Calculate the evaluation and jacobians of geometry mappings of cells
using sum factorization. By avoiding all geometry mapping of intersections
we can avoid the face-twist problem and just make the grid consistens (not
yet done).

TODO:
- Make grid consistent
- Vectorization
- 3D

Avoid explicit doubles.

Avoid explicit doubles.

This is currently only used for level 4 instrumentation,
as these start and stop markers were messing heavily with
dependencies in the sum factorization code. This way, the necessary but
ugly work of adding instrumentation is separated much more
nicely.

I was tired of the amount of ifs that changed behaviour
depending on stage 1 or 3. This is a cleaner approach.

By implementing repr such that instance addresses are
not part of sorting anymore

It does not yet do all the jobs it can do, but it exists and we can
run tests with it.

Instationary stuff not fixed so far.

When doing jacobians of nonlinear systems, the inames used for
a given sum factorization kernel output depend on the accumulation
context.

Save all stage 1 sum factorization kernels that are used in
accumulation expression in the cache during the dry run. Discard all
inactive sum factorization kernels in decide_vetorization_strategy.

It will be necessary to correctly do fastdg for systems

Make anisotropic quadrature order possible for non DG examples.

- Use TensorProductElement in one example.

- We still use the sumfact option to swicth to the sum factorization
  code branch. This way it is still possible to easily swicth between
  sumfact and non sumfact code.

- Only TensorProductElements with the same degree in all directions
  will work. Anisotropie and adaption of quadrature rule will happen
  in the next commits.