def testOrderEightWords(self):
# number of words along the search path
nr_words = 8
cues = ['cottage', 'swiss', 'cake']
target = 'cheese'
target_id = self.net.voc[target]
# get word ids
cue_ids = [self.net.voc[c] for c in cues]
act_alg, visited_alg = spread_activity(init_nodes=cue_ids,
target=target_id,
W=self.net.W,
max_visited=nr_words)
self.net.setup_problem(cues, target)
self.net.max_visited = nr_words
self.net.run()
visited_net = self.net.visited()
np.testing.assert_equal(visited_alg, visited_net)
a1 = self.net.a[self.net.t_max, visited_net]
a2 = act_alg[visited_alg]
# tolerate diffrences in activities up to 0.1
np.testing.assert_allclose(a1, a2, rtol=1e-1)
def testEqual(self):
equal = 0
not_equal = []
for i, rat_item in enumerate(self.items):
# words
cues, target = rat_item[:3], rat_item[3]
# word ids
cue_ids = [self.net.voc[c] for c in cues]
target_id = self.net.voc[target]
# run the algorithm simulation
_, visited_alg = spread_activity(init_nodes=cue_ids,
target=target_id,
W=self.net.W,
max_visited=self.nr_words)
# ...and the network simulation
self.net.setup_problem(cues, target)
print '\n', i, cues, target, target_id
# WTA can fail if noise added to two equal numbers is not enough
# to pick a winner. If this happens, the simulation is repeated
ok = True
while ok:
try:
self.net.run()
ok = False
except BaseException:
print 'WTA failed, retrying the run!'
continue
l1, l2 = visited_alg, list(self.net.visited())
if target_id in set(l1) and target_id not in set(l2) or\
target_id not in set(l1) and target_id in set(l2):
not_equal.append(i)
else:
print 'ok', equal
equal += 1
print 'A:', l1
print 'N:', l2
print not_equal
def testActivityEqualThreeCues(self):
cues = ['match', 'game', 'stick']
target = 'fire'
target_id = self.net.voc[target]
max_visited = 3
self.net.max_visited = max_visited
self.net.setup_problem(cues, target)
act_alg, _ = spread_activity(init_nodes=self.net.cue_ids,
target=target_id,
W=self.net.W,
max_visited=max_visited)
self.net.run()
np.testing.assert_almost_equal(act_alg,
self.net.a[self.net.t_max],
decimal=2)
def testActivityEqualSingleCue(self):
cue = 'match'
target = 'fire'
target_id = self.net.voc[target]
max_visited = 1
self.net.max_visited = max_visited
act_alg, _ = spread_activity(init_nodes=[self.net.voc[cue]],
target=target_id,
W=self.net.W,
max_visited=max_visited)
self.net.setup_problem([cue], target)
self.net.run()
np.testing.assert_almost_equal(act_alg,
self.net.a[self.net.t_max],
decimal=3)