def test_graph_crf_inference():
# create two samples with different graphs
# two states only, pairwise smoothing
for inference_method in get_installed(['qpbo', 'lp', 'ad3', 'dai', 'ogm']):
crf = GraphCRF(n_states=2, n_features=2,
inference_method=inference_method)
assert_array_equal(crf.inference((x_1, g_1), w), y_1)
assert_array_equal(crf.inference((x_2, g_2), w), y_2)
print crf._get_pairwise_potentials((x_1, g_1), w)
def test_graph_crf_inference():
# create two samples with different graphs
# two states only, pairwise smoothing
for inference_method in get_installed(['qpbo', 'lp', 'ad3', 'dai', 'ogm']):
crf = GraphCRF(n_states=2, n_features=2,
inference_method=inference_method)
assert_array_equal(crf.inference((x_1, g_1), w), y_1)
assert_array_equal(crf.inference((x_2, g_2), w), y_2)
print crf._get_pairwise_potentials((x_1, g_1), w)
def test_directed_graph_crf_inference():
# create two samples with different graphs
# two states only, pairwise smoothing
# same as above, only with full symmetric matrix
for inference_method in get_installed(['qpbo', 'lp', 'ad3', 'dai', 'ogm']):
crf = GraphCRF(n_states=2, n_features=2,
inference_method=inference_method, directed=True)
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)
print crf._get_pairwise_potentials((x_1, g_1), w_sym)
def test_directed_graph_crf_inference():
# create two samples with different graphs
# two states only, pairwise smoothing
# same as above, only with full symmetric matrix
for inference_method in get_installed(['qpbo', 'lp', 'ad3', 'dai', 'ogm']):
crf = GraphCRF(n_states=2, n_features=2,
inference_method=inference_method, directed=True)
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)
print crf._get_pairwise_potentials((x_1, g_1), w_sym)
