2020/12/18第三次上机

博客记录了构造函数和拷贝构造函数的多次调用情况,如多次出现“Constructor called”和“Copy constructor called”,随后记录了多次析构函数调用,出现多个“Destructor”。

T1

#include<iostream>
using namespace std;
class Fraction {   //数据成员,访问控制属性默认是私有
    int m_numerator = 0; //  分子默认为0;  C++11
    int m_denominator = 1; //分母默认为1;
public://公有成员函数
    Fraction(int above = 0, int below = 1) : m_numerator(above), m_denominator(below) {
        cout << "Constructor called" << endl;
    }
    Fraction(const Fraction& rhs) : m_numerator(rhs.m_numerator),      m_denominator(rhs.m_denominator) {
        cout << "Copy constructor called" << endl;
    }
    ~Fraction(){
        cout << "Dead" << endl;
    }
    void divide(){
        int m = gcd(m_numerator, m_denominator);
        m_numerator /= m;
        m_denominator /= m;
    };
    int getnumerator() const {
        return m_numerator;
    };
    int getdenominator() const{
        return m_denominator;
    };
    Fraction operator /(const Fraction&b){
        Fraction f(m_numerator*b.getdenominator(),m_denominator*b.getnumerator());
        f.divide();
        return f;
    }
   ostream& operator << (ostream& os,const Fraction &a){
    return os << a.m_numerator << " / " << a.m_denominator << endl;
}
private:
    int gcd(int a,int b){
        return b == 0?a:gcd(b,a%b);
    }
};

Fraction divide1(const Fraction& divident, const Fraction& divisor) {
        return Fraction(divident.getnumerator() * divisor.getdenominator(),     divident.getdenominator() * divisor.getnumerator());
}
Fraction divide2(Fraction divident, Fraction divisor) {
    Fraction result(divident.getnumerator() * divisor.getdenominator(),      divident.getdenominator() * divisor.getnumerator());
    return result;
}
Fraction makeCommon(const Fraction&a,const Fraction&b){
    Fraction f(a.getnumerator()*b.getdenominator() + a.getdenominator()*b.getnumerator(),a.getdenominator() * b.getdenominator());
    f.divide();
    return f;
}
int main(){
    Fraction f1(2,4);
    cout << f1;
    f1.divide();
    cout << f1;
    Fraction f2(4,5);
    Fraction f = makeCommon(f1, f2);
    cout << f;
    Fraction ff = f1 / f2;
    cout << ff;
    return 0;
}

在这里插入图片描述
Constructor called
Copy constructor called
Constructor called
Constructor called
Constructor called
Constructor called
Copy constructor called
Copy constructor called
Constructor called
Destructor
Destructor
Destructor
Destructor
Destructor
Destructor
Destructor
Destructor
Destructor

T2

#include<iostream>
#include<algorithm>
using namespace std;
int a[5] = { 19,67,24,11,17 }, b[5] = { 2,3,9,17,59 };
int find_k_byorder(int a[],int len,int k){
    for(int i = 0;i < len;++i){
        if(a[i] == k) return i;
    }
    return -1;
}
int binary_search_k(int a[],int len,int k){
    sort(a,a + len);
    int l = 0,r = len;
    while (l <= r) {
        int mid = (l + r) >> 1;
        if(a[mid] == k) return mid;
        else if(a[mid] > k) r = mid-1;
        else l = mid + 1;
    }
    return l;
}
int main(){
    cout << find_k_byorder(a,5,17) << endl;
    cout << find_k_byorder(b,5,17) << endl;
    cout << binary_search_k(a,5,17) << endl;
    cout << binary_search_k(b,5,17) << endl;
    return 0;
}

#include <cmath>
#include <vector>
#include <iostream>
using namespace std;
int a[5] = { 19,67,24,11,17 }, b[5] = { 2,3,9,17,59 };
void select_sort(vector<int>& t)
{
    int len = t.size();
    for (int i = 0;i < len;++i)
    {
        int k = t[i], p = i;
        for (int j = i;j < len;++j)
        {
            if (t[j] < k)
            {
                k = t[j];
                p = j;
            }
        }
        swap(t[i], t[p]);
    }
}
bool isPrime(int k) {
    if (k == 2) return true;
    if ((k & 1) == 0) return false;
    for (int i = 2;i <= sqrt(k);++i) {
        if (k % i == 0) return false;
    }
    return true;
}
int main() {
    vector<int> t;
    for (int i = 0;i < 5;++i) {
        if (isPrime(a[i])) t.push_back(a[i]);
    }
    for (int i = 0;i < 5;++i) {
        if (isPrime(b[i]) && b[i] != 17) t.push_back(b[i]);
    }
    select_sort(t);
    cout << "Increase:";
    for (vector<int>::iterator it = t.begin();it != t.end();++it) {
        cout << *it << " ";
    }
    cout << endl;
    return 0;
}

T3

#include<cmath>
#include<iostream>
using namespace std;
const double PI = 3.1415926;
class Circle;
class Point {
    double m_x = 0, m_y = 0;
    friend class Circle;
    friend double dist(const Point&,const Point&);
public:
    Point(double x=0, double y=0) : m_x(x), m_y(y) {
        cout << "Constructor of Point" << endl;
    }
    Point(const Point &p) :m_x(p.m_x), m_y(p.m_y) {
        cout << "Copy constructor of Point" << endl;
    }
    ~Point() {
        cout << "Destructor of Point" << endl;
    }
    double getMX(){
        return m_x;
    }
    double getMY(){
        return m_y;
    }
};
class Circle {
    Point m_center;
    double m_radius = 1.0;
public:
    Circle(double r=1, const Point &p=Point()) :m_center(p), m_radius(r) {                 cout << "Constructor of Circle" << endl;
    }
    ~Circle() {
        cout << "Destructor of Circle" << endl;
    }
    double getX(){
        return m_center.getMX();
    }
    double getY(){
        return m_center.getMY();
    }
    double area(){
        return PI*m_radius*m_radius;
    }
    double circumference(){
        return 2*PI*m_radius;
    }
};
double dist(const Point&a,const Point&b){
    return sqrt((a.m_x - b.m_x)*(a.m_x - b.m_x) + (a.m_y - b.m_y)*(a.m_y - b.m_y));
}
int main() {
    Circle a(2, Point(1, 3));
    cout << "(" << a.getX() << "," << a.getY() << ")" << endl;
    Point c(1,2);
    Point b(3,5);
    cout << dist(c, b) << endl;
    
    cout << a.area() << " " << a.circumference() <<endl;
    cout << "end" << endl;
    return 0;
}

根据原作 https://pan.quark.cn/s/459657bcfd45 的源码改编 Classic-ML-Methods-Algo 引言 建立这个项目,是为了梳理和总结传统机器学习(Machine Learning)方法(methods)或者算法(algo),和各位同仁相互学习交流. 现在的深度学习本质上来自于传统的神经网络模型,很大程度上是传统机器学习的延续,同时也在不少时候需要结合传统方法来实现. 任何机器学习方法基本的流程结构都是通用的;使用的评价方法也基本通用;使用的一些数学知识也是通用的. 本文在梳理传统机器学习方法算法的同时也会顺便补充这些流程,数学上的知识以供参考. 机器学习 机器学习是人工智能(Artificial Intelligence)的一个分支,也是实现人工智能最重要的手段.区别于传统的基于规则(rule-based)的算法,机器学习可以从数据中获取知识,从而实现规定的任务[Ian Goodfellow and Yoshua Bengio and Aaron Courville的Deep Learning].这些知识可以分为四种: 总结(summarization) 预测(prediction) 估计(estimation) 假想验证(hypothesis testing) 机器学习主要关心的是预测[Varian在Big Data : New Tricks for Econometrics],预测的可以是连续性的输出变量,分类,聚类或者物品之间的有趣关联. 机器学习分类 根据数据配置(setting,是否有标签,可以是连续的也可以是离散的)和任务目标,我们可以将机器学习方法分为四种: 无监督(unsupervised) 训练数据没有给定...
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