def generate_map_homes_data(N, number_of_runs=50):
""" generate pairs of (map, homes)
5 movingai maps, {original (closed), open}
5 fixed mazes, {closed,open}
5 {10,20,30}% map {closed,open}
"""
print "using N=%s" % N
def iter_maps():
for i in xrange(5):
yield maps.read_maze('maze_%03d.map' % i)
for m in iter_maps():
rows = len(m)
max_col = max(len(x) for x in m)
if rows > N or max_col > N:
print "Warning: you are chunking your maze from (%d,%d) to %d" % (
rows, max_col, N)
fixed_mazes = [
lambda maze=maps.chunk(N, maps.read_maze('maze_%03d.map' % i)):
maze for i in xrange(5)]
fixed_percent = sum([
[lambda: maps.grid_generators.grid_makers[0](size=(N,N), p_empty=p_empty)
for p_empty in [p]*5]
for p in [0.9, 0.8, 0.7]
],
[])
# movingai maps - not chunked. This is important.
movingai_closed = [lambda maze=maps.read_movingai(m): maze for m in glob('movingai/closed/*.map')]
movingai_open = [lambda maze=maps.read_movingai(m): maze for m in glob('movingai/open/*.map')]
p = itertools.product
c = itertools.chain
def do_one((maze_gen, extend_map)):
map_count = 0
while map_count < number_of_runs:
thrown = 0
zmap, homes = maps.make_map_with_ants_on_vacancies(
default_homes=[(2,2), (3,7)], make_map=maze_gen, make_homes=maps.random_homes)
a = astar(homes, zmap)
if a is None or a < 20:
thrown += 1
continue
print("ASTAR: %d (thrown %d)" % (a, thrown))
if extend_map:
xmap = extend_and_add_trap_to_map(zmap)
else:
xmap = zmap
return xmap, homes, {'closed': not extend_map}
map_count += 1
#astar, ROA, ROA one ant, GOA, GOA one ant
# time, num of pheromones
pairs = c(p(movingai_closed, [False]), p(movingai_open, [True]),
p(fixed_mazes + fixed_percent, [False, True]))
# XXX - can always turn this back to a yield, but then need to move the
# consumer into the p.map, into do_one, to gain multiprocessing?
ret = pmap_interleaved(pool, do_one, pairs)
return ret
def iter_maps():
for i in xrange(5):
yield maps.read_maze('maze_%03d.map' % i)
