The BaseBayesianForecaster class currently has several responsibilities beyond forecasting using Bayesian inference. These responsibilities include:
Plotting
Selecting an optimizer
Managing exogenous effects
Scaling
It would improve maintainability and documentation if these responsibilities were separated into distinct components. This refactor would allow each component to focus on a single responsibility, making the codebase cleaner and easier to understand.
Proposal:
Create separate classes or modules for:
Plotting
Optimizer selection
Exogenous effects management
Scaling
Refactor the BaseBayesianForecaster class to utilize these new components, ensuring that it focuses solely on the Bayesian forecasting logic.
Update the documentation to reflect the new structure, providing clear guidelines on how to use and extend each component.
Write unit tests for each new component to ensure they work correctly both in isolation and when integrated with the BaseBayesianForecaster.
Benefits:
Improved code readability and maintainability
Easier to document and understand each component's functionality
Enhanced ability to test individual components independently
Facilitates future enhancements and modifications
Additional Information:
If there are any specific considerations or constraints that need to be taken into account during this refactor, please share them in the comments.
Description:
The BaseBayesianForecaster class currently has several responsibilities beyond forecasting using Bayesian inference. These responsibilities include:
It would improve maintainability and documentation if these responsibilities were separated into distinct components. This refactor would allow each component to focus on a single responsibility, making the codebase cleaner and easier to understand.
Proposal:
Benefits:
Additional Information: If there are any specific considerations or constraints that need to be taken into account during this refactor, please share them in the comments.