def test_edge_type_graph_crf():
# create two samples with different graphs
# two states only, pairwise smoothing
# all edges are of the first type. should do the same as GraphCRF
# if we make w symmetric
for inference_method in get_installed(['qpbo', 'lp', 'ad3', 'dai', 'ogm']):
crf = EdgeTypeGraphCRF(n_states=2, inference_method=inference_method,
n_edge_types=1)
assert_array_equal(crf.inference((x_1, [g_1]), w_sym), y_1)
assert_array_equal(crf.inference((x_2, [g_2]), w_sym), y_2)
# same, only with two edge types and no edges of second type
w_sym_ = np.array([1, 0, # unary
0, 1,
.22, 0, # pairwise
0, .22,
2, -1, # second edge type, doesn't exist
-1, 3])
for inference_method in get_installed(['qpbo', 'lp', 'ad3', 'dai', 'ogm']):
crf = EdgeTypeGraphCRF(n_states=2, inference_method=inference_method,
n_edge_types=2)
assert_array_equal(crf.inference((x_1,
[g_1, np.zeros((0, 2),
dtype=np.int)]),
w_sym_), y_1)
assert_array_equal(crf.inference((x_2, [g_2, np.zeros((0, 2),
dtype=np.int)]),
w_sym_), y_2)
print crf.get_pairwise_potentials((x_2, [g_2, np.zeros((0, 2),
dtype=np.int)]),
w_sym_)
