1. 01 Sep, 2017 1 commit
2. 29 Aug, 2017 1 commit
3. 26 Aug, 2017 1 commit
• analytic test for complex case · 3513aec8
Pavel Kus authored
taking into account, that computed eigenvectors can be arbitrarily
"rotated" by multiplying by complex number. Hopefully dealt with in
a robust way. Enabling analytic complex double and single
4. 25 Aug, 2017 1 commit
• templating test_analytic · 15a6cbc3
Pavel Kus authored
test analytic has been transformed to template to allow all
real/complex and single/double variants. However, at this
commit, only real double and real single variants are enabled
5. 24 Aug, 2017 1 commit
6. 21 Aug, 2017 1 commit
7. 18 Aug, 2017 2 commits
8. 17 Aug, 2017 3 commits
9. 10 Aug, 2017 2 commits
10. 31 Jul, 2017 1 commit
11. 30 Jul, 2017 1 commit
• Loop over all possible domain decompositions · fabb1c42
Lorenz Huedepohl authored
We got reports from a user that there were troubles with certain domain
decompositions. So far the tests only looked at (approximately) square
decompositions in column-major process order.

Now, a new class of tests loops over all possible decompositions
(row * col) for a given number of total tasks.

So far, we can not confirm that there are any problems, all
possibilities work as expected.
12. 18 Jul, 2017 3 commits
13. 17 Jul, 2017 2 commits
• Introducing analytical test · 8a9c9df1
Pavel Kus authored
Introducing new test in which matrix and its eigendecomposition is
known and thus can be easily created and checked directly, without the
need to use scalapack or any other communication (apart from reducing
error).

The test is based on the fact, that if L_A and S_A are eigenvalues and
eigenvectors of matrix A, respectively, and L_B and S_B eigenvalues and
eigenvectors of B, then kron(L_A, L_B) and kron (S_A, S_B) are
eigenvalues and eigenvectors of kron(A, B).
Since it is easy to know exact eigendecomposition of a small matrix (e.g.
2x2), and kron operator has very simple structure, we can construct
arbitrarily large matrix and its eigendecomposition. We only have to
select small matrices such that the resulting matrix has unique and
ordered eigenvalues, so that the checking of the result is than easy.
Each element of matrix, eigenvector matrix and eigenvalue vector can
be quickly computed independently, just using its global coordinates.

The test is currently limited to matrices of size 2^n, but by
storing eigendecompositions of more small matrices (e.g. 3x3 and 5x5) we
could construct any matrix of size 2^n*3^m*5^o, which would probably be
sufficient, since most often used sizes (150, 1000, 5000, 2000, 60000)
are of this form.
• Test "eigenvalues" and "solve_tridiagonal" · dde98bdb
Andreas Marek authored
The routines "eigenvalues" and "solve_tridiagonal" are now
also tested directly with the new API (and not only via the
legacy API -> new API mapping)

Todo: adapt test generator script to contain some logic
14. 07 Jul, 2017 1 commit
15. 03 Jul, 2017 1 commit
16. 12 Jun, 2017 1 commit
17. 01 Jun, 2017 2 commits