Enhanced Visualization for Activity Selection Algorithms

📅 2024-04-17 — Session: Enhanced Visualization for Activity Selection Algorithms

🕒 03:00–05:30
🏷️ Labels: Visualization, Dynamic Programming, Activity Selection, Matplotlib, Algorithm
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance the visualization capabilities of various activity selection algorithms, including GreedySelector, BacktrackingSelector, and DynamicProgrammingSelector, using Python’s matplotlib.

Key Activities

• Modified the visualizar method to separate selected and unselected activities using distinct colors and adjusted y-axis coordinates.
• Integrated intermediate visualizations in GreedySelector to display the state of activities after each decision.
• Adapted the visualizar method for BacktrackingSelector to graphically represent selected and evaluated activities.
• Implemented visualizations in DynamicProgrammingSelector to illustrate memoization table filling and solution reconstruction.
• Reviewed and clarified the reconstruction logic of the dynamic programming algorithm for activity selection.

Achievements

• Successfully integrated visualization techniques across different selection algorithms, improving the understanding of decision-making processes.
• Clarified the decision-making and reconstruction processes in dynamic programming, identifying and correcting potential errors.

Pending Tasks

• Further testing and validation of the visualization methods in different algorithmic contexts to ensure robustness and accuracy.
• Exploration of additional visualization libraries or techniques that could enhance the current implementations.