C# Класс TemporalNetworks.TemporalNetworkEnsemble

This class contains a number of static methods to create random temporal networks with given betweenness preference

Открытые методы

Метод	Описание
InitializeRandomGenerator ( int seed ) : void	Reinitializes the internal random generator with a specific seed
ShuffleEdges ( TemporalNetwork net, int length, int precision = 1000 ) : TemporalNetwork	Creates a random temporal network by shuffling the edges present in an original weighted network
ShuffleTwoPaths ( TemporalNetwork temp_net, int length, int precision = 1000 ) : TemporalNetwork	This method creates a random sequence of two paths, where the betweenness preferences as well as edge weights match those of a given temporal network. The model implemented here can be viewd in two different ways: 1.) It can be seen as a reshuffling of two paths realized in a given temporal network, while destroying other correlations like bursty activity patterns 2.) Alternatively, it can be seen as a random sampling based on the betweenness preference matrices of nodes as computed from an empirical network

Описание методов

InitializeRandomGenerator() публичный статический Метод

Reinitializes the internal random generator with a specific seed

public static InitializeRandomGenerator ( int seed ) : void
seed	int
Результат	void

ShuffleEdges() публичный статический Метод

Creates a random temporal network by shuffling the edges present in an original weighted network

public static ShuffleEdges ( TemporalNetwork net, int length, int precision = 1000 ) : TemporalNetwork
net	TemporalNetwork	The weighted network to draw the microstate from
length	int	The length of the sequence in terms of the number of time-stamped interactions
precision	int
Результат	TemporalNetwork

ShuffleTwoPaths() публичный статический Метод

This method creates a random sequence of two paths, where the betweenness preferences as well as edge weights match those of a given temporal network. The model implemented here can be viewd in two different ways: 1.) It can be seen as a reshuffling of two paths realized in a given temporal network, while destroying other correlations like bursty activity patterns 2.) Alternatively, it can be seen as a random sampling based on the betweenness preference matrices of nodes as computed from an empirical network

public static ShuffleTwoPaths ( TemporalNetwork temp_net, int length, int precision = 1000 ) : TemporalNetwork
temp_net	TemporalNetwork	The temporal network based on which a randomized sequence of two paths will be created
length	int	The length of the sequence in terms of the number of time-stamped interactions
precision	int	The numerical precision that will be used when sampling from the distribution. This /// at the same time affects the memory requirements of the procedure, which is at most precision*two_paths in the input network
Результат	TemporalNetwork