C# Class TemporalNetworks.TemporalNetworkEnsemble

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

Méthode Description
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

Method Details

InitializeRandomGenerator() public static méthode

Reinitializes the internal random generator with a specific seed
public static InitializeRandomGenerator ( int seed ) : void
seed int
Résultat void

ShuffleEdges() public static méthode

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
Résultat TemporalNetwork

ShuffleTwoPaths() public static méthode

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
Résultat TemporalNetwork