Deploying to gh-pages from @ 49181f7 🚀

index.html

@@ -77,8 +77,28 @@
 <div class="textblock"><p><a class="anchor" id="md_README"></a> A lightweight library for calculating neutrino oscillation probabilities using tensors typically used in machine learning.</p>
 <p><img src="doc/nuTens-logo.png" alt="nuTens" class="right" align="top" width="400" class="inline"/></p>
 <p><a href="https://github.com/ewanwm/nuTens/actions/workflows/CI-build-and-test.yml"><img src="https://github.com/ewanwm/nuTens/actions/workflows/CI-build-and-test.yml/badge.svg" alt="CI badge" style="pointer-events: none;" class="inline"/></a> <a href="https://ewanwm.github.io/nuTens/index.html"><img src="https://img.shields.io/badge/Code-Doxygen-2ea44f" alt="Code - Doxygen" class="inline"/></a></p>
-<h2><a class="anchor" id="autotoc_md1"></a>
-Feature Wishlist</h2>
+<h1><a class="anchor" id="autotoc_md1"></a>
+Installation</h1>
+<h2><a class="anchor" id="autotoc_md2"></a>
+Requirements</h2>
+<ul>
+<li>CMake - Should work with most modern versions. If you wish to use precompiled headers to speed up build times you will need CMake &gt; 3.16.</li>
+<li>Compiler with support for c++17 standard - Tested with gcc</li>
+<li><a href="https://pytorch.org/">PyTorch</a> - The recommended way to install is using PyTorch_requirements.txt: <div class="fragment"><div class="line">pip install -r PyTorch_requirements.txt</div>
+</div><!-- fragment --> (or see <a href="https://pytorch.org/get-started/locally/">PyTorch installation instructions</a> for instructions on how to build yourself)</li>
+</ul>
+<h2><a class="anchor" id="autotoc_md3"></a>
+Installation</h2>
+<p>Assuming PyTorch was built using pip, nuTens can be built using </p><div class="fragment"><div class="line">mkdir build</div>
+<div class="line">cd build</div>
+<div class="line">cmake -DCMAKE_PREFIX_PATH=`python3 -c &#39;import torch;print(torch.utils.cmake_prefix_path)&#39;`</div>
+<div class="line">make &lt;-j Njobs&gt;</div>
+</div><!-- fragment --><p>(installation with a non-pip install of PyTorch have not been tested but should be possible)</p>
+<h2><a class="anchor" id="autotoc_md4"></a>
+Verifying Installation</h2>
+<p>Once nuTens has been built, you can verify your installation by running </p><div class="fragment"><div class="line">make test</div>
+</div><!-- fragment --><h1><a class="anchor" id="autotoc_md5"></a>
+Feature Wishlist</h1>
 <ul>
 <li>[x] Support PyTorch in tensor library</li>
 <li>[x] Vacuum oscillation calculations</li>