# This is a simple script to automatically design a maze:
from vmfactory import Vmaze_NHT
from vmfactory.canvas import squares_grid
canvas = squares_grid(4,4) # nodes will be numbered 0..15
# NHT means no half-turns (can't pass a light twice in a row)
maze = Vmaze_NHT(canvas, start = 0, goal = 15)
maze.colorize( maze.random_colors() )
maze.anneal(400,20) # optimize the maze
# maze.make_report().savefig('myreport.png')
maze.to_file('my_nice_maze.vm')
# This script shows how to evolve mazes with custom criteria.
# We create a subclass ``Vmaze_NHT_long`` where the score is
# simply the length of a minimal solution of the labyrinth is
#there is one. Note that we d'ont even check the unicity of
#sthe solution. ::
import networkx as nx
from vmfactory import Vmaze_NHT
from vmfactory.canvas import squares_grid
class Vmaze_NHT_long(Vmaze_NHT):
""" A class that will tend to optimize mazes so that
their solution is very long. The unicity of the
solution is not granted. """
def compute_score(self):
graph = self.compute_graph()
if self.start not in graph.nodes(): return 0
shortest = nx.shortest_path(graph, self.start)
if graph.goal not in shortest.keys(): return 0
return len(shortest[graph.goal])
canvas = squares_grid(4,4)
maze = Vmaze_NHT_long(canvas, start = 0, goal = 15)
maze.colorize( maze.random_colors() )
maze.anneal(200,20) # optimize the maze
maze.make_report().savefig('myreport.png')
# This is a simple script to automatically design a maze:
from vmfactory import Vmaze_NHT
from vmfactory.canvas import squares_grid
canvas = squares_grid(4, 4) # nodes will be numbered 0..15
# NHT means no half-turns (can't pass a light twice in a row)
maze = Vmaze_NHT(canvas, start=0, goal=15)
maze.colorize(maze.random_colors())
maze.anneal(400, 20) # optimize the maze
# maze.make_report().savefig('myreport.png')
maze.to_file('my_nice_maze.vm')
# simply the length of a minimal solution of the labyrinth is
# there is one. Note that we d'ont even check the unicity of
# sthe solution. ::
import networkx as nx
from vmfactory import Vmaze_NHT
from vmfactory.canvas import squares_grid
class Vmaze_NHT_long(Vmaze_NHT):
""" A class that will tend to optimize mazes so that
their solution is very long. The unicity of the
solution is not granted. """
def compute_score(self):
graph = self.compute_graph()
if self.start not in graph.nodes():
return 0
shortest = nx.shortest_path(graph, self.start)
if graph.goal not in shortest.keys():
return 0
return len(shortest[graph.goal])
canvas = squares_grid(4, 4)
maze = Vmaze_NHT_long(canvas, start=0, goal=15)
maze.colorize(maze.random_colors())
maze.anneal(200, 20) # optimize the maze
maze.make_report().savefig("myreport.png")