int igraph_i_is_separator(const igraph_t *graph,
igraph_vit_t *vit,
long int except,
igraph_bool_t *res,
igraph_vector_bool_t *removed,
igraph_dqueue_t *Q,
igraph_vector_t *neis,
long int no_of_nodes) {
long int start=0;
if (IGRAPH_VIT_SIZE(*vit) >= no_of_nodes-1) {
/* Just need to check that we really have at least n-1 vertices in it */
igraph_vector_bool_t hit;
long int nohit=0;
IGRAPH_CHECK(igraph_vector_bool_init(&hit, no_of_nodes));
IGRAPH_FINALLY(igraph_vector_bool_destroy, &hit);
for (IGRAPH_VIT_RESET(*vit);
!IGRAPH_VIT_END(*vit);
IGRAPH_VIT_NEXT(*vit)) {
long int v=IGRAPH_VIT_GET(*vit);
if (!VECTOR(hit)[v]) {
nohit++;
VECTOR(hit)[v] = 1;
}
}
igraph_vector_bool_destroy(&hit);
IGRAPH_FINALLY_CLEAN(1);
if (nohit >= no_of_nodes-1) {
*res = 0;
return 0;
}
}
/* Remove the given vertices from the graph, do a breadth-first
search and check the number of components */
if (except < 0) {
for (IGRAPH_VIT_RESET(*vit);
!IGRAPH_VIT_END(*vit);
IGRAPH_VIT_NEXT(*vit)) {
VECTOR(*removed)[ (long int) IGRAPH_VIT_GET(*vit) ] = 1;
}
} else {
/* There is an exception */
long int i;
for (i=0, IGRAPH_VIT_RESET(*vit);
i<except;
i++, IGRAPH_VIT_NEXT(*vit)) {
VECTOR(*removed)[ (long int) IGRAPH_VIT_GET(*vit) ] = 1;
}
for (IGRAPH_VIT_NEXT(*vit);
!IGRAPH_VIT_END(*vit);
IGRAPH_VIT_NEXT(*vit)) {
VECTOR(*removed)[ (long int) IGRAPH_VIT_GET(*vit) ] = 1;
}
}
/* Look for the first node that is not removed */
while (start < no_of_nodes && VECTOR(*removed)[start]) start++;
if (start==no_of_nodes) {
IGRAPH_ERROR("All vertices are included in the separator",
IGRAPH_EINVAL);
}
igraph_dqueue_push(Q, start);
VECTOR(*removed)[start]=1;
while (!igraph_dqueue_empty(Q)) {
long int node=(long int) igraph_dqueue_pop(Q);
long int j, n;
igraph_neighbors(graph, neis, (igraph_integer_t) node, IGRAPH_ALL);
n=igraph_vector_size(neis);
for (j=0; j<n; j++) {
long int nei=(long int) VECTOR(*neis)[j];
if (!VECTOR(*removed)[nei]) {
IGRAPH_CHECK(igraph_dqueue_push(Q, nei));
VECTOR(*removed)[nei]=1;
}
}
}
/* Look for the next node that was neighter removed, not visited */
while (start < no_of_nodes && VECTOR(*removed)[start]) start++;
/* If there is another component, then we have a separator */
*res = (start < no_of_nodes);
return 0;
}
int igraph_pagerank(const igraph_t *graph, igraph_vector_t *vector,
igraph_real_t *value, const igraph_vs_t vids,
igraph_bool_t directed, igraph_real_t damping,
const igraph_vector_t *weights,
igraph_arpack_options_t *options) {
igraph_matrix_t values;
igraph_matrix_t vectors;
igraph_integer_t dirmode;
igraph_vector_t outdegree;
igraph_vector_t tmp;
long int i;
long int no_of_nodes=igraph_vcount(graph);
long int no_of_edges=igraph_ecount(graph);
options->n = igraph_vcount(graph);
options->nev = 1;
options->ncv = 3;
options->which[0]='L'; options->which[1]='M';
options->start=1; /* no random start vector */
directed = directed && igraph_is_directed(graph);
if (weights && igraph_vector_size(weights) != igraph_ecount(graph))
{
IGRAPH_ERROR("Invalid length of weights vector when calculating "
"PageRank scores", IGRAPH_EINVAL);
}
IGRAPH_MATRIX_INIT_FINALLY(&values, 0, 0);
IGRAPH_MATRIX_INIT_FINALLY(&vectors, options->n, 1);
if (directed) { dirmode=IGRAPH_IN; } else { dirmode=IGRAPH_ALL; }
IGRAPH_VECTOR_INIT_FINALLY(&outdegree, options->n);
IGRAPH_VECTOR_INIT_FINALLY(&tmp, options->n);
RNG_BEGIN();
if (!weights) {
igraph_adjlist_t adjlist;
igraph_i_pagerank_data_t data = { graph, &adjlist, damping,
&outdegree, &tmp };
IGRAPH_CHECK(igraph_degree(graph, &outdegree, igraph_vss_all(),
directed ? IGRAPH_OUT : IGRAPH_ALL, /*loops=*/ 0));
/* Avoid division by zero */
for (i=0; i<options->n; i++) {
if (VECTOR(outdegree)[i]==0) {
VECTOR(outdegree)[i]=1;
}
MATRIX(vectors, i, 0) = VECTOR(outdegree)[i];
}
IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, dirmode));
IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist);
IGRAPH_CHECK(igraph_arpack_rnsolve(igraph_i_pagerank,
&data, options, 0, &values, &vectors));
igraph_adjlist_destroy(&adjlist);
IGRAPH_FINALLY_CLEAN(1);
} else {
igraph_adjedgelist_t adjedgelist;
igraph_i_pagerank_data2_t data = { graph, &adjedgelist, weights,
damping, &outdegree, &tmp };
IGRAPH_CHECK(igraph_adjedgelist_init(graph, &adjedgelist, dirmode));
IGRAPH_FINALLY(igraph_adjedgelist_destroy, &adjedgelist);
/* Weighted degree */
for (i=0; i<no_of_edges; i++) {
long int from=IGRAPH_FROM(graph, i);
long int to=IGRAPH_TO(graph, i);
igraph_real_t weight=VECTOR(*weights)[i];
VECTOR(outdegree)[from] += weight;
if (!directed) {
VECTOR(outdegree)[to] += weight;
}
}
/* Avoid division by zero */
for (i=0; i<options->n; i++) {
if (VECTOR(outdegree)[i]==0) {
VECTOR(outdegree)[i]=1;
}
MATRIX(vectors, i, 0) = VECTOR(outdegree)[i];
}
IGRAPH_CHECK(igraph_arpack_rnsolve(igraph_i_pagerank2,
&data, options, 0, &values, &vectors));
igraph_adjedgelist_destroy(&adjedgelist);
IGRAPH_FINALLY_CLEAN(1);
}
RNG_END();
igraph_vector_destroy(&tmp);
igraph_vector_destroy(&outdegree);
IGRAPH_FINALLY_CLEAN(2);
if (value) {
*value=MATRIX(values, 0, 0);
}
if (vector) {
long int i;
igraph_vit_t vit;
long int nodes_to_calc;
igraph_real_t sum=0;
for (i=0; i<no_of_nodes; i++) {
sum += MATRIX(vectors, i, 0);
}
IGRAPH_CHECK(igraph_vit_create(graph, vids, &vit));
IGRAPH_FINALLY(igraph_vit_destroy, &vit);
nodes_to_calc=IGRAPH_VIT_SIZE(vit);
IGRAPH_CHECK(igraph_vector_resize(vector, nodes_to_calc));
for (IGRAPH_VIT_RESET(vit), i=0; !IGRAPH_VIT_END(vit);
IGRAPH_VIT_NEXT(vit), i++) {
VECTOR(*vector)[i] = MATRIX(vectors, (long int)IGRAPH_VIT_GET(vit), 0);
VECTOR(*vector)[i] /= sum;
}
igraph_vit_destroy(&vit);
IGRAPH_FINALLY_CLEAN(1);
}
if (options->info) {
IGRAPH_WARNING("Non-zero return code from ARPACK routine!");
}
igraph_matrix_destroy(&vectors);
igraph_matrix_destroy(&values);
IGRAPH_FINALLY_CLEAN(2);
return 0;
}
/**
* \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;
}
