A* Visualizer

A python library to visualize A* Path finding Algorithm in action

Dependencies

• pip install pygame
• sudo apt-get install python3-pygame (linux)

Usage

• Download the source code
• Import the Colors and Visualizer classes

from main import Colors, Visualizer

• The Visualizer class takes in 4 parameters

  • size: size of the window (in px)
  • rows: Number of rows and columns in the grid
  • Colors: Colors Used in the Visualizer
  • Enable Diagonal Paths: Are diagonal paths allowed ? (boolean)

• Create a Colors Class

col = Colors() # Use Default Colors
vis = Visualizer(1300, 20, col, False)
                                  ^ No Diagonal Paths

• The program can now be run.

Adding Nodes

• The first click (left mouse) adds the start node.
• The second click (left mouse) adds the end/destination node.
• Every click after the second creates a barrier/wall node. A barrier is a node which cannot become a path.
• A right click resets a node
• Pressing space starts the algorithm.

Using Custom Colors

• Colors are passed in as RGB Values in a tuple

col = Colors() # Create a colors Object

col.neutral = (255, 247, 243) # Neutral Nodes
col.explored = (33, 53, 85) # Nodes which have been explored 
col.exploring = (62, 88, 121) # Nodes being explored in the current iteration
col.inactive = (42, 51, 53) # Wall/Barrier nodes
col.path = (250, 208, 196) # Nodes which form the path
col.end = (239, 182, 200) # End Node
col.start = (239, 182, 200) # Start Node

• This colors object can noe be passed into the Visualizer class

vis = Visualizer(1500, 30, col, True)
                            ^ Pass the custom Colors as argument

Custom Heuristic Functions

• The default implementation uses euclidean distance.
• Other Heuristic Functions can be set as follows

from main import Colors, Visualizer

# Custom Heuristic Function
def h(position1, position2):
    x1, y1 = position1
    x2, y2 = position2
    return abs((x2-x1) + (y2-y1))

col = Colors()
vis = Visualizer(1300, 20, col, False)
vis.custom_heuristic = h # the new heuristic function is used