int igraph_clusters_weak(const igraph_t *graph, igraph_vector_t *membership,
igraph_vector_t *csize, igraph_integer_t *no) {
long int no_of_nodes=igraph_vcount(graph);
char *already_added;
long int first_node, act_cluster_size=0, no_of_clusters=1;
igraph_dqueue_t q=IGRAPH_DQUEUE_NULL;
long int i;
igraph_vector_t neis=IGRAPH_VECTOR_NULL;
already_added=igraph_Calloc(no_of_nodes,char);
if (already_added==0) {
IGRAPH_ERROR("Cannot calculate clusters", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, already_added);
IGRAPH_DQUEUE_INIT_FINALLY(&q, no_of_nodes > 100000 ? 10000 : no_of_nodes/10);
IGRAPH_VECTOR_INIT_FINALLY(&neis, 0);
/* Memory for result, csize is dynamically allocated */
if (membership) {
IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes));
}
if (csize) {
igraph_vector_clear(csize);
}
/* The algorithm */
for (first_node=0; first_node < no_of_nodes; ++first_node) {
if (already_added[first_node]==1) continue;
IGRAPH_ALLOW_INTERRUPTION();
already_added[first_node]=1;
act_cluster_size=1;
if (membership) {
VECTOR(*membership)[first_node]=no_of_clusters-1;
}
IGRAPH_CHECK(igraph_dqueue_push(&q, first_node));
while ( !igraph_dqueue_empty(&q) ) {
long int act_node=(long int) igraph_dqueue_pop(&q);
IGRAPH_CHECK(igraph_neighbors(graph, &neis,
(igraph_integer_t) act_node, IGRAPH_ALL));
for (i=0; i<igraph_vector_size(&neis); i++) {
long int neighbor=(long int) VECTOR(neis)[i];
if (already_added[neighbor]==1) { continue; }
IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor));
already_added[neighbor]=1;
act_cluster_size++;
if (membership) {
VECTOR(*membership)[neighbor]=no_of_clusters-1;
}
}
}
no_of_clusters++;
if (csize) {
IGRAPH_CHECK(igraph_vector_push_back(csize, act_cluster_size));
}
}
/* Cleaning up */
if (no) { *no = (igraph_integer_t) no_of_clusters-1; }
igraph_Free(already_added);
igraph_dqueue_destroy(&q);
igraph_vector_destroy(&neis);
IGRAPH_FINALLY_CLEAN(3);
return 0;
}
int igraph_is_bipartite(const igraph_t *graph,
igraph_bool_t *res,
igraph_vector_bool_t *type) {
/* We basically do a breadth first search and label the
vertices along the way. We stop as soon as we can find a
contradiction.
In the 'seen' vector 0 means 'not seen yet', 1 means type 1,
2 means type 2.
*/
long int no_of_nodes=igraph_vcount(graph);
igraph_vector_char_t seen;
igraph_dqueue_t Q;
igraph_vector_t neis;
igraph_bool_t bi=1;
long int i;
IGRAPH_CHECK(igraph_vector_char_init(&seen, no_of_nodes));
IGRAPH_FINALLY(igraph_vector_char_destroy, &seen);
IGRAPH_DQUEUE_INIT_FINALLY(&Q, 100);
IGRAPH_VECTOR_INIT_FINALLY(&neis, 0);
for (i=0; bi && i<no_of_nodes; i++) {
if (VECTOR(seen)[i]) { continue; }
IGRAPH_CHECK(igraph_dqueue_push(&Q, i));
VECTOR(seen)[i]=1;
while (bi && !igraph_dqueue_empty(&Q)) {
long int n, j;
igraph_integer_t actnode=(igraph_integer_t) igraph_dqueue_pop(&Q);
char acttype=VECTOR(seen)[actnode];
IGRAPH_CHECK(igraph_neighbors(graph, &neis, actnode, IGRAPH_ALL));
n=igraph_vector_size(&neis);
for (j=0; j<n; j++) {
long int nei=(long int) VECTOR(neis)[j];
if (VECTOR(seen)[nei]) {
long int neitype=VECTOR(seen)[nei];
if (neitype == acttype) {
bi=0;
break;
}
} else {
VECTOR(seen)[nei] = 3 - acttype;
IGRAPH_CHECK(igraph_dqueue_push(&Q, nei));
}
}
}
}
igraph_vector_destroy(&neis);
igraph_dqueue_destroy(&Q);
IGRAPH_FINALLY_CLEAN(2);
if (res) { *res=bi; }
if (type && bi) {
IGRAPH_CHECK(igraph_vector_bool_resize(type, no_of_nodes));
for (i=0; i<no_of_nodes; i++) {
VECTOR(*type)[i] = VECTOR(seen)[i] - 1;
}
}
igraph_vector_char_destroy(&seen);
IGRAPH_FINALLY_CLEAN(1);
return 0;
}
int igraph_clusters_strong(const igraph_t *graph, igraph_vector_t *membership,
igraph_vector_t *csize, igraph_integer_t *no) {
long int no_of_nodes=igraph_vcount(graph);
igraph_vector_t next_nei=IGRAPH_VECTOR_NULL;
long int i, n, num_seen;
igraph_dqueue_t q=IGRAPH_DQUEUE_NULL;
long int no_of_clusters=1;
long int act_cluster_size;
igraph_vector_t out=IGRAPH_VECTOR_NULL;
const igraph_vector_int_t* tmp;
igraph_adjlist_t adjlist;
/* The result */
IGRAPH_VECTOR_INIT_FINALLY(&next_nei, no_of_nodes);
IGRAPH_VECTOR_INIT_FINALLY(&out, 0);
IGRAPH_DQUEUE_INIT_FINALLY(&q, 100);
if (membership) {
IGRAPH_CHECK(igraph_vector_resize(membership, no_of_nodes));
}
IGRAPH_CHECK(igraph_vector_reserve(&out, no_of_nodes));
igraph_vector_null(&out);
if (csize) {
igraph_vector_clear(csize);
}
IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_OUT));
IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist);
num_seen = 0;
for (i=0; i<no_of_nodes; i++) {
IGRAPH_ALLOW_INTERRUPTION();
tmp = igraph_adjlist_get(&adjlist, i);
if (VECTOR(next_nei)[i] > igraph_vector_int_size(tmp)) {
continue;
}
IGRAPH_CHECK(igraph_dqueue_push(&q, i));
while (!igraph_dqueue_empty(&q)) {
long int act_node=(long int) igraph_dqueue_back(&q);
tmp = igraph_adjlist_get(&adjlist, act_node);
if (VECTOR(next_nei)[act_node]==0) {
/* this is the first time we've met this vertex */
VECTOR(next_nei)[act_node]++;
} else if (VECTOR(next_nei)[act_node] <= igraph_vector_int_size(tmp)) {
/* we've already met this vertex but it has more children */
long int neighbor=(long int) VECTOR(*tmp)[(long int)
VECTOR(next_nei)[act_node]-1];
if (VECTOR(next_nei)[neighbor] == 0) {
IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor));
}
VECTOR(next_nei)[act_node]++;
} else {
/* we've met this vertex and it has no more children */
IGRAPH_CHECK(igraph_vector_push_back(&out, act_node));
igraph_dqueue_pop_back(&q);
num_seen++;
if (num_seen % 10000 == 0) {
/* time to report progress and allow the user to interrupt */
IGRAPH_PROGRESS("Strongly connected components: ",
num_seen * 50.0 / no_of_nodes, NULL);
IGRAPH_ALLOW_INTERRUPTION();
}
}
} /* while q */
} /* for */
IGRAPH_PROGRESS("Strongly connected components: ", 50.0, NULL);
igraph_adjlist_destroy(&adjlist);
IGRAPH_FINALLY_CLEAN(1);
IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_IN));
IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist);
/* OK, we've the 'out' values for the nodes, let's use them in
decreasing order with the help of a heap */
igraph_vector_null(&next_nei); /* mark already added vertices */
num_seen = 0;
while (!igraph_vector_empty(&out)) {
long int grandfather=(long int) igraph_vector_pop_back(&out);
if (VECTOR(next_nei)[grandfather] != 0) { continue; }
VECTOR(next_nei)[grandfather]=1;
act_cluster_size=1;
if (membership) {
VECTOR(*membership)[grandfather]=no_of_clusters-1;
}
IGRAPH_CHECK(igraph_dqueue_push(&q, grandfather));
num_seen++;
if (num_seen % 10000 == 0) {
/* time to report progress and allow the user to interrupt */
IGRAPH_PROGRESS("Strongly connected components: ",
50.0 + num_seen * 50.0 / no_of_nodes, NULL);
IGRAPH_ALLOW_INTERRUPTION();
}
while (!igraph_dqueue_empty(&q)) {
long int act_node=(long int) igraph_dqueue_pop_back(&q);
tmp = igraph_adjlist_get(&adjlist, act_node);
n = igraph_vector_int_size(tmp);
for (i=0; i<n; i++) {
long int neighbor=(long int) VECTOR(*tmp)[i];
if (VECTOR(next_nei)[neighbor] != 0) { continue; }
IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor));
VECTOR(next_nei)[neighbor]=1;
act_cluster_size++;
if (membership) {
VECTOR(*membership)[neighbor]=no_of_clusters-1;
}
num_seen++;
if (num_seen % 10000 == 0) {
/* time to report progress and allow the user to interrupt */
IGRAPH_PROGRESS("Strongly connected components: ",
50.0 + num_seen * 50.0 / no_of_nodes, NULL);
IGRAPH_ALLOW_INTERRUPTION();
}
}
}
no_of_clusters++;
if (csize) {
IGRAPH_CHECK(igraph_vector_push_back(csize, act_cluster_size));
}
}
IGRAPH_PROGRESS("Strongly connected components: ", 100.0, NULL);
if (no) { *no=(igraph_integer_t) no_of_clusters-1; }
/* Clean up, return */
igraph_adjlist_destroy(&adjlist);
igraph_vector_destroy(&out);
igraph_dqueue_destroy(&q);
igraph_vector_destroy(&next_nei);
IGRAPH_FINALLY_CLEAN(4);
return 0;
}
int igraph_i_minimum_spanning_tree_unweighted(const igraph_t* graph,
igraph_vector_t* res) {
long int no_of_nodes=igraph_vcount(graph);
long int no_of_edges=igraph_ecount(graph);
char *already_added;
char *added_edges;
igraph_dqueue_t q=IGRAPH_DQUEUE_NULL;
igraph_vector_t tmp=IGRAPH_VECTOR_NULL;
long int i, j;
igraph_vector_clear(res);
added_edges=igraph_Calloc(no_of_edges, char);
if (added_edges==0) {
IGRAPH_ERROR("unweighted spanning tree failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, added_edges);
already_added=igraph_Calloc(no_of_nodes, char);
if (already_added==0) {
IGRAPH_ERROR("unweighted spanning tree failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, already_added);
IGRAPH_VECTOR_INIT_FINALLY(&tmp, 0);
IGRAPH_DQUEUE_INIT_FINALLY(&q, 100);
for (i=0; i<no_of_nodes; i++) {
if (already_added[i]>0) { continue; }
IGRAPH_ALLOW_INTERRUPTION();
already_added[i]=1;
IGRAPH_CHECK(igraph_dqueue_push(&q, i));
while (! igraph_dqueue_empty(&q)) {
long int act_node=(long int) igraph_dqueue_pop(&q);
IGRAPH_CHECK(igraph_incident(graph, &tmp, (igraph_integer_t) act_node,
IGRAPH_ALL));
igraph_vector_sort(&tmp);
for (j=0; j<igraph_vector_size(&tmp); j++) {
long int edge=(long int) VECTOR(tmp)[j];
if (added_edges[edge]==0) {
igraph_integer_t from, to;
igraph_edge(graph, (igraph_integer_t) edge, &from, &to);
if (act_node==to) { to=from; }
if (already_added[(long int) to]==0) {
already_added[(long int) to]=1;
added_edges[edge]=1;
IGRAPH_CHECK(igraph_vector_push_back(res, edge));
IGRAPH_CHECK(igraph_dqueue_push(&q, to));
}
}
}
}
}
igraph_dqueue_destroy(&q);
igraph_Free(already_added);
igraph_vector_destroy(&tmp);
igraph_Free(added_edges);
IGRAPH_FINALLY_CLEAN(4);
return IGRAPH_SUCCESS;
}
/**
* \ingroup structural
* \function igraph_betweenness_estimate
* \brief Estimated betweenness centrality of some vertices.
*
* </para><para>
* The betweenness centrality of a vertex is the number of geodesics
* going through it. If there are more than one geodesic between two
* vertices, the value of these geodesics are weighted by one over the
* number of geodesics. When estimating betweenness centrality, igraph
* takes into consideration only those paths that are shorter than or
* equal to a prescribed length. Note that the estimated centrality
* will always be less than the real one.
*
* \param graph The graph object.
* \param res The result of the computation, a vector containing the
* estimated betweenness scores for the specified vertices.
* \param vids The vertices of which the betweenness centrality scores
* will be estimated.
* \param directed Logical, if true directed paths will be considered
* for directed graphs. It is ignored for undirected graphs.
* \param cutoff The maximal length of paths that will be considered.
* If zero or negative, the exact betweenness will be calculated
* (no upper limit on path lengths).
* \return Error code:
* \c IGRAPH_ENOMEM, not enough memory for
* temporary data.
* \c IGRAPH_EINVVID, invalid vertex id passed in
* \p vids.
*
* Time complexity: O(|V||E|),
* |V| and
* |E| are the number of vertices and
* edges in the graph.
* Note that the time complexity is independent of the number of
* vertices for which the score is calculated.
*
* \sa Other centrality types: \ref igraph_degree(), \ref igraph_closeness().
* See \ref igraph_edge_betweenness() for calculating the betweenness score
* of the edges in a graph.
*/
int igraph_betweenness_estimate(const igraph_t *graph, igraph_vector_t *res,
const igraph_vs_t vids, igraph_bool_t directed,
igraph_integer_t cutoff) {
long int no_of_nodes=igraph_vcount(graph);
igraph_dqueue_t q=IGRAPH_DQUEUE_NULL;
long int *distance;
long int *nrgeo;
double *tmpscore;
igraph_stack_t stack=IGRAPH_STACK_NULL;
long int source;
long int j, k;
igraph_integer_t modein, modeout;
igraph_vit_t vit;
igraph_vector_t *neis;
igraph_adjlist_t adjlist_out, adjlist_in;
igraph_adjlist_t *adjlist_out_p, *adjlist_in_p;
IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit));
IGRAPH_FINALLY(igraph_vit_destroy, &vit);
directed=directed && igraph_is_directed(graph);
if (directed) {
modeout=IGRAPH_OUT;
modein=IGRAPH_IN;
IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist_out, IGRAPH_OUT));
IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist_out);
IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist_in, IGRAPH_IN));
IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist_in);
adjlist_out_p=&adjlist_out;
adjlist_in_p=&adjlist_in;
} else {
modeout=modein=IGRAPH_ALL;
IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist_out, IGRAPH_ALL));
IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist_out);
adjlist_out_p=adjlist_in_p=&adjlist_out;
}
distance=igraph_Calloc(no_of_nodes, long int);
if (distance==0) {
IGRAPH_ERROR("betweenness failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, distance);
nrgeo=igraph_Calloc(no_of_nodes, long int);
if (nrgeo==0) {
IGRAPH_ERROR("betweenness failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, nrgeo);
tmpscore=igraph_Calloc(no_of_nodes, double);
if (tmpscore==0) {
IGRAPH_ERROR("betweenness failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, tmpscore);
IGRAPH_DQUEUE_INIT_FINALLY(&q, 100);
igraph_stack_init(&stack, no_of_nodes);
IGRAPH_FINALLY(igraph_stack_destroy, &stack);
IGRAPH_CHECK(igraph_vector_resize(res, IGRAPH_VIT_SIZE(vit)));
igraph_vector_null(res);
/* here we go */
for (source=0; source<no_of_nodes; source++) {
IGRAPH_PROGRESS("Betweenness centrality: ", 100.0*source/no_of_nodes, 0);
IGRAPH_ALLOW_INTERRUPTION();
memset(distance, 0, no_of_nodes*sizeof(long int));
memset(nrgeo, 0, no_of_nodes*sizeof(long int));
memset(tmpscore, 0, no_of_nodes*sizeof(double));
igraph_stack_clear(&stack); /* it should be empty anyway... */
IGRAPH_CHECK(igraph_dqueue_push(&q, source));
nrgeo[source]=1;
distance[source]=0;
while (!igraph_dqueue_empty(&q)) {
long int actnode=igraph_dqueue_pop(&q);
if (cutoff > 0 && distance[actnode] >= cutoff) continue;
neis = igraph_adjlist_get(adjlist_out_p, actnode);
for (j=0; j<igraph_vector_size(neis); j++) {
long int neighbor=VECTOR(*neis)[j];
if (nrgeo[neighbor] != 0) {
/* we've already seen this node, another shortest path? */
if (distance[neighbor]==distance[actnode]+1) {
nrgeo[neighbor]+=nrgeo[actnode];
}
} else {
/* we haven't seen this node yet */
nrgeo[neighbor]+=nrgeo[actnode];
distance[neighbor]=distance[actnode]+1;
IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor));
IGRAPH_CHECK(igraph_stack_push(&stack, neighbor));
}
}
} /* while !igraph_dqueue_empty */
/* Ok, we've the distance of each node and also the number of
shortest paths to them. Now we do an inverse search, starting
with the farthest nodes. */
while (!igraph_stack_empty(&stack)) {
long int actnode=igraph_stack_pop(&stack);
if (distance[actnode]<=1) { continue; } /* skip source node */
/* set the temporary score of the friends */
neis = igraph_adjlist_get(adjlist_in_p, actnode);
for (j=0; j<igraph_vector_size(neis); j++) {
long int neighbor=VECTOR(*neis)[j];
if (distance[neighbor]==distance[actnode]-1 && nrgeo[neighbor] != 0) {
tmpscore[neighbor] +=
(tmpscore[actnode]+1)*nrgeo[neighbor]/nrgeo[actnode];
}
}
}
/* Ok, we've the scores for this source */
for (k=0, IGRAPH_VIT_RESET(vit); !IGRAPH_VIT_END(vit);
IGRAPH_VIT_NEXT(vit), k++) {
long int node=IGRAPH_VIT_GET(vit);
VECTOR(*res)[k] += tmpscore[node];
tmpscore[node] = 0.0; /* in case a node is in vids multiple times */
}
} /* for source < no_of_nodes */
/* divide by 2 for undirected graph */
if (!directed) {
for (j=0; j<igraph_vector_size(res); j++) {
VECTOR(*res)[j] /= 2.0;
}
}
/* clean */
igraph_Free(distance);
igraph_Free(nrgeo);
igraph_Free(tmpscore);
igraph_dqueue_destroy(&q);
igraph_stack_destroy(&stack);
igraph_vit_destroy(&vit);
IGRAPH_FINALLY_CLEAN(6);
if (directed) {
igraph_adjlist_destroy(&adjlist_out);
igraph_adjlist_destroy(&adjlist_in);
IGRAPH_FINALLY_CLEAN(2);
} else {
igraph_adjlist_destroy(&adjlist_out);
IGRAPH_FINALLY_CLEAN(1);
}
return 0;
}
/**
* \ingroup structural
* \function igraph_closeness_estimate
* \brief Closeness centrality estimations for some vertices.
*
* </para><para>
* The closeness centrality of a vertex measures how easily other
* vertices can be reached from it (or the other way: how easily it
* can be reached from the other vertices). It is defined as the
* number of the number of vertices minus one divided by the sum of the
* lengths of all geodesics from/to the given vertex. When estimating
* closeness centrality, igraph considers paths having a length less than
* or equal to a prescribed cutoff value.
*
* </para><para>
* If the graph is not connected, and there is no such path between two
* vertices, the number of vertices is used instead the length of the
* geodesic. This is always longer than the longest possible geodesic.
*
* </para><para>
* Since the estimation considers vertex pairs with a distance greater than
* the given value as disconnected, the resulting estimation will always be
* lower than the actual closeness centrality.
*
* \param graph The graph object.
* \param res The result of the computation, a vector containing the
* closeness centrality scores for the given vertices.
* \param vids Vector giving the vertices for which the closeness
* centrality scores will be computed.
* \param mode The type of shortest paths to be used for the
* calculation in directed graphs. Possible values:
* \clist
* \cli IGRAPH_OUT
* the lengths of the outgoing paths are calculated.
* \cli IGRAPH_IN
* the lengths of the incoming paths are calculated.
* \cli IGRAPH_ALL
* the directed graph is considered as an
* undirected one for the computation.
* \endclist
* \param cutoff The maximal length of paths that will be considered.
* If zero or negative, the exact closeness will be calculated
* (no upper limit on path lengths).
* \return Error code:
* \clist
* \cli IGRAPH_ENOMEM
* not enough memory for temporary data.
* \cli IGRAPH_EINVVID
* invalid vertex id passed.
* \cli IGRAPH_EINVMODE
* invalid mode argument.
* \endclist
*
* Time complexity: O(n|E|),
* n is the number
* of vertices for which the calculation is done and
* |E| is the number
* of edges in the graph.
*
* \sa Other centrality types: \ref igraph_degree(), \ref igraph_betweenness().
*/
int igraph_closeness_estimate(const igraph_t *graph, igraph_vector_t *res,
const igraph_vs_t vids, igraph_neimode_t mode,
igraph_integer_t cutoff) {
long int no_of_nodes=igraph_vcount(graph);
igraph_vector_t already_counted, *neis;
long int i, j;
long int nodes_reached;
igraph_adjlist_t allneis;
igraph_dqueue_t q;
long int nodes_to_calc;
igraph_vit_t vit;
IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit));
IGRAPH_FINALLY(igraph_vit_destroy, &vit);
nodes_to_calc=IGRAPH_VIT_SIZE(vit);
if (mode != IGRAPH_OUT && mode != IGRAPH_IN &&
mode != IGRAPH_ALL) {
IGRAPH_ERROR("calculating closeness", IGRAPH_EINVMODE);
}
IGRAPH_VECTOR_INIT_FINALLY(&already_counted, no_of_nodes);
IGRAPH_DQUEUE_INIT_FINALLY(&q, 100);
IGRAPH_CHECK(igraph_adjlist_init(graph, &allneis, mode));
IGRAPH_FINALLY(igraph_adjlist_destroy, &allneis);
IGRAPH_CHECK(igraph_vector_resize(res, nodes_to_calc));
igraph_vector_null(res);
for (IGRAPH_VIT_RESET(vit), i=0;
!IGRAPH_VIT_END(vit);
IGRAPH_VIT_NEXT(vit), i++) {
IGRAPH_CHECK(igraph_dqueue_push(&q, IGRAPH_VIT_GET(vit)));
IGRAPH_CHECK(igraph_dqueue_push(&q, 0));
nodes_reached=1;
VECTOR(already_counted)[(long int)IGRAPH_VIT_GET(vit)]=i+1;
IGRAPH_PROGRESS("Closeness: ", 100.0*i/no_of_nodes, NULL);
IGRAPH_ALLOW_INTERRUPTION();
while (!igraph_dqueue_empty(&q)) {
long int act=igraph_dqueue_pop(&q);
long int actdist=igraph_dqueue_pop(&q);
VECTOR(*res)[i] += actdist;
if (cutoff>0 && actdist>=cutoff) continue;
neis=igraph_adjlist_get(&allneis, act);
for (j=0; j<igraph_vector_size(neis); j++) {
long int neighbor=VECTOR(*neis)[j];
if (VECTOR(already_counted)[neighbor] == i+1) { continue; }
VECTOR(already_counted)[neighbor] = i+1;
nodes_reached++;
IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor));
IGRAPH_CHECK(igraph_dqueue_push(&q, actdist+1));
}
}
VECTOR(*res)[i] += ((igraph_integer_t)no_of_nodes * (no_of_nodes-nodes_reached));
VECTOR(*res)[i] = (no_of_nodes-1) / VECTOR(*res)[i];
}
IGRAPH_PROGRESS("Closeness: ", 100.0, NULL);
/* Clean */
igraph_dqueue_destroy(&q);
igraph_vector_destroy(&already_counted);
igraph_vit_destroy(&vit);
igraph_adjlist_destroy(&allneis);
IGRAPH_FINALLY_CLEAN(4);
return 0;
}
/**
* \ingroup structural
* \function igraph_edge_betweenness_estimate
* \brief Estimated betweenness centrality of the edges.
*
* </para><para>
* The betweenness centrality of an edge is the number of geodesics
* going through it. If there are more than one geodesics between two
* vertices, the value of these geodesics are weighted by one over the
* number of geodesics. When estimating betweenness centrality, igraph
* takes into consideration only those paths that are shorter than or
* equal to a prescribed length. Note that the estimated centrality
* will always be less than the real one.
* \param graph The graph object.
* \param result The result of the computation, vector containing the
* betweenness scores for the edges.
* \param directed Logical, if true directed paths will be considered
* for directed graphs. It is ignored for undirected graphs.
* \param cutoff The maximal length of paths that will be considered.
* If zero or negative, the exact betweenness will be calculated
* (no upper limit on path lengths).
* \return Error code:
* \c IGRAPH_ENOMEM, not enough memory for
* temporary data.
*
* Time complexity: O(|V||E|),
* |V| and
* |E| are the number of vertices and
* edges in the graph.
*
* \sa Other centrality types: \ref igraph_degree(), \ref igraph_closeness().
* See \ref igraph_betweenness() for calculating the betweenness score
* of the vertices in a graph.
*/
int igraph_edge_betweenness_estimate(const igraph_t *graph, igraph_vector_t *result,
igraph_bool_t directed, igraph_integer_t cutoff) {
long int no_of_nodes=igraph_vcount(graph);
long int no_of_edges=igraph_ecount(graph);
igraph_dqueue_t q=IGRAPH_DQUEUE_NULL;
long int *distance;
long int *nrgeo;
double *tmpscore;
igraph_stack_t stack=IGRAPH_STACK_NULL;
long int source;
long int j;
igraph_adjedgelist_t elist_out, elist_in;
igraph_adjedgelist_t *elist_out_p, *elist_in_p;
igraph_vector_t *neip;
long int neino;
long int i;
igraph_integer_t modein, modeout;
directed=directed && igraph_is_directed(graph);
if (directed) {
modeout=IGRAPH_OUT;
modein=IGRAPH_IN;
IGRAPH_CHECK(igraph_adjedgelist_init(graph, &elist_out, IGRAPH_OUT));
IGRAPH_FINALLY(igraph_adjedgelist_destroy, &elist_out);
IGRAPH_CHECK(igraph_adjedgelist_init(graph, &elist_in, IGRAPH_IN));
IGRAPH_FINALLY(igraph_adjedgelist_destroy, &elist_in);
elist_out_p=&elist_out;
elist_in_p=&elist_in;
} else {
modeout=modein=IGRAPH_ALL;
IGRAPH_CHECK(igraph_adjedgelist_init(graph,&elist_out, IGRAPH_ALL));
IGRAPH_FINALLY(igraph_adjedgelist_destroy, &elist_out);
elist_out_p=elist_in_p=&elist_out;
}
distance=igraph_Calloc(no_of_nodes, long int);
if (distance==0) {
IGRAPH_ERROR("edge betweenness failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, distance);
nrgeo=igraph_Calloc(no_of_nodes, long int);
if (nrgeo==0) {
IGRAPH_ERROR("edge betweenness failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, nrgeo);
tmpscore=igraph_Calloc(no_of_nodes, double);
if (tmpscore==0) {
IGRAPH_ERROR("edge betweenness failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, tmpscore);
IGRAPH_DQUEUE_INIT_FINALLY(&q, 100);
IGRAPH_CHECK(igraph_stack_init(&stack, no_of_nodes));
IGRAPH_FINALLY(igraph_stack_destroy, &stack);
IGRAPH_CHECK(igraph_vector_resize(result, no_of_edges));
igraph_vector_null(result);
/* here we go */
for (source=0; source<no_of_nodes; source++) {
IGRAPH_PROGRESS("Edge betweenness centrality: ", 100.0*source/no_of_nodes, 0);
IGRAPH_ALLOW_INTERRUPTION();
memset(distance, 0, no_of_nodes*sizeof(long int));
memset(nrgeo, 0, no_of_nodes*sizeof(long int));
memset(tmpscore, 0, no_of_nodes*sizeof(double));
igraph_stack_clear(&stack); /* it should be empty anyway... */
IGRAPH_CHECK(igraph_dqueue_push(&q, source));
nrgeo[source]=1;
distance[source]=0;
while (!igraph_dqueue_empty(&q)) {
long int actnode=igraph_dqueue_pop(&q);
if (cutoff > 0 && distance[actnode] >= cutoff ) continue;
neip=igraph_adjedgelist_get(elist_out_p, actnode);
neino=igraph_vector_size(neip);
for (i=0; i<neino; i++) {
igraph_integer_t edge=VECTOR(*neip)[i], from, to;
long int neighbor;
igraph_edge(graph, edge, &from, &to);
neighbor = actnode!=from ? from : to;
if (nrgeo[neighbor] != 0) {
/* we've already seen this node, another shortest path? */
if (distance[neighbor]==distance[actnode]+1) {
nrgeo[neighbor]+=nrgeo[actnode];
}
} else {
/* we haven't seen this node yet */
nrgeo[neighbor]+=nrgeo[actnode];
distance[neighbor]=distance[actnode]+1;
IGRAPH_CHECK(igraph_dqueue_push(&q, neighbor));
IGRAPH_CHECK(igraph_stack_push(&stack, neighbor));
}
}
} /* while !igraph_dqueue_empty */
/* Ok, we've the distance of each node and also the number of
shortest paths to them. Now we do an inverse search, starting
with the farthest nodes. */
while (!igraph_stack_empty(&stack)) {
long int actnode=igraph_stack_pop(&stack);
if (distance[actnode]<1) { continue; } /* skip source node */
/* set the temporary score of the friends */
neip=igraph_adjedgelist_get(elist_in_p, actnode);
neino=igraph_vector_size(neip);
for (i=0; i<neino; i++) {
igraph_integer_t from, to;
long int neighbor;
long int edgeno=VECTOR(*neip)[i];
igraph_edge(graph, edgeno, &from, &to);
neighbor= actnode != from ? from : to;
if (distance[neighbor]==distance[actnode]-1 &&
nrgeo[neighbor] != 0) {
tmpscore[neighbor] +=
(tmpscore[actnode]+1)*nrgeo[neighbor]/nrgeo[actnode];
VECTOR(*result)[edgeno] +=
(tmpscore[actnode]+1)*nrgeo[neighbor]/nrgeo[actnode];
}
}
}
/* Ok, we've the scores for this source */
} /* for source <= no_of_nodes */
IGRAPH_PROGRESS("Edge betweenness centrality: ", 100.0, 0);
/* clean and return */
igraph_Free(distance);
igraph_Free(nrgeo);
igraph_Free(tmpscore);
igraph_dqueue_destroy(&q);
igraph_stack_destroy(&stack);
IGRAPH_FINALLY_CLEAN(5);
if (directed) {
igraph_adjedgelist_destroy(&elist_out);
igraph_adjedgelist_destroy(&elist_in);
IGRAPH_FINALLY_CLEAN(2);
} else {
igraph_adjedgelist_destroy(&elist_out);
IGRAPH_FINALLY_CLEAN(1);
}
/* divide by 2 for undirected graph */
if (!directed || !igraph_is_directed(graph)) {
for (j=0; j<igraph_vector_size(result); j++) {
VECTOR(*result)[j] /= 2.0;
}
}
return 0;
}
