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_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_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 event have times values from 0 to
max_t (exclusive).
See the list of distributions in the relevant section of the documentation.
This approach might not work on all distributions. It is up to the user to think about whether this suits their use case.