UVa Problem 112 - Tree Summing

// UVa Problem 112 - Tree Summing
// Verdict: Accepted
// Submission Date: 2011-11-26
// UVa Run Time: 0.304s
//
// 版权所有(C)2011,邱秋。metaphysis # yeah dot net
//
// [解题方法]
// 本题可以归结为数据结构问题。
//
// 使用链表来表示树,若是使用数组,可能因为树的深度较大导致数组过大。关键是如何将输入解析成链表表
// 示的树,本题解利用了 cin.putback() 帮助完成。解析完成,剩下的就是树遍历的问题了。

#include <iostream>
#include <cstdlib>

using namespace std;

struct node
{
	struct node *parent;
	struct node *leftChild, *rightChild;
	int value;
};

bool haveTargetSum, emptyTree;

// 将路径和保存在叶子节点上。
void summingTree(node *current)
{
	if (current->leftChild != NULL)
	{
		current->leftChild->value += current->value;
		summingTree(current->leftChild);
	}

	if (current->rightChild != NULL)
	{
		current->rightChild->value += current->value;
		summingTree(current->rightChild);
	}
}

// 利用 cin.putback() 递归解析树。
void parseTree(node *current)
{
	bool isLeaf = false;

	char c;
	while (cin >> c, c != '(')
		;

	// 需要考虑负数的情况。
	cin >> c;
	if (isdigit(c) || c == '-')
	{
		int sign = (c == '-' ? (-1) : 1);
		int number;

		if (isdigit(c))
			number = c - '0';
		else
			number = 0;

		while (cin >> c, isdigit(c))
		{
			number *= 10;
			number += (c - '0');
		}

		cin.putback(c);
		current->value = number * sign;
	}
	else
	{
		cin.putback(c);

		// 若当前节点为空,则将父节点的相应子节点设为空。
		if (current->parent != NULL)
		{
			if (current == current->parent->leftChild)
				current->parent->leftChild = NULL;
			else
				current->parent->rightChild = NULL;
		}
		else
			emptyTree = true;

		isLeaf = true;
	}

	// 若不是叶子节点,则继续解析子树。
	if (!isLeaf)
	{
		node *left = new node;
		current->leftChild = left;
		left->parent = current;
		parseTree(left);

		node *right = new node;
		current->rightChild = right;
		right->parent = current;
		parseTree(right);
	}

	while (cin >> c, c != ')')
		;
}

// 遍历树,检查叶子节点保存的路径和是否为目标值。
void travelTree(node *current, int targetSum)
{
	if (haveTargetSum)
		return;

	if (current->leftChild == NULL && current->rightChild == NULL)
		if (current->value == targetSum)
			haveTargetSum = true;

	if (current->leftChild != NULL)
		travelTree(current->leftChild, targetSum);

	if (current->rightChild != NULL)
		travelTree(current->rightChild, targetSum);
}

int main(int argc, char const *argv[])
{
	int targetSum;
	while (cin >> targetSum)
	{
		node *root = new node;

		emptyTree = false;
		parseTree(root);

		summingTree(root);

		haveTargetSum = false;
		if (!emptyTree)
			travelTree(root, targetSum);

		cout << (haveTargetSum ? "yes\n" : "no\n");

		delete root;
	}

	return 0;
}


### 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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