Refactoring the HSSM class

[cpaniaguam]

The HSSM class is large and complex, making it difficult to maintain and extend. Before implementing the model registration abstraction it seems reasonable to refactor its functionality for readability and extensibility. I can think of two refactoring approaches: either modularization or composition with helper classes.

Approach 1: Modularization

This approach involves breaking down the [HSSM] class into separate modules based on functionality. Each module will handle a specific responsibility, such as sampling, plotting, data handling, and model management.

Steps:

1. Create Separate Modules:

   • sampling.py for sampling-related methods
   • plotting.py for plotting-related methods
   • data_handling.py for data handling and preprocessing methods
   • model_management.py for model saving and loading methods

2. Move Methods to Appropriate Modules:

   • Extract methods from the HSSM class and place them in the corresponding modules
   • Keep the core functionality in the HSSM class and delegate tasks to the modules

Pros:

• Separation of Concerns: Each module has a clear responsibility, making the code easier to understand and maintain.
• Scalability: New functionalities can be added to specific modules without affecting the entire class.
• Reusability: Modules can be reused in other parts of the project if needed.

Cons:

• Might require significant initial effort to refactor and test the code.
• Managing dependencies between modules can become complex.

Approach 2: Composition with Helper Classes

This approach involves breaking down the HSSM class into smaller, more focused helper classes that handle specific responsibilities. These helper classes are then composed within the main HSSM class.

Steps:

1. Create Helper Classes

   • SamplingHelper
   • PlottingHelper
   • DataHandlingHelper
   • ModelManagementHelper

2. Integrate Helper Classes:

   • Instantiate helper classes within the HSSM class.
   • Delegate tasks to the helper classes.

Pros:

• Encapsulation: Each helper class encapsulates specific functionality, making the code more modular.
• Maintainability: Smaller classes are easier to maintain and test.
• Flexibility: Helper classes can be easily modified or replaced without affecting the main class.

Cons:

• Complexity: Increases the number of classes, which may add complexity to the codebase.
• Coordination: Requires careful coordination between the main class and helper classes to ensure smooth integration.

@digicosmos86 @AlexanderFengler Thoughts?

[AlexanderFengler]

@cpaniaguam few thoughts:

Following the modularization approach, would we add the functions from separate modules as class-methods inside the hssm class (via a decorator e.g.)?

I like the separation of concerns, but would need a quick example here to understand better how this would example play out.

Also, it seems like the modularization refactor is something that can be done iteratively (module by module e.g.) over a span of time, without having an intermediate 'everything is broken until we have a new castle to inhabit' situation, which would be great true. Related, I would strongly advocate for working on the "model registration" functionality before this refactor (or during, if possible) and not make it contingent on that if not absolutely necessary.