Postprocessing Notebooks

.github/workflows/run_exhaustive_examples.yml

@@ -68,6 +68,17 @@ jobs:
       # Debugging session
       #- name: Setup tmate session
       #  uses: mxschmitt/action-tmate@v3
+
+      # Test walkthrough notebook
+      - name: Test postprocessing notebooks
+        run: |
+          cd examples/16_postprocessing
+          gdown --no-check-certificate 1_FJaN-W1DoPNmO6YLSjnftvq6-7bn4VI
+          unzip outputs
+          treon plot_FAST.ipynb
+          treon rev_DLCs_WEIS.ipynb
+          treon rev_Opt.ipynb
+          treon rev_WEIS_CSV.ipynb
 
       # Run all examples
       - name: Run tests within WEIS

environment.yml

@@ -14,6 +14,7 @@ dependencies:
   - et-xmlfile
   - future
   - git
+  - gdown
   - imagesize
   - jinja2
   - jsonmerge
@@ -57,6 +58,7 @@ dependencies:
   - sphinxcontrib-serializinghtml
   - statsmodels
   - swig
+  - treon
   - pyzmq
 #  - versioneer
   - pip:

examples/16_postprocessing/README.md

@@ -0,0 +1,23 @@
+# Postprocessing Notebooks
+
+Here are a set of jupyter notebooks for postprocessing WEIS results.  They run using a set of pre-defined output files that can be downloaded from [here](https://drive.google.com/file/d/1_FJaN-W1DoPNmO6YLSjnftvq6-7bn4VI/view?usp=sharing), or with the following set of commands
+
+```
+gdown --no-check-certificate 1_FJaN-W1DoPNmO6YLSjnftvq6-7bn4VI
+unzip outputs
+```
+
+`plot_FAST.ipynb` is used to plot OpenFAST outputs.
+
+`rev_DLCs_WEIS.ipynb` is used to review aggregate statistics generated using pCrunch in WEIS
+
+`rev_Opt.ipynb` is used to review optimization iterations generated from openmdao logs
+
+`rev_WEIS_CSV.ipynb` is use to review the csv output files of WEIS
+
+## Jupyter Notebooks
+These notebooks require installing a few extra tools via anaconda and linking with the weis conda environment.  The following commands may be helpful:
+```
+conda install jupyterlab ipykernel
+python -m ipykernel install --user --name=<weis_env_name>
+```