  One-dimensional run-and-tumble processes may converge towards some localized
non-equilibrium steady state when the two velocities and/or the two switching
rates are space-dependent. A long dynamical trajectory can be then analyzed via
the large deviations at Level 2.5 for the joint probability of the empirical
densities, of the empirical spatial currents and of the empirical switching
flows. The Level 2 for the empirical densities alone can be then derived via
the optimization of the Level 2.5 over the empirical flows. More generally, the
large deviations of any time-additive observable can be also obtained via
contraction from the Level 2.5, or equivalently via the deformed generator
method and the corresponding Doob conditioned process. Finally, the large
deviations for the empirical intervals between consecutive switching events can
be obtained via the introduction of the alternate Markov chain that governs the
series of all the switching events of a long trajectory.
