Problem
You want an efficient matrix implementation where the dimensions (i.e., number of rows and columns) are constants known at compile time.
Solution
When the dimensions of a matrix are known at compile time, the compiler can more easily optimize an implementation that accepts the row and columns as template parameters as shown in Example 11-30.
Example 11-30. kmatrix.hpp
#ifndef KMATRIX_HPP
#define KMATRIX_HPP
#include "kvector.hpp"
#include "kstride_iter.hpp"
template
class kmatrix
{
public:
// public typedefs
typedef Value_T value_type;
typedef kmatrix self;
typedef Value_T* iterator;
typedef const Value_T* const_iterator;
typedef kstride_iter row_type;
typedef kstride_iter col_type;
typedef kstride_iter const_row_type;
typedef kstride_iter const_col_type;
// public constants
static const int nRows = Rows_N;
static const int nCols = Cols_N;
// constructors
kmatrix( ) { m = Value_T( ); }
kmatrix(const self& x) { m = x.m; }
explicit kmatrix(Value_T& x) { m = x.m; }
// public functions
static int rows( ) { return Rows_N; }
static int cols( ) { return Cols_N; }
row_type row(int n) { return row_type(begin( ) + (n * Cols_N)); }
col_type col(int n) { return col_type(begin( ) + n); }
const_row_type row(int n) const {
return const_row_type(begin( ) + (n * Cols_N));
}
const_col_type col(int n) const {
return const_col_type(begin( ) + n);
}
iterator begin( ) { return m.begin( ); }
iterator end( ) { return m.begin( ) + size( ); }
const_iterator begin( ) const { return m; }
const_iterator end( ) const { return m + size( ); }
static int size( ) { return Rows_N * Cols_N; }
// operators
row_type operator[](int n) { return row(n); }
const_row_type operator[](int n) const { return row(n); }
// assignment operations
self& operator=(const self& x) { m = x.m; return *this; }
self& operator=(value_type x) { m = x; return *this; }
self& operator+=(const self& x) { m += x.m; return *this; }
self& operator-=(const self& x) { m -= x.m; return *this; }
self& operator+=(value_type x) { m += x; return *this; }
self& operator-=(value_type x) { m -= x; return *this; }
self& operator*=(value_type x) { m *= x; return *this; }
self& operator/=(value_type x) { m /= x; return *this; }
self operator-( ) { return self(-m); }
// friends
friend self operator+(self x, const self& y) { return x += y; }
friend self operator-(self x, const self& y) { return x -= y; }
friend self operator+(self x, value_type y) { return x += y; }
friend self operator-(self x, value_type y) { return x -= y; }
friend self operator*(self x, value_type y) { return x *= y; }
friend self operator/(self x, value_type y) { return x /= y; }
friend bool operator==(const self& x, const self& y) { return x != y; }
friend bool operator!=(const self& x, const self& y) { return x.m != y.m; }
private:
kvector m;
};
#endif
Example 11-31 shows a program that demonstrates how to use the kmatrix template class.
Example 11-31. Using kmatrix
#include "kmatrix.hpp"
#include
using namespace std;
template
void outputRowOrColumn(Iter_T iter, int n) {
for (int i=0; i < n; ++i) {
cout << iter[i] << " ";
}
cout << endl;
}
template
void initializeMatrix(Matrix_T& m) {
int k = 0;
for (int i=0; i < m.rows( ); ++i) {
for (int j=0; j < m.cols( ); ++j) {
m[i][j] = k++;
}
}
}
template
void outputMatrix(Matrix_T& m) {
for (int i=0; i < m.rows( ); ++i) {
cout << "Row " << i << " = ";
outputRowOrColumn(m.row(i), m.cols( ));
}
for (int i=0; i < m.cols( ); ++i) {
cout << "Column " << i << " = ";
outputRowOrColumn(m.col(i), m.rows( ));
}
}
int main( )
{
kmatrix m;
initializeMatrix(m);
m *= 2;
outputMatrix(m);
}
The program in Example 11-31 produces the following output:
Row 0 = 0 2 4 6 Row 1 = 8 10 12 14 Column 0 = 0 8 Column 1 = 2 10 Column 2 = 4 12 Column 3 = 6 14
Discussion
This design and usage for the kmatrix class template in Example 11-30 and Example 11-31 is very similar to the matrix class template presented in Recipe 11.14. The only significant difference is that to declare an instance of a kmatrix you pass the dimensions as template parameters, as follows:
kmatrix m; // declares a matrix with five rows and six columns
It is common for many kinds of applications requiring matricies that the dimensions are known at compile-time. Passing the row and column size as template parameters enables the compiler to more easily apply common optimizations such as loop-unrolling, function inlining, and faster indexing.
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See Also
Recipe 11.14 and Recipe 11.16
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