def test_small_distance_from_other_schedule(slots, events):
X_orig = np.array([
[1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0],
[0, 1, 0, 0, 0, 0, 0]
])
schedule = scheduler.array_to_schedule(array=X_orig, slots=slots,
events=events)
solution = scheduler.solution(
events=events, slots=slots,
objective_function=of.number_of_changes,
original_schedule=schedule,
)
assert type(solution) is list
assert list(solution) == [(0, 5), (1, 4), (2, 6)]
X_orig = np.array([
[0, 0, 0, 0, 0, 0, 1],
[0, 0, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0]
])
schedule = scheduler.array_to_schedule(array=X_orig, slots=slots,
events=events)
solution = scheduler.solution(
events=events, slots=slots,
objective_function=of.number_of_changes,
original_schedule=schedule,
)
assert list(solution) == [(0, 6), (1, 0), (2, 5)]
def test_unsolvable_raises_error(events):
slots = [
Slot(
venue='Main Hall', starts_at='15-Sep-2016 09:30', duration=30,
capacity=50, session="01 Morning A"
)
]
with pytest.raises(ValueError):
scheduler.solution(events, slots)
def test_unsolvable_raises_error(events):
slots = [
Slot(
venue='Main Hall', starts_at=datetime(2016, 9, 15, 9, 30),
duration=30, capacity=50, session="01 Morning A"
)
]
with pytest.raises(ValueError):
scheduler.solution(events, slots)
def test_demand_difference_schedule(slots, events):
solution = scheduler.solution(
events=events, slots=slots,
objective_function=of.capacity_demand_difference
)
assert type(solution) is list
assert list(solution) == [(0, 3), (1, 4), (2, 6)]
def test_solution_solver_recognised_by_pulp_raises_error(events, slots):
with pytest.raises(AttributeError):
scheduler.solution(events, slots, solver="Not a real solver")
speaker_clashes = definition['speaker_clashes']
talk_clashes = {
talks.index(talk): [
talks.index(t) for s in clashing_speakers for t in talks
if t['speaker'] == s
]
for speaker, clashing_speakers in speaker_clashes.items() for talk in talks
if talk['speaker'] == speaker
}
for talk, clashing_talks in talk_clashes.items():
events['talk'][talk].add_unavailability(
*[events['talk'][t] for t in clashing_talks])
solution = scheduler.solution(events['talk'],
slots['talk'],
solver=pulp.GLPK())
conference = {
'session_times': session_times,
'slot_times': slot_times,
'venues': venues,
'days': days,
'slots': slots,
'events': events,
'solution': solution
}
with open('definition/conference.bin', 'wb') as file:
pickle.dump(conference, file)
def solution(shape):
return [item for item in scheduler.solution(shape)]
def solution(events, slots):
return list(scheduler.solution(events, slots))