def test_max_marginals():
"""
Test that max-marginals are correct.
"""
for h in hypergraphs():
w = utils.random_viterbi_potentials(h)
print w.show(h)
path = ph.best_path(h, w)
best = w.dot(path)
print "BEST"
print "\n".join(["%20s : %s"%(edge.label, w[edge]) for edge in path.edges])
print best
nt.assert_not_equal(best, 0.0)
max_marginals = ph.compute_marginals(h, w)
for node in h.nodes:
other = max_marginals[node]
nt.assert_less_equal(other, best + 1e-4)
for edge in h.edges:
other = max_marginals[edge]
nt.assert_less_equal(other, best + 1e-4)
if edge in path:
nt.assert_almost_equal(other, best)
def test_variables():
"""
Test variable constraint checking.
"""
for h in hypergraphs():
w = utils.random_viterbi_potentials(h)
variables, edge = random_constraint_trans(h)
path = ph.best_path(h, w)
match = list(variables.check(path))
if edge not in path:
print "Should not have", edge.id
assert "have" in match
assert "not" not in match
else:
print "Should have", edge.id
assert "have" not in match
nt.assert_equal(len(match), 1)
def test_outside():
"""
Test outside chart properties.
"""
for h in hypergraphs():
w = utils.random_viterbi_potentials(h)
path = ph.best_path(h, w)
chart = ph.inside_values(h, w)
best = w.dot(path)
nt.assert_not_equal(best, 0.0)
out_chart = ph.outside_values(h, w, chart)
for node in h.nodes:
other = chart[node] * out_chart[node]
nt.assert_less_equal(other, best + 1e-4)
for edge in path.edges:
for node in edge.tail:
if node.is_terminal:
nt.assert_almost_equal(other, best)
def test_pruning():
for h in hypergraphs():
w = utils.random_viterbi_potentials(h)
original_path = ph.best_path(h, w)
new_hyper, new_potentials = ph.prune_hypergraph(h, w, -0.99)
prune_path = ph.best_path(new_hyper, new_potentials)
assert len(original_path.edges) > 0
for edge in original_path.edges:
assert edge in prune_path
valid_path(new_hyper, prune_path)
original_score = w.dot(original_path)
print original_score
print new_potentials.dot(prune_path)
nt.assert_almost_equal(original_score,
new_potentials.dot(prune_path))
# Test pruning amount.
prune = 0.001
max_marginals = ph.compute_marginals(h, w)
new_hyper, new_potentials = ph.prune_hypergraph(h, w, prune)
assert (len(new_hyper.edges) > 0)
original_edges = {}
for edge in h.edges:
original_edges[edge.label] = edge
new_edges = {}
for edge in new_hyper.edges:
new_edges[edge.label] = edge
for name, edge in new_edges.iteritems():
orig = original_edges[name]
nt.assert_almost_equal(w[orig], new_potentials[edge])
m = max_marginals[orig]
nt.assert_greater(m, prune)