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* introduced method createRandomMatrixOfRank (R = U*D*V where U,V unitary, D r-by-c diag. with rank non-zero values)
* switched lu/qr tests to be using createRandomMatrixOfRank * removed unused methods doSomeRankPreservingOperations * removed NOTE about doSomeRankPreservingOperations
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30
test/lu.cpp
30
test/lu.cpp
@@ -25,44 +25,16 @@
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#include "main.h"
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#include <Eigen/LU>
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template<typename Derived>
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void doSomeRankPreservingOperations(Eigen::MatrixBase<Derived>& m)
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{
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typedef typename Derived::RealScalar RealScalar;
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for(int a = 0; a < 3*(m.rows()+m.cols()); a++)
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{
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RealScalar d = Eigen::ei_random<RealScalar>(-1,1);
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int i = Eigen::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 = Eigen::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 = Eigen::ei_random<int>(0,m.cols()-1); // i is a random column number
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do {
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j = Eigen::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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template<typename MatrixType> void lu_non_invertible()
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{
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/* this test covers the following files:
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LU.h
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*/
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// NOTE there seems to be a problem with too small sizes -- could easily lie in the doSomeRankPreservingOperations function
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int rows = ei_random<int>(20,200), cols = ei_random<int>(20,200), cols2 = ei_random<int>(20,200);
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int rank = ei_random<int>(1, std::min(rows, cols)-1);
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MatrixType m1(rows, cols), m2(cols, cols2), m3(rows, cols2), k(1,1);
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m1 = MatrixType::Random(rows,cols);
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if(rows <= cols)
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for(int i = rank; i < rows; i++) m1.row(i).setZero();
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else
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for(int i = rank; i < cols; i++) m1.col(i).setZero();
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doSomeRankPreservingOperations(m1);
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createRandomMatrixOfRank(rank, rows, cols, m1);
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LU<MatrixType> lu(m1);
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typename LU<MatrixType>::KernelResultType m1kernel = lu.kernel();
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