Move semantics performance test - c++

I wrote this code to test the performance of move constructor, comparing to STL vector. Created 2 classes LargeType uses the vector container from the Standard Template Library (STL). On the other hand, LargeTypeRaw uses a raw pointer.
At the end created two vectors of LargeType and LargeTypeRaw with random numbers Calls a custom insertSort function to sort the two vectors Measures the time it takes to sort the two vectors and prints the results. Results for 10.000 vectorsize are like:
Sorting LargeType Result: 2.52 sec --- Sorting LargeTypeRaw Result: 0.28 sec
My question : Is the difference between 2 tests are extremely high? and what might be the reason regarding the complete code below? Could you please help me figure out?
t#include <iostream>
#include <vector>
#include <ctime>
using namespace std;
template <typename T>
class LargeType {
public:
explicit LargeType(int initialSize = 10)
: data(initialSize) {}
int getSize() const {
return data.size();
}
// Operator '<' LargeType
bool operator<(const LargeType& rhs) {
return data.size() < rhs.data.size();
}
private:
vector<T> data;
};
// Assignment Part 2 -3
template <typename T>
class LargeTypeRaw {
public:
explicit LargeTypeRaw(int size = 10)
:sizeRaw {size}, dataRaw {new T[sizeRaw] }
{}
// LargeTypeRaw Copy constructor
LargeTypeRaw(const LargeTypeRaw <T>& rhs)
//: sizeRaw {rhs.sizeRaw}, dataRaw {new T[sizeRaw] }
{
sizeRaw = rhs.sizeRaw;
dataRaw = new T[sizeRaw];
copy(rhs.dataRaw, rhs.dataRaw + sizeRaw, dataRaw);
//copy(rhs.dataRaw, rhs.dataRaw + sizeRaw,dataRaw);
}
// LargeTypeRaw Move constructor
LargeTypeRaw(LargeTypeRaw&& rhs) noexcept
: sizeRaw{rhs.sizeRaw} , dataRaw {rhs.dataRaw}
{
rhs.dataRaw = nullptr;
}
// LargeTypeRaw Copy assignment operator '= '
LargeTypeRaw& operator=(const LargeTypeRaw& rhs) {
if (this != &rhs) {
delete[] dataRaw;
sizeRaw = rhs.sizeRaw;
dataRaw= new T [sizeRaw];
copy(rhs.dataRaw, rhs.dataRaw+sizeRaw, dataRaw);
}
return *this;
// LargeTypeRaw Smaller than operator ' <'
}
bool operator<(LargeTypeRaw & rhs) {
return this->sizeRaw < rhs.getSize();
}
// LargeTypeRaw Move assignment operator
LargeTypeRaw& operator=(LargeTypeRaw && rhs) noexcept {
if (this != &rhs) {
delete[] dataRaw;
sizeRaw= rhs.sizeRaw;
dataRaw = rhs.dataRaw;
rhs.dataRaw = nullptr;
}
return *this;
}
// LargeTypeRaw Destructor
~LargeTypeRaw() {
delete[] dataRaw;
}
int getSize() const
{
return sizeRaw;
}
private:
int* dataRaw;
int sizeRaw;
};
//Insertion sort algorithm with vector
template <typename T>
void insertSort(vector<T> & arr) {
for (int i = 1; i < arr.size(); i++) {
auto key = move(arr[i]);
int j = i - 1;
while (j > -1 && key < arr[j]) {
arr[j + 1] = move(arr[j]);
j--;
}
arr[j + 1] = move(key);
}
}
int main() {
srand (time(NULL));
// Assignment Part 4- Testing and comparing the Copy and Move Constructor performances
int vecSize = 10000;
// Filling the vector arrays with random numbers 1-100
vector<LargeType<int>> vecLarge (vecSize);
vector<LargeTypeRaw <int>> vecRaw (vecSize);
for (int i = 0; i < vecSize; i++) {
int randNum =rand() % 100;
vecLarge[i]= LargeType<int> {randNum};
vecRaw[i] = LargeTypeRaw<int> {randNum};
}
// Setting the start time
clock_t start1 = clock();
//Calling the sorting function and printing out the elapsed execution time
insertSort(vecLarge);
cout << "Sorting LargeType Result: " << (clock() - start1) / (double)(CLOCKS_PER_SEC ) << endl;
clock_t start2 = clock(); // Reset the start time for the second sort function call
insertSort(vecRaw);
cout << "Sorting LargeTypeRaw Result: " << (clock() - start2) / (double)(CLOCKS_PER_SEC ) << endl;
the expected result: largetype vector result should be faster than typeraw vector and the anticipated gap might be less?

Related

why is my rudimentary implementation of Vector faster than the stl version for push_back?

I have implemented a rudimentary vector using the code from the Weiss C++ textbook on data structures (see below). when i time it with 100,000 push_backs it takes 0.001 seconds.
when i do the exact same experiment using the stl::vector, it takes 0.008 seconds (roughly 8x slower). does anyone know why this is? thanks
#include <iostream>
#include <algorithm>
#include <ctime>
#include <vector>
template<typename Object>
class Vector {
public:
// normal constructor
explicit Vector(int initialSize = 0) :
theSize{ initialSize }, theCapacity{ initialSize + SPARE_CAPACITY },
objects{ new Object[theCapacity] }
{}
// copy constructor
Vector(const Vector& rhs) :
theSize{ rhs.theSize }, theCapacity{ rhs.theCapacity }, objects{ nullptr }
{
objects = new Object[theCapacity];
for (int k = 0; k < theSize; ++k)
objects[k] = rhs.objects[k];
}
// copy assignment operator
Vector& operator=(const Vector& rhs)
{
Vector copy = rhs;
std::swap(*this, copy);
return *this;
}
// destructor
~Vector()
{
delete[] objects;
}
// move constructor
Vector(Vector&& rhs) :
theSize{ rhs.theSize }, theCapacity{ rhs.theCapacity }, objects{ rhs.objects }
{
rhs.objects = nullptr;
rhs.theSize = 0;
rhs.theCapacity = 0;
}
// move assignment operator
Vector& operator=(Vector&& rhs)
{
std::swap(theSize, rhs.theSize);
std::swap(theCapacity, rhs.theCapacity);
std::swap(objects, rhs.objects);
return *this;
}
void resize(int newSize)
{
if (newSize > theCapacity)
reserve(newSize * 2); // talk about amortized time (python book)
theSize = newSize;
}
void reserve(int newCapacity)
{
if (newCapacity < theSize)
return;
Object* newArray = new Object[newCapacity];
for (int k = 0; k < theSize; ++k)
newArray[k] = std::move(objects[k]);
theCapacity = newCapacity;
std::swap(objects, newArray);
delete[] newArray;
}
Object& operator[](int index)
{
return objects[index];
}
const Object& operator[](int index)const
{
return objects[index];
}
bool empty() const
{
return size() == 0;
}
int size() const
{
return theSize;
}
int capacity() const
{
return theCapacity;
}
void push_back(const Object& x)
{
if (theSize == theCapacity)
reserve(2 * theCapacity + 1);
objects[theSize++] = x;
}
void push_back(Object&& x)
{
if (theSize == theCapacity)
reserve(2 * theCapacity + 1);
objects[theSize++] = std::move(x);
}
void pop_back()
{
--theSize;
}
const Object& back() const
{
return objects[theSize - 1];
}
// iterator
typedef Object* iterator;
typedef const Object* const_iterator;
iterator begin()
{
return &objects[0];
}
const_iterator begin() const
{
return &objects[0];
}
iterator end()
{
return &objects[size()];
}
const_iterator end() const
{
return &objects[size()];
}
static const int SPARE_CAPACITY = 16;
private:
int theSize;
int theCapacity;
Object* objects;
};
int main()
{
std::clock_t start;
start = std::clock();
std::vector<int> vec2{ 0 };
for (int i = 0; i < 100000; i++)
vec2.push_back(i);
double duration = (std::clock() - start) / (double)CLOCKS_PER_SEC;
std::cout << "printf: " << duration << '\n';
start = std::clock();
Vector<int> vec{ 0 };
for (int i = 0; i < 100000; i++)
vec.push_back(i);
duration = (std::clock() - start) / (double)CLOCKS_PER_SEC;
std::cout << "printf: " << duration << '\n';
}
You compiled it in debug.
In debug, visual studio instruments std::vector with a bunch of debugging aids. It will detect in some cases if you try to use invalidated iterators, for example.
In general, doing performance testing in debug is useless. The only reason you should do it is if you are having problems where your debug build it too slow for development purposes.
Real use of your application should be done in release mode, which does optimization, and also removes extra "double check" work to help find bugs.
Your vector is indeed different, but that difference isn't that important at all.
Your vector implementation and std::vector are fundamentally different.
Your vector default-constructs all values in the vector, up to reserve capacity, and push_back() merely replaces the next reserved value with the new value, using the assignment operator.
std::vector is fundamentally different,, and does not default-construct "non-existent" values in the vector, but constructs them "for real-sies". std::vector::push_back constructs the new value in the vector, your push_back assigns it.
Depending on the object in the container, its assignment operator and its constructor may have completely different logic, and comparative benchmarks are meaningless.

How to create a large number of combinations lazily in C++

I want to create a combination of K elements one each from K sets. Each set can have n elements in it.
set1 = {a1, a2, a3}
set2 = {b1, b2, b3 , b4}
set3 = {c1, c2}
Required Combinations = {{a1,b1,c1}, {a1,b2,c1} ... {a3,b4,c2}}
Number of combinations = 3*4*2 =24
So if K is large and n is large we run into Out of Memory very quickly. Refer to the below code snippet how we are creating combinations today. If we create all the combinations in a case where K is relatively large, we go out of memory! So for instance, if K=20 and each set has 5 elements, the combinations are 5^20, which is extremely large in memory. So I want an alternative algorithm where I don't need to store all those combinations in memory all at a time before I start consuming the combinations.
vector<vector<string>> setsToCombine;
vector<vector<string>> allCombinations;
vector<vector<string>> *current =
new vector<vector<string>>{vector<string>()};
vector<vector<string>> *next = new vector<vector<string>>();
vector<vector<string>> *temp;
for (const auto& oneSet : setsToCombine) {
for (auto& cur : *current) {
for (auto& oneEle : oneSet) {
cur.push_back(oneEle);
next->push_back(cur);
cur.pop_back();
}
}
temp = current;
current = next;
next = temp;
next->clear();
}
for (const auto& cur : *current) {
allCombinations.push_back(cur);
}
current->clear();
next->clear();
delete current;
delete next;
You can store the indexes and lazely iterate over the combinations
#include <cstdint>
#include <iostream>
#include <vector>
using v_size_type = std::vector<int>::size_type;
using vv_size_type = std::vector<v_size_type>::size_type;
bool increment(std::vector<v_size_type> &counters, std::vector<v_size_type> &ranges) {
for (auto idx = counters.size(); idx > 0; --idx) {
++counters[idx - 1];
if (counters[idx - 1] == ranges[idx - 1]) counters[idx - 1] = 0;
else return true;
}
return false;
}
std::vector<int> get(const std::vector<std::vector<int>> &sets, const std::vector<v_size_type> &counters) {
std::vector<int> result(sets.size());
for (vv_size_type idx = 0; idx < counters.size(); ++idx) {
result[idx] = sets[idx][counters[idx]];
}
return result;
}
void print(const std::vector<int> &result) {
for (const auto el : result) {
std::cout << el << ' ';
}
}
int main() {
const std::vector<std::vector<int>> sets = {{-5, 2}, {-100, -21, 0, 15, 32}, {1, 2, 3}};
std::vector<v_size_type> ranges(sets.size());
for (vv_size_type idx = 0; idx < sets.size(); ++idx) {
ranges[idx] = sets[idx].size();
}
std::vector<v_size_type> counters(sets.size());
while (true) {
print(get(sets, counters));
std::cout << '\n';
if (!increment(counters, ranges)) break;
}
}
Godbolt
You can also use the odometer approach.
First, let us look again, what an odometer is. It looks like this:
There are several disks, with values printed on it. And if the odometer runs forward, it will show the Cartesian product of all values on the disks.
That is somehow clear, but how to use this principle? The solution is, that each set of values will be a disk, and the values of the set, will be put on the corresponding disk. With that, we will have an odometer, where the number of values on each disk is different. But this does not matter.
Also here, if a disks overflows, the next disk is incremented. Same principle like a standard odometer. Just with maybe more or less values.
And, you can put everything on a disk, not just integers. This approach will work always.
We can abstract a disk as a std::vector of your desired type. And the odometer is a std::vector of disks.
All this we can design in a class. And if we add iterator functionality to the class, we can easily handle it.
In the example below, I show only a minimum set of functions. You can add as many useful functions to this class as you like and tailor it to your needs.
The object oriented approach is often better to understand in the end.
Please check:
#include <iostream>
#include <fstream>
#include <string>
#include <vector>
#include <initializer_list>
#include <algorithm>
#include <iterator>
using MyType = int;
using Disk = std::vector<MyType>;
using Disks = std::vector<Disk>;
// Abstraction for a very simple odometer
class Odometer {
Disks disks{};
public:
// We will do nearly everything with the iterator of the odometer class
struct iterator {
// Definitions for iterator ----------------
using iterator_category = std::forward_iterator_tag;
using difference_type = std::ptrdiff_t;
using value_type = std::vector<MyType>;
using pointer = std::vector<MyType>*;
using reference = std::vector<MyType>&;
const Disks& d; // Reference to disks from super class
int overflow{}; // Indicates an overflow of all disks
std::vector<std::size_t>positions{}; // Stores position of any disks
// Iterator constructor
iterator(const Disks& dd, const int over = 0) : d(dd), overflow(over) {
positions = std::vector<std::size_t>(dd.size(), 0);
}
// Dereference iterator
value_type operator*() const {
std::vector<MyType> result(d.size());
for (std::size_t i{}; i < d.size(); ++i) result[i] = d[i][positions[i]];
return result;
};
// Comparison
bool operator != (const iterator& other) { return positions != other.positions or overflow != other.overflow; }
// And increment the iterator
iterator operator++() {
int carry = 0; std::size_t i{};
for (i=0; i < d.size(); ++i) {
if (positions[i] >= d[i].size() - 1) {
positions[i] = 0;
carry = 1;
}
else {
++positions[i];
carry = 0;
break;
}
}
overflow = (i == d.size() and carry) ? 1 : 0;
return *this;
}
};
// Begin and End functions. End is true, if there is a flip over of all disks
iterator begin() const { return iterator(disks); }
iterator end() const { return iterator(disks, 1); }
// Constructors
Odometer() {}; // Default (useless for this example)
// Construct from 2d initializer list
Odometer(const std::initializer_list<const std::initializer_list<MyType>> iil) {
for (const std::initializer_list<MyType>& il : iil) {
disks.push_back(il);
}
}
// Variadic. Parameter pack and fold expression
template <typename ... Args>
Odometer(Args&&... args) {
(disks.push_back(std::forward<Args>(args)), ...);
}
// Simple output of everything
friend std::ostream& operator << (std::ostream& os, const Odometer& o) {
for (const auto vi : o) {
for (const MyType i : vi) os << i << ' ';
os << '\n';
}
return os;
}
};
// Some test
int main() {
// Define Odometer. Initialiaze wit normal initializer list
Odometer odo1{ {1,2},{3},{4,5,6} };
// Show complete output
std::cout << odo1 << "\n\n\n";
// Create additional 3 vectors for building a new cartesian product
std::vector<MyType> v1{ 1,2 };
std::vector<MyType> v2{ 3,4 };
std::vector<MyType> v3{ 5,6 };
// Define next Odometer and initialize with variadic constructor
Odometer odo2(v1, v2, v3);
// Use range based for loop for output
for (const std::vector<MyType>& vm : odo2) {
for (const MyType i : vm) std::cout << i << ' ';
std::cout << '\n';
}
}

C++: Disassemble a flat vector into multiple vectors of equal size without copying

Is it possible in C++ to split a flat vector (or C style array) into multiple vectors of equal size without copying any of its containing data? That is, disassembling the original vector by moving its content to a new vector, which invalidates the original vector. The following code example should illustrate this:
#include <cassert>
#include <vector>
void f(int* v) {
for (int i = 0; i < 100; i++) {
v[i] = i;
}
}
/**
* Split v into n vectors of equal size without copy its data (assert v.size() % n == 0)
*/
std::vector<std::vector<int>> g(std::vector<int> v, int n) {
std::vector<std::vector<int>> vs(n);
int vec_size = v.size() / n;
for (int i = 0; i < n; i++) {
vs[i].assign(v.begin() + i * vec_size, v.begin() + (i + 1) * vec_size); // copies?
// how to let vs[i] point to v.begin() + i * vec_size?
}
return vs;
}
int main() {
std::vector<int> v(100);
f(v.data());
std::vector<std::vector<int>> vs = g(std::move(v), 10);
for (int i = 0; i < 10; i++) {
for (int j = 0; j < 10; j++) {
assert(vs[i][j] == i * 10 + j);
}
}
return 0;
}
Yes, in my opinion this is possible. Moving the elements, but not copying the elements.
C++ offers std::make_move_iterator. Please read here about that.
To check that, I created a small class to output, to see, if we copy or move something.
So, if your data can "move", then it will work, otherwise of course a copy will be made. With the following we see the result.
struct Test {
int data{};
Test(int d) : data(d) { std::cout << "Construct and init\n"; }
Test() { std::cout << "Default construct\n"; };
~Test() { std::cout << "Destruct\n"; };
Test(const Test& other) { std::cout << "Construct\n"; data = other.data; }
Test(const Test&& other) noexcept { std::cout << "Move Construct\n"; data = other.data; }
Test& operator =(const Test& other) noexcept { std::cout << "Assign\n"; data = other.data; return *this; }
Test& operator =(const Test&& other) noexcept { std::cout << "Move Assign\n"; data = other.data; return *this; }
};
We will additionally add a small function, which calculates the offsets of the chunks that will be moved.
And then, we can come up with a small function to implement that.
#include <iostream>
#include <vector>
#include <numeric>
#include <iterator>
#include <iomanip>
// Calculate start and end index for all chunks
std::vector<std::pair<size_t, size_t>> calculatePairs(const size_t low, const size_t high, const size_t numberOfGroups) {
// Here we will store the resulting pairs with start and end values
std::vector<std::pair<size_t, size_t>> pairs{};
// Calculate chung size and remainder
const size_t delta = high - low;
const size_t chunk = delta / numberOfGroups;
size_t remainder = delta % numberOfGroups;
// Calculate the chunks start and end addresses for all chunks
size_t startIndex{}, endIndex{};
for (size_t i = 0; i < numberOfGroups; ++i) {
// Calculate end address and distribute remainder equally
endIndex = startIndex + chunk + (remainder ? 1 : 0);
// Store a new pair of start and end indices
pairs.emplace_back(startIndex, endIndex);
// Next start index
startIndex = endIndex;
// We now consumed 1 remainder
if (remainder) --remainder;
}
//--pairs.back().second;
return pairs;
}
struct Test {
int data{};
Test(int d) : data(d) { std::cout << "Construct and init\n"; }
Test() { std::cout << "Default construct\n"; };
~Test() { std::cout << "Destruct\n"; };
Test(const Test& other) { std::cout << "Construct\n"; data = other.data; }
Test(const Test&& other) noexcept { std::cout << "Move Construct\n"; data = other.data; }
Test& operator =(const Test& other) noexcept { std::cout << "Assign\n"; data = other.data; return *this; }
Test& operator =(const Test&& other) noexcept { std::cout << "Move Assign\n"; data = other.data; return *this; }
};
std::vector<std::vector<Test>> split(std::vector<Test>& v, unsigned int n) {
std::vector<std::vector<Test>> result{};
if (v.size() > n) {
result.resize(n);
std::vector<std::pair<size_t, size_t>> offset = calculatePairs(0u, v.size(), n);
for (size_t i{}; i < n; ++i) {
result[i].insert(result[i].end(), std::make_move_iterator(v.begin() + offset[i].first),
std::make_move_iterator(v.begin() + offset[i].second));
}
}
return result;
}
constexpr size_t NumberOfElements = 30u;
constexpr unsigned int NumberOfGroups = 3;
static_assert (NumberOfElements >= NumberOfGroups, "Number of elements must be greater/equal then number of elements\n");
int main() {
std::cout << "\n\n\nCreate vector with " << NumberOfElements << " elements\n\n";
std::vector<Test> v1(NumberOfElements);
std::cout << "\n\n\nFill vector with std::iota\n\n";
std::iota(v1.begin(), v1.end(), 1);
std::cout << "\n\n\nSplit in " << NumberOfGroups<< "\n\n";
std::vector<std::vector<Test>> s = split(v1, NumberOfGroups);
std::cout << "\n\n\nOutput\n\n";
for (const std::vector<Test>& vt : s) {
for (const Test& d : vt) std::cout << std::setw(3) << d.data << ' ';
std::cout << "\n\n";
}
}
But my strong guess is that you want to splice the data. The underlying elements fo the std::vector which you can get with the data() function.
You can access the data easily with pointer arithmetic on data().
But if you want to have the data in a new container, then this is difficult with a std::vector. It can for example be done with a std::list that has a splice function and does, what you want.
Or, you need to implement your own dynamic array and implement a splice function . . .
Checksum:
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Template function calling

#include <iostream>
#include <memory>
#include <initializer_list>
#include <cassert>
template <typename T>
class Vector
{
// Your implementation of the Vector class starts here
private:
//attributes
int length;
T* data;
public:
//constructors
Vector()
:length(0),
data(nullptr)
{
std::cout<<"New empty object created"<<std::endl;
}
Vector(int length)
:length(length),
data(new T[length])
{
std::cout<< "Length of object is = " <<length <<std::endl;
}
//use a copy of another Vector
Vector(const Vector& other)
: Vector(other.length)
{
for(int i=0;i<length;i++)
data[i]=other.data[i];
}
// using initializer list
Vector(std::initializer_list<T> list)
: Vector((int)list.size())
{
std::uninitialized_copy(list.begin(), list.end(), data);
std::cout<< "The elements in the object are: ";
for (auto it = std::begin(list); it!=std::end(list); ++it)
std::cout << ' ' << *it;
std::cout<<std::endl;
}
//operators
//copy
Vector<T>& operator=(const Vector<T>& other)
{
if(this!= &other)
{
std::cout<<"Copied constructor"<<std::endl;
delete[] data;
length = other.length;
std::cout<<"New length ="<<length<<std::endl;
data = new T[length];
std::cout<<"The elements in the object are: ";
for(int i=0;i<length;i++)
{
data[i]=other.data[i];
std::cout<<data[i]<<" ";
}
}
std::cout<<std::endl;
//std::cout << "copy operator" << std::endl;
return *this;
}
//move
Vector<T>& operator=(Vector<T>&& other)
{
if(this!= &other)
{
delete[] data;
length = other.length;
data = new T[length];
for(int i=0;i<length;i++){
data[i]=other.data[i];}
other.length = 0;
delete[] other.data;
other.data = nullptr;
}
//std::cout << "Move operator" << std::endl;
return *this;
}
///////////////////////////////////////////////
//add
Vector<T> operator+(const Vector<T>& other) const
{
assert(length == other.length);
Vector<T> newer(length);
std::cout<<"The addition gives: ";
for(auto i=0;i<length;i++)
{
newer.data[i] = data[i]+other.data[i];
std::cout<<newer.data[i]<<" ";
}
std::cout<<std::endl;
return newer;
}
//minus
Vector<T> operator-(const Vector<T>& other) const
{
assert(length == other.length);
Vector<T> newer(length);
for(auto i=0;i<length;i++)
newer.data[i] = data[i]-other.data[i];
return newer;
}
// Multiply by a scalar
Vector<T> operator*(T scalar)
{
Vector<T> newer(length);
std::cout<<"Multiplication of a new vector by scalar provides: ";
for (auto i=0; i<length; i++)
{
newer.data[i] = data[i] * scalar;
std::cout<<newer.data[i]<<" ";
}
std::cout<<std::endl;
return newer;
}
//////////////////////////////////////////
// Add to existing Vector
Vector<T>& operator+=(const Vector<T>& other)
{
for (auto i=0; i<length; i++)
data[i] += other.data[i];
return *this;
}
// Multiply existing Vector by a scalar
Vector<T>& operator*=(T scalar)
{
std::cout<<"Multiplication of an existing vector by scalar provides: ";
for (auto i=0; i<length; i++)
{
data[i] *= scalar;
std::cout<<data[i]<<" ";
}
std::cout<<std::endl;
return *this;
}
double Valueform(int i)
{
return data[i];
}
int Lengthfinder()
{
return length;
}
///////////////////////////////////////////
//destructor
~Vector()
{
delete[] data;
data = nullptr;
length = 0;
}
};
template<typename T>
T dot(const Vector<T>& lhs, const Vector<T>& rhs)
{
// Your implementation of the dot function starts here
T result = 0;
for (auto i=0; i<lhs.Lengthfinder(); i++)
{
result = lhs.Valueform(i)*rhs.Valueform(i);
//result + = multiply(lhs.data[i],rhs.data[i]);
// result += lhs.data[i]*rhs.data[i];
}
return result;
}
//failsafe for value multiplied by a vector
template <typename T, typename I>
Vector<T> operator*(I i,Vector<T> other)
{
std::cout<<"Multiplication was done by a vector and failsafe activated"<<std::endl;
return(other* T(i)) ;
}
int main()
{
Vector<double> a(5);
Vector<double> b({ 1 , 2 , 3 , 4 });
Vector<double> c({ 2 , 3 , 4 });
Vector<double> d({ 5 , 2 , 1 });
// std::cout<< "a=c" <<std::endl;
a = c;
// std::cout<< "e = c+d" <<std::endl;
Vector<double> e;
e = c+d;
// std::cout<< "f = c*5" <<std::endl;
Vector<double> f;
f = c*5;
// std::cout<< "g = 5*d" <<std::endl;
Vector<double> g;
g = 5*d;
Vector<double> Dott;
Dott = dot(c,d);
return 0;
}
The code does not allow me to call for the functions Valueform and Lengthfinder, anyone has a possible work around where I can get specific data values and length since the class variables are private? The functions are mostly worked around the template but I would like to just call 2 functions to get certain attributes and they are giving me errors that shouldn't exist, althought I'm not sure why exactly.
Your dot function is taking constant vectors:
template<typename T>
T dot(const Vector<T>& lhs, const Vector<T>& rhs)
{ // ^^^^^-----------------^^^^^----- these are const
// Your implementation of the dot function starts here
}
But, your member functions are not marked as const. You should declare them const to make these functions available:
double Valueform(int i) const
{
return data[i];
}
int Lengthfinder() const
{
return length;
}

Cartesian product from a vector in C++11? [duplicate]

I've a vector of vectors say vector<vector<int> > items of different sizes like as follows
1,2,3
4,5
6,7,8
I want to create combinations in terms of Cartesian product of these vectors like
1,4,6
1,4,7
1,4,8
and so on till
3,5,8
How can I do that ? I've looked up several links and I've also listed them at the end of this post but I'm not able to interpret that as I'm not that familiar with the language. Could some body help me with this.
#include <iostream>
#include <iomanip>
#include <vector>
using namespace std;
int main()
{
vector<vector<int> > items;
int k = 0;
for ( int i = 0; i < 5; i++ ) {
items.push_back ( vector<int>() );
for ( int j = 0; j < 5; j++ )
items[i].push_back ( k++ );
}
cartesian ( items ); // I want some function here to do this.
}
This program has equal length vectors and I put this so that it will be easier to understand my data structure. It will be very helpful even if somebody uses others answers from other links and integrate with this to get the result. Thank you very much
Couple of links I looked at
one
Two
Program from : program
First, I'll show you a recursive version.
// Cartesion product of vector of vectors
#include <vector>
#include <iostream>
#include <iterator>
// Types to hold vector-of-ints (Vi) and vector-of-vector-of-ints (Vvi)
typedef std::vector<int> Vi;
typedef std::vector<Vi> Vvi;
// Just for the sample -- populate the intput data set
Vvi build_input() {
Vvi vvi;
for(int i = 0; i < 3; i++) {
Vi vi;
for(int j = 0; j < 3; j++) {
vi.push_back(i*10+j);
}
vvi.push_back(vi);
}
return vvi;
}
// just for the sample -- print the data sets
std::ostream&
operator<<(std::ostream& os, const Vi& vi)
{
os << "(";
std::copy(vi.begin(), vi.end(), std::ostream_iterator<int>(os, ", "));
os << ")";
return os;
}
std::ostream&
operator<<(std::ostream& os, const Vvi& vvi)
{
os << "(\n";
for(Vvi::const_iterator it = vvi.begin();
it != vvi.end();
it++) {
os << " " << *it << "\n";
}
os << ")";
return os;
}
// recursive algorithm to to produce cart. prod.
// At any given moment, "me" points to some Vi in the middle of the
// input data set.
// for int i in *me:
// add i to current result
// recurse on next "me"
//
void cart_product(
Vvi& rvvi, // final result
Vi& rvi, // current result
Vvi::const_iterator me, // current input
Vvi::const_iterator end) // final input
{
if(me == end) {
// terminal condition of the recursion. We no longer have
// any input vectors to manipulate. Add the current result (rvi)
// to the total set of results (rvvvi).
rvvi.push_back(rvi);
return;
}
// need an easy name for my vector-of-ints
const Vi& mevi = *me;
for(Vi::const_iterator it = mevi.begin();
it != mevi.end();
it++) {
// final rvi will look like "a, b, c, ME, d, e, f"
// At the moment, rvi already has "a, b, c"
rvi.push_back(*it); // add ME
cart_product(rvvi, rvi, me+1, end); add "d, e, f"
rvi.pop_back(); // clean ME off for next round
}
}
// sample only, to drive the cart_product routine.
int main() {
Vvi input(build_input());
std::cout << input << "\n";
Vvi output;
Vi outputTemp;
cart_product(output, outputTemp, input.begin(), input.end());
std::cout << output << "\n";
}
Now, I'll show you the recursive iterative version that I shamelessly stole from #John :
The rest of the program is pretty much the same, only showing the cart_product function.
// Seems like you'd want a vector of iterators
// which iterate over your individual vector<int>s.
struct Digits {
Vi::const_iterator begin;
Vi::const_iterator end;
Vi::const_iterator me;
};
typedef std::vector<Digits> Vd;
void cart_product(
Vvi& out, // final result
Vvi& in) // final result
{
Vd vd;
// Start all of the iterators at the beginning.
for(Vvi::const_iterator it = in.begin();
it != in.end();
++it) {
Digits d = {(*it).begin(), (*it).end(), (*it).begin()};
vd.push_back(d);
}
while(1) {
// Construct your first product vector by pulling
// out the element of each vector via the iterator.
Vi result;
for(Vd::const_iterator it = vd.begin();
it != vd.end();
it++) {
result.push_back(*(it->me));
}
out.push_back(result);
// Increment the rightmost one, and repeat.
// When you reach the end, reset that one to the beginning and
// increment the next-to-last one. You can get the "next-to-last"
// iterator by pulling it out of the neighboring element in your
// vector of iterators.
for(Vd::iterator it = vd.begin(); ; ) {
// okay, I started at the left instead. sue me
++(it->me);
if(it->me == it->end) {
if(it+1 == vd.end()) {
// I'm the last digit, and I'm about to roll
return;
} else {
// cascade
it->me = it->begin;
++it;
}
} else {
// normal
break;
}
}
}
}
Here is a solution in C++11.
The indexing of the variable-sized arrays can be done eloquently with modular arithmetic.
The total number of lines in the output is the product of the sizes of the input vectors. That is:
N = v[0].size() * v[1].size() * v[2].size()
Therefore the main loop has n as the iteration variable, from 0 to N-1. In principle, each value of n encodes enough information to extract each of the indices of v for that iteration. This is done in a subloop using repeated modular arithmetic:
#include <cstdlib>
#include <iostream>
#include <numeric>
#include <vector>
using namespace std;
void cartesian( vector<vector<int> >& v ) {
auto product = []( long long a, vector<int>& b ) { return a*b.size(); };
const long long N = accumulate( v.begin(), v.end(), 1LL, product );
vector<int> u(v.size());
for( long long n=0 ; n<N ; ++n ) {
lldiv_t q { n, 0 };
for( long long i=v.size()-1 ; 0<=i ; --i ) {
q = div( q.quot, v[i].size() );
u[i] = v[i][q.rem];
}
// Do what you want here with u.
for( int x : u ) cout << x << ' ';
cout << '\n';
}
}
int main() {
vector<vector<int> > v { { 1, 2, 3 },
{ 4, 5 },
{ 6, 7, 8 } };
cartesian(v);
return 0;
}
Output:
1 4 6
1 4 7
1 4 8
...
3 5 8
Shorter code:
vector<vector<int>> cart_product (const vector<vector<int>>& v) {
vector<vector<int>> s = {{}};
for (const auto& u : v) {
vector<vector<int>> r;
for (const auto& x : s) {
for (const auto y : u) {
r.push_back(x);
r.back().push_back(y);
}
}
s = move(r);
}
return s;
}
Seems like you'd want a vector of iterators which iterate over your individual vector<int>s.
Start all of the iterators at the beginning. Construct your first product vector by pulling out the element of each vector via the iterator.
Increment the rightmost one, and repeat.
When you reach the end, reset that one to the beginning and increment the next-to-last one. You can get the "next-to-last" iterator by pulling it out of the neighboring element in your vector of iterators.
Continue cycling through until both the last and next-to-last iterators are at the end. Then, reset them both, increment the third-from-last iterator. In general, this can be cascaded.
It's like an odometer, but with each different digit being in a different base.
Here's my solution. Also iterative, but a little shorter than the above...
void xp(const vector<vector<int>*>& vecs, vector<vector<int>*> *result) {
vector<vector<int>*>* rslts;
for (int ii = 0; ii < vecs.size(); ++ii) {
const vector<int>& vec = *vecs[ii];
if (ii == 0) {
// vecs=[[1,2],...] ==> rslts=[[1],[2]]
rslts = new vector<vector<int>*>;
for (int jj = 0; jj < vec.size(); ++jj) {
vector<int>* v = new vector<int>;
v->push_back(vec[jj]);
rslts->push_back(v);
}
} else {
// vecs=[[1,2],[3,4],...] ==> rslts=[[1,3],[1,4],[2,3],[2,4]]
vector<vector<int>*>* tmp = new vector<vector<int>*>;
for (int jj = 0; jj < vec.size(); ++jj) { // vec[jj]=3 (first iter jj=0)
for (vector<vector<int>*>::const_iterator it = rslts->begin();
it != rslts->end(); ++it) {
vector<int>* v = new vector<int>(**it); // v=[1]
v->push_back(vec[jj]); // v=[1,3]
tmp->push_back(v); // tmp=[[1,3]]
}
}
for (int kk = 0; kk < rslts->size(); ++kk) {
delete (*rslts)[kk];
}
delete rslts;
rslts = tmp;
}
}
result->insert(result->end(), rslts->begin(), rslts->end());
delete rslts;
}
I derived it with some pain from a haskell version I wrote:
xp :: [[a]] -> [[a]]
xp [] = []
xp [l] = map (:[]) l
xp (h:t) = foldr (\x acc -> foldr (\l acc -> (x:l):acc) acc (xp t)) [] h
Since I needed the same functionality, I implemented an iterator which computes the Cartesian product on the fly, as needed, and iterates over it.
It can be used as follows.
#include <forward_list>
#include <iostream>
#include <vector>
#include "cartesian.hpp"
int main()
{
// Works with a vector of vectors
std::vector<std::vector<int>> test{{1,2,3}, {4,5,6}, {8,9}};
CartesianProduct<decltype(test)> cp(test);
for(auto const& val: cp) {
std::cout << val.at(0) << ", " << val.at(1) << ", " << val.at(2) << "\n";
}
// Also works with something much less, like a forward_list of forward_lists
std::forward_list<std::forward_list<std::string>> foo{{"boo", "far", "zab"}, {"zoo", "moo"}, {"yohoo", "bohoo", "whoot", "noo"}};
CartesianProduct<decltype(foo)> bar(foo);
for(auto const& val: bar) {
std::cout << val.at(0) << ", " << val.at(1) << ", " << val.at(2) << "\n";
}
}
The file cartesian.hpp looks like this.
#include <cassert>
#include <limits>
#include <stdexcept>
#include <vector>
#include <boost/iterator/iterator_facade.hpp>
//! Class iterating over the Cartesian product of a forward iterable container of forward iterable containers
template<typename T>
class CartesianProductIterator : public boost::iterator_facade<CartesianProductIterator<T>, std::vector<typename T::value_type::value_type> const, boost::forward_traversal_tag>
{
public:
//! Delete default constructor
CartesianProductIterator() = delete;
//! Constructor setting the underlying iterator and position
/*!
* \param[in] structure The underlying structure
* \param[in] pos The position the iterator should be initialized to. std::numeric_limits<std::size_t>::max()stands for the end, the position after the last element.
*/
explicit CartesianProductIterator(T const& structure, std::size_t pos);
private:
//! Give types more descriptive names
// \{
typedef T OuterContainer;
typedef typename T::value_type Container;
typedef typename T::value_type::value_type Content;
// \}
//! Grant access to boost::iterator_facade
friend class boost::iterator_core_access;
//! Increment iterator
void increment();
//! Check for equality
bool equal(CartesianProductIterator<T> const& other) const;
//! Dereference iterator
std::vector<Content> const& dereference() const;
//! The part we are iterating over
OuterContainer const& structure_;
//! The position in the Cartesian product
/*!
* For each element of structure_, give the position in it.
* The empty vector represents the end position.
* Note that this vector has a size equal to structure->size(), or is empty.
*/
std::vector<typename Container::const_iterator> position_;
//! The position just indexed by an integer
std::size_t absolutePosition_ = 0;
//! The begin iterators, saved for convenience and performance
std::vector<typename Container::const_iterator> cbegins_;
//! The end iterators, saved for convenience and performance
std::vector<typename Container::const_iterator> cends_;
//! Used for returning references
/*!
* We initialize with one empty element, so that we only need to add more elements in increment().
*/
mutable std::vector<std::vector<Content>> result_{std::vector<Content>()};
//! The size of the instance of OuterContainer
std::size_t size_ = 0;
};
template<typename T>
CartesianProductIterator<T>::CartesianProductIterator(OuterContainer const& structure, std::size_t pos) : structure_(structure)
{
for(auto & entry: structure_) {
cbegins_.push_back(entry.cbegin());
cends_.push_back(entry.cend());
++size_;
}
if(pos == std::numeric_limits<std::size_t>::max() || size_ == 0) {
absolutePosition_ = std::numeric_limits<std::size_t>::max();
return;
}
// Initialize with all cbegin() position
position_.reserve(size_);
for(std::size_t i = 0; i != size_; ++i) {
position_.push_back(cbegins_[i]);
if(cbegins_[i] == cends_[i]) {
// Empty member, so Cartesian product is empty
absolutePosition_ = std::numeric_limits<std::size_t>::max();
return;
}
}
// Increment to wanted position
for(std::size_t i = 0; i < pos; ++i) {
increment();
}
}
template<typename T>
void CartesianProductIterator<T>::increment()
{
if(absolutePosition_ == std::numeric_limits<std::size_t>::max()) {
return;
}
std::size_t pos = size_ - 1;
// Descend as far as necessary
while(++(position_[pos]) == cends_[pos] && pos != 0) {
--pos;
}
if(position_[pos] == cends_[pos]) {
assert(pos == 0);
absolutePosition_ = std::numeric_limits<std::size_t>::max();
return;
}
// Set all to begin behind pos
for(++pos; pos != size_; ++pos) {
position_[pos] = cbegins_[pos];
}
++absolutePosition_;
result_.emplace_back();
}
template<typename T>
std::vector<typename T::value_type::value_type> const& CartesianProductIterator<T>::dereference() const
{
if(absolutePosition_ == std::numeric_limits<std::size_t>::max()) {
throw new std::out_of_range("Out of bound dereference in CartesianProductIterator\n");
}
auto & result = result_[absolutePosition_];
if(result.empty()) {
result.reserve(size_);
for(auto & iterator: position_) {
result.push_back(*iterator);
}
}
return result;
}
template<typename T>
bool CartesianProductIterator<T>::equal(CartesianProductIterator<T> const& other) const
{
return absolutePosition_ == other.absolutePosition_ && structure_ == other.structure_;
}
//! Class that turns a forward iterable container of forward iterable containers into a forward iterable container which iterates over the Cartesian product of the forward iterable containers
template<typename T>
class CartesianProduct
{
public:
//! Constructor from type T
explicit CartesianProduct(T const& t) : t_(t) {}
//! Iterator to beginning of Cartesian product
CartesianProductIterator<T> begin() const { return CartesianProductIterator<T>(t_, 0); }
//! Iterator behind the last element of the Cartesian product
CartesianProductIterator<T> end() const { return CartesianProductIterator<T>(t_, std::numeric_limits<std::size_t>::max()); }
private:
T const& t_;
};
If someone has comments how to make it faster or better, I'd highly appreciate them.
I was just forced to implement this for a project I was working on and I came up with the code below. It can be stuck in a header and it's use is very simple but it returns all of the combinations you can get from a vector of vectors. The array that it returns only holds integers. This was a conscious decision because I just wanted the indices. In this way, I could index into each of the vector's vector and then perform the calculations I/anyone would need... best to avoid letting CartesianProduct hold "stuff" itself, it is a mathematical concept based around counting not a data structure. I'm fairly new to c++ but this was tested in a decryption algorithm pretty thoroughly. There is some light recursion but overall this is a simple implementation of a simple counting concept.
// Use of the CartesianProduct class is as follows. Give it the number
// of rows and the sizes of each of the rows. It will output all of the
// permutations of these numbers in their respective rows.
// 1. call cp.permutation() // need to check all 0s.
// 2. while cp.HasNext() // it knows the exit condition form its inputs.
// 3. cp.Increment() // Make the next permutation
// 4. cp.permutation() // get the next permutation
class CartesianProduct{
public:
CartesianProduct(int num_rows, vector<int> sizes_of_rows){
permutation_ = new int[num_rows];
num_rows_ = num_rows;
ZeroOutPermutation();
sizes_of_rows_ = sizes_of_rows;
num_max_permutations_ = 1;
for (int i = 0; i < num_rows; ++i){
num_max_permutations_ *= sizes_of_rows_[i];
}
}
~CartesianProduct(){
delete permutation_;
}
bool HasNext(){
if(num_permutations_processed_ != num_max_permutations_) {
return true;
} else {
return false;
}
}
void Increment(){
int row_to_increment = 0;
++num_permutations_processed_;
IncrementAndTest(row_to_increment);
}
int* permutation(){
return permutation_;
}
int num_permutations_processed(){
return num_permutations_processed_;
}
void PrintPermutation(){
cout << "( ";
for (int i = 0; i < num_rows_; ++i){
cout << permutation_[i] << ", ";
}
cout << " )" << endl;
}
private:
int num_permutations_processed_;
int *permutation_;
int num_rows_;
int num_max_permutations_;
vector<int> sizes_of_rows_;
// Because CartesianProduct is called first initially with it's values
// of 0 and because those values are valid and important output
// of the CartesianProduct we increment the number of permutations
// processed here when we populate the permutation_ array with 0s.
void ZeroOutPermutation(){
for (int i = 0; i < num_rows_; ++i){
permutation_[i] = 0;
}
num_permutations_processed_ = 1;
}
void IncrementAndTest(int row_to_increment){
permutation_[row_to_increment] += 1;
int max_index_of_row = sizes_of_rows_[row_to_increment] - 1;
if (permutation_[row_to_increment] > max_index_of_row){
permutation_[row_to_increment] = 0;
IncrementAndTest(row_to_increment + 1);
}
}
};
#include <iostream>
#include <vector>
void cartesian (std::vector<std::vector<int>> const& items) {
auto n = items.size();
auto next = [&](std::vector<int> & x) {
for ( int i = 0; i < n; ++ i )
if ( ++x[i] == items[i].size() ) x[i] = 0;
else return true;
return false;
};
auto print = [&](std::vector<int> const& x) {
for ( int i = 0; i < n; ++ i )
std::cout << items[i][x[i]] << ",";
std::cout << "\b \n";
};
std::vector<int> x(n);
do print(x); while (next(x)); // Shazam!
}
int main () {
std::vector<std::vector<int>>
items { { 1, 2, 3 }, { 4, 5 }, { 6, 7, 8 } };
cartesian(items);
return 0;
}
The idea behind this is as follows.
Let n := items.size().
Let m_i := items[i].size(), for all i in {0,1,...,n-1}.
Let M := {0,1,...,m_0-1} x {0,1,...,m_1-1} x ... x {0,1,...,m_{n-1}-1}.
We first solve the simpler problem of iterating through M. This is accomplished by the next lambda. The algorithm is simply the "carrying" routine grade schoolers use to add 1, albeit with a mixed radix number system.
We use this to solve the more general problem by transforming a tuple x in M to one of the desired tuples via the formula items[i][x[i]] for all i in {0,1,...,n-1}. We perform this transformation in the print lambda.
We then perform the iteration with do print(x); while (next(x));.
Now some comments on complexity, under the assumption that m_i > 1 for all i:
This algorithm requires O(n) space. Note that explicit construction of the Cartesian product takes O(m_0 m_1 m_2 ... m_{n-1}) >= O(2^n) space. So this is exponentially better on space than any algorithm which requires all tuples to be stored simultaneously in memory.
The next function takes amortized O(1) time (by a geometric series argument).
The print function takes O(n) time.
Hence, altogether, the algorithm has time complexity O(n|M|) and space complexity O(n) (not counting the cost of storing items).
An interesting thing to note is that if print is replaced with a function which inspects on average only O(1) coordinates per tuple rather than all of them, then time complexity falls to O(|M|), that is, it becomes linear time with respect to the size of the Cartesian product. In other words, avoiding the copy of the tuple each iterate can be meaningful in some situations.
This version supports no iterators or ranges, but it is a simple direct implementation that uses the multiplication operator to represent the Cartesian product, and a lambda to perform the action.
The interface is designed with the particular functionality I needed. I needed the flexibility to choose vectors over which to apply the Cartesian product in a way that did not obscure the code.
int main()
{
vector< vector<long> > v{ { 1, 2, 3 }, { 4, 5 }, { 6, 7, 8 } };
(Cartesian<long>(v[0]) * v[1] * v[2]).ForEach(
[](long p_Depth, long *p_LongList)
{
std::cout << p_LongList[0] << " " << p_LongList[1] << " " << p_LongList[2] << std::endl;
}
);
}
The implementation uses recursion up the class structure to implement the embedded for loops over each vector. The algorithm works directly on the input vectors, requiring no large temporary arrays. It is simple to understand and debug.
The use of std::function p_Action instead of void p_Action(long p_Depth, T *p_ParamList) for the lambda parameter would allow me to capture local variables, if I wanted to. In the above call, I don't.
But you knew that, didn't you. "function" is a template class which takes the type parameter of a function and makes it callable.
#include <vector>
#include <iostream>
#include <functional>
#include <string>
using namespace std;
template <class T>
class Cartesian
{
private:
vector<T> &m_Vector;
Cartesian<T> *m_Cartesian;
public:
Cartesian(vector<T> &p_Vector, Cartesian<T> *p_Cartesian=NULL)
: m_Vector(p_Vector), m_Cartesian(p_Cartesian)
{};
virtual ~Cartesian() {};
Cartesian<T> *Clone()
{
return new Cartesian<T>(m_Vector, m_Cartesian ? m_Cartesian->Clone() : NULL);
};
Cartesian<T> &operator *=(vector<T> &p_Vector)
{
if (m_Cartesian)
(*m_Cartesian) *= p_Vector;
else
m_Cartesian = new Cartesian(p_Vector);
return *this;
};
Cartesian<T> operator *(vector<T> &p_Vector)
{
return (*Clone()) *= p_Vector;
};
long Depth()
{
return m_Cartesian ? 1 + m_Cartesian->Depth() : 1;
};
void ForEach(function<void (long p_Depth, T *p_ParamList)> p_Action)
{
Loop(0, new T[Depth()], p_Action);
};
private:
void Loop(long p_Depth, T *p_ParamList, function<void (long p_Depth, T *p_ParamList)> p_Action)
{
for (T &element : m_Vector)
{
p_ParamList[p_Depth] = element;
if (m_Cartesian)
m_Cartesian->Loop(p_Depth + 1, p_ParamList, p_Action);
else
p_Action(Depth(), p_ParamList);
}
};
};