No complete notebook showing Model Learning using c3-toolset

[lazyoracle]

Is your issue related to a problem? Please describe.
There is no demonstration notebook showing how one would perform the whole cycle of c3-toolset including the model learning phase.

• Bug Fix: Model Learning is broken
• Feature Req: No Model Learning notebook

Describe the solution you'd like

• Define a simple model (configs and hjsons) - Can we use one of the existing ones that are present for two_qubits.ipynb/Simulated_calibration.ipynb or in one of the tests?
• Run C1 and C2 on this model (or just run C2 at least?)
• Store the data being generated in the C2 step (How? Similar to c3-paper? Just store a pickle file? numpy arrays?)
• Read the data stored in previous step and parse all the values (including reloading the current model from a config file)
• Run C3 model learning with this data on the previously defined model

If beyond the scope, it might be adequate to start directly from step 4 with some dummy dataset from a previous C2 run and perform model learning on that data.

TO-DO/Status

• Trace current function paths
• Check points where API is broken due to updates elsewhere
• Explore and understand code/API design choices (data structure, FOMs, sampling, data assumptions)
• Change/Update code/implementation structure as required
• Change/Update API design as required
• Update data structure and storage format to something portable and sensible ( might relate to data saving in C2, save as dataframes instead of list of dicts)
• Check/update integration with main.py and Optimizer
• Check/update integration with config files
• Run Model Learning from CLI
• Update Docstrings and Type Annotations
• Update config files
• Add tests
• Create Model Learning Notebook as outlined above
• Add docs based on examples

Note
Model Learning Experimentation being tracked in a separate issue #105

[lazyoracle]

Call graph for current code: