def test_spn_construction_by_add_and_evaluation():
spn = Spn()
# building the same levels
input_layer = build_spn_indicator_layer(vars)
sum_layer, prod_layer = build_spn_layers(input_layer)
# adding all layers to the spn
spn.set_input_layer(input_layer)
spn.add_layer(sum_layer)
spn.add_layer(prod_layer)
res = spn.eval(I)
print('First evaluation')
print(res)
assert_log_array_almost_equal(root_vals, res)
def test_spn_construction_by_add_and_evaluation_II():
spn = Spn()
# print('empty spn')
# print(spn)
input_layer = build_spn_smoothed_layer(vars, dicts, alpha)
prod_layer = build_spn_layers_II(input_layer)
# adding all layers to the spn
spn.set_input_layer(input_layer)
spn.add_layer(prod_layer)
# print('created spn')
# print(spn)
res = spn.eval(I)
print('First smoothed evaluation')
print(res)
assert_log_array_almost_equal(root_vals, res)