# How Voting Systems Work 10, Exercise 1: add a top-two runoff to the toolkit and compare it.
# Assumed model: the chapter's uniform electorates (25 voters, 5 candidates, 2000 elections, seed 31).
# Needs votelab.py (the chapter's toolkit) in the same folder.
import random
from votelab import make_electorate, make_ballots, condorcet, plurality, irv, regret

def runoff(b):
    """Two rounds: the two largest first-place totals meet; each voter backs whichever they rank higher."""
    t = [0] * b["n"]
    for r in b["rank"]:
        t[r[0]] += 1
    order = sorted(range(b["n"]), key=lambda c: (-t[c], c))
    a, c = order[0], order[1]
    a_votes = sum(1 for r in b["rank"] if r.index(a) < r.index(c))
    return a if a_votes * 2 >= len(b["rank"]) else c

rng = random.Random(31)
contenders = {"plurality": plurality, "runoff": runoff, "irv": irv}
has_cw, agree, reg = 0, {k: 0 for k in contenders}, {k: 0.0 for k in contenders}
runs = 2000
for _ in range(runs):
    voters, cands = make_electorate(rng, "uniform")
    b = make_ballots(voters, cands)
    cw = condorcet(b)
    has_cw += cw is not None
    for name, m in contenders.items():
        w = m(b)
        reg[name] += regret(voters, cands, w)
        agree[name] += (cw is not None and w == cw)
for name in contenders:
    print(f"{name:>9}: picks Condorcet winner {agree[name] / has_cw:.1%}, mean regret {reg[name] / runs:.4f}")

# Output from a real run:
# plurality: picks Condorcet winner 54.4%, mean regret 0.0289
#    runoff: picks Condorcet winner 74.4%, mean regret 0.0131
#       irv: picks Condorcet winner 77.2%, mean regret 0.0111