The solution is to use FunctionWrappers.jl which provides a high
interface for C function pointers.

All tests passed.

update_state functions but performance gets worst.
With bench/pkg/abstract_arrays.jl i've highligthed each time a function
is in a collection performance gets worst.

Julia shouldn't crash but rather raise an error about the existence
of a function generated by metaprogramming. I didn't manage to isolate
the segfault withtout the package.
To overcome the issue, I add another level of multiple dispatch/abstract
type for synchronized models.
Test of the euclidean distance automaton works.

This commit groups the change operated to the creation of models and
simulate function of a ContinuousTimeModel.
The general idea is to create a concrete type and a simulate function
 per model creation by metaprogramming.
- Now, ContinuousTimeModel is an abstract type. Each creation of a model
defines a concrete type T <: ContinuousTimeModel by meta programming.
- f! and isabsorbing ContinuousTimeModel fields are Symbols.
- simulate(::ContinuousTimeModel) is run by multiple dispatch, according
to the type of the model.

Can't run the whole tests for now but unit/simulate_available_models.jl
runs properly (i've updated the list of models in this commit), and I've
manually checked in the repl that simulations run correctly (distributed
/ plots).

edge_candidates on top-level of next_state! function.

1) LHA now have names. 2) Period automaton executes well and was runned on the doping 3way oscillator model. Not stattistically tested yet

Fix in simulation of macro generated models. Small changes with variables types of the pkg. Small change in test of macro models.

models. It's a better semantic and improve performance as well as
readability of the code. All the tests passes (except the remark in the
last commit).

variableautomaton. It improves performance.

Tests of Cosmos doesn't pass on the bounds (with a parameter equal to
zero). It's a problem of design (there are issues for cosmos too).

of automata: it wasn't an issue about the simulation code of LHA but an
issue of LHA designs.

Improvement of a Cosmos utils method.

Now A.constants is a NamedTuple.

distributed_mean_value_lha now takes several variables.

Fix about methods of SynchronizedTrajectory + tests.

Simulation for ParametricModel works.

efficient.

First bricks of the automaton_abc algorithm.

Add several convenient methods for parameters of model.

Next step: implementation of simulate with resize!.

order to replace vcat by push!.

The benchmarks are at least equal, and better when the buffer size is
small. However, no significative difference of performance with adequate
buffer size.

My opinion the gain can be seen when simulations are going to be very
long with more complicated models than we have implemented for now.

All tests passed.

Add of a new type of Trajectory: SynchronizedTrajectory which is created
by the simulation of a synchronized model with an LHA.

Simulate function for SynchronizedModel executes and is tested by two
simple models.

Next step : Cosmos based tests.

Add of several useful functions for access values of model, lha and
trajectory objects.

an object.

Type stability of simulate, dist, read_trajectory seems to be preserved.