Roughness

Functions to compute the roughness of a given network, as described in https://doi.org/10.1039/D3ME00189J

topsearch.analysis.roughness.get_population(ktn: KineticTransitionNetwork, min_node: int, ts_node: int, lengthscale: float) → float

Compute the population of a given minimum in the network. Population is the value of the RBF kernel at the separation between minimum and transition state

topsearch.analysis.roughness.roughness_contributors(ktn: KineticTransitionNetwork, lengthscale: float = 0.8, features: List[int] = []) → list[RoughnessContribution]

Compute the roughness metric for the current kinetic transition network, and return all the contributing transition states with their frustration values

Returns: a list of frustration contributions

topsearch.analysis.roughness.roughness_metric(ktn: KineticTransitionNetwork, lengthscale: float = 0.8) → float

Compute the roughness metric for the current kinetic transition network