add load setting and weights

docs/examples/advanced.rst → docs/advanced.rst

@@ -1,8 +1,39 @@
-Advanced Features in PINNICLE
-=============================
+Advanced Features
+=================
 
 PINNICLE is under active development, and several **advanced**/**experimental** features are listed here in alphabetical order:
 
+Load Settings from Previous Experiment
+--------------------------------------
+
+Each PINNICLE experiment will save the entire settings to the folder defined in ``hp["save_path"]`` if ``hp["is_save"]=True``. The settings are saved into a ``params.json`` file containing all the non-default settings from ``hp``.
+
+To repeat a new experiment with the same settings as in some ``folder_path``, you can easily load the settings by:
+
+.. code-block:: python
+
+   experiment = pinnicle.PINN(loadFrom=folder_path)
+
+However, if you want to run the experiment and save the results in a new folder, you will need to set the ``"save_path"`` and update the experiment:
+
+.. code-block:: python
+
+   experiment.update_parameters({"save_path": new_folder})
+
+Then, compile and train the model.
+
+Load Weights from Previously Trained Neural Network
+---------------------------------------------------
+
+PINNICLE can also load the weights from a previous experiment. You can either load the settings from a saved experiment or set up a completely new one. After that, you can load the weights of the neural network from the ``folder_path`` which contains the entire experiment (including ``params.json``, a folder called ``pinn``, and some figures).
+
+.. code-block:: python
+
+   experiment.load_model(path=folder_path)
+
+After loading the weights, compiling and training are the same as for other experiments.
+
+
 Additional Loss Functions
 -------------------------
 

docs/index.rst

@@ -48,6 +48,7 @@ User guide
    :maxdepth: 1
 
    data
+   advanced
    pinnicle_examples
 
 

docs/pinnicle_examples.rst

@@ -19,5 +19,5 @@ Advanced
 .. toctree::
    :maxdepth: 2
 
-   examples/advanced
+..   examples/advanced