Kinetic transition network

Module which contains the KineticTransitionNetwork class. This class has methods for storing and extracting stationary point information encoded as a network graph

class topsearch.data.kinetic_transition_network.KineticTransitionNetwork(dump_path='/home/runner/work/topography-searcher/topography-searcher', dump_suffix='')

Description

A class to store and operate on the network of minima and transition states. Stationary points are stored in a networkx graph. All addition, removal and accessing of properties is performed through this class.

G

The network object that contains all the minima (nodes) and transition states (edges between directly connected minima)

Type:: networkx graph

n_minima

Number of minima in the network

Type:: int

n_ts

Number of transition states in the network

Type:: int

pairlist

Stores the pairs of minima between which connections have already been attempted. Useful to avoid repetition of calculations

Type:: numpy array

similarity

Evalutes the similarity between any two given configurations

Type:: class instance

dump_path

Type:: default directory to dump the network

dump_suffix

Type:: default suffix for dump files

add_minimum(min_coords: NDArray[Any, Any], energy: float) → None: Add a node to the network with data for the minimum

add_network(other_ktn: KineticTransitionNetwork, similarity: StandardSimilarity, coords: StandardCoordinates) → None: Method to combine a second network with the current one. Compares all stationary points in other_ktn and adds any non-repeats to the current network

add_ts(ts_coords: NDArray[Any, Any], energy: float, min_plus: NDArray[Any, Any], min_minus: NDArray[Any, Any]) → None: Add an edge to the network with the transition state data

dump_minima_csv(text_string: str = '') → None: Method to dump all the minima into a csv format

dump_network(text_string: str = '', text_path: str = '') → None: Write network to text files: min.data stores the index and energy. ts.data stores the connected minima and energy. min/ts.coords store the coordinates of each stationary point

get_minimum_coords(minimum: int) → NDArray[Any, Any]: Returns the coordinates of a given node minimum

get_minimum_energy(minimum: int) → float: Returns the energy of a given node minimum

get_ts_coords(min_plus: int, min_minus: int, edge_index: int = 0) → NDArray[Any, Any]: Returns coordinates of edge_index-th ts edge between min_plus and min_minus

get_ts_energy(min_plus: int, min_minus: int, edge_index: int = 0) → float: Returns energy of edge_index-th ts edge between min_plus and min_minus

read_network(text_path: str = '', text_string: str = '') → None: Returns G network from files that resulted from dump_network

remove_all_ts(minimum1: int, minimum2: int) → None: Removes all transition states connecting the two passed minima

remove_all_tss(minima: list) → None: Remove all transition states between minima in one go

remove_minima(minima: list[int]) → None: Remove the nodes with the given indices in removed_minima

remove_minimum(minimum: int) → None: Remove a node from the network correpsonding to index minimum

remove_ts(minimum1: int, minimum2: int, edge_index: int = -1) → None: Remove the edge_index-th transition state connecting the two passed minima If edge_index is not passed, or is equal to -1, will remove the latest TS added

remove_tss(minima: list) → None: Remove an array of transition states in one go

reset_network() → None: Empty the network