def test_eliminate(self, ballots):
amy = Candidate("Amy")
kamala = Candidate("Kamala")
elizabeth = Candidate("Elizabeth")
schedule = PreferenceSchedule(ballots, candidates={amy, kamala, elizabeth})
schedule.eliminate(elizabeth)
for candidate in schedule.candidates:
for ballot, weight in candidate.votes:
assert str(elizabeth) not in ballot
def test_from_ballotS(self):
schedule = PreferenceSchedule.from_ballots(
[
("Kamala", "Elizabeth", "Amy"),
("Kirsten", "Elizabeth"),
("Kamala", "Elizabeth", "Amy"),
("Amy", "Elizabeth", "Kirsten"),
]
)
assert schedule is not None
def test_can_normalize_a_dataframe(self):
df = pandas.DataFrame(
{
"first": [None, "Amy", "Amy", "Kamala"],
"second": ["Elizabeth", "Elizabeth", "Amy", "Amy"],
"third": ["Kamala", "Kamala", "Elizabeth", "Elizabeth"],
}
)
schedule = PreferenceSchedule.from_dataframe(df)
assert set(schedule) == {
(("Elizabeth", "Kamala"), 1),
(("Amy", "Elizabeth", "Kamala"), 1),
(("Amy", "Elizabeth"), 1),
(("Kamala", "Amy", "Elizabeth"), 1),
}
def run_stv(dataframe):
schedule = PreferenceSchedule.from_dataframe(dataframe)
stv = FractionalSTV(schedule, seats=3)
return stv.elect()
def test_create_from_dataframe(self, dataframe):
schedule = PreferenceSchedule.from_dataframe(dataframe)
assert schedule
def run_stv(dataframe):
assert len(dataframe.columns) == 3
schedule = PreferenceSchedule.from_dataframe(dataframe)
stv = FractionalSTV(schedule, seats=3)
return stv.elect()