std::string beta_transition::fire(MLNetworkSharedPtr& mnet, const NodeSharedPtr& node, long time) {
std::string current_status = mnet->actor_features()->getString(node->actor->id,_S_current);
if (current_status==status) {
for (NodeSharedPtr n: mnet->neighbors(node,IN)) {
if (mnet->actor_features()->getString(n->actor->id,_S_current)==neighbor_status && test(beta)) {
return new_status;
}
}
}
return "";
}
property_matrix<ActorSharedPtr,LayerSharedPtr,double> actor_degree_property_matrix(const MLNetworkSharedPtr& mnet, edge_mode mode) {
property_matrix<ActorSharedPtr,LayerSharedPtr,double> P(mnet->get_actors()->size(),mnet->get_layers()->size(),0);
for (ActorSharedPtr actor: *mnet->get_actors()) {
for (LayerSharedPtr layer: *mnet->get_layers()) {
NodeSharedPtr node = mnet->get_node(actor,layer);
if (!node) P.set_na(actor,layer);
else P.set(actor,layer,mnet->neighbors(node,mode)->size());
}
}
return P;
}
double relevance(const MLNetworkSharedPtr& mnet, const ActorSharedPtr& actor, const LayerSharedPtr& layer, edge_mode mode) {
set<actor_id> neighbors_on_selected_layers;
set<actor_id> all_neighbors;
for (NodeSharedPtr node: *mnet->get_nodes(actor)) {
for (NodeSharedPtr neighbor: *mnet->neighbors(node, mode)) {
all_neighbors.insert(neighbor->actor->id);
if (layer == neighbor->layer)
neighbors_on_selected_layers.insert(neighbor->actor->id);
}
}
if (all_neighbors.size()==0) return 0; // by definition
else return (double)neighbors_on_selected_layers.size()/all_neighbors.size();
}
// only works for multiplex networks (no inter-layer edges)
property_matrix<triad,LayerSharedPtr,bool> triangle_existence_property_matrix(const MLNetworkSharedPtr& mnet) {
long n = mnet->get_actors()->size();
property_matrix<triad,LayerSharedPtr,bool> P(n*(n-1)*(n-2)/6,mnet->get_layers()->size(),false);
for (LayerSharedPtr layer: *mnet->get_layers()) {
hash_set<NodeSharedPtr> processed1;
for (NodeSharedPtr n1: *mnet->get_nodes(layer)) {
processed1.insert(n1);
hash_set<NodeSharedPtr> processed2;
for (NodeSharedPtr n2: *mnet->neighbors(n1,INOUT)) {
if (processed1.count(n2)>0) continue;
processed2.insert(n2);
for (NodeSharedPtr n3: *mnet->neighbors(n2,INOUT)) {
if (processed1.count(n3)>0) continue;
if (processed2.count(n3)>0) continue;
if (mnet->get_edge(n3,n1)) {
triad t(n1->actor,n2->actor,n3->actor);
P.set(t,layer,true);
}
}
}
}
}
return P;
}
double cc(const MLNetworkSharedPtr& mnet, const NodeSharedPtr& node) {
int num_edges = 0;
NodeListSharedPtr neigh = mnet->neighbors(node,INOUT);
int num_neigh = neigh->size();
if (num_neigh<=1) return 0.0;
for (NodeSharedPtr n1: *neigh) {
for (NodeSharedPtr n2: *neigh) {
if (n1>=n2) continue;
if (mnet->get_edge(n1,n2))
num_edges++;
}
}
return num_edges*2.0/(num_neigh*(num_neigh-1));
}
double xrelevance(const MLNetworkSharedPtr& mnet, const ActorSharedPtr& actor, const std::unordered_set<LayerSharedPtr>& layers, edge_mode mode) {
set<actor_id> neighbors_on_selected_layers;
set<actor_id> neighbors_on_other_layers;
set<actor_id> all_neighbors;
for (NodeSharedPtr node: *mnet->get_nodes(actor)) {
for (NodeSharedPtr neighbor: *mnet->neighbors(node, mode)) {
all_neighbors.insert(neighbor->actor->id);
if (layers.count(neighbor->layer)>0)
neighbors_on_selected_layers.insert(neighbor->actor->id);
else neighbors_on_other_layers.insert(neighbor->actor->id);
}
}
if (all_neighbors.size()==0) return 0; // by definition
else {
for (actor_id actor: neighbors_on_other_layers)
neighbors_on_selected_layers.erase(actor);
return (double)neighbors_on_selected_layers.size()/all_neighbors.size();
}
}
