msmtools.flux.ReactiveFlux¶

class
msmtools.flux.
ReactiveFlux
(A, B, flux, mu=None, qminus=None, qplus=None, gross_flux=None)¶ A>B reactive flux from transition path theory (TPT)
This object describes a reactive flux, i.e. a network of fluxes from a set of source states A, to a set of sink states B, via a set of intermediate nodes. Every node has three properties: the stationary probability mu, the forward committor qplus and the backward committor qminus. Every pair of edges has the following properties: a flux, generally a net flux that has no unnecessary backfluxes, and optionally a gross flux.
Flux objects can be used to compute transition pathways (and their weights) from A to B, the total flux, the total transition rate or mean first passage time, and they can be coarsegrained onto a set discretization of the node set.
Fluxes can be computed in EMMA using transition path theory  see
msmtools.tpt()
Parameters:  A (array_like) – List of integer state labels for set A
 B (array_like) – List of integer state labels for set B
 flux ((n,n) ndarray or scipy sparse matrix) – effective or net flux of A>B pathways
 mu ((n,) ndarray (optional)) – Stationary vector
 qminus ((n,) ndarray (optional)) – Backward committor for A>B reaction
 qplus ((n,) ndarray (optional)) – Forward committor for A> B reaction
 gross_flux ((n,n) ndarray or scipy sparse matrix) – gross flux of A>B pathways, if available
Notes
Reactive flux contains a flux network from educt states (A) to product states (B).
See also
msmtools.tpt

__init__
(A, B, flux, mu=None, qminus=None, qplus=None, gross_flux=None)¶ x.__init__(…) initializes x; see help(type(x)) for signature
Methods
__init__
(A, B, flux[, mu, qminus, qplus, …])x.__init__(…) initializes x; see help(type(x)) for signature coarse_grain
(user_sets)Coarsegrains the flux onto userdefined sets. major_flux
([fraction])Returns the main pathway part of the net flux comprising at most the requested fraction of the full flux. pathways
([fraction, maxiter])Decompose flux network into dominant reaction paths. Attributes
A
Returns the set of reactant (source) states. B
Returns the set of product (target) states I
Returns the set of intermediate states backward_committor
Returns the backward committor probability committor
Returns the forward committor probability flux
Returns the effective or net flux forward_committor
Returns the forward committor probability gross_flux
Returns the gross A–>B flux mfpt
Returns the rate (inverse mfpt) of A–>B transitions net_flux
Returns the effective or net flux nstates
Returns the number of states. rate
Returns the rate (inverse mfpt) of A–>B transitions stationary_distribution
Returns the stationary distribution total_flux
Returns the total flux 
A
¶ Returns the set of reactant (source) states.

B
¶ Returns the set of product (target) states

I
¶ Returns the set of intermediate states

backward_committor
¶ Returns the backward committor probability

coarse_grain
(user_sets)¶ Coarsegrains the flux onto userdefined sets.
Parameters: user_sets (list of intiterables) – sets of states that shall be distinguished in the coarsegrained flux. Returns: (sets, tpt) – sets contains the sets tpt is computed on. The tpt states of the new tpt object correspond to these sets of states in this order. Sets might be identical, if the user has already provided a complete partition that respects the boundary between A, B and the intermediates. If not, Sets will have more members than provided by the user, containing the “remainder” states and reflecting the splitting at the A and B boundaries. tpt contains a new tpt object for the coarsegrained flux. All its quantities (gross_flux, net_flux, A, B, committor, backward_committor) are coarsegrained to sets. Return type: (list of intiterables, tptobject) Notes
All userspecified sets will be split (if necessary) to preserve the boundary between A, B and the intermediate states.

committor
¶ Returns the forward committor probability

flux
¶ Returns the effective or net flux

forward_committor
¶ Returns the forward committor probability

gross_flux
¶ Returns the gross A–>B flux

major_flux
(fraction=0.9)¶ Returns the main pathway part of the net flux comprising at most the requested fraction of the full flux.

mfpt
¶ Returns the rate (inverse mfpt) of A–>B transitions

net_flux
¶ Returns the effective or net flux

nstates
¶ Returns the number of states.

pathways
(fraction=1.0, maxiter=1000)¶ Decompose flux network into dominant reaction paths.
Parameters:  fraction (float, optional) – Fraction of total flux to assemble in pathway decomposition
 maxiter (int, optional) – Maximum number of pathways for decomposition
Returns:  paths (list) – List of dominant reaction pathways
 capacities (list) – List of capacities corresponding to each reactions pathway in paths
References
[1] P. Metzner, C. Schuette and E. VandenEijnden. Transition Path Theory for Markov Jump Processes. Multiscale Model Simul 7: 11921219 (2009)

rate
¶ Returns the rate (inverse mfpt) of A–>B transitions

stationary_distribution
¶ Returns the stationary distribution

total_flux
¶ Returns the total flux