C++ multiset with struct erase only one, fast (overload?) - c++

struct node {
int idx; // each node have a unique index
int value; // different nodes can have same value
}
struct node_help {
bool operator()(const node &a, const node &b) const
{
return a.value < b.value;
}
}
std::multiset<node, node_help> Nodes;
So far so good. Now I want to erase a specific node from the multiset. When I use this:
Nodes.erase(node (x, y));
Every node with the value y gets removed but I want only the node to be removed with the value y and index x.
I solved this by doing it manually:
for (std::multiset<node, node_comp>::iterator iter = Nodes.begin(); iter != Nodes.end(); iter++) {
node actual_node = *iter;
if (actual_node.idx == to_delete.idx && actual_node.value == to_delete.value) {
Nodes.erase(iter);
}
return;
}
But this seems to have a bad performance.
I have millions of nodes to I need every speedup I can get. :)
Any ideas?
OK all fine. I've just forgot to take the lines with the log off. So after every change in the set, a log was created and saved directly to the disk. Commenting this out reduced the time from 50 seconds to 0,0x seconds. Fast enough. :)
But ty anyways for all the responses.

struct node_help {
bool operator()(const node &a, const node &b) const
{
return a.value <= b.value; // changes the equality check
}
}
If you have C++11 you can define a lambda as follows and make it a better code. Otherwise you may need to use function object in place of lambda.
std::remove(std::begin(Nodes), std::end(Nodes),
[&to_delete]( struct node & x )
{
return ( x.idx == to_delete.idx &&
x.value == to_delete.value);
}
Please note, to use std::remove() you have to incclude algorithm header file:
#include<algorithm>

You can somehow obtain an iterator to an element which is equal to node (x, y). Then, a erase with an iterator will remove only one element.
That said, with such comparison function, you will have some trouble (in terms of complexity) finding node (x, y) anyway, since nodes with the same y and different x are not efficiently searchable by x.
One solution is to change the comparison function to order by y and then by x, and perhaps use a set instead of a multiset then.
After that, if you want an element with a specific y, you can use something like Nodes.lower_bound (node (-INFINITY, y)) which has complexity O (log n).

how about
std::multiset<node, node_help> Nodes;
Nodes.insert(node{ 1, 10 });
Nodes.insert(node{ 2, 1 });
Nodes.insert(node{ 3, 1 });
Nodes.insert(node{ 4, 100 });
cout << "before\n";
for (const auto& n : Nodes)
{
cout << n.idx << " " << n.value << "\n";
}
auto it = Nodes.find(node{ 0,1 });
while(it != Nodes.end())
{
Nodes.erase(it);
it = Nodes.find(node{ 0,1 });
}
cout << "\nafter\n";
for (const auto& n : Nodes)
{
cout << n.idx << " " << n.value << "\n";
}

You can get a constant factor speedup by only looking at the nodes where y matches
auto [first, last] = Nodes.equal_range(to_delete);
auto it = std::find(first, last, to_delete);
if (it != last) {
Nodes.erase(it);
}
Or without C++17
auto range = Nodes.equal_range(to_delete);
auto it = std::find(range.first, range.second, to_delete);
if (it != range.second) {
Nodes.erase(it);
}
With C++14 you could have Nodes searchable by either node or int
struct node {
int idx; // each node have a unique index
int value; // different nodes can have same value
};
struct node_less {
using is_transparent = void;
bool operator()(const node &a, const node &b) const
{
return std::tie(a.value, a.key) < std::tie(b.value, b.key);
}
bool operator()(int a, const node &b) const
{
return a < b.value;
}
bool operator()(const node &a, int b) const
{
return a.value < b;
}
};
std::set<node, node_less> Nodes;
Nodes.find(node{ x, y }); // single node
Nodes.equal_range(y); // all nodes that match y

Related

C++ - Iterate over vector of doubles as tuples

I have a C++ vector of doubles, which is guaranteed to have an even number of elements. This vector stores the coordinates of a set of points as x, y coordinates:
A[2 * i ] is the x coordinate of the i'th point.
A[2 * i + 1] is the y coordinate of the i'th point.
How to implement an iterator that allows me to use STL style algorithms (one that takes an iterator range, where dereferencing an iterator gives back the pair of doubles corresponding to the x, y coordinates of the corresponding point) ?
I'm using C++17 if that helps.
We can use range-v3, with two adapters:
chunk(n) takes a range and adapts it into a range of non-overlapping ranges of size n
transform(f) takes a range of x and adapts it into a range of f(x)
Putting those together we can create an adaptor which takes a range and yields a range of non-overlapping pairs:
auto into_pairs = rv::chunk(2)
| rv::transform([](auto&& r){ return std::pair(r[0], r[1]); });
Using the r[0] syntax assumes that the input range is random-access, which in this case is fine since we know we want to use it on a vector, but it can also be generalized to work for forward-only ranges at the cost of a bit more syntax:
| rv::transform([](auto&& r){
auto it = ranges::begin(r);
auto next = ranges::next(it);
return std::pair(*it, *next);
})
Demo, using fmt for convenient printing:
int main() {
std::vector<int> v = {1, 1, 2, 2, 3, 3, 4, 4, 5, 5};
auto into_pairs = rv::chunk(2)
| rv::transform([](auto&& r){ return std::pair(r[0], r[1]); });
// prints {(1, 1), (2, 2), (3, 3), (4, 4), (5, 5)}
fmt::print("{}\n", v | into_pairs);
}
It's unclear from the question if you wanted pair<T, T>s or pair<T&, T&>s. The latter is doable by providing explicit types to std::pair rather than relying on class template argument deduction.
C++ is a bit of a moving target - also when it comes to iterators (c++20 has concepts for that...). But would it not be nice to have a lazy solution to the problem. I.e. The tuples get generated on the fly, without casting (see other answers) and without having to write a loop to transform a vector<double> to a vector<tuple<double,double>>?
Now I feel I need a disclaimer because I am not sure this is entirely correct (language lawyers will hopefully point out, if I missed something). But it compiles and produces the expected output. That is something, yes?! Yes.
The idea is to build a pseudo container (which actually is just a facade to an underlying container) with an iterator of its own, producing the desired output type on the fly.
#include <vector>
#include <tuple>
#include <iostream>
#include <iterator>
template <class SourceIter>
struct PairWise {
PairWise() = delete;
PairWise(SourceIter first, SourceIter last)
: first{first}
, last{last}
{
}
using value_type =
typename std::tuple<
typename SourceIter::value_type,
typename SourceIter::value_type
>;
using source_iter = SourceIter;
struct IterState {
PairWise::source_iter first;
PairWise::source_iter last;
PairWise::source_iter current;
IterState(PairWise::source_iter first, PairWise::source_iter last)
: first{first}
, last{last}
, current{first}
{
}
friend bool operator==(const IterState& a, const IterState& b) {
// std::cout << "operator==(a,b)" << std::endl;
return (a.first == b.first)
&& (a.last == b.last)
&& (a.current == b.current);
}
IterState& operator++() {
// std::cout << "operator++()" << std::endl;
if (std::distance(current,last) >= 2) {
current++;
current++;
}
return *this;
}
const PairWise::value_type operator*() const {
// std::cout << "operator*()" << std::endl;
return std::make_tuple(*current, *(current+1));
}
};
using iterator = IterState;
using const_iterator = const IterState;
const_iterator cbegin() const {
return IterState{first,last};
}
const_iterator cend() const {
auto i = IterState{first,last};
i.current = last;
return i;
}
const_iterator begin() const {
// std::cout << "begin()" << std::endl;
return IterState{first,last};
}
const_iterator end() const {
// std::cout << "end()" << std::endl;
auto i = IterState{first,last};
i.current = last;
return i;
}
source_iter first;
source_iter last;
};
std::ostream& operator<<(std::ostream& os, const std::tuple<double,double>& value) {
auto [a,b] = value;
os << "<" << a << "," << b << ">";
return os;
}
template <class Container>
auto pairwise( const Container& container)
-> PairWise<typename Container::const_iterator>
{
return PairWise(container.cbegin(), container.cend());
}
int main( int argc, const char* argv[]) {
using VecF64_t = std::vector<double>;
VecF64_t data{ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };
for (const auto x : pairwise(data)) {
std::cout << x << std::endl;
}
return 0;
}
Elements in vector are stored in contiguous memory area, so you can use simple pointer arithmetics to access pair of doubles.
operator++ for iterator should skip 2 doubles at every use.
operator* can return tuple of references to double values, so you can read (pair = *it) or edit values (*it = pair).
struct Cont {
std::vector<double>& v;
Cont(std::vector<double>& v) : v(v) {}
struct Iterator : public std::iterator<std::input_iterator_tag , std::pair<double,double>> {
double* ptrData = nullptr;
Iterator(double* data) : ptrData(data) {}
Iterator& operator++() { ptrData += 2; return *this; }
Iterator operator++(int) { Iterator copy(*this); ptrData += 2; return copy; }
auto operator*() { return std::tie(*ptrData,*(ptrData+1)); }
bool operator!=(const Iterator& other) const { return ptrData != other.ptrData; }
};
auto begin() { return Iterator(v.data()); }
auto end() { return Iterator(v.data()+v.size());}
};
int main() {
std::vector<double> v;
v.resize(4);
Cont c(v);
for (auto it = c.begin(); it != c.end(); it++) {
*it = std::tuple<double,double>(20,30);
}
std::cout << v[0] << std::endl; // 20
std::cout << v[1] << std::endl; // 30
}
Demo
There's not an easy "C++" way to do this that's clean and avoids a copy of the original array. There's always this (make a copy):
vector<double> A; // your original list of points
vector<pair<double,double>> points;
for (size_t i = 0; i < A.size()/2; i+= 2)
{
points[i*2] = pair<double,double>(A[i], A[i+1]);
}
The following would likely work, violates a few standards, and the language lawyers will sue me in court for suggesting it. But if we can assume that the sizeof(XY) is the size of two doubles, has no padding, and expected alignment then cheating with a cast will likely work. This assumes you don't need a std::pair
Non standard stuff ahead
vector<double> A; // your original list of points
struct XY {
double x;
double y;
};
static_assert(sizeof(double)*2 == sizeof(XY));
static_assert(alignof(double) == alignof(XY));
XY* points = reinterpret_cast<XY*>(A.data());
size_t numPoints = A.size()/2;
// iterate
for (size_t i = 0; i < numPoints; i++) {
XY& point = points[i];
cout << point.x << "," << point.y << endl;
}
If you can guarantee that std::vector will always have an even number of entries, you could exploit the fact that an vector of doubles will have the same memory layout as a vector of pairs of doubles. This is kind of a dirty trick though so I wouldn't recommend it if you can avoid it. The good news is that the standard guarantees that vector elements will be contiguous.
inline const std::vector<std::pair<double, double>>& make_dbl_pair(std::vector<double>& v)
{
return reinterpret_cast<std::vector<std::pair<double, double>>&>(v);
}
This will only work for iteration with iterators. The size is likely to be double the number of pairs in the vector because it is still a vector of doubles underneath.
Example:
int main(int argc, char* argv[])
{
std::vector<double> dbl_vec = { 0.0, 1.1, 2.2, 3.3, 4.4, 5.5 };
const std::vector<std::pair<double, double>>& pair_vec = make_dbl_pair(dbl_vec);
for (auto it = pair_vec.begin(); it != pair_vec.end(); ++it) {
std::cout << it->first << ", " << it->second << "\n";
}
std::cout << "Size: " << dbl_vec.size() << "\n";
return 0;
}

How can I generate the cartesian product of some vectors, whose number is given at runtime in C++? [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);
}
};
};

Set of custom class objects and their < operator

I am trying to implement A* algorithm (with visualization in Qt). I've got this method:
result_path astar_algorithm::calculate(mapview* m_view)
{
map_view = m_view;
auto closed_set = std::vector<std::shared_ptr<node>>();
auto start_node = std::make_shared<node>(_start);
auto open_set = std::vector<std::shared_ptr<node>>{start_node};
std::map<node, node> came_from;
std::shared_ptr<node> current;
while (!open_set.empty())
{
current = *std::min_element(open_set.begin(), open_set.end());
if (*current == _end)
{
// TODO: Reconstruct a result path!!!
break;
}
open_set.erase(std::find(open_set.begin(), open_set.end(), current));
closed_set.push_back(current);
auto neighbors = get_neighbors(*current);
for (auto& neighbor : neighbors)
{
if (std::find_if(closed_set.begin(), closed_set.end(),
[&](std::shared_ptr<node> const& p) { return *p == neighbor; }) !=
closed_set.end())
continue;
auto tentative_g_score = current->G + 1;
if (std::find_if(open_set.begin(), open_set.end(), [&](std::shared_ptr<node> const& p) {
return *p == neighbor;
}) == open_set.end())
{
neighbor.G = tentative_g_score;
neighbor.H = heuristic_cost_estimate(neighbor.pos, _end);
neighbor.parent = current;
open_set.push_back(std::make_shared<node>(neighbor));
}
else if (tentative_g_score < neighbor.G)
{
neighbor.parent = current;
neighbor.G = tentative_g_score;
}
}
}
auto result = result_path();
while (*current != *start_node)
{
result.path.push_back(current->pos);
current = current->parent;
}
result.path.push_back(start_node.pos);
std::reverse(result.path.begin(), result.path.end());
return result;
}
It works, but I have a few problems:
if (std::find_if(closed_set.begin(), closed_set.end(),
[&](std::shared_ptr<node> const& p) { return *p == neighbor; }) !=
closed_set.end())
continue;
This line checks if a node is present in an std::vector and if so, it continues the loop (then there is a second line similar to this, it just checks if node is not actually present in the vector). I guess the better way would be to store those nodes in a vector and then searching and further adding would be easier (cuz I just have to check if the insert succeeded).
The problem is, afaik, to make this work I have to implement < operator. And so I did. I also made == and !=:
class node
{
public:
node() {}
node(const QPoint& p) : pos(p) {}
bool operator == (const node& o ) const { return pos == o.pos; }
bool operator == (const QPoint& o ) const { return pos == o; }
bool operator != (const node& o) const {return pos != o.pos; }
bool operator <(const node& o ) const { return G + H < o.G + o.H; }
QPoint pos;
std::shared_ptr<node> parent;
int G = 0;
int H = 0;
};
It works perfectly for the earlier search for std::min_element (it searches for a node with the lowest F value (F=G+H)), it uses < operator. But then I tried to use a set, so those two vectors at the beginning of the method were set and when I wanted to just insert or even check if a node is already in a set and then insert I had a problem. Many of those nodes will have the same G+H value, as the maze which I used was kind of simple (i.e. a maze completely without terrains). I checked it under the debugger and the nodes with unique .pos values (QPoint) were not added to the set just like they weren't unique (but if the node had a different G+H value than any node in the set, it would be added). For the vector the same nodes of course work, cuz there are no checks made, I checked everything carefully under the debugger.
I don't know if I am getting this wrong, but I thought it would use a == or != operators but as seen in this answer: link, it actually uses < operator, which in my case would not distinguish between two nodes (cuz the unique part of each node is its position in the grid (node represents a box in a grid, which can represent a maze or smth similar))
So, is there something I am doing wrong or am I actually getting this right, and the inserting (which checks if the element is unique) or checking if the element exists in a set uses < operator and I cannot do anything about it? (cuz I would like to have my < operator with comparing G+H and then I would like the searching/inserting to use the == operator to compare)
This is the example that I wrote (I forgot I have Microsoft C++ Compiler from the command line - cl.exe)
#include <algorithm>
#include <iostream>
#include <memory>
#include <set>
class Point
{
public:
int _x, _y;
Point() : _x(0), _y(0) {}
Point(int x, int y) : _x(x), _y(y) {}
bool operator==(const Point& p) const { return _x == p._x && _y == p._y; }
bool operator!=(const Point& p) const { return _x != p._x && _y != p._y; }
};
class node
{
public:
node() {}
node(const Point& p) : pos(p) {}
bool operator==(const node& o) const { return pos == o.pos; }
bool operator==(const Point& o) const { return pos == o; }
bool operator!=(const node& o) const { return pos != o.pos; }
bool operator<(const node& o) const { return G + H < o.G + o.H; }
Point pos;
std::shared_ptr<node> parent;
int G = 0;
int H = 0;
};
int main()
{
node n1(Point(0, 0));
n1.G = 1;
n1.H = 1;
node n2(Point(1, 1));
n2.G = 2;
n2.H = 2;
node n3(Point(2, 2));
n3.G = 1;
n3.H = 1;
std::set<node> nodes;
nodes.insert(n1);
nodes.insert(n2);
nodes.insert(n3);
auto min = (*std::min_element(nodes.begin(), nodes.end())).pos;
std::cout << min._x << " " << min._y << '\n';
std::cout << nodes.size() << '\n';
}
>main.exe
0 0
2
std::min_element works, but those are 3 unique nodes for me (differet .pos values) so there should be 3 nodes in the set. And that's what I want to achieve
I thought it would use a == or != operators
No, std::set does not use operators == and !=,
std::set uses just one function, the comparison function (the second template argument, which defaults to std::less<T>).
Uniqueness is based on the equivalence relation which is derived from applying the same comparison function twice: !a<b && !b<a.
It seems you don't really need uniqueness, in which case you can use std::multiset instead. It will maintain the order, but will not enforce uniqueness.
std::set<node> nodes;
. . .
auto min = (*std::min_element(nodes.begin(), nodes.end())).pos;
std::min_element is always O(N). Using it on a set defeats the purpose of having a set.
Just get the first element, which will be the smallest (according to the comparison function).
auto min = begin(nodes)->pos;

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);
}
};
};

How can I create cartesian product of vector of vectors?

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);
}
};
};