.. ULaMDyn documentation master file, created by
   sphinx-quickstart on Sat May  8 16:39:57 2021.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

Welcome to ULaMDyn's documentation!
===================================

**ULaMDyn** is a python-based toolkit for data analysis of (nonadiabatic) molecular dynamics (MD) simulations built on top of the Pandas and Scikit-Learn framework. 
It provides a set of classes and methods to perform the preprocessing, statistical, and unsupervised learning analysis of MD trajectories data generated by the 
`Newton-X <https://newtonx.org/>`_ program. ULaMDyn was designed to automate the search and discovery of hidden patterns in high-dimensional molecular data sets
representing complex potential energy surfaces, thereby enhancing the interpretability and understanding of nonadiabatic dynamics simulations.

Features
--------

- **Data curation:**

  + Collect and process text outputs from multiple MD trajectories to construct structured data sets.
  + Facilitate data sharing by providing data sets in standard csv format.

- **Statistical analysis:**

  + Perform a descriptive statistics by computing the *median*, *mean* and *standard deviation* over all available MD trajectories.
  + The bootstrap algorithm can be used to determine the uncertainty of molecular properties within a given confidence level.

- **Dimensionality reduction:**

  + Principal Component Analysis (PCA).
  + Kernel Principal Component Analysis (KPCA).
  + Isometric Mapping.
  + t-distributed Stochastic Neighbor Embedding (TSNE).

- **Patterns search in full dimensional MD data:**

  + K-Means clustering.
  + Hierarchical agglomerative clustering.
  + Spectral clustering.


.. toctree::
   :maxdepth: 2
   :caption: Getting Started:
   
   installation
   wrapper

.. toctree::
   :maxdepth: 2
   :caption: Tutorial:

   data_curation.ipynb

.. toctree::
   :maxdepth: 2
   :caption: Source documentation:

   ulamdyn

License
-------

This package is freely available for use and distribution under the terms of the GNU Public License (GPL version 3).

Our team:
---------

Light and Molecules group - Aix-Marseille University (AMU), France 🇫🇷

:Maintainers:
    - Max Pinheiro Jr (AMU), max.pinheiro-jr@univ-amu.fr

:Contributors:
    - Mariana Casal (AMU): Jupyter notebook tutorials

:Coordinator:
    - Prof. Mario Barbatti (AMU)

We encourage any contributions and feedback. Feel free to fork and make pull-request to the "development" branch in GitLab.