TPR lab2_1

mat = [
    [5, 3,  1,  2,  8,  4,  6,  7],
    [5, 4,  3,  1,  8,  2,  6,  7],
    [1, 7,  5,  4,  8,  2,  3,  6],
    [6, 4,  2.5,    2.5,    8,  1,  7,  5],
    [8, 2,  4,  6,  3,  5,  1,  7],
    [5, 6,  4,  3,  2,  1,  7,  8],
    [6, 1,  2,  3,  5,  4,  8,  7],
    [5, 1,  3,  2,  7,  4,  6,  8],
    [6, 1,  3,  2,  5,  4,  7,  8],
    [5, 3,  2,  1,  8,  4,  6,  7],
    [7, 1,  3,  2,  6,  4,  5,  8],
    [1, 6,  5,  3,  8,  4,  2,  7]
]


def ar_mean():
    print('Впорядкування за середнiми арифметичними рангiв:')
    mean = list()
    freq = dict()
    freq[-1.0] = 1
    for j in range(0, 8):
        cur = 0
        for o in mat:
            cur += o[j]
        cur = round(cur / 12, 3)
        if cur not in freq:   freq[cur] = 0
        freq[cur] += 1
        mean.append((cur, chr(1040 + j)))
    mean.sort(key=lambda o: o[0])
    rank = -1
    last = -1.0
    ranking = dict()
    for o in mean:
        if last != o[0]:
            rank += freq[last]
            last = o[0]
        ranking[o[1]] = rank + (freq[o[0]] + 1) / 2
        print('\t', o[1], 'новий ранг', rank + (freq[o[0]] + 1) / 2, 'cередня оцiнка', o[0])
    return ranking


def ar_med():
    print('Впорядкування за медiанами рангiв:')
    med = list()
    freq = dict()
    freq[-1.0] = 1
    for j in range(0, 8):
        col = []
        for o in mat:
            col.append(o[j])
        col.sort()
        cur = round((col[5] + col[6]) / 2.0, 3)
        if cur not in freq:   freq[cur] = 0
        freq[cur] += 1
        med.append((cur, chr(1040 + j)))
    med.sort(key=lambda me: me[0])
    rank = -1
    last = -1.0
    ranking = dict()
    for o in med:
        if last != o[0]:
            rank += freq[last]
            last = o[0]
        ranking[o[1]] = rank + (freq[o[0]] + 1) / 2
        print('\t', o[1], 'новий ранг', rank + (freq[o[0]] + 1) / 2, 'медiана', o[0])
    return ranking


def dfs(cur, used, res, flag, g):
    used[cur] = 1
    for to in g[cur]:
        if not used[to]:
            if used[cur] == 1:
                used[cur] = 2
                res[0] += '{ '
            dfs(to, used, res, True, g)
    res[0] += chr(1040 + cur)
    if flag:
        res[0] += ' , '
    if used[cur] == 2:
        res[0] += ' }'


def cluster(ranking1, ranking2):
    g = [[] for _ in range(8)]
    print('Ядро суперечностей:')
    for i in range(0, 8):
        g[i].append(i)
        for j in range(i + 1, 8):
            u = chr(1040 + i)
            v = chr(1040 + j)
            if (ranking1[u] < ranking1[v] and ranking2[u] > ranking2[v]) or (ranking1[u] > ranking1[v] and ranking2[u] < ranking2[v]):
                g[i].append(j)
                g[j].append(i)
                print('\t(', u, ',', v, ')')
    print('\nКластеризоване ранжування:')
    pos = list(range(0, 8))
    pos.sort(key=lambda p: [ranking1[chr(1040 + p)], ranking2[chr(1040 + p)]])
    used = [0] * 8
    res = ['']
    for e in pos:
        if not used[e]:
            if len(res[0]):    res[0] += ' < '
            dfs(e, used, res, False, g)
    print('\t', res[0])


ar_ranking = ar_mean()
print('\n')
med_ranking = ar_med()
print('\n')
cluster(ar_ranking, med_ranking)