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Make the SVD's output unitary and improved unit tests.

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This commit is contained in:
Hauke Heibel 2010-09-24 16:28:20 +02:00
parent 1c54514bfc
commit 053261de88
2 changed files with 19 additions and 6 deletions
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13
Eigen/src/SVD/SVD.h
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@ -445,6 +445,19 @@ SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix)
m_matU.leftCols(n) = A;
m_matU.rightCols(m-n).setZero();
// Gram Schmidt orthogonalization to fill up U
for (int col = A.cols(); col < A.rows(); ++col)
{
typename MatrixUType::ColXpr colVec = m_matU.col(col);
colVec(col) = 1;
for (int prevCol = 0; prevCol < col; ++prevCol)
{
typename MatrixUType::ColXpr prevColVec = m_matU.col(prevCol);
colVec -= colVec.dot(prevColVec)*prevColVec;
}
m_matU.col(col) = colVec.normalized();
}
m_isInitialized = true;
return *this;
}

12
test/svd.cpp
View File

@ -47,9 +47,9 @@ template<typename MatrixType> void svd(const MatrixType& m)
sigma.diagonal() = svd.singularValues();
matU = svd.matrixU();
//VERIFY_IS_UNITARY(matU);
VERIFY_IS_UNITARY(matU);
matV = svd.matrixV();
//VERIFY_IS_UNITARY(matV);
VERIFY_IS_UNITARY(matV);
VERIFY_IS_APPROX(a, matU * sigma * matV.transpose());
}
@ -57,10 +57,10 @@ template<typename MatrixType> void svd(const MatrixType& m)
if (rows>=cols)
{
SVD<MatrixType> svd(a);
Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> x = Matrix<Scalar, MatrixType::ColsAtCompileTime, 1>::Random(cols,1);
Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> b = a * x;
Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> result = svd.solve(b);
VERIFY_IS_APPROX(a * result, b);
Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> b = Matrix<Scalar, MatrixType::ColsAtCompileTime, 1>::Random(rows,1);
Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> x = svd.solve(b);
// evaluate normal equation which works also for least-squares solutions
VERIFY_IS_APPROX(a.adjoint()*a*x,a.adjoint()*b);
}