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and supplied to the elpa object by set methods

because otherwise the cannons algorithm is not usually tested

added possibility to re-use the already decomposed matrix B in the
generalized problem
Added respective test

* tested with elpa1 only (should be sufficient)
* not using Hermitian multiply at the moment
* requires scalapack

executables were generated event though the functionality is not present
in test.c

test.c currently does not support all the flags test.F90 does, so there
were a lot of useless test cases generated.

- per default only some tests are run
- by setting CHECK_LEVEL=extended all test jobs are run

To be used like this

   class(elpa_t), pointer      :: e
   class(elpa_autotune_t), pointer :: tune_state

   e => elpa_allocate()
   call e%set(...)
   [...]
   assert_elpa_ok(e%setup())

   tune_state => e%autotune_setup(ELPA_AUTOTUNE_FAST, ELPA_AUTOTUNE_DOMAIN_REAL)

   ! Autotuning loop, continues until all combinations have been tried
   do while (e%autotune_step(tune_state))
     ! Do the steps that are representative of your calculation
     call e%eigenvectors(a, ev, z, error)
   end do

   ! Fix best parameters, and de-allocate the autotune object
   call e%autotune_set_best(tune_state)
   call elpa_autotune_deallocate(tune_state)

both fortran and C tests generated in generate_automake_test_programs.py
linker flags added by hand -- FIX this

adding variants for single precision and complex math datatype
for the scalapack test

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

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

with obvious meaning