.. image:: images/logo.png

-------------------------------------

Overview
---------

**FracAbility** is a Python toolbox that can be used to analyse fracture networks and estimate length distributions considering and correcting the effect of right-censoring using survival analysis.

These are the main features available :

- **Shapefile importing support**


- **Topological analysis and identification of I,Y,X and U nodes**


- **Backbone identification**


- **Statistical analysis tools:**
    + Empirical CDF and SF calculation
    + Distribution fitting with survival analysis
    + Model selection methods

- **Plotting tools:**
    + Network objects plotting using matplotlib or vtk
    + Ternary node plot
    + Probability Integral Transform plots


The name FracAbility recalls the `reliability <https://github.com/MatthewReid854/reliability/tree/master>`_
library that inspired and helped in the creation of this project.

Documentation contents
-----------------------

1. Quickstart & Introduction
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. toctree::
  :maxdepth: 1

  Quickstart
.. toctree::
  :maxdepth: 1

  Introduction to fracture network analysis


2. Theory and recommended resources
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. toctree::
  :maxdepth: 2

  Theory reference


3. Tutorials
~~~~~~~~~~~~~~~~~~~


.. toctree::
  :maxdepth: 2

  Tutorial reference


4. API
~~~~~~~~~~~~~~~~~~~


.. toctree::
  :maxdepth: 2

  API reference


Library status information
----------------------------------------------

.. |pypi| image:: https://img.shields.io/pypi/v/fracability.svg?logo=python&logoColor=white
   :target: https://pypi.org/project/pyvista/

.. |conda| image:: https://img.shields.io/conda/vn/conda-forge/fracability.svg?logo=conda-forge&logoColor=white
   :target: https://anaconda.org/conda-forge/pyvista

.. |stars| image:: https://img.shields.io/github/stars/gbene/fracability.svg?style=social&label=Stars
   :target: https://github.com/gbene/fracability
   :alt: GitHub

.. |maintained| image:: https://img.shields.io/badge/maintained-yes-green
   :target: https://github.com/gbene/fracability
   :alt: GitHub

.. |AGPL| image:: https://img.shields.io/badge/License-AGPL--3.0-orange.svg
   :target: https://opensource.org/license/agpl-v3/

.. |python| image:: https://img.shields.io/badge/python-3.10+-orange.svg
   :target: https://www.python.org/downloads/

.. |issues| image:: https://img.shields.io/badge/GitHub-Issues-orange?logo=github
   :target: https://github.com/gbene/FracAbility/issues

.. |zenodo| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.11165916.svg
  :target: https://doi.org/10.5281/zenodo.11165916

+----------------------+--------------------------------------+
| Deployment           | |pypi|                               |
+----------------------+--------------------------------------+
| GitHub               | |maintained|                         |
+----------------------+--------------------------------------+
| Citation             | |zenodo|                             |
+----------------------+--------------------------------------+
| License              | |AGPL|                               |
+----------------------+--------------------------------------+


Authors
--------

This library and its contents was written and curated with love and care by:

+ Gabriele Benedetti (`gabri.benedetti@gmail.com <mailto:gabri.benedetti@gmail.com>`_)
+ Stefano Casiraghi (`s.casiraghi21@campus.unimib.it <mailto:s.casiraghi21@campus.unimib.it>`_)
+ Daniela Bertacchi (`daniela.bertacchi@unimib.it <mailto:daniela.bertacchi@unimib.it>`_)
+ Andrea Bistacchi (`andrea.bistacchi@unimib.it <mailto:andrea.bistacchi@unimib.it>`_)