials

See the [Tutorials](https://deltares.github.io/ProbabilisticLibrary/tutorials/tutorials.html) for several demonstrations and instructions on how to use the Probabilistic Library.
