msmbuilder.msm_analysis.calc_expectation_timeseries¶
- msmbuilder.msm_analysis.calc_expectation_timeseries(tprob, observable, init_pop=None, timepoints=1000000, n_modes=100, lagtime=15.0)[source]¶
Calculates the expectation value over time <A(t)> for some observable in an MSM. Does this by eigenvalue decomposition, according to the eq
math :: langle A
angle (t) = sum_{i=0}^N langle p(0), psi^L_i
angle e^{ - lambda_i t } langle psi^R_i, A angle
Parameters: tprob : matrix
The transition probability matrix (of size N) for the MSM.
- observable : array_like, float
A len N array of the values A of the observable for each state.
- init_pop : array_like, float
A len N array of the initial populations of each state. If None is passed, then the function will start from even populations in each state.
- timepoints : int
The number of timepoints to calculate - the final timeseries will be in length LagTime x timepoints
- n_modes : int
The number of eigenmodes to include in the calculation. This number will depend on the timescales involved in the relatation of the observable.
Returns: timeseries : array_like, float
A timeseries of the observable over time, in units of the lag time of the transition matrix.