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0ef1efdbdb
(the global funcs in MathFunctions.h and Fuzzy.h don't count as internal). * Mainpage.dox. Add a few prospective Eigen users; change the recommended -finline-limit from 10000 to 1000. The reason is: it could be harmful to have a too big value here, couldn't it? (e.g. exceedingly large executables, cache misses). Looking at gcc, a value of 900 would exactly mean "determine the inlining of all functions as if they were marked with 'inline' keyword". So a value of 1000 seems a reasonable round number. In the benchmark that motivated this (TestEigenSolvers) a value of 400 is enough on my system.
72 lines
1.8 KiB
C++
72 lines
1.8 KiB
C++
#include <Eigen/Core>
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USING_PART_OF_NAMESPACE_EIGEN
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namespace Eigen {
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template<typename Derived>
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void echelon(MatrixBase<Derived>& m)
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{
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const int N = std::min(m.rows(), m.cols());
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for(int k = 0; k < N; k++)
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{
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int rowOfBiggest, colOfBiggest;
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int cornerRows = m.rows()-k;
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int cornerCols = m.cols()-k;
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m.corner(BottomRight, cornerRows, cornerCols)
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.findBiggestCoeff(&rowOfBiggest, &colOfBiggest);
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m.row(k).swap(m.row(k+rowOfBiggest));
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m.col(k).swap(m.col(k+colOfBiggest));
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for(int r = k+1; r < m.rows(); r++)
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m.row(r).end(cornerCols) -= m.row(k).end(cornerCols) * m(r,k) / m(k,k);
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}
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}
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template<typename Derived>
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void doSomeRankPreservingOperations(MatrixBase<Derived>& m)
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{
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for(int a = 0; a < 3*(m.rows()+m.cols()); a++)
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{
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double d = ei_random<double>(-1,1);
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int i = ei_random<int>(0,m.rows()-1); // i is a random row number
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int j;
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do {
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j = ei_random<int>(0,m.rows()-1);
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} while (i==j); // j is another one (must be different)
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m.row(i) += d * m.row(j);
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i = ei_random<int>(0,m.cols()-1); // i is a random column number
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do {
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j = ei_random<int>(0,m.cols()-1);
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} while (i==j); // j is another one (must be different)
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m.col(i) += d * m.col(j);
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}
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}
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} // namespace Eigen
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using namespace std;
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int main(int, char **)
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{
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srand((unsigned int)time(0));
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const int Rows = 6, Cols = 4;
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typedef Matrix<double, Rows, Cols> Mat;
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const int N = Rows < Cols ? Rows : Cols;
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// start with a matrix m that's obviously of rank N-1
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Mat m = Mat::identity(Rows, Cols); // args just in case of dyn. size
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m.row(0) = m.row(1) = m.row(0) + m.row(1);
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doSomeRankPreservingOperations(m);
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// now m is still a matrix of rank N-1
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cout << "Here's the matrix m:" << endl << m << endl;
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cout << "Now let's echelon m:" << endl;
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echelon(m);
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cout << "Now m is:" << endl << m << endl;
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}
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