This repository has been archived on 2021-05-25. You can view files and clone it, but cannot push or open issues or pull requests.
pyRCV2/tests/test_aec.py

81 lines
3.3 KiB
Python

# pyRCV2: Preferential vote counting
# Copyright © 2020–2021 Lee Yingtong Li (RunasSudo)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
from pytest import approx
from pytest_steps import test_steps
import pyRCV2.blt
import pyRCV2.numbers
from pyRCV2.method.gregory import UIGSTVCounter
from pyRCV2.model import CandidateState, CountCompleted
import csv
import gzip
# Read model CSV
with open('tests/data/aec-senate-formalpreferences-24310-TAS.csv', 'r', newline='') as f:
reader = csv.reader(f)
data = [x for x in reader]
candidates = [data[i][0] for i in range(2, len(data) - 2)]
@test_steps(*['Stage {}'.format(data[0][i]) for i in range(1, len(data[0]), 2)])
def test_aec_tas19():
"""Compare count of aec-senate-formalpreferences-24310-TAS.blt.gz with model result at https://results.aec.gov.au/24310/Website/External/SenateStateDop-24310-TAS.pdf"""
pyRCV2.numbers.set_numclass(pyRCV2.numbers.Native)
with gzip.open('tests/data/aec-senate-formalpreferences-24310-TAS.blt.gz', 'rt') as f:
election = pyRCV2.blt.readBLT(f.read())
assert len(election.candidates) == len(candidates)
counter = UIGSTVCounter(election, {
'surplus_order': 'order',
'exclusion': 'by_value',
'bulk_exclude': True,
'round_quota': 0,
'round_votes': 0,
})
result = counter.reset()
for i in range(1, len(data[0]), 2):
stage = int(data[0][i])
while len(counter.step_results) < stage:
result = counter.step()
comment = data[1][i]
assert result.comment == comment, 'Failed to verify comment'
for j, cand in enumerate(candidates):
votes = pyRCV2.numbers.Num(data[j + 2][i])
cc = next(cc for c, cc in result.candidates.items() if c.name == cand)
assert cc.votes.impl == approx(votes.impl), 'Failed to verify candidate "{}" votes, got {} expected {}'.format(cand, cc.votes.pp(0), votes.pp(0))
state = data[j + 2][i + 1] if len(data[j + 2]) > (i + 1) else ''
accept = {'': CandidateState.HOPEFUL, 'PEL': CandidateState.PROVISIONALLY_ELECTED, 'EL': CandidateState.ELECTED, 'EX': CandidateState.EXCLUDED, 'EXCLUDING': CandidateState.EXCLUDING}
assert cc.state == accept[state], 'Failed to verify candidate "{}" state'.format(cand)
exhausted = pyRCV2.numbers.Num(data[len(candidates) + 2][i])
assert result.exhausted.votes.impl == approx(exhausted.impl), 'Failed to verify exhausted votes, got {} expected {}'.format(result.exhausted.votes.pp(0), exhausted.pp(0))
loss_fraction = pyRCV2.numbers.Num(data[len(candidates) + 3][i])
assert result.loss_fraction.votes.impl == approx(loss_fraction.impl), 'Failed to verify loss to fraction, got {} expected {}'.format(result.loss_fraction.votes.pp(0), loss_fraction.pp(0))
yield 'Stage {}'.format(stage)