Update Docs

docs/source/index.rst

@@ -21,24 +21,14 @@ for deep learning assisted reacting flow simulations. It is also has the scope t
 .. toctree::
    :maxdepth: 3
    :numbered:
-   :caption: Installation
-   :glob:
-
-   installation/index
-
-.. _quikstart:
-
-.. toctree::
-   :maxdepth: 3
    :caption: Quick Start
    :glob:
 
-   quickstart/index
+   qs/install
+   qs/examples
+   qs/input
 
 
-
-
-
 .. _solvers:
 
 .. toctree::

docs/source/qs/examples.rst

@@ -0,0 +1,88 @@
+Two Examples 
+===================
+
+DeepFlame with DNN
+--------------------------
+
+If you choose to use PyTorch as the integratgor and use the compilation flag `--use_pytorch`, you can run examples stored in `$HOME/deepflame-dev/examples/.../pytorchIntegratgor`. To run an example, you first need to source your OpenFOAM:
+
+.. code-block:: bash
+
+    source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
+
+Then, source your DeepFlame:
+
+.. code-block:: bash
+
+    source $HOME/deepflame-dev/bashrc
+
+Next, you can go to the directory of any example case that you want to run. For example:
+
+.. code-block:: bash
+
+    cd $HOME/deepflame-dev/examples/zeroD_cubicReactor/H2/pytorchIntegratgor
+
+This is an example for the zero-dimensional hydrogen combustion with PyTorch as the integrator. All files needed by DNN are stored in `pytorchDNN` folder, and the inference file is `inference.py`. Configurations regarding DNN are included in `constant/CanteraTorchProperties`.
+
+The case is run by simply typing: 
+
+.. code-block:: bash
+
+    ./Allrun
+
+.. Note:: Users can go to `constant/CanteraTorchProperties` and check if `torch` is switched on. Switch it `on` to run DNN cases, and switch `off` to run CVODE cases.
+
+If you plot PyTorch's result together with CVODE's result, the graph is expected to look like:
+
+.. figure:: pytorch.png
+
+    Visualisation of 0D results from PyTorch and CVODE integrators 
+
+
+
+DeepFlame without DNN
+------------------------------
+CVODE Integrator is the one without the application of Deep Neural Network (DNN). Follow the steps below to run an example of CVODE. Examples are stored in the directory: 
+.. code-block:: bash
+
+    $HOME/deepflame-dev/examples
+
+To run these examples, first source your OpenFOAM, depending on your OpenFOAM path:
+
+.. code-block:: bash
+
+    source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
+
+Then, source your DeepFlame:
+
+.. code-block:: bash
+
+    source $HOME/deepflame-dev/bashrc
+
+Next, you can go to the directory of any example case that you want to run. For example:
+
+.. code-block:: bash
+
+    cd $HOME/deepflame-dev/examples/zeroD_cubicReactor/H2/cvodeIntegrator
+
+This is an example for the zero-dimensional hydrogen combustion  with CVODE integrator.
+
+The case is run by simply typing: 
+
+.. code-block:: bash
+
+    ./Allrun
+
+The probe used for post processing is defined in ``/system/probes``. In this case, the probe is located at the coordinates (0.0025 0.0025 0.0025) to measure temperature variation with time. 
+If the case is successfully run, the result can be found in ``/postProcessing/probes/0/T``, and it can be visualized by running: 
+
+.. code-block:: bash
+
+    gunplot
+    plot "/your/path/to/postProcessing/probes/0/T"
+
+You will get a graph:
+
+.. figure:: 0Dcvode.jpg
+
+    Visualisation of the zero-dimensional hydrogen combustion result with CVODE integrator

docs/source/qs/input.rst

@@ -0,0 +1,59 @@
+Brief Introduction to Inputs
+======================================
+The dictionary ``CanteraTorchProperties`` is the original dictionay of DeepFlame. It read in netowrk realted parameters and configurations. It typically looks like:
+
+.. code-block::
+
+    chemistry           on;
+    CanteraMechanismFile "ES80_H2-7-16.yaml";
+    transportModel "Mix";//"UnityLewis";
+    odeCoeffs
+    {
+        //"relTol"   1e-15;
+        //"absTol"   1e-24;
+    }
+    inertSpecie        "N2";
+
+    zeroDReactor
+    {
+        constantProperty "pressure";
+    }
+
+    torch on;
+    GPU on;
+    torchModel1 "ESH2-sub1.pt";
+    torchModel2 "ESH2-sub2.pt";
+    torchModel3 "ESH2-sub3.pt";
+
+    torchParameters1
+    {
+        Tact 700  ;
+        Qdotact  3e7;
+        coresPerGPU 4;
+    }
+    torchParameters2
+    {
+        Tact 2000;
+        Qdotact  3e7;
+    }
+    torchParameters3
+    {
+        Tact 2000;
+        Qdotact  7e8;
+    }
+    loadbalancing
+    {
+            active  false;
+            //log   true;
+    }
+
+
+In the above example, the meanings of the parameters are:
+
+* ``CanteraMechanismFile``: the name of the reaction mechanism file 
+* ``odeCoeffs``: the ode torlerance. 1e-15 and 1e-24 are used for network training, so it should keep the same when comparing results with nd without DNN.
+* ``torch``: the switch used to control the on and off of DNN. If users are running CVODE, this needs to be switched off.
+* ``GPU``: the switch used to control whether GPU or CPU is used to carry out inference.
+* ``torchModel``: name of network.
+* ``torchParameters``: thresholds used to decide when to use network.
+* ``coresPerGPU``: number of CPU cores on one node.