# Welcome to aPriori

## Overview 

This guide explains how to use the library and its main features. 

The first section [Getting Started](https://apriori.gitbook.io/apriori-documentation-1/getting-started) introduces the aim of the project, explains how to install the package in your Python environment and provides a code that can be used immediately to perform analysis on a Direct Numerical Simulation (DNS) of a hydrogen flame. The second section [Fundamentals and Usage](https://apriori.gitbook.io/apriori-documentation-1/fundamentals-and-usage) goes into more detail, giving examples of how to use the single blocks of the library to obtain the maximum from it. If the code in the quickstart was too complex, this section is the right one to get more insight. The third section [API Guide](https://apriori.gitbook.io/apriori-documentation-1/api-guide) clarifies the code from a developer's point of view, explaining each function and the main classes with their attributes and methods. If you are interested in the library as a user, you can skip this section.

## [Source Code](https://github.com/LorenzoPiu/aPrioriDNS) 💻

The source code is updated and available at the following link on the [GitHub page](https://github.com/LorenzoPiu/aPrioriDNS). In the Tags section, are benchmarked the different releases of the software. Any problem with the code can be reported in the issue section. If you have any further questions regarding the code, don't hesitate to send an e-mail to <lorenzo.piu@ulb.be>

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{% hint style="warning" %}
**Disclaimer:** This webpage may be missing some of the latest functionalities added to the software. Please contact me at <lorenzo.piu@ulb.be> in case you need any further information regarding the code. In the meantime, I am working to keep the documentation updated.
{% endhint %}

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## Documentation outline

### Getting Started

* [What is aPriori?](https://apriori.gitbook.io/apriori-documentation-1/getting-started/what-is-apriori)
* [Installation](https://apriori.gitbook.io/apriori-documentation-1/getting-started/installation)
* [Quickstart](https://apriori.gitbook.io/apriori-documentation-1/getting-started/quickstart)

### Fundamentals and Usage

* [aPriori Fundamentals](https://apriori.gitbook.io/apriori-documentation-1/fundamentals-and-usage/apriori-fundamentals)
* [Tutorial](https://apriori.gitbook.io/apriori-documentation-1/fundamentals-and-usage/machine-learning-tutorials)
  * [Dynamic Data-Driven Smagorinky Closure for LES](https://apriori.gitbook.io/apriori-documentation-1/fundamentals-and-usage/machine-learning-tutorials/dynamic-data-driven-smagorinky-closure-for-les)
  * [Data-Driven Closure for Turbulence-Chemistry Interaction](https://apriori.gitbook.io/apriori-documentation-1/fundamentals-and-usage/machine-learning-tutorials/data-driven-closure-for-turbulence-chemistry-interaction)

### API Guide

* [Field3D](https://apriori.gitbook.io/apriori-documentation-1/api-guide/field3d)
* [Scalar3D](https://apriori.gitbook.io/apriori-documentation-1/api-guide/scalar3d)
* [Mesh3D](https://apriori.gitbook.io/apriori-documentation-1/api-guide/mesh3d)