This pull request includes refactoring and enhancements to the survival analysis tools, particularly focusing on the Cox Proportional Hazards (CoxPH), Weibull Accelerated Failure Time (Weibull AFT), and Log-Logistic Accelerated Failure Time (Log-Logistic AFT) models. The changes improve the flexibility and usability of these models by adding new parameters and restructuring the code.

Refactoring and Enhancements:

• Code Refactoring:

  • Split the _regression_model function into two separate functions: _regression_model_data_frame_preparation and _regression_model_populate_adata.

• Cox Proportional Hazards Model:

  • Added new parameters to the cox_ph function to provide more control over the model fitting process, such as inplace, key_added_prefix, alpha, label, baseline_estimation_method, penalizer, l1_ratio, strata, n_baseline_knots, knots, breakpoints, weights_col, cluster_col, robust, formula, batch_mode, show_progress, initial_point, and fit_options.

• Weibull Accelerated Failure Time Model:

  • Enhanced the weibull_aft function with additional parameters similar to those added to the cox_ph function.

• Log-Logistic Accelerated Failure Time Model:

  • Updated the log_logistic_aft function to include new parameters.

• Testing Adjustments:

  • Modified the _sa_func_test method in tests/tools/test_sa.py to accommodate the updated function signatures, ensuring that tests pass with the new parameters.