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    <title>Project Shingle: Generalised self-consistent and automated domain discretisation for multi-scale geophysical models</title>

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<p><img src="./data/shingle.png?raw=true" alt="Shingle" title="Shingle"></p>
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        <h1>
<a name="shingle" class="anchor" href="#shingle"><span class="octicon octicon-link"></span></a>Shingle</h1>

<p>
Generalised self-consistent and automated domain discretisation for multi-scale geophysical models.
</p>

<p>
LibShingle: a computational research software library providing a high-level abstraction to spatial discretisation, or mesh generation, for domains containing complex, fractal-like boundaries that characterise those in numerical simulations of geophysical dynamics.  This is accompanied by a compact, shareable and necessarily complete description of the domain discretisation.
</p>

<p>
Geophysical model domains typically contain irregular, complex fractal-like boundaries and physical processes that act over a wide range of scales. Constructing geographically constrained boundary-conforming spatial discretisations of these domains with flexible use of anisotropic, fully unstructured meshes is a challenge. The problem contains a wide range of scales and a relatively large, heterogeneous constraint parameter space. Approaches are commonly ad hoc, model or application specific and insufficiently described. Development of new spatial domains is frequently time-consuming, hard to repeat, error prone and difficult to ensure consistent due to the significant human input required. As a consequence, it is difficult to reproduce simulations, ensure a provenance in model data handling and initialisation, and a challenge to conduct model intercomparisons rigorously. Moreover, for flexible unstructured meshes, there is additionally a greater potential for inconsistencies in model initialisation and forcing parameters. This library introduces a consistent approach to unstructured mesh generation for geophysical models, that is automated, quick-to-draft and repeat, and provides a rigorous and robust approach that is consistent to the source data throughout. The approach is enabling further new research in complex multi-scale domains, difficult or not possible to achieve with existing methods.
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<p>
Further details are provided in the library source and <a href="http://homepage.tudelft.nl/w8w0h/4fcf65d8/shingle_manual.pdf">Shingle project manual</a>.
</p>

<p>
For further information and updates, please contact the lead author Dr Adam S. Candy at <a href="mailto:contact@shingleproject.org">contact@shingleproject.org</a>.</p>

<p class="view">
  View the project on GitHub:
  <a href="https://github.com/shingleproject/Shingle">shingleproject/Shingle</a>.</p>
  <div class=bar>
      <ul>
        <li><a href="https://github.com/shingleproject/Shingle/zipball/master">Download <strong>ZIP File</strong></a></li>
        <li><a href="https://github.com/shingleproject/Shingle/tarball/master">Download <strong>TAR Ball</strong></a></li>
        <li><a href="https://github.com/shingleproject/Shingle">View On <strong>GitHub</strong></a></li>
      </ul>
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<h2>
<a name="build-status" class="anchor" href="#build-status"><span class="octicon octicon-link"></span></a>Build status</h2>

<p><a href="http://travis-ci.org/shingleproject/Shingle"><img src="https://travis-ci.org/shingleproject/Shingle.svg?branch=master" alt="Build Status"></a></p>


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<h2>
<a name="examples" class="anchor" href="#example"></a>Example geophysical domains</h2>
<p>
A selection of geophysical domains where Shingle has been applied to describe and generate geophysical domain spatial discretisation.
</p>
<p><img src="./data/shingleexamples.jpg?raw=true" alt="Shingle" title="Shingle"></p>
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<h2>
<a name="outline" class="anchor" href="#outline"><span class="octicon octicon-link"></span></a>Objectives</h2>

<ol>
<li>Introduce a consistent approach to the generation of boundary representation to arbitrary geoid bounds.</li>
<li>A user-friendly, accessible and extensible framework for model-independent geophysical domain mesh generation.</li>
<li>An intuitive, hierarchical formal grammar to fully describe and share the full heterogeneous set of constraints for the spatial discretisation of geophysical model domains.</li>
<li>Natural language basis for describing geophysical domain features.</li>
<li>Self-consistent, scalable, automated and efficient mesh prototyping.</li>
<li>Platform for iterative development that is repeatable, reproducible with a provenance history of generation.</li>
<li>Enabling rigorous unstructured mesh generation in general, for a wide range of geophysical applications, in a process that is automated, quick-to-draft and repeat, rigorous and robust, and consistent to the source data throughout.</li>
</ol>

<h2>
<a name="outline" class="anchor" href="#outline"><span class="octicon octicon-link"></span></a>Verification test engine</h2>

<p>
Includes a selection of examples, from a relatively straight-forward high-level GUI-driven interaction accessible to modellers new to mesh generation, to complex low-level development communicating with the LibShingle library.  Python interaction is used within the source, in generating documentation and in example Jupyter notebooks.
</p>

<p>
A verification test engine is continuously run in response to source code changes, some of which is tested under <a href="http://travis-ci.org/shingleproject/Shingle">Travis</a>.
</p>

<p>
An earlier version of the library Shingle 1.0 is available at: <a href="https://github.com/shingleproject/Shingle1.0">https://github.com/shingleproject/Shingle1.0</a>,
with details on the <a href="./index_shingle1.0.html">Shingle1.0 webpage</a>.
</p>

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        <p>This project is maintained by <a href="https://github.com/adamcandy">Dr Adam S. Candy</a>.</p>
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