Example #1
0
def hidden_image_maze(fname, style='jittery'):
    """ Supported styles: jittery, smooth, sketch"""
    H = models.image_grid_graph(fname)  # get a subgraph of the grid corresponding to edges between black pixels
    G = H.base_graph

    # for every edge in H, make the corresponding edge in H have weight 0
    for u,v in H.edges():
        G[u][v]['weight'] = 0

    # find a minimum spanning tree on G (which will include the maze solution)
    T = nx.minimum_spanning_tree(G)

    # find the maze solution in the spanning tree
    P = models.my_path_graph(nx.shortest_path(T, (0,0), max(H.nodes())))

    # generate the dual graph, including edges not crossed by the spanning tree
    D = models.dual_grid(G, T)
    views.add_maze_boundary(D, max(G.nodes()))
    views.make_entry_and_exit(D, max(G.nodes()))
    pos = views.layout_maze(D, fast=(style == 'jittery'))
    views.plot_maze(D, pos, P, G.pos)

    # make it stylish if requested
    if style == 'sketch':
        plt.figure(1)
        D_pos = views.layout_maze(D, fast=True)
        nx.draw_networkx_edges(D, D_pos, width=1, edge_color='k')
        D_pos = views.layout_maze(D, fast=True)
        nx.draw_networkx_edges(D, D_pos, width=1, edge_color='k')

    
    # show the pixel colors loaded from the file, for "debugging"
    plt.figure(2)
    for v in G:
        plt.plot([G.pos[v][0]], [G.pos[v][1]], '.', alpha=.5, color=G.node[v]['color'])
Example #2
0
def random_maze(n=25):
    G = models.my_grid_graph([n,n])

    T = nx.minimum_spanning_tree(G)
    P = models.my_path_graph(nx.shortest_path(T, (0,0), (n-1, n-1)))

    D = models.dual_grid(G, T)
    views.add_maze_boundary(D, [n, n])
    views.make_entry_and_exit(D, [n, n])
    pos = views.layout_maze(D, fast=True)
    views.plot_maze(D, pos, P, G.pos)
Example #3
0
def random_maze(n=25):
    G = models.my_grid_graph([n, n])

    T = nx.minimum_spanning_tree(G)
    P = models.my_path_graph(nx.shortest_path(T, (0, 0), (n - 1, n - 1)))

    D = models.dual_grid(G, T)
    views.add_maze_boundary(D, [n, n])
    views.make_entry_and_exit(D, [n, n])
    pos = views.layout_maze(D, fast=True)
    views.plot_maze(D, pos, P, G.pos)
Example #4
0
   def test_graph_utils(self):
       P = model.my_path_graph(model.nx.shortest_path(self.G, (0,0), (4,4)))
       H = model.image_grid_graph('test.png')

       d = model.dual_grid_edge((0,0), (0,1))
       assert d == ((-0.5, 0.5), (0.5, 0.5)), 'dual of integer lattice should be offset by .5s'

       D = model.dual_grid(H.base_graph, H)
       graphics.add_maze_boundary(D, [5,5])
       graphics.make_entry_and_exit(D, [5,5])
       HH = graphics.split_edges(H)
Example #5
0
    def test_graph_utils(self):
        P = model.my_path_graph(model.nx.shortest_path(self.G, (0, 0), (4, 4)))
        H = model.image_grid_graph('test.png')

        d = model.dual_grid_edge((0, 0), (0, 1))
        assert d == ((-0.5, 0.5),
                     (0.5,
                      0.5)), 'dual of integer lattice should be offset by .5s'

        D = model.dual_grid(H.base_graph, H)
        graphics.add_maze_boundary(D, [5, 5])
        graphics.make_entry_and_exit(D, [5, 5])
        HH = graphics.split_edges(H)
Example #6
0
def hidden_image_maze(fname, style='jittery'):
    """ Supported styles: jittery, smooth, sketch"""
    H = models.image_grid_graph(
        fname
    )  # get a subgraph of the grid corresponding to edges between black pixels
    G = H.base_graph

    # for every edge in H, make the corresponding edge in H have weight 0
    for u, v in H.edges():
        G[u][v]['weight'] = 0

    # find a minimum spanning tree on G (which will include the maze solution)
    T = nx.minimum_spanning_tree(G)

    # find the maze solution in the spanning tree
    P = models.my_path_graph(nx.shortest_path(T, (0, 0), max(H.nodes())))

    # generate the dual graph, including edges not crossed by the spanning tree
    D = models.dual_grid(G, T)
    views.add_maze_boundary(D, max(G.nodes()))
    views.make_entry_and_exit(D, max(G.nodes()))
    pos = views.layout_maze(D, fast=(style == 'jittery'))
    views.plot_maze(D, pos, P, G.pos)

    # make it stylish if requested
    if style == 'sketch':
        plt.figure(1)
        D_pos = views.layout_maze(D, fast=True)
        nx.draw_networkx_edges(D, D_pos, width=1, edge_color='k')
        D_pos = views.layout_maze(D, fast=True)
        nx.draw_networkx_edges(D, D_pos, width=1, edge_color='k')

    # show the pixel colors loaded from the file, for "debugging"
    plt.figure(2)
    for v in G:
        plt.plot([G.pos[v][0]], [G.pos[v][1]],
                 '.',
                 alpha=.5,
                 color=G.node[v]['color'])
Example #7
0
def ld_maze(n=25):
    """ having many low-degree vertices makes for hard mazes

    unfortunately, finding them is slow"""

    # start with an nxn square grid
    G = models.my_grid_graph([n,n])

    # make a pymc model of a low-degree spanning tree on this
    T = models.LDST(G, beta=10)
    mod_mc = mc.MCMC([T])
    mod_mc.use_step_method(models.STMetropolis, T)
    mod_mc.sample(100, burn=99)
    T = T.value

    P = models.my_path_graph(nx.shortest_path(T, (0,0), (n-1, n-1)))

    D = models.dual_grid(G, T)
    views.add_maze_boundary(D, [n,n])
    views.make_entry_and_exit(D, [n,n])
    D = views.split_edges(D)
    D = views.split_edges(D)
    D_pos = views.layout_maze(D, fast=False)
    views.plot_maze(D, D_pos, P, G.pos)
Example #8
0
def ld_maze(n=25):
    """ having many low-degree vertices makes for hard mazes

    unfortunately, finding them is slow"""

    # start with an nxn square grid
    G = models.my_grid_graph([n, n])

    # make a pymc model of a low-degree spanning tree on this
    T = models.LDST(G, beta=10)
    mod_mc = mc.MCMC([T])
    mod_mc.use_step_method(models.STMetropolis, T)
    mod_mc.sample(100, burn=99)
    T = T.value

    P = models.my_path_graph(nx.shortest_path(T, (0, 0), (n - 1, n - 1)))

    D = models.dual_grid(G, T)
    views.add_maze_boundary(D, [n, n])
    views.make_entry_and_exit(D, [n, n])
    D = views.split_edges(D)
    D = views.split_edges(D)
    D_pos = views.layout_maze(D, fast=False)
    views.plot_maze(D, D_pos, P, G.pos)