MSM Analysis: msmbuilder.msm_analysis¶
Functions for querying markov state models
Notes¶
Some functionality was moved to this module from MSMLib in version 2.6
Model Queries¶
| sample(transition_matrix, state, steps[, ...]) | Generate a random sequence of states by propogating a transition matrix. |
| propagate_model(transition_matrix, n_steps, ...) | Propogate the time evolution of a population vector. |
| get_eigenvectors(t_matrix, n_eigs[, ...]) | Get the left eigenvectors of a transition matrix, sorted by eigenvalue |
| get_implied_timescales(assignments_fn, lag_times) | Calculate implied timescales in parallel using multiprocessing library. |
| project_observable_onto_transition_matrix(...) | Projects an observable vector onto a probability transition matrix’s eigenmodes. |
| calc_expectation_timeseries(tprob, observable) | Calculates the expectation value over time <A(t)> for some observable |
Utils¶
| flatten(*args) | Return a generator for a flattened form of all arguments |
| is_transition_matrix(t_matrix[, epsilon]) | Check for row normalization of a matrix |
| are_all_dimensions_same(*args) | Are all the supplied arguments the same size |
| check_transition(t_matrix[, epsilon]) | Ensure that matrix is a row normalized stochastic matrix |
| check_dimensions(*args) | Ensure that all the dimensions of the inputs are identical |
| check_for_bad_eigenvalues(eigenvalues[, ...]) | Ensure that all eigenvalues are less than or equal to one |