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Update SVD Module to allow specifying computation options with a template parameter. Resolves #2051

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Arthur
2021-11-29 20:50:46 +00:00
committed by Rasmus Munk Larsen
parent 4a76880351
commit eef33946b7
23 changed files with 766 additions and 636 deletions
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4
doc/UsingBlasLapackBackends.dox
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@@ -101,8 +101,8 @@ m1.colPivHouseholderQr();
?geqp3
\endcode</td></tr>
<tr class="alt"><td>Singular value decomposition \n \c EIGEN_USE_LAPACKE </td><td>\code
JacobiSVD<MatrixXd> svd;
svd.compute(m1, ComputeThinV);
JacobiSVD<MatrixXd, ComputeThinV> svd;
svd.compute(m1);
\endcode</td><td>\code
?gesvd
\endcode</td></tr>

2
doc/examples/TutorialLinAlgSVDSolve.cpp
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@@ -11,5 +11,5 @@ int main()
VectorXf b = VectorXf::Random(3);
cout << "Here is the right hand side b:\n" << b << endl;
cout << "The least-squares solution is:\n"
<< A.bdcSvd(ComputeThinU | ComputeThinV).solve(b) << endl;
<< A.template bdcSvd<ComputeThinU | ComputeThinV>().solve(b) << endl;
}

2
doc/snippets/JacobiSVD_basic.cpp
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@@ -1,6 +1,6 @@
MatrixXf m = MatrixXf::Random(3,2);
cout << "Here is the matrix m:" << endl << m << endl;
JacobiSVD<MatrixXf> svd(m, ComputeThinU | ComputeThinV);
JacobiSVD<MatrixXf, ComputeThinU | ComputeThinV> svd(m);
cout << "Its singular values are:" << endl << svd.singularValues() << endl;
cout << "Its left singular vectors are the columns of the thin U matrix:" << endl << svd.matrixU() << endl;
cout << "Its right singular vectors are the columns of the thin V matrix:" << endl << svd.matrixV() << endl;