Major fix of type unstabilities which improved performances.
For now on, we observe for pygmalion benchmarks:
+2x speed simulation compared to simulation of models.
100x speed in terms of reading values (no allocations).

Add of bench for @view macro.

Implementation of the lp distance for trajectories.
Add of unit tests for lp distance.

previously loaded model). The package warns when this happen.

Several benchmarks for the data structure. Now we chose the row buffer
method according to results (mainly because the trajectory access with
far way faster, but strangly not that much differences in other cases).

- Add of benchmark scripts that compares perf wrt pygmalion.
=> As expected it is bad in terms of reading cost (because of row by row
matrix read) but it is also not good in terms of simulation cost.
hcat seems to perform badly, should investigate.