Remove for-loops inside the function.

Main change
- Variable local_beta, local_alpha, and local_gamma are made property objects.

Minor change
- Add an option to plot phase space in different style.

Remove part which was causing "damping".
We have to re-process the wake function at each track call and not to reuse the previously processed wake function

WakePotential -> add method to plot wake potential for a perfect gaussian bunch
utilities -> new function gaussian_bunch which gives the gaussian bunch profile
utilities -> read_IW2D now also reads wake function from IW2D
utilities -> new function read_IW2D_folder which reads the full results folder of IW2D into a WakeField element.
resistive_wall -> change the sign of the wake functions to agree with the code convention

Bugfix due to switch to numpy arrays.
Allow to save less mp than the full number in the bunch.

Bugfix2 : PhaseSpaceMonitor

Fix dipole_moment due to switch to numpy arrays for Bunch.binning

Update docstrings
Use pd.DataFrame representation for bunch __repr__
Add the track_alive option for Bunch and Beam.init_beam

The exact wake function for the transverse wake function is wrong (from paper) ! Need to find a better expression.

Change track method to allow for Beam objects
If pynaff can not find the tune, the tune value is nan.
Nanmean and nanstd are used to avoid to bias the tune value.
! Untested if some particles are lost !

WakePotentialMonitor now use interpolation on a fixed grid to be able to save the wake potential data (which size change from turn to turn).

1st test, not complete

Now based on two time arrays!
The bunch profile is computed from its own time array and interpolated into the wake function time array.
The input wake functions must be uniformly sampled!
Reference computation now gives loss factor and kick factor.
Tested with Wlong and Wxdip/Wydip -> OK
Untested for Wxquad/Wyquad.

Add CavityResonator class
Add BeamLoadingVlasov class, to do tested and developped further.
From BeamLoadingVlasov, only the beam_equilibrium method is well tested and benchmarked.
The cannonical_transform and solveB methods have to be tested and benchmarked further.

Compared to mbtrack, the head/tail convention is reversed which leads to this sign change.
In this python code, the head is for negative times, t<0.
The sign change allows successful tracking benchmark with mbtrack for pure inductive and resonator impedance

# Conflicts:
#	tracking/synchrotron.py

Modify the docstrings and add some precisions.

A method to compare energy loss from a wake potential to a loss factor.
Minor changes :
- sigma method in Ring object has been edited.
- add WakePotential in __init__ in tracking module.

Correct scale in plot_wakedata
Avoid circular import by moving import in function

Remove mean of tau array during wake function interpolation to avoid wrong interpolation if tau is not centered on zero

Add docstrings to Impedance and WakeFunction class
Rename functions for deconvolution method

Add transverse wake potential to WakePotential and move class to dedicated file
Merge Resonator and TransverseResonator into Resonator with dedicated file
wakefunction_from_imp -> change trimming to allow for a float value
wakefunction_from_imp -> transverse impedance divided by 1j, to be checked with impedance convention but ok with benchmark
Wakefield -> add wake_components