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Reticula
Reticula
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  • Generating networks
    • Path graphs
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    • Random Erdős–Rényi network
    • Random Barabási–Albert network
    • Random k-regular network
    • Random degree-sequence network
    • Random expected degree-sequence network
    • Random uniform hypergraphs
    • Fully-mixed temporal network
    • Link activation temporal network
    • Node activation temporal network
  • Randomising networks
    • Static Network Link Shuffling
    • Temporal Network Link Shuffling
    • Event shuffling
    • Timeline Shuffling
  • Network operations
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    • Occupation operations
    • Cartesian product
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  • Algorithms
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    • Assortativity
    • Static network reachability
    • Temporal network reachability
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    • Isotropic bond percolation in G(n, p) networks
    • Spreading and reachability in temporal networks
  • Citing Reticula
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Link activation temporal network¶

With residual time distribution¶

random_link_activation_temporal_network(base_net, max_t, iet_dist, res_dist, random_state, size_hint: int = 0)¶
template<temporal_network_edge EdgeT, typename ActivationF, typename ResActivationF, std::uniform_random_bit_generator Gen>
network<EdgeT> random_link_activation_temporal_network(const network<typename EdgeT::StaticProjectionType> &base_net, typename EdgeT::TimeType max_t, ActivationF &&inter_event_time_edge_activation, ResActivationF &&residual_time_edge_activation, Gen &generator, std::size_t size_hint = 0)¶

Generates a random link-activation temporal network by activating the edges in base_net first according to the residual time distribution (for the first activation time) then based on the inter-event time distribution, for time values from 0 to max_t (exclusive).

See the list of distributions in the relevant section of the documentation.

The output type depends on the type of base_net. If a (un)directed network or a (un)directed hypernetwork is provided, the output will be a (un)directed temporal network or a (un)directed temporal hypernetwork.

With burn-in¶

random_link_activation_temporal_network(base_net, max_t, iet_dist, random_state, size_hint: int = 0)
template<temporal_network_edge EdgeT, typename ActivationF, std::uniform_random_bit_generator Gen>
network<EdgeT> random_link_activation_temporal_network(const network<typename EdgeT::StaticProjectionType> &base_net, typename EdgeT::TimeType max_t, ActivationF &&inter_event_time_edge_activation, Gen &generator, std::size_t size_hint = 0)¶

Generates a random link-activation temporal network without a residual time distribution, by burning-in the inter-event time distribution for max_t time before recording events. The output events have times values from 0 to max_t (exclusive).

See the list of distributions in the relevant section of the documentation.

Warning

This approach might not work on all distributions. It is up to the user to think about whether this suits their use case.

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Node activation temporal network
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Fully-mixed temporal network
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On this page
  • Link activation temporal network
    • With residual time distribution
      • random_link_activation_temporal_network()
      • random_link_activation_temporal_network()
    • With burn-in
      • random_link_activation_temporal_network()