Update README.md

files/README.md

@@ -1,14 +1,23 @@
 # files
 You can find files useful for running the ML-aided workflows here.
 
-## ML_model
-This folder contains files related to the ML model --- its architecture and conversion to format used in the workflow. 
+## 1-data-generation
+This folder contains the scripts used to generate the ground truth data for training our ML model.
 
-## modified_HW
-The simulation software, BOUT++, comes with a set of examples, including the Hasegawa-Wakatani set of equations. We are using this example to demonstrate the whole workflow, but several files need to be modified in order to gain access to SmartRedis and the ML model. The modified files are included here.
+## 2-coarsening
+These scripts sample the fine grained ground truth generated in step 1 and produce the coarse grained ground truth.
 
-## run_SmartSim
-Scripts to start the in-memory database and to submit a job running the workflow.
+## 3-coarse_simulations
+This generates a simulated timestep from each ground truth timestep.
 
-## training
-Files/instructions prepared for specific events
+## 4-training-data
+This folder contains the post-processing script that gathers the training data for the model.
+
+## 5-training
+This folder contains files related to the ML model -- its architecture and training pipeline.
+
+## 6-simulation
+We demonstrate the workflow on the Hasegawa-Wakatani equations.
+
+## 7-visualisation
+This python notebook visualises the simulation data generated by the workflow.