def find_path(start, end, mesh, grid, tilesize=16):
""" Uses astar to find a path from start to end,
using the given mesh and tile grid.
>>> grid = [[0,0,0,0,0],[0,0,0,0,0],[0,0,1,0,0],[0,0,0,0,0],[0,0,0,0,0]]
>>> mesh = make_nav_mesh([(2,2,1,1)],(0,0,4,4),1)
>>> find_path((0,0),(4,4),mesh,grid,1)
[(4, 1), (4, 4)]
"""
# If there is a straight line, just return the end point
if not line_intersects_grid(start, end, grid, tilesize):
return [end]
# Copy mesh so we can add temp nodes
mesh = copy.deepcopy(mesh)
# Add temp notes for start
mesh[start] = dict([(n, point_dist(start,n)) for n in mesh if not line_intersects_grid(start,n,grid,tilesize)])
# Add temp nodes for end:
if end not in mesh:
endconns = [(n, point_dist(end,n)) for n in mesh if not line_intersects_grid(end,n,grid,tilesize)]
for n, dst in endconns:
mesh[n][end] = dst
neighbours = lambda n: mesh[n].keys()
cost = lambda n1, n2: mesh[n1][n2]
goal = lambda n: n == end
heuristic = lambda n: ((n[0]-end[0]) ** 2 + (n[1]-end[1]) ** 2) ** 0.5
nodes, length = astar(start, neighbours, goal, 0, cost, heuristic)
return nodes
def find_path(start, end, mesh, grid, tilesize=16):
""" Uses astar to find a path from start to end,
using the given mesh and tile grid.
>>> grid = [[0,0,0,0,0],[0,0,0,0,0],[0,0,1,0,0],[0,0,0,0,0],[0,0,0,0,0]]
>>> mesh = make_nav_mesh([(2,2,1,1)],(0,0,4,4),1)
>>> find_path((0,0),(4,4),mesh,grid,1)
[(4, 1), (4, 4)]
"""
# If there is a straight line, just return the end point
if not line_intersects_grid(start, end, grid, tilesize):
return [end]
# Copy mesh so we can add temp nodes
mesh = copy.deepcopy(mesh)
# Add temp notes for start
mesh[start] = dict([(n, point_dist(start, n)) for n in mesh
if not line_intersects_grid(start, n, grid, tilesize)])
# Add temp nodes for end:
if end not in mesh:
endconns = [(n, point_dist(end, n)) for n in mesh
if not line_intersects_grid(end, n, grid, tilesize)]
for n, dst in endconns:
mesh[n][end] = dst
neighbours = lambda n: mesh[n].keys()
cost = lambda n1, n2: mesh[n1][n2]
goal = lambda n: n == end
heuristic = lambda n: ((n[0] - end[0])**2 + (n[1] - end[1])**2)**0.5
nodes, length = astar(start, neighbours, goal, 0, cost, heuristic)
return nodes
def astar_path_length(m, start, end):
""" Length of a path from start to end """
neighbours = lambda n: m[n].keys()
cost = lambda n1, n2: m[n1][n2]
goal = lambda n: n == end
heuristic = lambda n: point_dist(end, n)
nodes, length = astar(start, neighbours, goal, 0, cost, heuristic)
return length
def astar_path_length(m, start, end):
""" Length of a path from start to end """
neighbours = lambda n: m[n].keys()
cost = lambda n1, n2: m[n1][n2]
goal = lambda n: n == end
heuristic = lambda n: point_dist(end, n)
nodes, length = astar(start, neighbours, goal, 0, cost, heuristic)
return length
