Parentheses followed by parentheses - c++

I am trying to understand what a piece of C++ code is doing, but know nothing about C.
I have a loop like this:
(_A[0])=eigenMatrix::Zero(_n, _n);
for(i=0; i<_n; i++){
for(j=0; j<=i; j++) (_A[0])(j,i)=(_A[0])(i,j)=value[i*n+j];
}
A is a vector of eigenMatrix type: vector <#eigenMatrix> _A;
I think the first line is defining (_A[0]) as a zero n*n matrix, but I can't work out what the (_A[0])(j,i) part is doing, and can't find any reference to this kind of ()() phrase in c++.

Operator Overloading
In C++ you can respecify the meaning of various operators. For a Matrix class, it does make sense to define a meaning for parentheses:
double & Matrix::operator()(int row, int col) {
return data[row][col];
}
would result in a Matrix object _A[0] from which elements can be obtained as in _A[0](2, 2).
lvalue Assignment
An interesting detail in your example is the assignment to an lvalue -- you can see _A[0](j,i) is on the left-hand side. Such an assignment is possible because we return a reference (double &) to the inner representation data.
If you open the header file that provides you with eigenMatrix (or rather its base class), you will find a declaration of a reference (&) returned by some Matrix::operator() method.
Why bother?
It provides convenient access to matrix elements while at the same time providing more control than simply exposing the inner data directly. For example you could imagine checks like
double & Matrix::operator()(int row, int col) {
assert((row >= 0) && (row < n_row) && (col >=0 ) && (col < n_col));
return data[row][col];
}

I am not sure why () are used around _A[0].
_A[0](i,j) probably just returns a reference to value in i-th row and j-th column or another way around.
Here you can see how this operator is used:
int main()
{
MatrixXd m(2,2);
m(0,0) = 3;
m(1,0) = 2.5;
m(0,1) = -1;
m(1,1) = m(1,0) + m(0,1);
}
and just to make everythign clear that's how you declare such an object.
class Matrix
{
private:
float value[4][4];
public:
float& operator()(int i, int j)
{
return value[i][j];
}
};

Lets break down this code.
so lets assume that this line:
(_A[0])=eigenMatrix::Zero(_n, _n);
is actually
A = eigen::Matrix::Zero(_n, _n);
I am making this assumption because
Only element 0 of _A is ever accessed.
I think maybe you are using the eigen Library.
The next part is then a little easier.
for(i=0; i<_n; i++){ // Loop from 0 to `_n` which is the size of the Zero Matrix.
for(j=0; j<=i; j++) // Loop from 0 to i, this means you are only accessing the
// lower left side of the matrix.
i=0 -> [j=0, ... No Access
i=1 -> [j=0, j=1, ... No Access
i=_n -> [j=0, j=1, ... j=_n
(A)(j,i) = (A)(i,j) = value[i*n+j];
The first part is redundant, you are assigning to yourself.
The second part ( = value[...]) is assigning the currently looked at matrix element to the same element but in a 2D array stored as a 1D vector called value.
}

Related

Having a hard time figuring out logic behind array manipulation

I am given a filled array of size WxH and need to create a new array by scaling both the width and the height by a power of 2. For example, 2x3 becomes 8x12 when scaled by 4, 2^2. My goal is to make sure all the old values in the array are placed in the new array such that 1 value in the old array fills up multiple new corresponding parts in the scaled array. For example:
old_array = [[1,2],
[3,4]]
becomes
new_array = [[1,1,2,2],
[1,1,2,2],
[3,3,4,4],
[3,3,4,4]]
when scaled by a factor of 2. Could someone explain to me the logic on how I would go about programming this?
It's actually very simple. I use a vector of vectors for simplicity noting that 2D matrixes are not efficient. However, any 2D matrix class using [] indexing syntax can, and should be for efficiency, substituted.
#include <vector>
using std::vector;
int main()
{
vector<vector<int>> vin{ {1,2},{3,4},{5,6} };
size_t scaleW = 2;
size_t scaleH = 3;
vector<vector<int>> vout(scaleH * vin.size(), vector<int>(scaleW * vin[0].size()));
for (size_t i = 0; i < vout.size(); i++)
for (size_t ii = 0; ii < vout[0].size(); ii++)
vout[i][ii] = vin[i / scaleH][ii / scaleW];
auto x = vout[8][3]; // last element s/b 6
}
Here is my take. It is very similar to #Tudor's but I figure between our two, you can pick what you like or understand best.
First, let's define a suitable 2D array type because C++'s standard library is very lacking in this regard. I've limited myself to a rather simple struct, in case you don't feel comfortable with object oriented programming.
#include <vector>
// using std::vector
struct Array2d
{
unsigned rows, cols;
std::vector<int> data;
};
This print function should give you an idea how the indexing works:
#include <cstdio>
// using std::putchar, std::printf, std::fputs
void print(const Array2d& arr)
{
std::putchar('[');
for(std::size_t row = 0; row < arr.rows; ++row) {
std::putchar('[');
for(std::size_t col = 0; col < arr.cols; ++col)
std::printf("%d, ", arr.data[row * arr.cols + col]);
std::fputs("]\n ", stdout);
}
std::fputs("]\n", stdout);
}
Now to the heart, the array scaling. The amount of nesting is … bothersome.
Array2d scale(const Array2d& in, unsigned rowfactor, unsigned colfactor)
{
Array2d out;
out.rows = in.rows * rowfactor;
out.cols = in.cols * colfactor;
out.data.resize(std::size_t(out.rows) * out.cols);
for(std::size_t inrow = 0; inrow < in.rows; ++inrow) {
for(unsigned rowoff = 0; rowoff < rowfactor; ++rowoff) {
std::size_t outrow = inrow * rowfactor + rowoff;
for(std::size_t incol = 0; incol < in.cols; ++incol) {
std::size_t in_idx = inrow * in.cols + incol;
int inval = in.data[in_idx];
for(unsigned coloff = 0; coloff < colfactor; ++coloff) {
std::size_t outcol = incol * colfactor + coloff;
std::size_t out_idx = outrow * out.cols + outcol;
out.data[out_idx] = inval;
}
}
}
}
return out;
}
Let's pull it all together for a little demonstration:
int main()
{
Array2d in;
in.rows = 2;
in.cols = 3;
in.data.resize(in.rows * in.cols);
for(std::size_t i = 0; i < in.rows * in.cols; ++i)
in.data[i] = static_cast<int>(i);
print(in);
print(scale(in, 3, 2));
}
This prints
[[0, 1, 2, ]
[3, 4, 5, ]
]
[[0, 0, 1, 1, 2, 2, ]
[0, 0, 1, 1, 2, 2, ]
[0, 0, 1, 1, 2, 2, ]
[3, 3, 4, 4, 5, 5, ]
[3, 3, 4, 4, 5, 5, ]
[3, 3, 4, 4, 5, 5, ]
]
To be honest, i'm incredibly bad at algorithms but i gave it a shot.
I am not sure if this can be done using only one matrix, or if it can be done in less time complexity.
Edit: You can estimate the number of operations this will make with W*H*S*S where Sis the scale factor, W is width and H is height of input matrix.
I used 2 matrixes m and r, where m is your input and r is your result/output. All that needs to be done is to copy each element from m at positions [i][j] and turn it into a square of elements with the same value of size scale_factor inside r.
Simply put:
int main()
{
Matrix<int> m(2, 2);
// initial values in your example
m[0][0] = 1;
m[0][1] = 2;
m[1][0] = 3;
m[1][1] = 4;
m.Print();
// pick some scale factor and create the new matrix
unsigned long scale = 2;
Matrix<int> r(m.rows*scale, m.columns*scale);
// i know this is bad but it is the most
// straightforward way of doing this
// it is also the only way i can think of :(
for(unsigned long i1 = 0; i1 < m.rows; i1++)
for(unsigned long j1 = 0; j1 < m.columns; j1++)
for(unsigned long i2 = i1*scale; i2 < (i1+1)*scale; i2++)
for(unsigned long j2 = j1*scale; j2 < (j1+1)*scale; j2++)
r[i2][j2] = m[i1][j1];
// the output in your example
std::cout << "\n\n";
r.Print();
return 0;
}
I do not think it is relevant for the question, but i used a class Matrix to store all the elements of the extended matrix. I know it is a distraction but this is still C++ and we have to manage memory. And what you are trying to achieve with this algorithm needs a lot of memory if the scale_factor is big so i wrapped it up using this:
template <typename type_t>
class Matrix
{
private:
type_t** Data;
public:
// should be private and have Getters but
// that would make the code larger...
unsigned long rows;
unsigned long columns;
// 2d Arrays get big pretty fast with what you are
// trying to do.
Matrix(unsigned long rows, unsigned long columns)
{
this->rows = rows;
this->columns = columns;
Data = new type_t*[rows];
for(unsigned long i = 0; i < rows; i++)
Data[i] = new type_t[columns];
}
// It is true, a copy constructor is needed
// as HolyBlackCat pointed out
Matrix(const Matrix& m)
{
rows = m.rows;
columns = m.columns;
Data = new type_t*[rows];
for(unsigned long i = 0; i < rows; i++)
{
Data[i] = new type_t[columns];
for(unsigned long j = 0; j < columns; j++)
Data[i][j] = m[i][j];
}
}
~Matrix()
{
for(unsigned long i = 0; i < rows; i++)
delete [] Data[i];
delete [] Data;
}
void Print()
{
for(unsigned long i = 0; i < rows; i++)
{
for(unsigned long j = 0; j < columns; j++)
std::cout << Data[i][j] << " ";
std::cout << "\n";
}
}
type_t* operator [] (unsigned long row)
{
return Data[row];
}
};
First of all, having a suitable 2D matrix class is presumed but not the question. But I don't know the API of yours, so I'll illustrate with something typical:
struct coord {
size_t x; // x position or column count
size_t y; // y position or row count
};
template <typename T>
class Matrix2D {
⋮ // implementation details
public:
⋮ // all needed special members (ctors dtor, assignment)
Matrix2D (coord dimensions);
coord dimensions() const; // return height and width
const T& cell (coord position) const; // read-only access
T& cell (coord position); // read-write access
// handy synonym:
const T& operator[](coord position) const { return cell(position); }
T& operator[](coord position) { return cell(position); }
};
I just showed the public members I need: create a matrix with a given size, query the size, and indexed access to the individual elements.
So, given that, your problem description is:
template<typename T>
Matrix2D<T> scale_pow2 (const Matrix2D& input, size_t pow)
{
const auto scale_factor= 1 << pow;
const auto size_in = input.dimensions();
Matrix2D<T> result ({size_in.x*scale_factor,size_in.y*scale_factor});
⋮
⋮ // fill up result
⋮
return result;
}
OK, so now the problem is precisely defined: what code goes in the big blank immediately above?
Each cell in the input gets put into a bunch of cells in the output. So you can either iterate over the input and write a clump of cells in the output all having the same value, or you can iterate over the output and each cell you need the value for is looked up in the input.
The latter is simpler since you don't need a nested loop (or pair of loops) to write a clump.
for (coord outpos : /* ?? every cell of the output ?? */) {
coord frompos {
outpos.x >> pow,
outpos.y >> pow };
result[outpos] = input[frompos];
}
Now that's simple!
Calculating the from position for a given output must match the way the scale was defined: you will have pow bits giving the position relative to this clump, and the higher bits will be the index of where that clump came from
Now, we want to set outpos to every legal position in the output matrix indexes. That's what I need. How to actually do that is another sub-problem and can be pushed off with top-down decomposition.
a bit more advanced
Maybe nested loops is the easiest way to get that done, but I won't put those directly into this code, pushing my nesting level even deeper. And looping 0..max is not the simplest thing to write in bare C++ without libraries, so that would just be distracting. And, if you're working with matrices, this is something you'll have a general need for, including (say) printing out the answer!
So here's the double-loop, put into its own code:
struct all_positions {
coord current {0,0};
coord end;
all_positions (coord end) : end{end} {}
bool next() {
if (++current.x < end.x) return true; // not reached the end yet
current.x = 0; // reset to the start of the row
if (++current.y < end.y) return true;
return false; // I don't have a valid position now.
}
};
This does not follow the iterator/collection API that you could use in a range-based for loop. For information on how to do that, see my article on Code Project or use the Ranges stuff in the C++20 standard library.
Given this "old fashioned" iteration helper, I can write the loop as:
all_positions scanner {output.dimensions}; // starts at {0,0}
const auto& outpos= scanner.current;
do {
⋮
} while (scanner.next());
Because of the simple implementation, it starts at {0,0} and advancing it also tests at the same time, and it returns false when it can't advance any more. Thus, you have to declare it (gives the first cell), use it, then advance&test. That is, a test-at-the-end loop. A for loop in C++ checks the condition before each use, and advances at the end, using different functions. So, making it compatible with the for loop is more work, and surprisingly making it work with the ranged-for is not much more work. Separating out the test and advance the right way is the real work; the rest is just naming conventions.
As long as this is "custom", you can further modify it for your needs. For example, add a flag inside to tell you when the row changed, or that it's the first or last of a row, to make it handy for pretty-printing.
summary
You need a bunch of things working in addition to the little piece of code you actually want to write. Here, it's a usable Matrix class. Very often, it's prompting for input, opening files, handling command-line options, and that kind of stuff. It distracts from the real problem, so get that out of the way first.
Write your code (the real code you came for) in its own function, separate from any other stuff you also need in order to house it. Get it elsewhere if you can; it's not part of the lesson and just serves as a distraction. Worse, it may be "hard" in ways you are not prepared for (or to do well) as it's unrelated to the actual lesson being worked on.
Figure out the algorithm (flowchart, pseudocode, whatever) in a general way before translating that to legal syntax and API on the objects you are using. If you're just learning C++, don't get bogged down in the formal syntax when you are trying to figure out the logic. Until you naturally start to think in C++ when doing that kind of planning, don't force it. Use whiteboard doodles, tinkertoys, whatever works for you.
Get feedback and review of the idea, the logic of how to make it happen, from your peers and mentors if available, before you spend time coding. Why write up an idea that doesn't work? Fix the logic, not the code.
Finally, sketch the needed control flow, functions and data structures you need. Use pseudocode and placeholder notes.
Then fill in the placeholders and replace the pseudo with the legal syntax. You already planned it out, so now you can concentrate on learning the syntax and library details of the programming language. You can concentrate on "how do I express (some tiny detail) in C++" rather than keeping the entire program in your head. More generally, isolate a part that you will be learning; be learning/practicing one thing without worrying about the entire edifice.
To a large extent, some of those ideas translate to the code as well. Top-Down Design means you state things at a high level and then implement that elsewhere, separately. It makes code readable and maintainable, as well as easier to write in the first place. Functions should be written this way: the function explains how to do (what it does) as a list of details that are just one level of detail further down. Each of those steps then becomes a new function. Functions should be short and expressed at one semantic level of abstraction. Don't dive down into the most primitive details inside the function that explains the task as a set of simpler steps.
Good luck, and keep it up!

C++ Avoiding Triple Pointers

I am trying to create an array of X pointers referencing matrices of dimensions Y by 16. Is there any way to accomplish this in C++ without the use of triple pointers?
Edit: Adding some context for the problem.
There are a number of geometries on the screen, each with a transform that has been flattened to a 1x16 array. Each snapshot represents the transforms for each of number of components. So the matrix dimensions are 16 by num_components by num_snapshots , where the latter two dimensions are known at run-time. In the end, we have many geometries with motion applied.
I'm creating a function that takes a triple pointer argument, though I cannot use triple pointers in my situation. What other ways can I pass this data (possibly via multiple arguments)? Worst case, I thought about flattening this entire 3D matrix to an array, though it seems like a sloppy thing to do. Any better suggestions?
What I have now:
function(..., double ***snapshot_transforms, ...)
What I want to accomplish:
function (..., <1+ non-triple pointer parameters>, ...)
Below isn't the function I'm creating that takes the triple pointer, but shows what the data is all about.
static double ***snapshot_transforms_function (int num_snapshots, int num_geometries)
{
double component_transform[16];
double ***snapshot_transforms = new double**[num_snapshots];
for (int i = 0; i < num_snapshots; i++)
{
snapshot_transforms[i] = new double*[num_geometries];
for (int j = 0; j < num_geometries; j++)
{
snapshot_transforms[i][j] = new double[16];
// 4x4 transform put into a 1x16 array with dummy values for each component for each snapshot
for (int k = 0; k < 16; k++)
snapshot_transforms[i][j][k] = k;
}
}
return snapshot_transforms;
}
Edit2: I cannot create new classes, nor use C++ features like std, as the exposed function prototype in the header file is getting put into a wrapper (that doesn't know how to interpret triple pointers) for translation to other languages.
Edit3: After everyone's input in the comments, I think going with a flattened array is probably the best solution. I was hoping there would be some way to split this triple pointer and organize this complex data across multiple data pieces neatly using simple data types including single pointers. Though I don't think there is a pretty way of doing this given my caveats here. I appreciate everyone's help =)
It is easier, better, and less error prone to use an std::vector. You are using C++ and not C after all. I replaced all of the C-style array pointers with vectors. The typedef doublecube makes it so that you don't have to type vector<vector<vector<double>>> over and over again. Other than that the code basically stays the same as what you had.
If you don't actually need dummy values I would remove that innermost k loop completely. reserve will reserve the memory space that you need for the real data.
#include <vector>
using std::vector; // so we can just call it "vector"
typedef vector<vector<vector<double>>> doublecube;
static doublecube snapshot_transforms_function (int num_snapshots, int num_geometries)
{
// I deleted component_transform. It was never used
doublecube snapshot_transforms;
snapshot_transforms.reserve(num_snapshots);
for (int i = 0; i < num_snapshots; i++)
{
snapshot_transforms.at(i).reserve(num_geometries);
for (int j = 0; j < num_geometries; j++)
{
snapshot_transforms.at(i).at(j).reserve(16);
// 4x4 transform put into a 1x16 array with dummy values for each component for each snapshot
for (int k = 0; k < 16; k++)
snapshot_transforms.at(i).at(j).at(k) = k;
}
}
return snapshot_transforms;
}
Adding a little bit of object-orientation usually makes the code easier to manage -- for example, here's some code that creates an array of 100 Matrix objects with varying numbers of rows per Matrix. (You could vary the number of columns in each Matrix too if you wanted to, but I left them at 16):
#include <vector>
#include <memory> // for shared_ptr (not strictly necessary, but used in main() to avoid unnecessarily copying of Matrix objects)
/** Represents a (numRows x numCols) 2D matrix of doubles */
class Matrix
{
public:
// constructor
Matrix(int numRows = 0, int numCols = 0)
: _numRows(numRows)
, _numCols(numCols)
{
_values.resize(_numRows*_numCols);
std::fill(_values.begin(), _values.end(), 0.0f);
}
// copy constructor
Matrix(const Matrix & rhs)
: _numRows(rhs._numRows)
, _numCols(rhs._numCols)
{
_values.resize(_numRows*_numCols);
std::fill(_values.begin(), _values.end(), 0.0f);
}
/** Returns the value at (row/col) */
double get(int row, int col) const {return _values[(row*_numCols)+col];}
/** Sets the value at (row/col) to the specified value */
double set(int row, int col, double val) {return _values[(row*_numCols)+col] = val;}
/** Assignment operator */
Matrix & operator = (const Matrix & rhs)
{
_numRows = rhs._numRows;
_numCols = rhs._numCols;
_values = rhs._values;
return *this;
}
private:
int _numRows;
int _numCols;
std::vector<double> _values;
};
int main(int, char **)
{
const int numCols = 16;
std::vector< std::shared_ptr<Matrix> > matrixList;
for (int i=0; i<100; i++) matrixList.push_back(std::make_shared<Matrix>(i, numCols));
return 0;
}

how to assign two 2d array

I have written a program which make a 2d array and then set its numbers.
The second step that I have problem in it is that when I want to shift rows and columns I face with a problem in this line nmatrix[i*c+j] = 0;
the error is this : error: incompatible types in assignment of 'int' to 'int [(((sizetype)(((ssizetype)(c + shiftc)) + -1)) + 1)]'
here is the code :
void shiftMatrix(int *matrix, int r,int c ,int shiftr,int shiftc){
int nmatrix [r+shiftr][c+shiftc];
for(int i = 0; i< shiftr; i++)
{
for(int j = 0; j<shiftc;j++)
{
nmatrix[i*c+j] = 0;
}
}
for(int i = shiftr; i< r; i++)
{
for(int j = shiftc; j<c;j++)
{
nmatrix[i*c+j] = matrix[i*c+j];
}
}
}
Any help please??
thanks in advance
int nmatrix [r+shiftr][c+shiftc];
First of all, you are using an array with non-constant bounds, which is a controversial feature.
In addition, here you are declaring a two-dimensional array nmatrix, but your other matrix (matrix) is a pointer to int (or a one-dimensional array, if you like to look at it this way). This is a recipe for confusion.
You can easily declare nmatrix ("new matrix"?) as a one-dimensional array:
int nmatrix[(r+shiftr) * (c+shiftc)];
Or (presumably better)
std::vector<int> nmatrix((r+shiftr) * (c+shiftc));
Then, your code nmatrix[i*c+j] = 0 will work (however, you have to change c to c+shiftc whenever you work with nmatrix).
You cannot define an array dynamically the way you do it.
You need to use the c++ keyword new:
int nmatrix[][] = new int [r+shiftr][c+shiftc];
You cannot define arrays the way you did, with non constant int value for dimension, because such static arrays are to be defined for memory at the compile stage. Thus dimensions should be const expression.
On the contrary with keyword new you can define dimensions for arrays at run-time stage, because it's dynamic allocation.
There are more detailed answers in this SO question here.

c++ matrix insert value using iterators (homework)

I'm pretty new to C++ and got an assignment to make a matrix using only STL containers. I've used a vector (rows) of vectors (columns). The problem I'm having is in the 'write' operation - for which I may only use an iterator-based implementation. Problem is, quite simply: it writes nothing.
I've tested with a matrix filled with different values, and while the iterator ends up on exactly the right spot, it doesn't change the value.
Here's my code:
void write(matrix mat, int row, int col, int input)
{
assert(row>=0 && col>=0);
assert(row<=mat.R && col<=mat.C);
//I set up the iterators.
vector<vector<int> >::iterator rowit;
vector<int>::iterator colit;
rowit = mat.rows.begin();
//I go to the row.
for(int i = 0; i<row-1; ++i)
{
++rowit;
}
colit = rowit->begin();
//I go to the column.
for(int j = 0; j<col-1; ++j)
{
++colit;
}
*colit = input; //Does nothing.
}
What am I overlooking?
Thanks.
matrix mat is a parameter by value, it copies the matrix and hence you are writing to a copy.
You should pass the matrix by reference instead, like matrix & mat.
But wait... You are passing the matrix every time as the first parameter, this is a bad sign!
This usually indicates that the parameter should be turned into an object on which you can run the methods; that way, you don't need to pass the parameter at all. So, create a Matrix class instead.
Please note that there is std::vector::operator[].
So, you could just do it like this:
void write(matrix & mat, int row, int col, int input)
{
assert(row>=0 && col>=0);
assert(row<=mat.R && col<=mat.C);
mat[row][col] = input;
}

swapping an inner and outer vector

I have a vector of vector of myObjects defined, creating essentially a 2D array. I would like to transpose this array such that rows become columns and columns become rows. Obviously I could do this in a double for-loop, but this seems massively inelegant and will be pretty slow. I was wondering if there's something clever in C++ or the STL that would let me swap the inner and outer vectors around quickly and efficiently, rather than writing...
for (int iRow = 0; iRow < nRows; ++iRow)
{
for (int iCol = 0; iCol < nCols; ++iCol)
{
myNew2DArray[iCol][iRow] = myOriginal2DArray[iRow][iCol];
}
}
Alternatively, you can store the matrix in a vector and have a flag that specifies whether the matrix is transposed or not. Then you simply calculate the index. Here is an example:
class Matrix {
private:
std::vector<int> matrix;
bool isTransposed = false;
int width, height;
public:
// ...
int getElement(int x, int y)
{
int w = width;
int h = height;
if(isTransposed) {
int z = x;
x = y;
y = x;
z = w;
w = h;
h = z;
}
return matrix[y * width + x];
}
// ...
};
This will reduce the cost of transposing the matrix, but increases the cost of actually accessing the elements.
My suggestion would be to make a class called Matrix that contains the matrix that you are talking about. Give the class a function transpose() that toggles a state flag for the state "transposed". Then, overload the [] operator to follow mwd's suggestion of inverting the indeces when the matrix is in the transposed state.
What you've coded already is pretty much the easiest way. Really you don't need a vector of vectors. You can just append each new 'row' to a single vector. Then what would have been element matrix[i][j] in your original vector of vectors is now matrix[(i*n)+j], when n is the 'width' of your matrix. The fiddly part is coming up with the algorithm to perform the transpose. I'm not saying this way is any better, but it's an alternative route, and what you've got already is fine.
Your best bet is using the Eigen matrix library, which stores the transposedness property in a parameter of the matrix class. If that is not an option, google for one of the numerous matrix transpose algorithms.