Milestone: Enhance MolBar Architecture for Improved Performance and Functionality

Objective: To refactor MolBar's architecture to leverage np.array for enhanced performance and to introduce new features, including a model for atropisomerism, VSEPR prediction, and extended support for metal complexes.

Key Deliverables:

1. Architecture Refactoring:

   • Transition to np.array: Refactor core components to utilize np.array for data storage and manipulation, aiming to improve computational efficiency and performance.
   • Code Optimization: Optimize existing algorithms to work seamlessly with np.array, ensuring compatibility and performance gains.

2. New Feature Implementations:

   • Atropisomerism Model: Develop a model to predict and analyze atropisomerism, focusing on the conformational stability and energy barriers of atropisomers.
   • VSEPR Prediction: Implement a VSEPR (Valence Shell Electron Pair Repulsion) prediction model to forecast molecular geometries based on electron pair repulsion theory.
   • Metal Eta Bonds Support: Enhance support for metal complexes, including eta-bond support, to better handle the unique bonding characteristics of metal-ligand interactions.

3. Statistical-Based Enhancements:

   • Geometry Prediction: Develop statistical models for the classification of complicated molecular geometries.
   • Connectivity Evaluation: Implement statistical methods for evaluating molecular connectivity for more robustness

4. Testing and Quality Assurance:

   • Extended Unit Test Coverage: Expand unit test coverage to ensure the reliability and accuracy of new features and refactored components.
   • Performance Benchmarking: Conduct performance benchmarking to measure the impact of architectural changes and optimizations.

Timeline:

• Phase 1 (2 weeks): Initial refactoring and transition to np.array.
• Phase 2 (3 weeks): Development of atropisomerism model and VSEPR prediction.
• Phase 3 (3 weeks): Enhance support for metal complexes and implement eta-bond support.
• Phase 4 (2 weeks): Develop statistical models for geometry prediction and connectivity evaluation.
• Phase 5 (2 weeks): Extend unit test coverage and conduct performance benchmarking.
• Phase 6 (1 week): Final testing, documentation, and release preparation.

Outcome: A more efficient and feature-rich MolBar with improved performance, enhanced predictive capabilities, and robust support for complex molecular structures.