def analyze(arg):
bin_size, results = arg
found=False
trials=0
while len(results) < COMPARISONS:
r1, r2 = random.sample(routes, 2)
while not bin_size <= distance(r1, r2) <= bin_size + BIN_SIZE and trials < 10000:
r1, r2 = random.sample(routes, 2)
if not found: trials += 1
if trials >= 10000: return (bin_size, [])
else: found=True
lat_range = min((r1[0], r2[0])), max((r1[0], r2[0]))
lon_range = min((r1[1], r2[1])), max((r1[1], r2[1]))
species_pool = []
for route in (r1,r2):
for sp, count in routes[route].iteritems():
species_pool += [sp] * count
try:
result = metrics.process(routes[r1], routes[r2], tree, species_pool)
if not result: continue
except IndexError:
# this means a species wasn't found in our tree
continue
print bin_size, result
results.append(result)
return (bin_size, results)
def analyze(arg):
grid, routes = arg
species_pool = []
for route in routes.values():
for sp, count in route.iteritems():
species_pool += [sp] * count
n = len(routes)
# compare all combinations of routes if n choose 2 < COMPARISONS,
# otherwise compare random combinations until you reach COMBINATIONS
# total comparisons
comparisons = n*(n-1) / 2
if comparisons < COMPARISONS:
to_compare = ((r1, r2) for r1 in routes for r2 in routes if not r1 == r2)
else:
def random_comparison():
while True:
yield tuple(sorted(random.sample(routes.keys(), 2)))
to_compare = random_comparison()
# compare pairs of communities
comms = []
while len(comms) < min(COMPARISONS, comparisons):
try: r1, r2 = next(to_compare)
except StopIteration: break
if len(routes[r1]) < 2 or len(routes[r2]) < 2: continue
try:
result = metrics.process(routes[r1], routes[r2], tree, species_pool)
if not result: continue
comms.append(result)
except IndexError:
# this means a species wasn't found in our tree
pass
print '**', grid, time.strftime('%D %T')
results = {}
for result in sorted(set(comms)):
percent = 100*len([c for c in comms if c == result]) / float(len(comms))
print '%s: %s%%' % (result, percent)
results[result] = percent
return grid, results
