CodeForces 810C - Do you want a date?(数学+排序)

本文介绍了一个计算机科学领域的算法问题,黑客Leha需要计算其控制的所有计算机之间的距离的最大值之和,以完成朋友Noora的挑战。文章详细解释了如何通过排序和数学公式优化计算过程。

C. Do you want a date?
time limit per test
2 seconds
memory limit per test
256 megabytes
input
standard input
output
standard output

Leha decided to move to a quiet town Vičkopolis, because he was tired by living in Bankopolis. Upon arrival he immediately began to expand his network of hacked computers. During the week Leha managed to get access to n computers throughout the town. Incidentally all the computers, which were hacked by Leha, lie on the same straight line, due to the reason that there is the only one straight street in Vičkopolis.

Let's denote the coordinate system on this street. Besides let's number all the hacked computers with integers from 1 to n. So the i-th hacked computer is located at the point xi. Moreover the coordinates of all computers are distinct.

Leha is determined to have a little rest after a hard week. Therefore he is going to invite his friend Noora to a restaurant. However the girl agrees to go on a date with the only one condition: Leha have to solve a simple task.

Leha should calculate a sum of F(a) for all a, where a is a non-empty subset of the set, that consists of all hacked computers. Formally, let's denote A the set of all integers from 1 to n. Noora asks the hacker to find value of the expression . Here F(a) is calculated as the maximum among the distances between all pairs of computers from the set a. Formally, . Since the required sum can be quite large Noora asks to find it modulo 109 + 7.

Though, Leha is too tired. Consequently he is not able to solve this task. Help the hacker to attend a date.

Input

The first line contains one integer n (1 ≤ n ≤ 3·105) denoting the number of hacked computers.

The second line contains n integers x1, x2, ..., xn (1 ≤ xi ≤ 109) denoting the coordinates of hacked computers. It is guaranteed that all xi are distinct.

Output

Print a single integer — the required sum modulo 109 + 7.

Examples
input
2
4 7
output
3
input
3
4 3 1
output
9
Note

There are three non-empty subsets in the first sample test: and . The first and the second subset increase the sum by 0and the third subset increases the sum by 7 - 4 = 3. In total the answer is 0 + 0 + 3 = 3.

There are seven non-empty subsets in the second sample test. Among them only the following subsets increase the answer: . In total the sum is (4 - 3) + (4 - 1) + (3 - 1) + (4 - 1) = 9.

对于已经从小到大排完序的aj-ai一共出现多少次,就是用集合的子集合的数量就可以算出来是2^(j-i+1)个。

但是这样还需要再求组合数来列出所有aj-ai的情况无疑是复杂的。

那么还有一种思路降低时间复杂度,就是求每一个ai作为最大值和最小值的次数。

分析:当ai作为最大值时,会出现2^(i-1)次,作为最小值时,会出现2^(n-i)次,只要将这些都加起来取模就行了。注意要用long long来存不然会wa。

#include <iostream>
#include <cstdio>
#include <cstring>
#include <algorithm>
#define MAX_N 300500
#define MOD 1000000007
using namespace std;
long long mul[MAX_N],a[MAX_N];
int main()
{
    int n;
    while(~scanf("%d",&n))
    {
        long long sum=0;
        mul[0]=1;
        for(int i=1;i<=n;i++)
            cin>>a[i];
        sort(a+1,a+1+n);
        for(int i=1;i<=n;i++)
            mul[i]=mul[i-1]*2%MOD;
        for(int i=1;i<=n;i++)
            sum=(sum+(mul[i-1]-mul[n-i])*a[i]%MOD)%MOD;
        cout<<sum<<endl;
    }
    return 0;
}


标题基于Python的汽车之家网站舆情分析系统研究AI更换标题第1章引言阐述汽车之家网站舆情分析的研究背景、意义、国内外研究现状、论文方法及创新点。1.1研究背景与意义说明汽车之家网站舆情分析对汽车行业及消费者的重要性。1.2国内外研究现状概述国内外在汽车舆情分析领域的研究进展与成果。1.3论文方法及创新点介绍本文采用的研究方法及相较于前人的创新之处。第2章相关理论总结和评述舆情分析、Python编程及网络爬虫相关理论。2.1舆情分析理论阐述舆情分析的基本概念、流程及关键技术。2.2Python编程基础介绍Python语言特点及其在数据分析中的应用。2.3网络爬虫技术说明网络爬虫的原理及在舆情数据收集中的应用。第3章系统设计详细描述基于Python的汽车之家网站舆情分析系统的设计方案。3.1系统架构设计给出系统的整体架构,包括数据收集、处理、分析及展示模块。3.2数据收集模块设计介绍如何利用网络爬虫技术收集汽车之家网站的舆情数据。3.3数据处理与分析模块设计阐述数据处理流程及舆情分析算法的选择与实现。第4章系统实现与测试介绍系统的实现过程及测试方法,确保系统稳定可靠。4.1系统实现环境列出系统实现所需的软件、硬件环境及开发工具。4.2系统实现过程详细描述系统各模块的实现步骤及代码实现细节。4.3系统测试方法介绍系统测试的方法、测试用例及测试结果分析。第5章研究结果与分析呈现系统运行结果,分析舆情数据,提出见解。5.1舆情数据可视化展示通过图表等形式展示舆情数据的分布、趋势等特征。5.2舆情分析结果解读对舆情分析结果进行解读,提出对汽车行业的见解。5.3对比方法分析将本系统与其他舆情分析系统进行对比,分析优劣。第6章结论与展望总结研究成果,提出未来研究方向。6.1研究结论概括本文的主要研究成果及对汽车之家网站舆情分析的贡献。6.2展望指出系统存在的不足及未来改进方向,展望舆情
【磁场】扩展卡尔曼滤波器用于利用高斯过程回归进行磁场SLAM研究(Matlab代码实现)内容概要:本文介绍了利用扩展卡尔曼滤波器(EKF)结合高斯过程回归(GPR)进行磁场辅助的SLAM(同步定位与地图构建)研究,并提供了完整的Matlab代码实现。该方法通过高斯过程回归对磁场空间进行建模,有效捕捉磁场分布的非线性特征,同时利用扩展卡尔曼滤波器融合传感器数据,实现移动机器人在复杂环境中的精确定位与地图构建。研究重点在于提升室内等无GPS环境下定位系统的精度与鲁棒性,尤其适用于磁场特征明显的场景。文中详细阐述了算法原理、数学模型构建、状态估计流程及仿真实验设计。; 适合人群:具备一定Matlab编程基础,熟悉机器人感知、导航或状态估计相关理论的研究生、科研人员及从事SLAM算法开发的工程师。; 使用场景及目标:①应用于室内机器人、AGV等在缺乏GPS信号环境下的高精度定位与地图构建;②为磁场SLAM系统的设计与优化提供算法参考和技术验证平台;③帮助研究人员深入理解EKF与GPR在非线性系统中的融合机制及实际应用方法。; 阅读建议:建议读者结合Matlab代码逐模块分析算法实现细节,重点关注高斯过程回归的训练与预测过程以及EKF的状态更新逻辑,可通过替换实际磁场数据进行实验验证,进一步拓展至多源传感器融合场景。
### Codeforces Problem 976C Solution in Python For solving problem 976C on Codeforces using Python, efficiency becomes a critical factor due to strict time limits aimed at distinguishing between efficient and less efficient solutions[^1]. Given these constraints, it is advisable to focus on optimizing algorithms and choosing appropriate data structures. The provided code snippet offers insight into handling string manipulation problems efficiently by customizing comparison logic for sorting elements based on specific criteria[^2]. However, for addressing problem 976C specifically, which involves determining the winner ('A' or 'B') based on frequency counts within given inputs, one can adapt similar principles of optimization but tailored towards counting occurrences directly as shown below: ```python from collections import Counter def determine_winner(): for _ in range(int(input())): count_map = Counter(input().strip()) result = "A" if count_map['A'] > count_map['B'] else "B" print(result) determine_winner() ``` This approach leverages `Counter` from Python’s built-in `collections` module to quickly tally up instances of 'A' versus 'B'. By iterating over multiple test cases through a loop defined by user input, this method ensures that comparisons are made accurately while maintaining performance standards required under tight computational resources[^3]. To further enhance execution speed when working with Python, consider submitting codes via platforms like PyPy instead of traditional interpreters whenever possible since they offer better runtime efficiencies especially important during competitive programming contests where milliseconds matter significantly.
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值