Consider coordinates $$$x$$$ and $$$y$$$ separately. Since $$$1 \le x_i, y_i \le m - 1$$$, after each step both coordinates increase and remain connected with the previous square.

From the picture we can see that each coordinate spans from the bottom-left corner of the first square to the top-right corner of the last square.

To calculate the perimeter we can add the length of that interval for both coordinates and multiply it by $$$2$$$, as it is counted in the perimeter twice, going in both directions:

The coordinates of the bottom-left corner of the first square are $$$(x_1, y_1)$$$ and of the top-right corner of the last square are $$$(m + \sum\limits_{i = 1}^n x_i, m + \sum\limits_{i = 1}^n y_i)$$$.

The lengths of the intervals are $$$m + \sum\limits_{i = 2}^n x_i$$$ and $$$m + \sum\limits_{i = 2}^n y_i$$$.

Therefore, the answer is $$$2(2m + \sum\limits_{i = 2}^n (x_i + y_i))$$$.

#include <bits/stdc++.h>

using namespace std;

void solve() {
    int n, m;
    cin >> n >> m;
    vector<int> x(n), y(n);
    for(int i = 0; i < n; i++) {
        cin >> x[i] >> y[i];
    }
    int ans = 2 * (accumulate(x.begin(), x.end(), 0) + m - x[0] + accumulate(y.begin(), y.end(), 0) + m - y[0]);
    cout << ans << '\n';
}

signed main() {
    ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);
    int ttt = 1;
    cin >> ttt;
    while(ttt--) {
        solve();
    }
}

Consider two elements $$$x < y$$$. Suppose their positions in $$$p$$$ are $$$i$$$ and $$$j$$$ correspondigly.

How can we determine if $$$i < j$$$? If $$$i < j$$$ and $$$x < y$$$, we will have $$$g_{x, y} = g_{y, x} = 1$$$. Otherwise, $$$i > j$$$ and $$$x < y$$$, so $$$g_{x, y} = g_{y, x} = 0$$$.

So if $$$g_{x, y} = 1$$$, we know that $$$i < j$$$, otherwise $$$i > j$$$.

That way we can determine for each pair of elements which one of them should appear earlier in the permutation. Notice that this is just a definition of a comparator, which proves that the permutation is indeed unique. We can find it by sorting $$$p = [1, 2, \ldots, n]$$$ with that comparator.

#include <bits/stdc++.h>
 
using namespace std;
 
void solve() {
    int n;
    cin >> n;
    vector<string> g(n);
    for(auto &i : g) {
        cin >> i;
    }
    vector<int> p(n);
    iota(p.begin(), p.end(), 0);
    sort(p.begin(), p.end(),
    [&](int x, int y) {
        if(g[x][y] == '1') return x < y;
        else return x > y;
    });
    for(auto i : p) cout << i + 1 << " "; cout << '\n';
}
 
signed main() {
    ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);
    int ttt = 1;
    cin >> ttt;
    while(ttt--) {
        solve();
    }
}

If $$$[a_1, a_2, \ldots, a_k, a_{n - k + 1}, a_{n - k + 2}, \ldots, a_n]$$$ is a palindrome, then $$$[a_1, a_2, \ldots, a_k, a_i, a_{n - k + 1}, a_{n - k + 2}, \ldots, a_n]$$$ is also a palindrome for all $$$k < i < n - k + 1$$$, because we make it's length odd and add $$$a_i$$$ to the middle.

We can use this to create a sequence with a big value of $$$g$$$. However, we shouldn't create a palindrome of a greater length than $$$2k + 1$$$ by using the fact above.

That make us try something like $$$a = [1, 2, 3, \ldots, n - 2, 1, 2]$$$. $$$f(a) = 3$$$ here, and any of $$$[a_1, a_i, a_{n - 1}]$$$ for $$$1 < i < n - 1$$$ and $$$[a_2, a_i, a_n]$$$ for $$$2 < i < n$$$ are palindromes, which means that $$$g(a) = 2(n - 3) = 2n - 6$$$.

This construction works for $$$n \ge 7$$$, so we have to handle $$$n = 6$$$ separately.

We can also use the construction from the example with $$$n = 6$$$ directly: $$$a = [1, 1, 2, 3, 4, \ldots, n - 3, 1, 2]$$$, which has $$$g(a) = 3n - 11$$$.

#include <bits/stdc++.h>

using namespace std;

void solve() {
    int n;
    cin >> n;
    if (n == 6) {
        cout << "1 1 2 3 1 2\n";
    }
    else if(n == 9) {
        cout << "7 3 3 7 5 3 7 7 3\n";
    }
    else if(n == 15) {
        cout << "15 8 8 8 15 5 8 1 15 5 8 15 15 15 8\n";
    }
    else {
        for(int i = 1; i <= n - 2; i++) cout << i << " "; cout << "1 2\n";
    }
}


signed main() {
    ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);
    int ttt = 1;
    cin >> ttt;
    while(ttt--) {
        solve();
    }
}

When is a subarray $$$a[l, r]$$$ not good?

If $$$r - l + 1$$$ is odd, $$$a[l, r]$$$ can't be bad. Otherwise, suppose the median of $$$a[l, r]$$$ is $$$x$$$. Then there need to be exactly $$$\frac{r - l + 1}{2}$$$ elements in $$$a[l, r]$$$ that are $$$\le x$$$ and exactly $$$\frac{r - l + 1}{2}$$$ that are $$$> x$$$.

This gives us an idea to calculate the number of bad subarrays with a median of $$$x$$$.

Create another array $$$b$$$ of size $$$n$$$, where $$$b_i = -1$$$ if $$$a_i \le x$$$ and $$$b_i = 1$$$ otherwise.

$$$a[l, r]$$$, which has a median of $$$x$$$, is bad if and only if $$$\sum\limits_{i = l}^r b_i = 0$$$ and $$$r - l + 1$$$ is even.

Notice that the second condition is not needed, as the sum of an odd length subarray of $$$b$$$ is always odd, so it can't be zero.

Therefore, $$$a[l, r]$$$ with a median of $$$x$$$ is bad iff $$$\sum\limits_{i = l}^r b_i = 0$$$.

If there is no $$$x$$$ in $$$[l, r]$$$, then the median of $$$a[l, r]$$$ trivially can't be equal to $$$x$$$.

If there is an occurrence of $$$x$$$ in $$$a[l, r]$$$ and $$$\sum\limits_{i = l}^r b_i = 0$$$, notice that the median of $$$a[l, r]$$$ will always be exactly $$$x$$$. This is true because $$$\frac{r - l + 1}{2}$$$ smallest elements of $$$a[l, r]$$$ are all $$$\le x$$$, and there is an occurrence of $$$x$$$, so $$$\frac{r - l + 1}{2}$$$-th smallest element must be $$$x$$$.

This allows us to simply count the number of subarrays of $$$b$$$ with a sum of $$$0$$$ and with an occurrence of $$$x$$$ to count the number of bad subarrays with median $$$x$$$.

We can subtract that value from $$$\frac{n(n + 1)}{2}$$$ for all $$$x$$$ between $$$1$$$ and $$$A = 10$$$ to solve the problem in $$$O(nA)$$$.

#include <bits/stdc++.h>

using namespace std;

const int MAX = 11;

int main() {
    int tests;
    cin >> tests;
    for(int test = 0; test < tests; test++) {
        int n;
        cin >> n;
        vector<int> a(n);
        for(auto &i : a) {
            cin >> i;
        }
        long long ans = 0;
        for(int x = 1; x < MAX; x++) {
            vector<int> b(n);
            for(int i = 0; i < n; i++) {
                b[i] = (a[i] > x? 1 : -1);
            }
            int sum = n;
            vector<int> pref(n);
            for(int i = 0; i < n; i++) {
                pref[i] = sum;
                sum += b[i];
            }
            vector<int> cnt(2 * n + 1);
            sum = n;
            int j = 0;
            for(int i = 0; i < n; i++) {
                if(a[i] == x) {
                    while(j <= i) {
                        cnt[pref[j]]++;
                        j++;
                    }
                }
                sum += b[i];
                ans += cnt[sum];
            }
        }
        ans = 1ll * n * (n + 1) / 2 - ans;
        cout << ans << '\n';
    }
    return 0;
}

Any good set has a tree-like structure.

Specifically, represent $$$S$$$ as a forest the following way: segment $$$[l, r]$$$ has a parent $$$[L, R]$$$ iff $$$[l, r] \in [L, R]$$$ and $$$R - L + 1$$$ is minimized (its parent is the shortest interval in which it lies). This segment is unique (or does not exist), because there can't be two segments with minimum length that cover $$$[l, r]$$$, as they would partially intersect otherwise.

Notice that we can always add $$$[1, n]$$$ and $$$[i, i]$$$ for all $$$1 \le i \le n$$$ if they aren't in $$$S$$$ yet. Now the forest of $$$S$$$ is a tree with exactly $$$n$$$ leaves.

Suppose $$$[L, R]$$$ has $$$k$$$ children $$$[l_1, r_1], [l_2, r_2], \ldots, [l_k, r_k]$$$. If $$$k > 2$$$, we can always add $$$[l_1, r_2]$$$ to $$$S$$$, which decreases the number of children of $$$[L, R]$$$ by $$$1$$$ and increases the size of $$$S$$$ by $$$1$$$.

Therefore, in the optimal solution each segment has at most $$$2$$$ children. Having exactly one child is impossible, as we have added all $$$[i, i]$$$, so every index of $$$[L, R]$$$ is covered by its children.

This means that we have a tree where each vertex has either $$$0$$$ or $$$2$$$ children, which is a full binary tree.

We have $$$n$$$ leaves, and every full binary tree with $$$n$$$ leaves has exactly $$$2n - 1$$$ vertices, so this is always the optimal size of $$$T$$$ regardless of $$$S$$$.

To count the number of $$$T$$$, notice that when $$$m = 0$$$ the answer is the number of full binary trees with $$$n$$$ leaves, which is $$$C_{n - 1}$$$, where $$$C$$$ denotes the Catalan's sequence.

To extend this to a general tree, we can add $$$[1, n]$$$ and $$$[i, i]$$$ for all $$$1 \le i \le n$$$ to $$$S$$$.

Now suppose $$$[L, R]$$$ has $$$k \ge 2$$$ children $$$[l_1, r_1], [l_2, r_2], \ldots, [l_k, r_k]$$$. We need to merge some children. We can treat $$$[l_1, r_1]$$$ as $$$[1, 1]$$$, $$$[l_2, r_2]$$$ as $$$[2, 2]$$$, etc. This is now the same case as $$$m = 0$$$, so there are $$$C_{k - 1}$$$ ways to merge children of $$$[L, R]$$$.

Each vertex is independent of each other, so the answer is $$$\prod C_{c_v - 1}$$$ over all non-leaves $$$v$$$, where $$$c_v$$$ is the number of children of $$$v$$$.

We can construct the tree in $$$O(n \log n)$$$ by definition or in $$$O(n)$$$ using a stack.

#include <bits/stdc++.h>

using namespace std;

const int mod = 998244353;
const int MAX = 4e5 + 42;

int fact[MAX], inv[MAX], inv_fact[MAX];

int C(int n, int k) {
    if(n < k || k < 0) return 0;
    return (long long) fact[n] * inv_fact[k] % mod * inv_fact[n - k] % mod;
}

int Cat(int n) {
    return (long long) C(2 * n, n) * inv[n + 1] % mod;
}

int binpow(int x, int n) {
    int ans = 1;
    while(n) {
        if(n & 1) ans = (long long) ans * x % mod;
        n >>= 1;
        x = (long long) x * x % mod;
    }
    return ans;
}

void solve() {
    int n, m;
    cin >> n >> m;
    int initial_m = m;
    vector<pair<int, int>> a(m);
    for(auto &[l, r] : a) {
        cin >> l >> r;
    }
    bool was_full = 0;
    vector<int> was_single(n + 1);
    for(auto [l, r] : a) was_full |= (r - l + 1 == n);
    for(auto [l, r] : a) {
        if(l == r) was_single[l] = 1;
    }
    if(!was_full) {
        a.push_back({1, n});
        m++;
    }
    for(int i = 1; i <= n; i++) {
        if(!was_single[i] && n != 1) {
            a.push_back({i, i});
            m++;
        }
    }
    for(auto &[l, r] : a) r = -r;
    sort(a.begin(), a.end());
    vector<int> deg(m);
    for(int i = 0; i < m; i++) {
        int j = i + 1;
        while(j < m) {
            if(-a[i].second < a[j].first) break;
            deg[i]++;
            j = upper_bound(a.begin(), a.end(), make_pair(-a[j].second, 1)) - a.begin();
        }
    }
    for(auto &[l, r] : a) r = -r;
    int ans = 1;
    for(int i = 0; i < m; i++) {
        if(deg[i] > 0) {
            assert(deg[i] >= 2);
            ans = (long long) ans * Cat(deg[i] - 1) % mod;
        }
    }
    cout << ans << '\n';
}

signed main() {
    fact[0] = 1;
    for(int i = 1; i < MAX; i++) fact[i] = (long long) fact[i - 1] * i % mod;
    inv_fact[MAX - 1] = binpow(fact[MAX - 1], mod - 2);
    for(int i = MAX - 1; i; i--) inv_fact[i - 1] = (long long) inv_fact[i] * i % mod;
    assert(inv_fact[0] == 1);
    for(int i = 1; i < MAX; i++) inv[i] = (long long) inv_fact[i] * fact[i - 1] % mod;
    ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);
    int ttt = 1;
    cin >> ttt;
    while(ttt--) {
        solve();
    }
}

The order of the sequence doesn't matter, so let's fix the sequence $$$\text{cnt}$$$ and calculate its contribution to the answer.

For a fixed $$$\text{cnt}$$$, the number of ways to order $$$a$$$ is $$$\binom{n}{\text{cnt}_0, \text{cnt}_1, \ldots, \text{cnt}_{m - 1}}$$$. By Lucas's theorem the contribution is odd iff for each set bit in $$$n$$$ there is exactly one $$$i$$$ such that $$$\text{cnt}_i$$$ has this bit set, and $$$\sum\limits_{i = 0}^{m - 1} \text{cnt}_i = n$$$. In other words, $$$\text{cnt}$$$ has to partition all set bits in $$$n$$$.

Since $$$\text{cnt}$$$ partitions the bits of $$$n$$$, there will be $$$i$$$ which has it's most significant bit. This means that $$$2\text{cnt}_i > n$$$, so $$$i$$$ will always be the median.

Suppose there are $$$p$$$ non-zero elements in $$$\text{cnt}$$$. We can partition all set bits of $$$n$$$ into $$$p$$$ non-empty subsequences and then choose which of the $$$m$$$ numbers will occur.

The only time we use the value of $$$n$$$ is when we partition all of it's set bits into subsequences. That means that the answer only depends on the number of set bits in $$$n$$$, not on $$$n$$$ itself.

So let's fix $$$p$$$ as the number of non-zero elements in $$$\text{cnt}$$$ and $$$x$$$ as the median. Denote $$$b$$$ as the number of set bits in $$$n$$$. There are $$$S(b, p)$$$ ways to partition the bits into $$$p$$$ non-empty subsequences, where $$$S$$$ denotes Stirling number of the second kind. There are $$$\binom{x}{p - 1}$$$ ways to choose which other elements will have non-zero $$$\text{cnt}$$$, because the median will always have the largest value and non-zero $$$\text{cnt}_i$$$ must be non-decreasing.

The answer is then $$$\oplus_{p = 1}^b \oplus_{x = 0}^{m - 1} \left(S(b, p) \bmod 2\right) \cdot \left(\binom{x}{p - 1} \bmod 2\right) \cdot x$$$, which we can calculate in $$$O(km)$$$, which solves the easy version.

To solve the hard version we can use Lucas's theorem again to get that the contribution of $$$x$$$ to the answer is the XOR of $$$S(b, p + 1) \bmod 2$$$ over all submasks $$$p$$$ of $$$x$$$. We can limit $$$p$$$ to be between $$$0$$$ and $$$b - 1$$$.

That means that only $$$L = \lceil \log_2 b \rceil$$$ last bits of $$$x$$$ determine whether $$$x$$$ contributes something to the answer. We can find which of $$$2^L$$$ of them will have an odd contribution by setting $$$dp_p = S(b, p + 1) \bmod 2$$$, and calculating it's SOS-dp. Then for fixed $$$L$$$ last bits it is easy to find the XOR of all $$$x < m$$$ with those bits.

Note that $$$S(n, k)$$$ is odd iff $$$(n - k) \text{&} \frac{k - 1}{2} = 0$$$, which we can derive from the recurrence, combinatorics, google or OEIS.

This solves the problem in $$$O(b \log b) = O(k \log k)$$$.

#include <bits/stdc++.h>
 
using namespace std;
 
int C(int n, int k) {
    return (n & k) == k;
}
 
int S(int n, int k) {
    return !(n - k & (k - 1 >> 1));
}
 
int brute_partition(int n, int m) {
    vector<int> cnt;
    int ans = 0;
    for(int k = 1; k <= n; k++) {
        if(!S(n, k)) continue;
        for(int median = 1; median < m; median++) {
            if(C(median, k - 1)) ans ^= median;
        }
    }
    return ans;
}
 
void solve() {
    int k, m;
    string s;
    cin >> k >> m >> s;
    int n = 0;
    for(auto &i : s) n += i & 1;
    int ans = brute_partition(n, m);
    cout << ans << '\n';
}
 
signed main() {
    ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);
    int ttt = 1;
    cin >> ttt;
    while(ttt--) {
        solve();
    }
}

#include <bits/stdc++.h>

using namespace std;

int S(int n, int k) {
    return !(n - k & (k - 1 >> 1));
}

int get(int n, int m) {
    int L = __lg(n) + 1;
    int up = 1 << L;
    vector<int> dp(up);
    for(int i = 0; i < n; i++) dp[i] = S(n, i + 1);
    for(int j = 0; j < L; j++) {
        for(int i = 0; i < up; i++) {
            if(i >> j & 1) dp[i] ^= dp[i ^ (1 << j)];
        }
    }
    int ans = 0;
    for(int lst = 0; lst < up && lst < m; lst++) {
        if(!dp[lst]) continue;
        int cnt = m - 1 - lst >> L;
        if(cnt & 1 ^ 1) ans ^= lst;
        if(cnt % 4 == 0) ans ^= cnt << L;
        else if(cnt % 4 == 1) ans ^= 1ll << L;
        else if(cnt % 4 == 2) ans ^= cnt + 1 << L;
        else ans ^= 0;
    }
    return ans;
}

void solve() {
    int k, m;
    string s;
    cin >> k >> m >> s;
    int n = 0;
    for(auto &i : s) n += i & 1;
    int ans = get(n, m);
    cout << ans << '\n';
}

signed main() {
    ios_base::sync_with_stdio(0); cin.tie(0); cout.tie(0);
    int ttt = 1;
    cin >> ttt;
    while(ttt--) {
        solve();
    }
}

import requests
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.cluster import KMeans
from collections import defaultdict

# Function to fetch all users from Codeforces API
def fetch_users():
    url = "https://codeforces.net/api/user.ratedList"
    response = requests.get(url)

    if response.status_code == 200:
        data = response.json()
        if data["status"] == "OK":
            return data["result"]
        else:
            print("Error in response: ", data["comment"])
    else:
        print("Error fetching data: ", response.status_code)
    return []

# Function to filter users by max rating
def filter_users_by_rating(users, min_rating):
    return [user for user in users if user.get('maxRating', 0) > min_rating]

# Function to cluster users by the similarity of their names
def cluster_users_by_name(usernames, num_clusters=10):
    # Vectorize the usernames using TF-IDF with character n-grams
    vectorizer = TfidfVectorizer(analyzer='char', ngram_range=(2, 3))
    X = vectorizer.fit_transform(usernames)

    # Perform k-means clustering
    kmeans = KMeans(n_clusters=num_clusters, random_state=42)
    clusters = kmeans.fit_predict(X)

    clustered_users = defaultdict(list)
    user_cluster_map = {}
    for username, cluster_id in zip(usernames, clusters):
        clustered_users[cluster_id].append(username)
        user_cluster_map[username] = cluster_id

    return clustered_users, user_cluster_map

# Main processing function
def process_users(min_rating, num_clusters):
    # Fetch users
    users = fetch_users()

    # Filter users by max rating
    filtered_users = filter_users_by_rating(users, min_rating)
    print(len(filtered_users))
    # Extract usernames
    usernames = [user["handle"] for user in filtered_users]

    # Cluster users by the similarity of their names
    clusters, user_cluster_map = cluster_users_by_name(usernames, num_clusters)

    return clusters, user_cluster_map

# Fetch and process users (run this once)
clusters, user_cluster_map = process_users(min_rating=1599, num_clusters=5000)

from google.colab import files

def save_clusters_to_file(clusters, filename="clusters.txt"):
    with open(filename, "w") as file:
        for cluster_id, user_list in clusters.items():
            cluster_size = len(user_list)
            file.write(f"{cluster_size} {' '.join(user_list)}\n")
    return filename

output_file = save_clusters_to_file(clusters)

# Provide a link to download the file in Google Colab
files.download(output_file)

def get_user_cluster(username):
    cluster_id = user_cluster_map.get(username, None)
    if cluster_id is not None:
        return clusters[cluster_id]
    else:
        return "User not found"

# Example usage
username = "nifeshe"
user_cluster = get_user_cluster(username)
if user_cluster != "User not found":
    print(len(user_cluster))
    print(f"The cluster for user '{username}' is: {user_cluster}")
else:
    print(user_cluster)