Reduced row echelon form: Difference between revisions

Undo revision 281314 by BobG112 (talk) Reinstate 8 year old code deleted without explanation by a new user
(Undo revision 281283 by Thundergnat (talk))
(Undo revision 281314 by BobG112 (talk) Reinstate 8 year old code deleted without explanation by a new user)
Line 809:
return 0;
}</lang>
 
=={{header|C++}}==
Note: This code is written in generic form. While it slightly complicates the code, it allows to use the same code for both built-in arrays and matrix classes. To use it with a matrix class, either program the matrix class to the specifications given in the matrix_traits comment, or specialize matrix_traits for the specific interface of your matrix class.
 
The test code uses a built-in array for the matrix.
 
{{works with|g++|4.1.2 20061115 (prerelease) (Debian 4.1.1-21)}}
<lang cpp>#include <algorithm> // for std::swap
#include <cstddef>
#include <cassert>
 
// Matrix traits: This describes how a matrix is accessed. By
// externalizing this information into a traits class, the same code
// can be used both with native arrays and matrix classes. To use the
// default implementation of the traits class, a matrix type has to
// provide the following definitions as members:
//
// * typedef ... index_type;
// - The type used for indexing (e.g. size_t)
// * typedef ... value_type;
// - The element type of the matrix (e.g. double)
// * index_type min_row() const;
// - returns the minimal allowed row index
// * index_type max_row() const;
// - returns the maximal allowed row index
// * index_type min_column() const;
// - returns the minimal allowed column index
// * index_type max_column() const;
// - returns the maximal allowed column index
// * value_type& operator()(index_type i, index_type k)
// - returns a reference to the element i,k, where
// min_row() <= i <= max_row()
// min_column() <= k <= max_column()
// * value_type operator()(index_type i, index_type k) const
// - returns the value of element i,k
//
// Note that the functions are all inline and simple, so the compiler
// should completely optimize them away.
template<typename MatrixType> struct matrix_traits
{
typedef typename MatrixType::index_type index_type;
typedef typename MatrixType::value_type value_type;
static index_type min_row(MatrixType const& A)
{ return A.min_row(); }
static index_type max_row(MatrixType const& A)
{ return A.max_row(); }
static index_type min_column(MatrixType const& A)
{ return A.min_column(); }
static index_type max_column(MatrixType const& A)
{ return A.max_column(); }
static value_type& element(MatrixType& A, index_type i, index_type k)
{ return A(i,k); }
static value_type element(MatrixType const& A, index_type i, index_type k)
{ return A(i,k); }
};
 
// specialization of the matrix traits for built-in two-dimensional
// arrays
template<typename T, std::size_t rows, std::size_t columns>
struct matrix_traits<T[rows][columns]>
{
typedef std::size_t index_type;
typedef T value_type;
static index_type min_row(T const (&)[rows][columns])
{ return 0; }
static index_type max_row(T const (&)[rows][columns])
{ return rows-1; }
static index_type min_column(T const (&)[rows][columns])
{ return 0; }
static index_type max_column(T const (&)[rows][columns])
{ return columns-1; }
static value_type& element(T (&A)[rows][columns],
index_type i, index_type k)
{ return A[i][k]; }
static value_type element(T const (&A)[rows][columns],
index_type i, index_type k)
{ return A[i][k]; }
};
 
// Swap rows i and k of a matrix A
// Note that due to the reference, both dimensions are preserved for
// built-in arrays
template<typename MatrixType>
void swap_rows(MatrixType& A,
typename matrix_traits<MatrixType>::index_type i,
typename matrix_traits<MatrixType>::index_type k)
{
matrix_traits<MatrixType> mt;
typedef typename matrix_traits<MatrixType>::index_type index_type;
 
// check indices
assert(mt.min_row(A) <= i);
assert(i <= mt.max_row(A));
 
assert(mt.min_row(A) <= k);
assert(k <= mt.max_row(A));
 
for (index_type col = mt.min_column(A); col <= mt.max_column(A); ++col)
std::swap(mt.element(A, i, col), mt.element(A, k, col));
}
 
// divide row i of matrix A by v
template<typename MatrixType>
void divide_row(MatrixType& A,
typename matrix_traits<MatrixType>::index_type i,
typename matrix_traits<MatrixType>::value_type v)
{
matrix_traits<MatrixType> mt;
typedef typename matrix_traits<MatrixType>::index_type index_type;
 
assert(mt.min_row(A) <= i);
assert(i <= mt.max_row(A));
 
assert(v != 0);
 
for (index_type col = mt.min_column(A); col <= mt.max_column(A); ++col)
mt.element(A, i, col) /= v;
}
 
// in matrix A, add v times row k to row i
template<typename MatrixType>
void add_multiple_row(MatrixType& A,
typename matrix_traits<MatrixType>::index_type i,
typename matrix_traits<MatrixType>::index_type k,
typename matrix_traits<MatrixType>::value_type v)
{
matrix_traits<MatrixType> mt;
typedef typename matrix_traits<MatrixType>::index_type index_type;
 
assert(mt.min_row(A) <= i);
assert(i <= mt.max_row(A));
 
assert(mt.min_row(A) <= k);
assert(k <= mt.max_row(A));
 
for (index_type col = mt.min_column(A); col <= mt.max_column(A); ++col)
mt.element(A, i, col) += v * mt.element(A, k, col);
}
 
// convert A to reduced row echelon form
template<typename MatrixType>
void to_reduced_row_echelon_form(MatrixType& A)
{
matrix_traits<MatrixType> mt;
typedef typename matrix_traits<MatrixType>::index_type index_type;
 
index_type lead = mt.min_row(A);
 
for (index_type row = mt.min_row(A); row <= mt.max_row(A); ++row)
{
if (lead > mt.max_column(A))
return;
index_type i = row;
while (mt.element(A, i, lead) == 0)
{
++i;
if (i > mt.max_row(A))
{
i = row;
++lead;
if (lead > mt.max_column(A))
return;
}
}
swap_rows(A, i, row);
divide_row(A, row, mt.element(A, row, lead));
for (i = mt.min_row(A); i <= mt.max_row(A); ++i)
{
if (i != row)
add_multiple_row(A, i, row, -mt.element(A, i, lead));
}
}
}
 
// test code
#include <iostream>
 
int main()
{
double M[3][4] = { { 1, 2, -1, -4 },
{ 2, 3, -1, -11 },
{ -2, 0, -3, 22 } };
 
to_reduced_row_echelon_form(M);
for (int i = 0; i < 3; ++i)
{
for (int j = 0; j < 4; ++j)
std::cout << M[i][j] << '\t';
std::cout << "\n";
}
 
return EXIT_SUCCESS;
}</lang>
{{out}}
<pre>
1 0 0 -8
-0 1 0 1
-0 -0 1 -2
</pre>
 
=={{header|C sharp|C#}}==
10,333

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