06-E. Point_Array(类+构造+对象数组)

这篇博客主要介绍了如何在C++中为Point类添加自定义拷贝构造函数和析构函数,以及如何根据用户输入创建Point对象数组,并计算数组中两点最大距离。博客内容包括修改getDisTo方法以接受const Point引用,以及展示不同构造和析构调用次数的影响。最后给出了示例输出,展示了如何输出指定精度的距离值。

06-构造与析构-

题目描述
在这里插入图片描述
上面是我们曾经练习过的一个习题,请在原来代码的基础上作以下修改:1、增加自写的拷贝构造函数;2、增加自写的析构函数;3、将getDisTo方法的参数修改为getDisTo(const Point &p);4、根据下面输出的内容修改相应的构造函数。

然后在主函数中根据用户输入的数目建立Point数组,求出数组内距离最大的两个点之间的距离值。

输入
测试数据的组数 t

第一组点的个数

第一个点的 x 坐标 y坐标

第二个点的 x坐标 y坐标

输出
输出第一组距离最大的两个点以及其距离



在C++中,输出指定精度的参考代码如下:

#include < iostream>

#include < iomanip> //必须包含这个头文件

using namespace std;

void main( )

{ double a =3.141596;

cout<<fixed<<setprecision(3)<<a<<endl; //输出小数点后3位

输入样例
2
4
0 0
5 0
5 5
2 10
3
-1 -8
0 9
5 0

Constructor.
Constructor.
Constructor.
Constructor.
The longeset distance is 10.44,between p[1] and p[3].
Distructor.
Distructor.
Distructor.
Distructor.
Constructor.
Constructor.
Constructor.
The longeset distance is 17.03,between p[0] and p[1].
Distructor.
Distructor.
Distructor.

1.关于const point &p
—如果使用(point p),由于传参时会调用默认拷贝构造函数,在主函数的冒泡排序时会共调用n!次默认构造函数,因此在析构时会多出(n+1)*n/2次
—使用const防止改变值
2.在函数里可以直接使用p.x、p.y,在主函数需要p.getx()、 p.gety()


#include <iostream>
#include <iomanip>
#include <cmath>
using namespace std;

class point
{
   
   
    double x,y;
    
public:
    point()
    {
   
   x
帮我改写下面的函数,功能相同,但不要使用递归的方法bool OtsTrack::BackTrackForArray(int startSearchingID, int *inner_id, std::vector<int> &array_temp, std::vector<int> &inner_temp, double **distancesOfAllPoints, VecPoint3D &pts3d_, VecPoint3D &arrayPoints, int &inner_pointer, std::vector<int> &inner_id_in_array, std::vector<int> &indexes) { std::string realArrayID = ""; int pointsSize = -1; int virtualID = array_temp[indexes[0]]; if (virtualID != -1) { int virtualArrayID = m_pointsMapArrayID[virtualID]; realArrayID = m_arrayMarkerIds[virtualArrayID]; pointsSize = m_mapToolSetting.at(realArrayID).FaceData[m_pointsMapFaceID[virtualID]].FaceMarkerNum; if (inner_pointer >= pointsSize) return true; } // find a point Point3D p1; int index = 0; // the the distance between first point and current point double distance = 0.0; for (size_t i = startSearchingID; i < pts3d_.size(); i++) { bool hasSameIndex = false; for (auto in : indexes) if (in == i) hasSameIndex = true; if (hasSameIndex || array_temp[i] != -1) continue; p1 = pts3d_[i]; index = i; if (fabs(distancesOfAllPoints[indexes[0]][i]) < 1e-5) { distance = (arrayPoints[0] - p1).Norm2(); distancesOfAllPoints[indexes[0]][i] = distance; } else distance = distancesOfAllPoints[indexes[0]][i]; if (distance > m_fMaxRefDistance) { continue; } // set indexes.emplace_back(index); arrayPoints.emplace_back(p1); if (inner_pointer == 1) { std::vector<int> spareArray; std::vector<int> inner_wrongConfirmed_id_1; //<0,1,2,3 std::vector<int> inner_wrongConfirmed_id_2; for (int k = 0; k < m_pointsMapArrayID.size(); k++) { for (int j1 = 0; j1 < m_AllRefDistances[k].size(); j1++) for (int j2 = j1 + 1; j2 < m_AllRefDistances[k].size(); j2++) { double diff_12 = fabs(m_AllRefDistances[k][j1][j2] - distance); if (diff_12 < m_OTSParam.fMatchingDistanceThreshold) { // less than m_OTSParam.fMatchingDistanceThreshold mm spareArray.emplace_back(k); inner_wrongConfirmed_id_1.emplace_back(j1); inner_wrongConfirmed_id_2.emplace_back(j2); } } } for (size_t h = 0; h < spareArray.size(); h++) { //<first and second point // set inner_id[0] = inner_wrongConfirmed_id_1[h]; inner_id[1] = inner_wrongConfirmed_id_2[h]; array_temp[indexes[0]] = spareArray[h]; array_temp[indexes[inner_pointer++]] = spareArray[h]; if (BackTrackForArray(i + 1, inner_id, array_temp, inner_temp, distancesOfAllPoints, pts3d_, arrayPoints, inner_pointer, inner_id_in_array, indexes)) { return true; } // resume inner_id[0] = -1; inner_id[1] = -1; array_temp[indexes[0]] = -1; array_temp[indexes[--inner_pointer]] = -1; } // resume arrayPoints.pop_back(); indexes.pop_back(); } // confirm the inner id else if (inner_pointer == 2) { std::vector<int> inner_wrongConfirmed_id_1; //<0,1,2,3 std::vector<int> numberofInner; std::vector<int> inner_wrongConfirmed_id_2; for (int q = 0; q < 2; q++) { for (int j2 = 0; j2 < pointsSize; j2++) { bool haveSameInnerId = false; for (int ind = 0; ind < inner_pointer; ind++) { if (inner_id[ind] == j2) { haveSameInnerId = true; break; } } if (haveSameInnerId) // continue; double diff_13 = fabs(m_AllRefDistances[virtualID][inner_id[q]][j2] - distance); if (diff_13 < m_OTSParam.fMatchingDistanceThreshold) { numberofInner.emplace_back(q); inner_wrongConfirmed_id_1.emplace_back(inner_id[q]); inner_wrongConfirmed_id_2.emplace_back(j2); } } } if (numberofInner.empty()) { arrayPoints.pop_back(); indexes.pop_back(); continue; } // bool matched = true; Point3D p2 = arrayPoints[1]; //<second point double distance_p1p2 = 0.0; if (fabs(distancesOfAllPoints[indexes[1]][index]) < 1e-5) { distance_p1p2 = (p2 - p1).Norm2(); distancesOfAllPoints[indexes[1]][index] = distance_p1p2; } else distance_p1p2 = distancesOfAllPoints[indexes[1]][index]; for (size_t h = 0; h < numberofInner.size(); h++) { int index_array_2 = numberofInner[h] == 0 ? 1 : 0; double diff_23 = fabs(m_AllRefDistances[virtualID][inner_id[index_array_2]][inner_wrongConfirmed_id_2[h]] - distance_p1p2); if (diff_23 < m_OTSParam.fMatchingDistanceThreshold) { inner_id_in_array.emplace_back(inner_id[numberofInner[h]]); // A inner_id_in_array.emplace_back(inner_id[index_array_2]); // B inner_id_in_array.emplace_back(inner_wrongConfirmed_id_2[h]); inner_temp[index] = inner_wrongConfirmed_id_2[h]; inner_id[inner_pointer++] = inner_wrongConfirmed_id_2[h]; array_temp[index] = virtualID; inner_temp[indexes[0]] = inner_id_in_array[0]; // first point inner_temp[indexes[1]] = inner_id_in_array[1]; // second point } else continue; bool angleMatched = AngleMatching(arrayPoints, inner_id_in_array, pointsSize, virtualID); if (!angleMatched) { // resume inner_temp[indexes[1]] = -1; inner_temp[indexes[0]] = -1; inner_temp[index] = -1; inner_id[--inner_pointer] = -1; array_temp[index] = -1; inner_id_in_array.pop_back(); inner_id_in_array.pop_back(); inner_id_in_array.pop_back(); // arrayPoints.pop_back(); // indexes.pop_back(); continue; } if (BackTrackForArray(i + 1, inner_id, array_temp, inner_temp, distancesOfAllPoints, pts3d_, arrayPoints, inner_pointer, inner_id_in_array, indexes)) { return true; } // resume inner_temp[indexes[1]] = -1; inner_temp[indexes[0]] = -1; inner_temp[index] = -1; inner_id[--inner_pointer] = -1; array_temp[index] = -1; inner_id_in_array.pop_back(); inner_id_in_array.pop_back(); inner_id_in_array.pop_back(); } arrayPoints.pop_back(); indexes.pop_back(); } else if (inner_pointer >= 3) { // if(inner_temp[indexes[0]] == -1){ // return false; // } for (int j2 = 0; j2 < pointsSize; j2++) { bool haveSameInnerId = false; for (int ind = 0; ind < inner_pointer; ind++) { if (inner_id_in_array[ind] == j2) { haveSameInnerId = true; break; } } if (haveSameInnerId) // continue; double diff = fabs(m_AllRefDistances[virtualID][inner_temp[indexes[0]]][j2] - distance); if (diff < m_OTSParam.fMatchingDistanceThreshold) { //< third point // set inner_id[inner_pointer++] = j2; //<inner_pointer = 4 inner_temp[index] = j2; array_temp[index] = virtualID; inner_id_in_array.emplace_back(j2); // D break; } } if (inner_pointer < arrayPoints.size()) { // this is no any operation on inner_id, inner_temp,inner_id_in_array arrayPoints.pop_back(); indexes.pop_back(); continue; } // cross validation bool matched = true; for (int j = 1; j < inner_pointer - 1; j++) { Point3D p2 = arrayPoints[j]; double distance_p1p2 = 0.0; if (fabs(distancesOfAllPoints[indexes[j]][index]) < 1e-5) { distance_p1p2 = (p2 - p1).Norm2(); distancesOfAllPoints[indexes[j]][index] = distance_p1p2; } else distance_p1p2 = distancesOfAllPoints[indexes[j]][index]; double diff = fabs(m_AllRefDistances[virtualID][inner_temp[indexes[j]]][inner_temp[index]] - distance_p1p2); if (diff > m_OTSParam.fMatchingDistanceThreshold) { matched = false; break; } } // resume if (!matched) { //< recover the data inner_pointer--; // inner_pointer = 3 /* As for disambiguity and array matching, there is no need to match every edges and angles. */ inner_id[inner_pointer] = -1; inner_temp[index] = -1; array_temp[index] = -1; inner_id_in_array.pop_back(); // D arrayPoints.pop_back(); indexes.pop_back(); continue; } if (BackTrackForArray(i + 1, inner_id, array_temp, inner_temp, distancesOfAllPoints, pts3d_, arrayPoints, inner_pointer, inner_id_in_array, indexes)) { return true; } // resume inner_pointer--; inner_id[inner_pointer] = -1; inner_temp[index] = -1; array_temp[index] = -1; inner_id_in_array.pop_back(); arrayPoints.pop_back(); indexes.pop_back(); } } if (arrayPoints.size() >= 3 && !realArrayID.empty()) { if (inner_pointer >= m_mapToolSetting.at(realArrayID).MinFaceMarkerNum) return true; } return false; }
最新发布
11-14
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
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