I was wondering either it is possible in the c++11 syntax to use the new container based for loop for multiple items, for example:
std::vector<double> x;
std::vector<double> y;
for (double& xp, yp : x, y)
{
std::cout << xp << yp << std::endl;
}
I was not able to find any information about using this loop for more than one container. I would appreciate all help.
Example effect in the classic for loop:
std::vector<double>::iterator itX = m_x.begin();
std::vector<double>::iterator itY = m_y.begin();
for (uint32_t i = 0; i < m_x.size(); i++, itX++, itY++)
{
// operations on the m_x and m_y vectors
}
There is a request in the language working group to support a very similar syntax to iterate simultaneously on many containers:
Section: 6.5.4 [stmt.ranged] Status: Open Submitter: Gabriel Dos Reis
Opened: 2013-01-12 Last modified: 2015-05-22
Discussion:
The new-style 'for' syntax allows us to dispense with administrative iterator declarations when iterating over a single sequence. The burden and noise remain, however, when iterating over two or more sequences simultaneously. We should extend the syntax to allow that. E.g. one should be able to write:
for (auto& x : v; auto& y : w)
a = combine(v, w, a);
instead of the noisier
auto p1 = v.begin();
auto q1 = v.end();
auto p2 = w.begin();
auto q2 = w.end();
while (p1 < q1 and p2 < q2) {
a = combine(*p1, *p2, a);
++p1;
++p2;
}
See http://cplusplus.github.io/EWG/ewg-active.html#43
So it could happen but not in the near future.
Meanwhile the best choice is probably the classical for loop.
I know this is a little old now, but I had a similar query and T.C.'s "you'd need some library help" comment made me grin, because I ended up solving a similar issue with only a few extra characters. To recycle the OP's first example, and assuming as stated that the vectors are guaranteed the same size, you can make C++11 referencing meet old-school pointer arithmetic, like so:
std::vector<double> x;
std::vector<double> y;
for (double &xp:x)
{
std::cout << xp << y[&xp-&x[0]] << std::endl;
}
Probably best not used in production code (I'm a self-taught hobbyist coder, so meh) but it works well enough, is simple, requires no libraries and does not seem to suffer any notable speed penalty (at least, that I've noticed). It even works in minimal C++11 environments (such as VC11). To be clear, I used this in a slightly different context, where (given the above example) I only accessed y[] when a change was actually required (so any possible speed reduction is mitigated in the noise), but since the y[] access was required at the same index as in x[] and required no extra variables/iterators, it fit the bill perfectly.
Also, +1 for manlio's answer; would you believe I actually tried to use exactly that syntax intuitively before I went looking for an alternative? :O
Related
I am trying to do a product operand on the values inside of a vector. It is a huge mess of code.. I have posted it previously but no one was able to help. I just wanna confirm which is the correct way to do a single part of it. I currently have:
vector<double> taylorNumerator;
for(a = 0; a <= (constant); a++) {
double Number = equation involving a to get numerous values;
taylorNumerator.push_back(Number);
for(b = 0; b <= (constant); b++) {
double NewNumber *= taylorNumerator[b];
}
This is what I have as a snapshot, it is very short from what I actually have. Someone told me it is better to do vector.at(index) instead. Which is the correct or best way to accomplish this? If you so desire I can paste all of the code, it works but the values I get are wrong.
When possible, you should probably avoid using indexes at all. Your options are:
A range-based for loop:
for (auto numerator : taylorNumerators) { ... }
An iterator-based loop:
for (auto it = taylorNumerators.begin(); it != taylorNuemrators.end(); ++it) { ... }
A standard algorithm, perhaps with a lambda:
#include <algorithm>
std::for_each(taylorNumerators, [&](double numerator) { ... });
In particular, note that some algorithms let you specify a number of iterations, like std::generate_n, so you can create exactly n items without counting to n yourself.
If you need the index in the calculation, then it can be appropriate to use a traditional for loop. You have to watch for a couple pitfalls: std::vector<T>::size() returns a std::vector<T>::size_type which is typically identical to std::size_type, which is (1) unsigned and (2) quite possibly larger than an int.
for (std::size_t i = 0; i != taylorNumerators.size(); ++i) { ... }
Your calculations probably deal with doubles or some numerical type other than std::size_t, so you have to consider the best way to convert it. Many programmers would rely on implicit conversions, but that can be dangerous unless you know the conversion rules very well. I'd generally start by doing a static cast of the index to the type I actually need. For example:
for (std::size_t i = 0; i != taylorNumerators.size(); ++i) {
const auto x = static_cast<double>(i);
/* calculation involving x */
}
In C++, it's probably far more common to make sure the index is in range and then use operator[] rather than to use at(). Many projects disable exceptions, so the safety guarantee of at() wouldn't really be available. And, if you can check the range once yourself, then it'll be faster to use operator[] than to rely on the range-check built into at() on each index operation.
What you have is fine. Modern compilers can optimize the heck out of the above such that the code is just as fast as the equivalent C code of accessing items direclty.
The only optimization for using vector I recommend is to invoke taylorNumerator.reserve(constant) to allocate the needed storage upfront instead of the vector resizing itself as new items are added.
About the only worthy optimization after that is to not use vector at all and just use a static array - especially if constant is small enough that it doesn't blow up the stack (or binary size if global).
double taylorNumerator[constant];
I have
typedef std::vector<int> IVec;
typedef std::vector<IVec> IMat;
and I would like to know how I can fill an IMat by using std algorithms, ie how to do the following with less code (all the IVecs have the same size) ?
void fill(IMat& mat){
for (int i=0;i<mat.size();i++){
for (int j=0;j<mat[i].size();j++){
mat[i][j] = i*j;
}
}
}
PS: already a way to fill the matrix with a constant would help me. And preferably with pre-C++11 algorithms.
The best solution is the one that you have already implemented. It takes advantage of using i/j as both offsets and as inputs to compute the algorithm.
Standard algorithms will have to use iterators for the elements and maintain counters. This data mirroring as a sure sign of a problem. But it can be done, even on one line if you wanna be fancy:
for_each(mat.begin(), mat.end(), [&](auto& i) { static auto row = 0; auto column = 0; generate(i.begin(), i.end(), [&]() { return row * column++; }); ++row; });
But as stated just cause it could be done doesn't mean that it should be done. The best way to approach this is the for-loop. Even doing it on one line is possible if that's your thing:
for(auto i = 0U;i < mat.size();i++) for(auto j = 0U;j < mat[i].size();j++) mat[i][j] = i*j;
Incidentally my standard algorithm works fine on Clang 3.7.0, gcc 5.1, and on Visual Studio 2015. However previously I used transform rather than generate. And there seem to be some implementation bugs in gcc 5.1 and Visual Studio 2015 with the captures of lambda scope static variables.
I don't know if this is better than a double for loop, but one possible way you could do it using STL in C++11 would be using two for_each as follows:
int i(0);
std::for_each(mat.begin(), mat.end(),
[&i](IVec &ivec){int j(0); std::for_each(ivec.begin(), ivec.end(),
[&i,&j](auto &k){k = i*j++;}); ++i;});
LIVE DEMO
Just thought I'd comment further on Jonathan's excellent answer.
Ignore the c++11 syntax for now and imagine that we had written some supporting classes (doesn't matter how for now).
we could conceivably come up with code like this:
auto main() -> int
{
// define a matrix (vector of vectors)
IMat mat;
// resize it through some previously defined function
resize(mat, 10, 10);
// get an object that is a pseudo-container representing its extent
auto extent = extent_of(mat);
// generate values in the pseudo-container which forwards to the matrix
std::generate(extent.begin(),
extent.end(),
[](auto pxy) { pxy.set_value(pxy.x * pxy.y); });
// or even
for (auto pxy : extent_of(mat)) {
pxy.set_value(product(pxy.coordinates()));
}
return 0;
}
100 lines of supporting code later (iterable containers and their proxies are not trivial) and this would compile and work.
Clever as it undoubtedly would be, there are some problems:
There's the small matter of the 100 extra lines of code.
It seems to me that this code is actually less expressive than yours. i.e. it's immediately obvious what your code is doing. With mine you have to make some assumptions or go and reason about the extra 100 lines of code.
my code needs a lot more maintenance (and documentation) than yours
Sometimes less is more.
After learning that one can calculate the mean of data, which is stored in a std::vector< std::vector<double> > data, can be done the following way:
void calculate_mean(std::vector<std::vector<double>>::iterator dataBegin,
std::vector<std::vector<double>>::iterator dataEnd,
std::vector<double>& rowmeans) {
auto Mean = [](std::vector<double> const& vec) {
return std::accumulate(vec.begin(), vec.end(), 0.0) / vec.size(); };
std::transform(dataBegin, dataEnd, rowmeans.begin(), Mean);
}
I made a function which takes the begin and the end of the iterator of the data vector to calculate the mean and std::vector<double> is where I store the result.
My first question is, how to handle the return value of function, when working with vectors. I mean in this case I make an Alias and modify in this way the vector I initialized before calling this function, so there is no copying back which is nice. So is this good programming practice?
Second my main questions is, how to adapt this function so one can calculate the standard deviation of each row in a similar way. I tried really hard but it only gives a huge mess, where nothing is working properly. So if someone sees it right away how to do that, I would be glad, for a insight. Thank you.
Edit: Solution
So here is my solution for the problem. Given a std::vector< vector<double> > data (rows, std::vector<double>(columns)), where the data is stored in the rows. The following function calculates the sample standard deviation of each row simultaneously.
auto begin = data.begin();
auto end = data.end();
std::vector<double> std;
std.resize(data.size());
void calculate_std(std::vector<std::vector<double>>::iterator dataBegin,
std::vector<std::vector<double>>::iterator dataEnd,
std::vector<double>& rowstds){
auto test = [](std::vector<double> const& vec) {
double sum = std::accumulate(vec.begin(), vec.end(), 0.0);
double mean = sum / vec.size();
double stdSum = 0.0;
auto Std = [&](const double x) { stdSum += (x - mean) * (x - mean); };
std::for_each(vec.begin(), vec.end(), Std);
return sqrt(stdSum / (vec.size() - 1));
};
std::transform(dataBegin, dataEnd, rowstds.begin(), test);
}
I tested it and it works just fine. So if anyone has some suggestions for improvement, please let me know. And is this piece of code good performance wise?
You will find relatively often the convention to write functions with input parameters first, followed by input / output parameters.
Output parameters (that you write to with the return values of your function) are often a pointer to the data, or a reference.
So your solution seems perfect, from that point of view.
Source:
Google's C++ coding conventions
I mean in this case I make an Alias and modify in this way the vector I initialized before calling this function, so there is no copying back which is nice. So is this good programming practice?
No, you should use a local vector<double> variable and return by value. Any compiler worth using would optimize away the copying/moving, and any conforming C++11 compiler is required to perform a move if for whatever reason it cannot elide the copy/move altogether.
Your code as written imposes additional requirements on the caller that are not obvious. For instance, rowmeans must contain enough elements to store the means, or undefined behavior results.
I was wondering if there's a neater (or better yet, more efficient), method of summing values of a vector/(asymmetric) matrix (a matrix having structure like symmetry, could of course be exploited in looping, but not that pertinent to my question) pointed by a collection of indices. Basically this code could be used to calculate, say, a cost of a route through a 2D matrix. I'm looking for a way to utilize CPU, not GPU.
Here's some relevant code, the one I'm more interested is the first case. I was thinking it's possible to use std::accumulate with a lambda to capture the indices vector, but then I got wondering, if there's already a neater way, perhaps with some other operator. Not a "real problem" as looping is quite clear for my tastes too, but in hunt for the super-neat or more efficient on-liner...
template<typename out_type>
out_type sum(std::vector<float> const& matrix, std::vector<int> const& indices)
{
out_type cost = 0;
for(decltype(indices.size()) i = 0; i < indices.size() - 1; ++i)
{
const int index = indices.size() * indices[i] + indices[i + 1];
cost += matrix[index];
}
const int index = indices.size() * indices[indices.size() - 1] + indices[0];
cost += matrix[index];
return cost;
}
template<typename out_type>
out_type sum(std::vector<std::vector<float>> const& matrix, std::vector<int> const& indices)
{
out_type cost = 0;
for(decltype(indices.size()) i = 0; i < indices.size() - 1; i++)
{
cost += matrix[indices[i]][indices[i + 1]];
}
cost += matrix[indices[indices.size() - 1]][indices[0]];
return cost;
}
Oh, and PPL/TBB are fair game too.
Edit
As an afterthought and as commented to John, would there be a place to employ std::common_type in the calculation as the input and output types may differ? This is a bit of hand-waving and more like learning techniques and libraries. A form of code kata, if you will.
Edit 2
Now, there's one option to make the loops faster, explained in blog writing How to process a STL vector using SSE code by a blogger theowl84. The code uses __m128 directly, but I wonder if there's something in DirectXMath library too.
Edit 3
Now, after writing some concrete code, I found std::accumulate wouldn't get me far. Or at least I couldn't find a way to do the [indices[i + 1] part in matrix[indices[i]][indices[i + 1]]; in a neat way, as std::accumulate itself gives access to only the current value and the sum. In that light, it looks like novelocrat's approach would be the most fruitful one.
DeadMG proposed using parallel_reduce with associativity caveats, further commented by novelocrat. I didn't go about seeing if I could use parallel_reduce, as the interface looked somewhat cumbersome for quick trying. Other than that, even though my code executes serially, it would suffer from the same floating some issues as the parallel reduction version. Though the parallel version would/could be (much) more unpredictable with than serial version, I think.
This goes somewhat tangential, but it may be of interest to some stumbling here, and to those of whom have read this far, may be (very) interested on article Wandering Precision in The NAG blog, which details some intricanciens even introduced by hardware instruction re-ordering! Then there are some ruminations about this very issue in distributed setting in #AltDevBlogADay Synchronous RTS Engines and a Tale of Desyncs. Also, ACCU (the general mailing list is excellent, by the way, and it's free to join) features several articles (e.g. this) on floating point accuracy. A tangential to tangential, I found Fernando Cacciola's Robustness issues in geometric computing to be a good article to read, originally from ACCU mailing list.
And then then the std::common_type. I couldn't find usage for that. If I had two different types as parameters, then the return value could/should be decided by std::common_type. Perhaps more pertinent is std::is_convertible with static_assert to make sure the desired result type is convertible from the argument types (with a clean error message). Other than that, I can only make up a check that the return value/intermediate calculation value accurracy is sufficient to represent the result of summation without overflows and things like that, but I haven't come across a standard facility for that.
That about that, I think, ladies and gentlemen. I enjoyed myself, I hope those reading this got something out of this too.
You could produce an iterator that takes matrix and indices and yields the appropriate values.
class route_iterator
{
vector<vector<float>> const& matrix;
vector<int> const& indices;
int i;
public:
route_iterator(vector<vector<float>> const& matrix_, vector<int> const& indices_,
int begin = 0)
: matrix(matrix_), indices(indices_), i(begin)
{ }
float operator*() {
return matrix[indices[i]][indices[(i + 1) % indices.size()]];
}
route_iterator& operator++() {
++i;
return *this;
}
};
Then your accumulate runs from route_iterator(matrix, indices) to route_iterator(matrix, indices, indices.size()).
Admittedly, though, this sequentializes without a smart compiler turning it into something parallel. What you really want are parallel map and fold (accumulate) operations.
out_type cost = 0;
for(decltype(indices.size()) i = 0; i < indices.size() - 1; i++)
{
cost += matrix[indices[i]][indices[i + 1]];
}
This is basically std::accumulate. PPL provides (and so does TBB, if I recall) parallel_reduce. This requires associativity but not commutivity, and + over the real/float/integer is associative.
I have a std::map that I'm using to store values for x and y coordinates. My data is very sparse, so I don't want to use arrays or vectors, which would result in a massive waste of memory. My data ranges from -250000 to 250000, but I'll only have a few thousand points at the most.
Currently I'm creating a std::string with the two coordinates (i.e. "12x45") and using it as a key. This doesn't seem like the best way to do it.
My other thoughts were to use an int64 and shove the two int32s into it and use it as a key.
Or to use a class with the two coordinates. What are the requirements on a class that is to be used as the key?
What is the best way to do this? I'd rather not use a map of maps.
Use std::pair<int32,int32> for the key:
std::map<std::pair<int,int>, int> myMap;
myMap[std::make_pair(10,20)] = 25;
std::cout << myMap[std::make_pair(10,20)] << std::endl;
I usually solve this kind of problem like this:
struct Point {
int x;
int y;
};
inline bool operator<(const Point& p1, const Point& p2) {
if (p1.x != p2.x) {
return p1.x < p2.x;
} else {
return p1.y < p2.y;
}
}
Boost has a map container that uses one or more indices.
Multi Index Map
What are the requirements on a class that is to be used as the key?
The map needs to be able to tell whether one key's value is less than another key's value: by default this means that (key1 < key2) must be a valid boolean expression, i.e. that the key type should implement the 'less than' operator.
The map template also implements an overloaded constructor which lets you pass-in a reference to a function object of type key_compare, which can implement the comparison operator: so that alternatively the comparison can be implemented as a method of this external function object, instead of needing to be baked in to whatever type your key is of.
This will stuff multiple integer keys into a large integer, in this case, an _int64. It compares as an _int64, AKA long long (The ugliest type declaration ever. short short short short, would only be slightly less elegant. 10 years ago it was called vlong. Much better. So much for "progress"), so no comparison function is needed.
#define ULNG unsigned long
#define BYTE unsigned char
#define LLNG long long
#define ULLNG unsigned long long
// --------------------------------------------------------------------------
ULLNG PackGUID(ULNG SN, ULNG PID, BYTE NodeId) {
ULLNG CompKey=0;
PID = (PID << 8) + NodeId;
CompKey = ((ULLNG)CallSN << 32) + PID;
return CompKey;
}
Having provided this answer, I doubt this is going to work for you, as you need two separate and distinct keys to navigate with in 2 dimensions, X and Y.
On the other hand, if you already have the XY coordinate, and just want to associate a value with that key, then this works spectacularly, because an _int64 compare takes the same time as any other integer compare on Intel X86 chips - 1 clock.
In this case, the compare is 3X as fast on this synthetic key, vs a triple compound key.
If using this to create a sparsely populated spreadsheet, I would RX using 2 distinct trees, one nested inside the other. Make the Y dimension "the boss", and search Y space first to resolution before proceeding to the X dimension. Spreadsheets are taller than they are wide, and you always want the 1st dimension in any compound key to have the largest number of unique values.
This arrangement would create a map for the Y dimension that would have a map for the X dimension as it's data. When you get to a leaf in the Y dimension, you start searching it's X dimension for the column in the spreadsheet.
If you want to create a very powerful spreadsheet system, add a Z dimension in the same way, and use that for, as an example, organizational units. This is the basis for a very powerful budgeting/forecasting/accounting system, one which allows admin units to have lots of gory detail accounts to track admin expenses and such, and not have those accounts take up space for line units which have their own kinds of detail to track.
I think for your use case, std::pair, as suggested in David Norman's answer, is the best solution. However, since C++11 you can also use std::tuple. Tuples are useful if you have more than two keys, for example if you have 3D coordinates (i.e. x, y, and z). Then you don't have to nest pairs or define a comparator for a struct. But for your specific use case, the code could be written as follows:
int main() {
using tup_t = std::tuple<int, int>;
std::map<tup_t, int> m;
m[std::make_tuple(78, 26)] = 476;
tup_t t = { 12, 45 }; m[t] = 102;
for (auto const &kv : m)
std::cout << "{ " << std::get<0>(kv.first) << ", "
<< std::get<1>(kv.first) << " } => " << kv.second << std::endl;
return 0;
}
Output:
{ 12, 45 } => 102
{ 78, 26 } => 476
Note: Since C++17 working with tuples has become easier, espcially if you want to access multiple elements simultaneously.
For example, if you use structured binding, you can print the tuple as follows:
for (auto const &[k, v] : m) {
auto [x, y] = k;
std::cout << "{ " << x << ", " << y << " } => " << v << std::endl;
}
Code on Coliru
Use std::pair. Better even use QHash<QPair<int,int>,int> if you have many of such mappings.
Hope you will find it useful:
map<int, map<int, int>> troyka = { {4, {{5,6}} } };
troyka[4][5] = 7;
An alternative for the top result that is slightly less performant but allows for easier indexing
std::map<int, std::map<int,int>> myMap;
myMap[10][20] = 25;
std::cout << myMap[10][20] << std::endl;
First and foremost, ditch the string and use 2 ints, which you may well have done by now. Kudos for figuring out that a tree is the best way to implement a sparse matrix. Usually a magnet for bad implementations it seems.
FYI, a triple compound key works too, and I assume a pair of pairs as well.
It makes for some ugly sub-scripting though, so a little macro magic will make your life easier. I left this one general purpose, but type-casting the arguments in the macro is a good idea if you create macros for specific maps. The TresKey12 is tested and running fine. QuadKeys should also work.
NOTE: As long as your key parts are basic data types you DON'T need to write anything more. AKA, no need to fret about comparison functions. The STL has you covered. Just code it up and let it rip.
using namespace std; // save some typing
#define DosKeys(x,y) std::make_pair(std::make_pair(x,y))
#define TresKeys12(x,y,z) std::make_pair(x,std::make_pair(y,z))
#define TresKeys21(x,y,z) std::make_pair(std::make_pair(x,y),z))
#define QuadKeys(w,x,y,z) std::make_pair(std::make_pair(w,x),std::make_pair(y,z))
map<pair<INT, pair<ULLNG, ULLNG>>, pIC_MESSAGE> MapMe;
MapMe[TresKey12(Part1, Part2, Part3)] = new fooObject;
If someone wants to impress me, show me how to make a compare operator for TresKeys that doesn't rely on nesting pairs so I can use a single struct with 3 members and use a comparison function.
PS: TresKey12 gave me problems with a map declared as pair,z as it makes x,pair, and those two don't play nice. Not a problem for DosKeys, or QuadKeys. If it's a hot summer Friday though, you may find an unexpected side-effect of typing in DosEquis
... err.. DosKeys a bunch of times, is a thirst for Mexican beer. Caveat Emptor. As Sheldon Cooper says, "What's life without whimsy?".