def test_readme_example():
""" Verify the example used in the repo README. """
resident_prefs = {
"A": ["C"],
"S": ["C", "M"],
"D": ["C", "M", "G"],
"J": ["C", "G", "M"],
"L": ["M", "C", "G"],
}
hospital_prefs = {
"M": ["D", "L", "S", "J"],
"C": ["D", "A", "S", "L", "J"],
"G": ["D", "J", "L"],
}
capacities = {hosp: 2 for hosp in hospital_prefs}
game = HospitalResident.create_from_dictionaries(resident_prefs,
hospital_prefs,
capacities)
(A, S, D, J, L), (M, C, G) = game.residents, game.hospitals
matching = hospital_resident(game.residents, game.hospitals)
assert matching == {M: [L, S], C: [D, A], G: [J]}
def test_example_in_issue():
""" Verify that the matching found is consistent with the example in #67.
"""
group_prefs = {
"Group 1": ["Intellectual property", "Privacy"],
"Group 2": ["Privacy", "Fairness in AI"],
"Group 3": ["Privacy", "Social media"],
}
topic_hospital_prefs = {
"Fairness in AI": ["Group 2"],
"Intellectual property": ["Group 1"],
"Privacy": ["Group 3", "Group 2", "Group 1"],
"Social media": ["Group 3"],
}
capacities = {t: 2 for t in topic_hospital_prefs}
game = HospitalResident.create_from_dictionaries(group_prefs,
topic_hospital_prefs,
capacities)
(G1, G2, G3), (F, I, P, S) = game.residents, game.hospitals
matching = hospital_resident(game.residents, game.hospitals)
assert matching == {I: [G1], P: [G3, G2], F: [], S: []}
def test_hospital_optimal(resident_names, hospital_names, capacities, seed):
""" Verify that the hospital-resident algorithm produces a valid,
hospital-optimal matching for an instance of HR. """
np.random.seed(seed)
residents, hospitals = make_players(resident_names, hospital_names,
capacities)
matching = hospital_resident(residents, hospitals, optimal="hospital")
assert set(hospitals) == set(matching.keys())
for hospital, matches in matching.items():
old_idx = -np.infty
for resident in matches:
idx = hospital.prefs.index(resident)
assert idx >= old_idx
old_idx = idx
def test_resident_optimal(resident_names, hospital_names, capacities, seed):
""" Verify that the hospital-resident algorithm produces a valid,
resident-optimal matching for an instance of HR. """
np.random.seed(seed)
residents, hospitals = make_players(resident_names, hospital_names,
capacities)
matching = hospital_resident(residents, hospitals, optimal="resident")
assert set(hospitals) == set(matching.keys())
assert all([
r in set(residents) for r in
{r_match
for matches in matching.values() for r_match in matches}
])
for resident in residents:
if resident.matching:
assert resident.prefs.index(resident.matching) == 0