pyemma.msm.its

pyemma.msm.its(dtrajs, lags=None, nits=10, reversible=True, connected=True)

Calculate implied timescales for a series of lag times.

Parameters:
  • dtrajs (array-like or list of array-likes) – discrete trajectories
  • lags (array-like of integers (optional)) – integer lag times at which the implied timescales will be calculated
  • nits (int (optional)) – number of implied timescales to be computed. Will compute less if the number of states are smaller
  • connected (boolean (optional)) – If true compute the connected set before transition matrix estimation at each lag separately
  • reversible (boolean (optional)) – Estimate the transition matrix reversibly (True) or nonreversibly (False)
Returns:

itsobj
Return type:

ImpliedTimescales object

See also

ImpliedTimescales()
The object returned by this function.
pyemma.plots.plot_implied_timescales()
Plotting function for the ImpliedTimescales object

References

[1]Swope, W. C. and J. W. Pitera and F. Suits Describing protein folding kinetics by molecular dynamics simulations: 1. Theory. J. Phys. Chem. B 108: 6571-6581 (2004)