Pathfinding Instructions:

  1. Click once to place the start point
  2. Click again to place the end point
  3. Click and drag to draw walls
  4. Select an algorithm and click "Start" to visualize
  5. Use "Clear" to reset the grid

🎨 Color Guide for Pathfinding:

Light Blue Areas: Shows nodes the algorithm has explored while searching for the shortest path

Yellow Line: The final shortest path found by the algorithm connecting start to end

Dijkstra: Explores more systematically, guaranteeing the shortest path

A*: Uses smart heuristics to explore more efficiently toward the target

Start
End
Wall
Explored
Shortest Path

Clustering Instructions:

  1. Choose between K-Means or Agglomerative clustering algorithm
  2. Set the number of clusters and parameters
  3. Click on the canvas to add data points manually
  4. Or use "Generate Random Points" to create sample data
  5. Click "Run Algorithm" to start the clustering process
  6. Watch as points get grouped into clusters
  7. Use "Clear Canvas" to start over
Progress:
0/0
Cluster 1
Cluster 2
Cluster 3
Cluster 4
Cluster 5
Cluster 6
Cluster 7
Cluster 8
⨯
Centroids
Select an algorithm tab to get started

📚 Step-by-Step Learning

Welcome to Algorithm Visualizer!
Choose an algorithm and start the visualization to see step-by-step explanations here.
This panel will guide you through what the algorithm is doing at each step with clear, educational explanations.