This class implements the hybrid eigenvector following routine for finding the nearest transition state
*orthogZeroEigs is system dependent, don’t forget to set it*
Parameters :  coords :
pot :
tol :
nsteps :
eigenvec0 :
nsteps_tangent1, nsteps_tangent2 : int
event : callable
iprint :
verbosity : int
orthogZeroEigs : callable
lowestEigenvectorQuenchParams : dict
tangentSpaceQuenchParams : dict
max_uphill_step_initial : float
max_uphill_step : float
check_negative : bool
demand_initial_negative_vec : bool
negatives_before_check : int
nfail_max :
hessian_diagonalization : bool


See also
Notes
It is composed of the following steps:
 Find eigenvector corresponding to the lowest nonzero eigenvector.
 Step uphill in the direction of the lowest eigenvector
 minimize in the space tangent to the lowest eigenvector
The tolerances for the various steps of this algorithm must be correlated. if the tolerance for tangent space search is lower than the total tolerance, then it will never finish
Methods
get_energy()  return the already computed energy at the current position 
get_gradient()  return the already computed gradient at the current position 
params([obj])  
run()  The main loop of the algorithm 