1. 18 Jul, 2017 1 commit
    • Lorenz Huedepohl's avatar
      Move module 'elpa_utilities' into legacy API · 3385f14e
      Lorenz Huedepohl authored
      The module is intended to be hidden, thus I moved it into the public
      part of the legacy API.
      Some test programs use it, thus the test programs have now also access
      to ELPA's private modules. This is of course anyway necessary to test
      ELPA internals that are not exposed via the public API.
  2. 17 Jul, 2017 1 commit
    • Pavel Kus's avatar
      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
      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.
  3. 15 Jul, 2017 6 commits
  4. 05 Jul, 2017 1 commit
  5. 30 Jun, 2017 3 commits
  6. 29 Jun, 2017 3 commits
  7. 28 Jun, 2017 1 commit
    • Pavel Kus's avatar
      Python plotting tool for displaying matrices introduced · 9ed892af
      Pavel Kus authored
      Introducing python script plot.py containing several classes used to
      plot matrices stored in block-cyclic distribution as a 1 global matrix.
      Docstrings in plot.py should explain the ussage. There are also two
      use cases included, both with commented scripts (using classes from
      plot.py) and a screenshot. One of the use cases contains also tarball
      with data.
      Apart from that, a VERY simple module matrix_plot.F90 was created. It
      is really simplistic, a more systematic approach towards loging should
      be designed. At the moment, matrix output has to be triggered explicitly
      in the code by calling a macro SAVE_MATR(event_description, iteration).
  8. 14 Jun, 2017 3 commits
  9. 13 Jun, 2017 1 commit
  10. 11 Jun, 2017 1 commit
  11. 10 Jun, 2017 1 commit
  12. 09 Jun, 2017 2 commits
  13. 08 Jun, 2017 1 commit
  14. 06 Jun, 2017 1 commit
  15. 05 Jun, 2017 1 commit
  16. 04 Jun, 2017 3 commits
  17. 03 Jun, 2017 2 commits
  18. 01 Jun, 2017 5 commits
  19. 22 May, 2017 3 commits