Luntik and Subsequences

这篇博客介绍了如何计算给定数组中所有1出现次数的子数组数量,其中子数组的数量由1的个数乘以2的非零元素计数的幂。通过自定义pow函数避免了double类型溢出问题,并考虑了数组长度可能带来的大整数计算挑战。

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此题出自:Codeforces Round #750 (Div. 2)

Thought:

容易得出规律,满足条件的子数组数量为:cnt1 * 2^cnt0。

Attention:

①用c/c++语言,很容易想到用pow函数,但是!容易出现问题:pow函数变量是double型,而我们的cnt0为int型,所以可以自定义函数。

②虽然ai的范围在int型之内,但数组长度可达60,也就是说,子数组数量可能达到大概2^60是一个很大的数,最好用long long做函数返回值。

Code:

// #define LOCAL
#include <bits/stdc++.h>
typedef long long ll;
using namespace std;

ll llpow(int x, int y);
int main(void) 
{
#ifdef LOCAL
    freopen ("in.txt", "r", stdin);
    freopen ("out.txt", "w", stdout);
#endif
    int t;
    cin >> t;
    int n;
    int a;
    while (t--) {
        int n0 = 0, n1 = 0;
        scanf("%d",&n);
        for (int i = 0; i < n; i++) {
            scanf("%d",&a);
            if (a==0) n0++;
            if (a==1) n1++;
        }
        ll num = n1 * llpow(2,n0);
        printf("%lld\n",num);
    }
    return 0;
}

ll llpow(int x, int y)
{
    ll result = 1;
    for (int i = 0; i < y; i++) {
        result *= x;
    }
    return result;
}


### USACO 2016 January Contest Subsequences Summing to Sevens Problem Solution and Explanation In this problem from the USACO contest, one is tasked with finding the size of the largest contiguous subsequence where the sum of elements (IDs) within that subsequence is divisible by seven. The input consists of an array representing cow IDs, and the goal is to determine how many cows are part of the longest sequence meeting these criteria; if no valid sequences exist, zero should be returned. To solve this challenge efficiently without checking all possible subsequences explicitly—which would lead to poor performance—a more sophisticated approach using prefix sums modulo 7 can be applied[^1]. By maintaining a record of seen remainders when dividing cumulative totals up until each point in the list by 7 along with their earliest occurrence index, it becomes feasible to identify qualifying segments quickly whenever another instance of any remainder reappears later on during iteration through the dataset[^2]. For implementation purposes: - Initialize variables `max_length` set initially at 0 for tracking maximum length found so far. - Use dictionary or similar structure named `remainder_positions`, starting off only knowing position `-1` maps to remainder `0`. - Iterate over given numbers while updating current_sum % 7 as you go. - Check whether updated value already exists inside your tracker (`remainder_positions`). If yes, compare distance between now versus stored location against max_length variable's content—update accordingly if greater than previous best result noted down previously. - Finally add entry into mapping table linking latest encountered modulus outcome back towards its corresponding spot within enumeration process just completed successfully after loop ends normally. Below shows Python code implementing described logic effectively handling edge cases gracefully too: ```python def find_largest_subsequence_divisible_by_seven(cow_ids): max_length = 0 remainder_positions = {0: -1} current_sum = 0 for i, id_value in enumerate(cow_ids): current_sum += id_value mod_result = current_sum % 7 if mod_result not in remainder_positions: remainder_positions[mod_result] = i else: start_index = remainder_positions[mod_result] segment_size = i - start_index if segment_size > max_length: max_length = segment_size return max_length ```
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