Singular Value Decomposition Solvers - SVD

slepc-3.14.2 2021-02-01
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## Singular Value Decomposition Solvers - SVD: Examples

The Singular Value Decomposition Solver (SVD) is very similar to the EPS object, but intended for the computation of the partial SVD of a rectangular matrix. With this type of object, the user can specify an SVD problem and solve it with any of the different solvers encapsulated by the package. Some of these solvers are actually implemented through calls to EPS eigensolvers.

The user interface is very similar to that of EPS, both for the options database (e.g., `-svd_nsv 4 -svd_type lanczos`), and for the programmatic interface (e.g., SVDSetDimensions() / SVDSetType()).

test1.c: Test the solution of a SVD without calling SVDSetFromOptions (based on ex8
test2.c: Test SVD with different builds with a matrix loaded from a file
test3.c: Test SVD with user-provided initial vectors
test4.c: Test an SVD problem with more columns than rows
test5.c: Test SVD view and monitor functionality
test6.c: SVD via the cross-product matrix with a user-provided EPS
test7.c: SVD via the cyclic matrix with a user-provided EPS
test8.c: Tests multiple calls to SVDSolve changing ncv
test9.c: Tests multiple calls to SVDSolve with different matrix size
test10.c: Lanczos SVD
test11.c: Tests a user-defined convergence test (based on ex8
test12.c: SVD problem with user-defined stopping test
test13.c: Test interface to external package PRIMME