def timescales(self, k=None):
r"""
The relaxation timescales corresponding to the eigenvalues
Parameters
----------
k : int
number of timescales to be returned. By default all available
eigenvalues, minus 1.
Returns
-------
ts : ndarray(m)
relaxation timescales in units of the input trajectory time step,
defined by :math:`-\tau / ln | \lambda_i |, i = 2,...,k+1`.
"""
if k is None:
self._ensure_eigenvalues()
else:
self._ensure_eigenvalues(neig=k + 1)
from msmtools.analysis.dense.decomposition import timescales_from_eigenvalues as _timescales
ts = _timescales(self._eigenvalues, tau=self._timeunit_model.dt)
if k is None:
return ts[1:]
else:
return ts[1:k + 1] # exclude the stationary process
def timescales(self):
r""" Relaxation timescales of the hidden transition matrix
Returns
-------
ts : ndarray(m)
relaxation timescales in units of the input trajectory time step,
defined by :math:`-tau / ln | \lambda_i |, i = 2,...,nstates`, where
:math:`\lambda_i` are the hidden transition matrix eigenvalues.
"""
from msmtools.analysis.dense.decomposition import timescales_from_eigenvalues as _timescales
ts = _timescales(self._eigenvalues, tau=self._lag)
return ts[1:]
def timescales(self):
r""" Relaxation timescales of the hidden transition matrix
Returns
-------
ts : ndarray(m)
relaxation timescales in units of the input trajectory time step,
defined by :math:`-tau / ln | \lambda_i |, i = 2,...,nstates`, where
:math:`\lambda_i` are the hidden transition matrix eigenvalues.
"""
from msmtools.analysis.dense.decomposition import timescales_from_eigenvalues as _timescales
ts = _timescales(self._eigenvalues, tau=self._lag)
return ts[1:]