> The failure of the BFGS and Newton tests is likely to be because of
> the high level functions (Numeric/LAPACK matrix operations in this
> case) mentioned by Gary in his post at
> https://mail.gna.org/public/relax-devel/2006-10/msg00117.html
> (Message-id: <4538955F.3090300@xxxxxxxxxxxxxxx>).
After looking more closely at the tests and their output, I realise that
the BFGS and Newton optimisation tests are the only ones failing with
this chi2 problem because they are the only ones setup to produce very
small chi2. The grid search gives finite chi2 for obvious reasons, and
in all of the other tests, optimisation is failing (because max_iter is
set too low, or with OverflowError). This is apparently the intended
behaviour in these tests because the tests pass even though the
optimisation failed. As chi2 never gets small in these tests, rounding
errors etc never become significant and all of these tests pass.
That would make sense. The function tolerance is not reached in the
steepest descent (SD) and coordinate descent (CD) tests. I had to cut
these off early because they take forever to minimise this test data.
The tests still tell you if these methods are working, even if the
minimum is never reached.
I note also that the BFGS and Newton tests are set up to test that the
number of iterations, function calls, etc, are 'correct'. In fact these
also depend on architecture/implimentation issues. These tests are not
evaluated because the chi2 test fails first.
I should probably change the test to print out the expected model-free
parameter values and the minimisation stats (the chi-squared value,
iteration count, function count, gradient count, and Hessian count) as
well as the values and stats returned in the test. After all this is
printed, then the test can be made to fail if necessary. This
additional output should be useful.
Edward
Re: Optimisation tests in the test suite.