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:]