def test_cat_and_dog_reduced_to_animal():
c1 = Classification(0.4, Label('02096294-n', 'australian terrier', ''))
c2 = Classification(0.4, Label('02123045-n', 'tabby, tabby cat', ''))
node = Hierarchy(0.7).place([c1, c2])
assert node == animal_node
def test_terrier_reduced_to_dog():
c1 = Classification(0.4, Label('02096294-n', 'australian terrier', ''))
# toy terrier is not actually a terrier breed, so does not exist as a 'terrier'
c2 = Classification(0.4, Label('02087046-n', 'toy terrier', ''))
node = Hierarchy(0.7).place([c1, c2])
assert node == dog_node
def test_terrier_groups_terrier_combination():
# multiple classifications of terrier breeds should sum
# to be 80% accuracy, result should be 'terrier'
c1 = Classification(0.4, Label('02096294-n', 'australian terrier', ''))
c2 = Classification(0.35, Label('02097658-n', 'silky terrier', ''))
c3 = Classification(0.05, Label('02094433-n', 'yorkshire terrier', ''))
node = Hierarchy(0.7).place([c1, c2, c3])
assert node == terrier_node
def test_terrier_groups_terrier():
# 80% accuracy on 70% hierarchy should group in 'terrier'
label = Label('02096294-n', 'australian terrier', '')
c = Classification(0.8, label)
node = Hierarchy(0.7).place([c])
assert node == terrier_node
def test_non_matching_group():
c = Classification(0.8, Label('04465501-n', 'tractor', ''))
node = Hierarchy(0.7).place([c])
assert node is None
def test_high_accuracy_hierarchy():
c = Classification(0.85, Label('02096294-n', 'australian terrier', ''))
node = Hierarchy(0.9).place([c])
assert node is None
def test_piano_is_instrument():
piano = Label('04515003-n', 'upright, upright piano', '')
instrument = wordnet.synsets('musical_instrument')[0]
assert piano.is_a(instrument)
def test_dog_is_cat():
dog = Label('02099601-n', 'golden retriever', '')
cat = wordnet.of2ss('02123045-n')
assert not dog.is_a(cat)
def test_cat_is_animal():
cat = Label('02123045-n', 'tabby, tabby cat', '')
animal = wordnet.synsets('animal')[0]
assert cat.is_a(animal)