# https://www.zg.ch/behoerden/staatskanzlei/kanzlei/abstimmungen-und-wahlen/wahlen-kr
# Gesamtergebnis der Sitzverteilung:
# https://www.zg.ch/behoerden/staatskanzlei/kanzlei/abstimmungen-und-wahlen/wahlen-kr/archiv-2018/downloads/2018-kr-dpt-gesamtergebnis-sitzverteilung.pdf

seats_mtrx_exp = matrix(
    c(0,3,3,5,2,3,3,
      0,0,2,1,0,0,1,
      0,1,1,1,0,1,2,
      0,0,1,1,0,0,1,
      0,2,3,2,1,3,4,
      0,1,3,2,1,1,2,
      0,1,2,1,0,1,1,
      0,2,2,1,0,0,1,
      0,1,2,2,0,0,2,
      0,0,1,1,0,0,0,
      0,0,1,0,0,0,1),
    nrow = 7
)

test_that("data input", {
    expect_equal(sum(seats_mtrx_exp), 80)
    expect_equal(unname(colSums(seats_mtrx_exp)), c(19,4,6,3,15,10,6,6,7,2,2))
    expect_equal(unname(rowSums(seats_mtrx_exp)), c(0,11,21,17,4,9,18))
})

colnames(seats_mtrx_exp) <- c("Zug", "Oberägeri", "Unterägeri", "Menzingen",
                              "Baar", "Cham", "Hünenberg", "Steinhausen",
                              "Risch", "Walchwil", "Neuheim")
rownames(seats_mtrx_exp) <- 1:7
names(dimnames(seats_mtrx_exp)) <- c("list_id", "entity_name")

test_that("pukelsheim with zug2018 is as expected", {
    votes_df = unique(zug2018[c("list_id", "entity_name", "list_votes")])
    district_seats_df = unique(zug2018[c("entity_name", "election_mandates")])

    seats_df = pukelsheim(votes_df,
                          district_seats_df,
                          quorum = quorum_any(any_district = 0.05,
                                              total = 0.03))
    seats_mtrx = pivot_to_matrix(seats_df[c(1,2,4)])

    expect_equal(seats_mtrx[,colnames(seats_mtrx_exp)], seats_mtrx_exp)
})

test_that("upper apportionment for districts", {
    votes_df = unique(zug2018[c("list_id", "entity_name", "list_votes")])
    votes_matrix = pivot_to_matrix(votes_df)

    x = biproporz(votes_matrix, 80)
    expect_equal(sum(x), 80)
})