#include<iostream> using namespace std; class Something { public: int j; Something():j(20) {cout<<"Something initialized. j="<<j<<endl;} }; class Base { private: Base(const Base&) {} public: Base() {} virtual Base *clone() { return new Base(*this); } virtual void ID() { cout<<"BASE"<<endl; } }; class Derived : public Base { pri
#include<iostream> using namespace std; class Something { public: int j; Something():j(20) {cout<<"Something initialized. j="<<j<<endl;} }; class Base { private: Base(const Base&) {} public: Base() {} virtual Base *clone() { return new Base(*this); } virtual void ID() { cout<<"BASE"<<endl; } }; class Derived : public Base { pri
Just a simple quick question which I couldn't find a solid answer to anywhere else. Is the default operator= just a shallow copy of all the class' members on the right hand side? Class foo { public: int a, b, c; }; foo f1, f2; ... f1 = f2; would be identical to: f1.a = f2.a; f1.b = f2.b; f1.c = f2.c; This seems to be true when I test it but I need to be sure I'm not missing so
只是一个简单的快速问题，我无法在其他任何地方找到可靠的答案。 默认的操作员=只是右边所有班级成员的浅表副本？ Class foo { public: int a, b, c; }; foo f1, f2; ... f1 = f2; 将与以下内容相同： f1.a = f2.a; f1.b = f2.b; f1.c = f2.c; 这在我测试时似乎是真实的，但我需要确保我不会错过某些特定情况。 我会说，默认operator=是一个副本。 它复制每个成员。 除非被复制的成员是某种间接方式（如指针），否
Possible Duplicate: What is the difference between a deep copy and a shallow copy? What is the difference between deep and shallow copy. What type of a copy does a copy constructor do? Shallow copy: Some members of the copy may reference the same objects as the original: class X { private: int i; int *pi; public: X() : pi(new int) { } X(const X& copy) /
可能重复： 深拷贝和浅拷贝之间有什么区别？ 深浅拷贝有什么区别？ 拷贝构造函数做什么类型的拷贝？ 浅拷贝： 该副本的某些成员可能会引用与原始相同的对象： class X { private: int i; int *pi; public: X() : pi(new int) { } X(const X& copy) // <-- copy ctor : i(copy.i), pi(copy.pi) { } }; 这里，原始和复制的X对象的pi成员都将指向相同的int 。 深层
Is the following code valid C++, according to the standard (discounting the ...s)? bool f(T& r) { if(...) { r = ...; return true; } return false; } T x = (f(x) ? x : T()); It is known to compile in the GCC versions this project uses (4.1.2 and 3.2.3... don't even get me started...), but should it? Edit : I added some details, for example as to how f()
根据标准，以下代码是否为有效的C ++（折扣... s）？ bool f(T& r) { if(...) { r = ...; return true; } return false; } T x = (f(x) ? x : T()); 已知在GCC版本中编译该项目使用（4.1.2和3.2.3 ...甚至不让我开始......），但是它应该如何？ 编辑 ：我添加了一些细节，例如f（）在原始代码中的概念外观。 基本上，它意味着在某些条件下初始化x。 但是，如果你尝试这样做，它的语
I am using GEOS's C API to manage geometry in a parallel simulator: I need to ensure that the objects stay inside a constrained area. To that end when my object makes a step, I check whether the line between its previous and current position intersects the border of the environment ( environment_manager_->get_border() , which returns a const GEOSPreparedGeometry* ). The code is running
我使用GEOS的C API在并行模拟器中管理几何：我需要确保对象保留在受限区域内。 为此，当我的对象做出一个步骤时，我检查它之前和当前位置之间的line是否与环境边界相交（ environment_manager_->get_border() ，它返回一个const GEOSPreparedGeometry* ）。 代码与多个OpenMP线程并行运行。 在开始模拟之前，我初始化了GEOS initGEOS_r(notice, log_and_exit); context_handler_ = GEOS_init_r(); 所以我只有一个处理程
I have a long-running simulation program and I plan to use OpenMP for paralleling some codes for speedup. I'm new to OpenMP and have the following question. Given that the simulation is a stochastic one, I have following data structure and I need to capture age-specific count of seeded agents [Edited: some code edited]: class CAgent { int ageGroup; bool isSeed; /* some other s
我有一个长期运行的模拟程序，我打算使用OpenMP来并行加速一些代码。 我是OpenMP的新手，并有以下问题。 鉴于模拟是随机模拟，我有以下数据结构，我需要捕获种子代理的年龄特定计数[编辑：编辑了一些代码]： class CAgent { int ageGroup; bool isSeed; /* some other stuff */ }; class Simulator { std::vector<int> seed_by_age; std::vector<CAgent> agents; void initEnv(); /
I have written a code related to quick sort with OpenMP as follows: #include <iostream> #include <ctime> #include <algorithm> #include <functional> #include <cmath> using namespace std; #include <omp.h> void ParallelQuickSort(int *begin, int *end) { if (begin+1 < end) { --end; int *middle = partition(begin, end, bind2nd(less<int
我写了一个与OpenMP快速排序相关的代码，如下所示： #include <iostream> #include <ctime> #include <algorithm> #include <functional> #include <cmath> using namespace std; #include <omp.h> void ParallelQuickSort(int *begin, int *end) { if (begin+1 < end) { --end; int *middle = partition(begin, end, bind2nd(less<int>(), *end));
I have one working solution for parallelization . However, execution time is very very slightly improved by parallelization. I thinks it comes from the fact I new and delete some variable in the loop. I would like it to be stack created, BUT Command class is abstract, and must remain abstract. What can I do to work around that? How to improve time spent on these very long loops??? #pragma o
我有一个并行化的工作解决方案。 但是，执行时间通过并行化得到很小的改进。 我认为它来自我新的事实，并删除循环中的一些变量。 我希望它是堆栈创建的，但是Command类是抽象的，并且必须保持抽象。 我能做些什么来解决这个问题？ 如何改善花在这些非常长的循环上的时间？ #pragma omp parallel for reduction(+:functionEvaluation) for (int i=rowStart;i<rowEnd+1;i++) { Model model_(varModel_); model_.a
i'm currently using binary files for quick access to custom objects stored in multidimensional arrays which are saved to file as object arrays. so far, reading from file hasn't been too much of a problem since i've been reading the array into an identical object array on the stack. it looks something like this: Foo foo[5][10]; ifstream infile("foofile.dat",ios::in|ios::binary); inf
我目前使用二进制文件快速访问存储在多维数组中的自定义对象，这些自定义对象被保存为文件作为对象数组。 到目前为止，从文件读取没有太多的问题，因为我已经将数组读入堆栈中的相同对象数组。 它看起来像这样： Foo foo[5][10]; ifstream infile("foofile.dat",ios::in|ios::binary); infile.read((char*)&foo, sizeof Foo); 我目前遇到的问题是，我越来越多地存储大量的数据，并且在创建本地对象数组时溢出了我的堆栈
I have few functions that should be applied to matrix of some structures serially. For single thread I use the following code: for(int t = 0; t < maxT; ++t) { for(int i = 0; i < maxI; ++i) for(int j = 0; j < maxJ; ++j) function1(i, j); for(int i = 0; i < maxI; ++i) for(int j = 0; j < maxJ; ++j) function2(i, j); } Now I'm tryin
我有几个函数应该适用于一些结构的矩阵串行。 对于单线程，我使用下面的代码： for(int t = 0; t < maxT; ++t) { for(int i = 0; i < maxI; ++i) for(int j = 0; j < maxJ; ++j) function1(i, j); for(int i = 0; i < maxI; ++i) for(int j = 0; j < maxJ; ++j) function2(i, j); } 现在我正在尝试并行化该代码： #pragma omp parallel { for(int t = 0