dt = 0.1 # Time step
Defines the time step dt for the simulation (how much time elapses between updates).
spread = np.sqrt(2 self.diffusion_coefficient dt)
Calculates the spread (standard deviation) for the Gaussian filter based on the time step and diffusion_coefficient. Higher values lead to faster diffusion.
self.world = gaussian_filter(self.world, sigma=spread)
Applies a Gaussian filter (representing diffusion) to the pheromone concentration array (self.world). The sigma parameter governs the spread of the filter.
The GUI.py is our old version to visualize pheromones on pheromone.world
dt = 0.1 # Time step Defines the time step dt for the simulation (how much time elapses between updates). spread = np.sqrt(2 self.diffusion_coefficient dt) Calculates the spread (standard deviation) for the Gaussian filter based on the time step and diffusion_coefficient. Higher values lead to faster diffusion. self.world = gaussian_filter(self.world, sigma=spread) Applies a Gaussian filter (representing diffusion) to the pheromone concentration array (self.world). The sigma parameter governs the spread of the filter.
The GUI.py is our old version to visualize pheromones on pheromone.world