int igraph_forest_fire_game(igraph_t *graph, igraph_integer_t nodes,
igraph_real_t fw_prob, igraph_real_t bw_factor,
igraph_integer_t pambs, igraph_bool_t directed) {
igraph_vector_long_t visited;
long int no_of_nodes=nodes, actnode, i;
igraph_vector_t edges;
igraph_vector_t *inneis, *outneis;
igraph_i_forest_fire_data_t data;
igraph_dqueue_t neiq;
long int ambs=pambs;
igraph_real_t param_geom_out=1-fw_prob;
igraph_real_t param_geom_in=1-fw_prob*bw_factor;
if (fw_prob < 0) {
IGRAPH_ERROR("Forest fire model: 'fw_prob' should be between non-negative",
IGRAPH_EINVAL);
}
if (bw_factor < 0) {
IGRAPH_ERROR("Forest fire model: 'bw_factor' should be non-negative",
IGRAPH_EINVAL);
}
if (ambs < 0) {
IGRAPH_ERROR("Number of ambassadors ('ambs') should be non-negative",
IGRAPH_EINVAL);
}
if (fw_prob == 0 || ambs == 0) {
IGRAPH_WARNING("'fw_prob or ambs is zero, creating empty graph");
IGRAPH_CHECK(igraph_empty(graph, nodes, directed));
return 0;
}
IGRAPH_VECTOR_INIT_FINALLY(&edges, 0);
inneis=igraph_Calloc(no_of_nodes, igraph_vector_t);
if (!inneis) {
IGRAPH_ERROR("Cannot run forest fire model", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, inneis);
outneis=igraph_Calloc(no_of_nodes, igraph_vector_t);
if (!outneis) {
IGRAPH_ERROR("Cannot run forest fire model", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, outneis);
data.inneis=inneis;
data.outneis=outneis;
data.no_of_nodes=no_of_nodes;
IGRAPH_FINALLY(igraph_i_forest_fire_free, &data);
for (i=0; i<no_of_nodes; i++) {
IGRAPH_CHECK(igraph_vector_init(inneis+i, 0));
IGRAPH_CHECK(igraph_vector_init(outneis+i, 0));
}
IGRAPH_CHECK(igraph_vector_long_init(&visited, no_of_nodes));
IGRAPH_FINALLY(igraph_vector_long_destroy, &visited);
IGRAPH_DQUEUE_INIT_FINALLY(&neiq, 10);
RNG_BEGIN();
#define ADD_EDGE_TO(nei) \
if (VECTOR(visited)[(nei)] != actnode+1) { \
VECTOR(visited)[(nei)] = actnode+1; \
IGRAPH_CHECK(igraph_dqueue_push(&neiq, nei)); \
IGRAPH_CHECK(igraph_vector_push_back(&edges, actnode)); \
IGRAPH_CHECK(igraph_vector_push_back(&edges, nei)); \
IGRAPH_CHECK(igraph_vector_push_back(outneis+actnode, nei)); \
IGRAPH_CHECK(igraph_vector_push_back(inneis+nei, actnode)); \
}
IGRAPH_PROGRESS("Forest fire: ", 0.0, NULL);
for (actnode=1; actnode < no_of_nodes; actnode++) {
IGRAPH_PROGRESS("Forest fire: ", 100.0*actnode/no_of_nodes, NULL);
IGRAPH_ALLOW_INTERRUPTION();
/* We don't want to visit the current vertex */
VECTOR(visited)[actnode] = actnode+1;
/* Choose ambassador(s) */
for (i=0; i<ambs; i++) {
long int a=RNG_INTEGER(0, actnode-1);
ADD_EDGE_TO(a);
}
while (!igraph_dqueue_empty(&neiq)) {
long int actamb=(long int) igraph_dqueue_pop(&neiq);
igraph_vector_t *outv=outneis+actamb;
igraph_vector_t *inv=inneis+actamb;
long int no_in=igraph_vector_size(inv);
long int no_out=igraph_vector_size(outv);
long int neis_out=(long int) RNG_GEOM(param_geom_out);
long int neis_in=(long int) RNG_GEOM(param_geom_in);
/* outgoing neighbors */
if (neis_out >= no_out) {
for (i=0; i<no_out; i++) {
long int nei=(long int) VECTOR(*outv)[i];
ADD_EDGE_TO(nei);
}
} else {
long int oleft=no_out;
for (i=0; i<neis_out && oleft > 0; ) {
long int which=RNG_INTEGER(0, oleft-1);
long int nei=(long int) VECTOR(*outv)[which];
VECTOR(*outv)[which] = VECTOR(*outv)[oleft-1];
VECTOR(*outv)[oleft-1] = nei;
if (VECTOR(visited)[nei] != actnode+1) {
ADD_EDGE_TO(nei);
i++;
}
oleft--;
}
}
/* incoming neighbors */
if (neis_in >= no_in) {
for (i=0; i<no_in; i++) {
long int nei=(long int) VECTOR(*inv)[i];
ADD_EDGE_TO(nei);
}
} else {
long int ileft=no_in;
for (i=0; i<neis_in && ileft > 0; ) {
long int which=RNG_INTEGER(0, ileft-1);
long int nei=(long int) VECTOR(*inv)[which];
VECTOR(*inv)[which] = VECTOR(*inv)[ileft-1];
VECTOR(*inv)[ileft-1] = nei;
if (VECTOR(visited)[nei] != actnode+1) {
ADD_EDGE_TO(nei);
i++;
}
ileft--;
}
}
} /* while neiq not empty */
} /* actnode < no_of_nodes */
#undef ADD_EDGE_TO
RNG_END();
IGRAPH_PROGRESS("Forest fire: ", 100.0, NULL);
igraph_dqueue_destroy(&neiq);
igraph_vector_long_destroy(&visited);
igraph_i_forest_fire_free(&data);
igraph_free(outneis);
igraph_free(inneis);
IGRAPH_FINALLY_CLEAN(5);
IGRAPH_CHECK(igraph_create(graph, &edges, nodes, directed));
igraph_vector_destroy(&edges);
IGRAPH_FINALLY_CLEAN(1);
return 0;
}
int igraph_i_maximal_cliques(const igraph_t *graph, igraph_i_maximal_clique_func_t func, void* data) {
int directed=igraph_is_directed(graph);
long int i, j, k, l;
igraph_integer_t no_of_nodes, nodes_to_check, nodes_done;
igraph_integer_t best_cand = 0, best_cand_degree = 0, best_fini_cand_degree;
igraph_adjlist_t adj_list;
igraph_stack_ptr_t stack;
igraph_i_maximal_cliques_stack_frame frame, *new_frame_ptr;
igraph_vector_t clique, new_cand, new_fini, cn, best_cand_nbrs, best_fini_cand_nbrs;
igraph_bool_t cont = 1;
int assret;
if (directed)
IGRAPH_WARNING("directionality of edges is ignored for directed graphs");
no_of_nodes = igraph_vcount(graph);
if (no_of_nodes == 0)
return IGRAPH_SUCCESS;
/* Construct an adjacency list representation */
IGRAPH_CHECK(igraph_adjlist_init(graph, &adj_list, IGRAPH_ALL));
IGRAPH_FINALLY(igraph_adjlist_destroy, &adj_list);
IGRAPH_CHECK(igraph_adjlist_simplify(&adj_list));
igraph_adjlist_sort(&adj_list);
/* Initialize stack */
IGRAPH_CHECK(igraph_stack_ptr_init(&stack, 0));
IGRAPH_FINALLY(igraph_i_maximal_cliques_stack_destroy, &stack);
/* Create the initial (empty) clique */
IGRAPH_VECTOR_INIT_FINALLY(&clique, 0);
/* Initialize new_cand, new_fini, cn, best_cand_nbrs and best_fini_cand_nbrs (will be used later) */
IGRAPH_VECTOR_INIT_FINALLY(&new_cand, 0);
IGRAPH_VECTOR_INIT_FINALLY(&new_fini, 0);
IGRAPH_VECTOR_INIT_FINALLY(&cn, 0);
IGRAPH_VECTOR_INIT_FINALLY(&best_cand_nbrs, 0);
IGRAPH_VECTOR_INIT_FINALLY(&best_fini_cand_nbrs, 0);
/* Find the vertex with the highest degree */
best_cand = 0; best_cand_degree = igraph_vector_size(igraph_adjlist_get(&adj_list, 0));
for (i = 1; i < no_of_nodes; i++) {
j = igraph_vector_size(igraph_adjlist_get(&adj_list, i));
if (j > best_cand_degree) {
best_cand = i;
best_cand_degree = j;
}
}
/* Create the initial stack frame */
IGRAPH_CHECK(igraph_vector_init_seq(&frame.cand, 0, no_of_nodes-1));
IGRAPH_FINALLY(igraph_vector_destroy, &frame.cand);
IGRAPH_CHECK(igraph_vector_init(&frame.fini, 0));
IGRAPH_FINALLY(igraph_vector_destroy, &frame.fini);
IGRAPH_CHECK(igraph_vector_init(&frame.cand_filtered, 0));
IGRAPH_FINALLY(igraph_vector_destroy, &frame.cand_filtered);
IGRAPH_CHECK(igraph_vector_difference_sorted(&frame.cand,
igraph_adjlist_get(&adj_list, best_cand), &frame.cand_filtered));
IGRAPH_FINALLY_CLEAN(3);
IGRAPH_FINALLY(igraph_i_maximal_cliques_stack_frame_destroy, &frame);
/* TODO: frame.cand and frame.fini should be a set instead of a vector */
/* Main loop starts here */
nodes_to_check = igraph_vector_size(&frame.cand_filtered); nodes_done = 0;
while (!igraph_vector_empty(&frame.cand_filtered) || !igraph_stack_ptr_empty(&stack)) {
if (igraph_vector_empty(&frame.cand_filtered)) {
/* No candidates left to check in this stack frame, pop out the previous stack frame */
igraph_i_maximal_cliques_stack_frame *newframe = igraph_stack_ptr_pop(&stack);
igraph_i_maximal_cliques_stack_frame_destroy(&frame);
frame = *newframe;
free(newframe);
if (igraph_stack_ptr_size(&stack) == 1) {
/* We will be using the next candidate node in the next iteration, so we can increase
* nodes_done by 1 */
nodes_done++;
}
/* For efficiency reasons, we only check for interruption and show progress here */
IGRAPH_PROGRESS("Maximal cliques: ", 100.0 * nodes_done / nodes_to_check, NULL);
IGRAPH_ALLOW_INTERRUPTION();
igraph_vector_pop_back(&clique);
continue;
}
/* Try the next node in the clique */
i = igraph_vector_pop_back(&frame.cand_filtered);
IGRAPH_CHECK(igraph_vector_push_back(&clique, i));
/* Remove the node from the candidate list */
assret=igraph_vector_binsearch(&frame.cand, i, &j); assert(assret);
igraph_vector_remove(&frame.cand, j);
/* Add the node to the finished list */
assret = !igraph_vector_binsearch(&frame.fini, i, &j); assert(assret);
IGRAPH_CHECK(igraph_vector_insert(&frame.fini, j, i));
/* Create new_cand and new_fini */
IGRAPH_CHECK(igraph_vector_intersect_sorted(&frame.cand, igraph_adjlist_get(&adj_list, i), &new_cand));
IGRAPH_CHECK(igraph_vector_intersect_sorted(&frame.fini, igraph_adjlist_get(&adj_list, i), &new_fini));
/* Do we have anything more to search? */
if (igraph_vector_empty(&new_cand)) {
if (igraph_vector_empty(&new_fini)) {
/* We have a maximal clique here */
IGRAPH_CHECK(func(&clique, data, &cont));
if (!cont) {
/* The callback function requested to stop the search */
break;
}
}
igraph_vector_pop_back(&clique);
continue;
}
if (igraph_vector_empty(&new_fini) && igraph_vector_size(&new_cand) == 1) {
/* Shortcut: only one node left */
IGRAPH_CHECK(igraph_vector_push_back(&clique, VECTOR(new_cand)[0]));
IGRAPH_CHECK(func(&clique, data, &cont));
if (!cont) {
/* The callback function requested to stop the search */
break;
}
igraph_vector_pop_back(&clique);
igraph_vector_pop_back(&clique);
continue;
}
/* Find the next best candidate node in new_fini */
l = igraph_vector_size(&new_cand);
best_cand_degree = -1;
j = igraph_vector_size(&new_fini);
for (i = 0; i < j; i++) {
k = (long int)VECTOR(new_fini)[i];
IGRAPH_CHECK(igraph_vector_intersect_sorted(&new_cand, igraph_adjlist_get(&adj_list, k), &cn));
if (igraph_vector_size(&cn) > best_cand_degree) {
best_cand_degree = igraph_vector_size(&cn);
IGRAPH_CHECK(igraph_vector_update(&best_fini_cand_nbrs, &cn));
if (best_cand_degree == l) {
/* Cool, we surely have the best candidate node here as best_cand_degree can't get any better */
break;
}
}
}
/* Shortcut here: we don't have to examine new_cand */
if (best_cand_degree == l) {
igraph_vector_pop_back(&clique);
continue;
}
/* Still finding best candidate node */
best_fini_cand_degree = best_cand_degree;
best_cand_degree = -1;
j = igraph_vector_size(&new_cand);
l = l - 1;
for (i = 0; i < j; i++) {
k = (long int)VECTOR(new_cand)[i];
IGRAPH_CHECK(igraph_vector_intersect_sorted(&new_cand, igraph_adjlist_get(&adj_list, k), &cn));
if (igraph_vector_size(&cn) > best_cand_degree) {
best_cand_degree = igraph_vector_size(&cn);
IGRAPH_CHECK(igraph_vector_update(&best_cand_nbrs, &cn));
if (best_cand_degree == l) {
/* Cool, we surely have the best candidate node here as best_cand_degree can't get any better */
break;
}
}
}
/* Create a new stack frame in case we back out later */
new_frame_ptr = igraph_Calloc(1, igraph_i_maximal_cliques_stack_frame);
if (new_frame_ptr == 0) {
IGRAPH_ERROR("cannot allocate new stack frame", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, new_frame_ptr);
*new_frame_ptr = frame;
memset(&frame, 0, sizeof(frame));
IGRAPH_CHECK(igraph_stack_ptr_push(&stack, new_frame_ptr));
IGRAPH_FINALLY_CLEAN(1); /* ownership of new_frame_ptr taken by the stack */
/* Ownership of the current frame and its vectors (frame.cand, frame.done, frame.cand_filtered)
* is taken by the stack from now on. Vectors in frame must be re-initialized with new_cand,
* new_fini and stuff. The old frame.cand and frame.fini won't be leaked because they are
* managed by the stack now. */
frame.cand = new_cand;
frame.fini = new_fini;
IGRAPH_CHECK(igraph_vector_init(&new_cand, 0));
IGRAPH_CHECK(igraph_vector_init(&new_fini, 0));
IGRAPH_CHECK(igraph_vector_init(&frame.cand_filtered, 0));
/* Adjust frame.cand_filtered */
if (best_cand_degree < best_fini_cand_degree) {
IGRAPH_CHECK(igraph_vector_difference_sorted(&frame.cand, &best_fini_cand_nbrs, &frame.cand_filtered));
} else {
IGRAPH_CHECK(igraph_vector_difference_sorted(&frame.cand, &best_cand_nbrs, &frame.cand_filtered));
}
}
IGRAPH_PROGRESS("Maximal cliques: ", 100.0, NULL);
igraph_adjlist_destroy(&adj_list);
igraph_vector_destroy(&clique);
igraph_vector_destroy(&new_cand);
igraph_vector_destroy(&new_fini);
igraph_vector_destroy(&cn);
igraph_vector_destroy(&best_cand_nbrs);
igraph_vector_destroy(&best_fini_cand_nbrs);
igraph_i_maximal_cliques_stack_frame_destroy(&frame);
igraph_i_maximal_cliques_stack_destroy(&stack);
IGRAPH_FINALLY_CLEAN(9);
return IGRAPH_SUCCESS;
}
int igraph_revolver_d_d(const igraph_t *graph,
igraph_integer_t niter,
const igraph_vector_t *vtime,
const igraph_vector_t *etime,
igraph_matrix_t *kernel,
igraph_matrix_t *sd,
igraph_matrix_t *norm,
igraph_matrix_t *cites,
igraph_matrix_t *expected,
igraph_real_t *logprob,
igraph_real_t *lognull,
const igraph_matrix_t *debug,
igraph_vector_ptr_t *debugres) {
igraph_integer_t no_of_events, vnoev, enoev;
igraph_vector_t st;
long int i;
igraph_integer_t maxdegree;
igraph_vector_t vtimeidx, etimeidx;
igraph_lazy_inclist_t inclist;
if (igraph_vector_size(vtime) != igraph_vcount(graph)) {
IGRAPH_ERROR("Invalid vtime length", IGRAPH_EINVAL);
}
if (igraph_vector_size(etime) != igraph_ecount(graph)) {
IGRAPH_ERROR("Invalid etime length", IGRAPH_EINVAL);
}
vnoev=(igraph_integer_t) igraph_vector_max(vtime)+1;
enoev=(igraph_integer_t) igraph_vector_max(etime)+1;
no_of_events= vnoev > enoev ? vnoev : enoev;
IGRAPH_VECTOR_INIT_FINALLY(&st, no_of_events);
for (i=0; i<no_of_events; i++) {
VECTOR(st)[i]=1;
}
IGRAPH_CHECK(igraph_maxdegree(graph, &maxdegree, igraph_vss_all(),
IGRAPH_ALL, IGRAPH_LOOPS));
IGRAPH_VECTOR_INIT_FINALLY(&vtimeidx, 0);
IGRAPH_VECTOR_INIT_FINALLY(&etimeidx, 0);
IGRAPH_CHECK(igraph_vector_order1(vtime, &vtimeidx, no_of_events));
IGRAPH_CHECK(igraph_vector_order1(etime, &etimeidx, no_of_events));
IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, IGRAPH_ALL));
IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist);
IGRAPH_PROGRESS("Revolver d-d", 0, NULL);
for (i=0; i<niter; i++) {
IGRAPH_ALLOW_INTERRUPTION();
if (i+1 != niter) { /* not the last iteration */
/* measure */
IGRAPH_CHECK(igraph_revolver_mes_d_d(graph, &inclist,
kernel, 0 /*sd*/, 0 /*norm*/,
0/*cites*/, 0/*debug*/, 0 /*debugres*/,
&st, vtime, &vtimeidx, etime,
&etimeidx, no_of_events,
maxdegree));
/* normalize */
igraph_matrix_scale(kernel, 1/igraph_matrix_sum(kernel));
/* update st */
IGRAPH_CHECK(igraph_revolver_st_d_d(graph, &inclist,
&st, kernel, vtime, &vtimeidx,
etime, &etimeidx,
no_of_events));
} else {
/* measure */
IGRAPH_CHECK(igraph_revolver_mes_d_d(graph, &inclist,
kernel, sd, norm, cites,
debug, debugres, &st, vtime, &vtimeidx,
etime, &etimeidx,
no_of_events, maxdegree));
/* normalize */
igraph_matrix_scale(kernel, 1/igraph_matrix_sum(kernel));
/* update st */
IGRAPH_CHECK(igraph_revolver_st_d_d(graph, &inclist,
&st, kernel, vtime, &vtimeidx,
etime, &etimeidx,
no_of_events));
/* expected number of citations */
if (expected) {
IGRAPH_CHECK(igraph_revolver_exp_d_d(graph, &inclist,
expected, kernel, &st,
vtime, &vtimeidx, etime, &etimeidx,
no_of_events,
maxdegree));
}
/* error calculation */
if (logprob || lognull) {
IGRAPH_CHECK(igraph_revolver_error_d_d(graph, &inclist,
kernel, &st,
vtime, &vtimeidx,
etime, &etimeidx, no_of_events,
maxdegree, logprob, lognull));
}
}
IGRAPH_PROGRESS("Revolver d-d", 100.0*(i+1)/niter, NULL);
}
igraph_lazy_inclist_destroy(&inclist);
igraph_vector_destroy(&etimeidx);
igraph_vector_destroy(&vtimeidx);
igraph_vector_destroy(&st);
IGRAPH_FINALLY_CLEAN(4);
return 0;
}
int igraph_revolver_p_p(const igraph_t *graph,
igraph_integer_t niter,
const igraph_vector_t *vtime,
const igraph_vector_t *etime,
const igraph_vector_t *authors,
const igraph_vector_t *eventsizes,
igraph_matrix_t *kernel,
igraph_matrix_t *sd,
igraph_matrix_t *norm,
igraph_matrix_t *cites,
igraph_matrix_t *expected,
igraph_real_t *logprob,
igraph_real_t *lognull,
const igraph_matrix_t *debug,
igraph_vector_ptr_t *debugres) {
igraph_integer_t no_of_events;
igraph_vector_t st;
long int i;
igraph_integer_t maxpapers=0;
igraph_vector_t vtimeidx, etimeidx;
igraph_lazy_inclist_t inclist;
igraph_vector_long_t papers;
if (igraph_vector_size(vtime) != igraph_vcount(graph)) {
IGRAPH_ERROR("Invalid vtime length", IGRAPH_EINVAL);
}
if (igraph_vector_size(etime) != igraph_ecount(graph)) {
IGRAPH_ERROR("Invalid etime length", IGRAPH_EINVAL);
}
no_of_events=(igraph_integer_t) igraph_vector_size(eventsizes);
IGRAPH_VECTOR_INIT_FINALLY(&st, no_of_events);
for (i=0; i<no_of_events; i++) {
VECTOR(st)[i]=1;
}
IGRAPH_CHECK(igraph_vector_long_init(&papers, igraph_vcount(graph)));
IGRAPH_FINALLY(igraph_vector_long_destroy, &papers);
for (i=0; i<igraph_vector_size(authors); i++) {
long int author=(long int) VECTOR(*authors)[i];
VECTOR(papers)[author] += 1;
if (VECTOR(papers)[author] > maxpapers) {
maxpapers=(igraph_integer_t) VECTOR(papers)[author];
}
}
igraph_vector_long_destroy(&papers);
IGRAPH_FINALLY_CLEAN(1);
IGRAPH_VECTOR_INIT_FINALLY(&vtimeidx, 0);
IGRAPH_VECTOR_INIT_FINALLY(&etimeidx, 0);
IGRAPH_CHECK(igraph_vector_order1(vtime, &vtimeidx, no_of_events));
IGRAPH_CHECK(igraph_vector_order1(etime, &etimeidx, no_of_events));
IGRAPH_CHECK(igraph_lazy_inclist_init(graph, &inclist, IGRAPH_ALL));
IGRAPH_FINALLY(igraph_lazy_inclist_destroy, &inclist);
IGRAPH_PROGRESS("Revolver p-p", 0, NULL);
for (i=0; i<niter; i++) {
IGRAPH_ALLOW_INTERRUPTION();
if (i+1 != niter) { /* not the last iteration */
/* measure */
IGRAPH_CHECK(igraph_revolver_mes_p_p(graph, &inclist,
kernel, 0 /*sd*/, 0 /*norm*/,
0/*cites*/, 0/*debug*/, 0 /*debugres*/,
&st, vtime, &vtimeidx, etime,
&etimeidx, no_of_events,
authors, eventsizes,
maxpapers));
/* normalize */
igraph_matrix_scale(kernel, 1/igraph_matrix_sum(kernel));
/* update st */
IGRAPH_CHECK(igraph_revolver_st_p_p(graph, &inclist,
&st, kernel, vtime, &vtimeidx,
etime, &etimeidx,
no_of_events, authors,
eventsizes, maxpapers));
} else {
/* measure */
IGRAPH_CHECK(igraph_revolver_mes_p_p(graph, &inclist,
kernel, sd, norm, cites,
debug, debugres, &st, vtime, &vtimeidx,
etime, &etimeidx,
no_of_events, authors,
eventsizes, maxpapers));
/* normalize */
igraph_matrix_scale(kernel, 1/igraph_matrix_sum(kernel));
/* update st */
IGRAPH_CHECK(igraph_revolver_st_p_p(graph, &inclist,
&st, kernel, vtime, &vtimeidx,
etime, &etimeidx,
no_of_events, authors, eventsizes,
maxpapers));
/* expected number of citations */
if (expected) {
IGRAPH_CHECK(igraph_revolver_exp_p_p(graph, &inclist,
expected, kernel, &st,
vtime, &vtimeidx, etime, &etimeidx,
no_of_events, authors, eventsizes,
maxpapers));
}
/* error calculation */
if (logprob || lognull) {
IGRAPH_CHECK(igraph_revolver_error_p_p(graph, &inclist,
kernel, &st,
vtime, &vtimeidx,
etime, &etimeidx, no_of_events,
authors, eventsizes,
maxpapers, logprob, lognull));
}
}
IGRAPH_PROGRESS("Revolver p-p", 100.0*(i+1)/niter, NULL);
}
igraph_lazy_inclist_destroy(&inclist);
igraph_vector_destroy(&etimeidx);
igraph_vector_destroy(&vtimeidx);
igraph_vector_destroy(&st);
IGRAPH_FINALLY_CLEAN(4);
return 0;
}
/**
* \function igraph_community_fastgreedy
* \brief Finding community structure by greedy optimization of modularity
*
* This function implements the fast greedy modularity optimization
* algorithm for finding community structure, see
* A Clauset, MEJ Newman, C Moore: Finding community structure in very
* large networks, http://www.arxiv.org/abs/cond-mat/0408187 for the
* details.
*
* </para><para>
* Some improvements proposed in K Wakita, T Tsurumi: Finding community
* structure in mega-scale social networks,
* http://www.arxiv.org/abs/cs.CY/0702048v1 have also been implemented.
*
* \param graph The input graph. It must be a simple graph, i.e. a graph
* without multiple and without loop edges. This is checked and an
* error message is given for non-simple graphs.
* \param weights Potentially a numeric vector containing edge
* weights. Supply a null pointer here for unweighted graphs. The
* weights are expected to be non-negative.
* \param merges Pointer to an initialized matrix or NULL, the result of the
* computation is stored here. The matrix has two columns and each
* merge corresponds to one merge, the ids of the two merged
* components are stored. The component ids are numbered from zero and
* the first \c n components are the individual vertices, \c n is
* the number of vertices in the graph. Component \c n is created
* in the first merge, component \c n+1 in the second merge, etc.
* The matrix will be resized as needed. If this argument is NULL
* then it is ignored completely.
* \param modularity Pointer to an initialized matrix or NULL pointer,
* in the former case the modularity scores along the stages of the
* computation are recorded here. The vector will be resized as
* needed.
* \return Error code.
*
* \sa \ref igraph_community_walktrap(), \ref
* igraph_community_edge_betweenness() for other community detection
* algorithms, \ref igraph_community_to_membership() to convert the
* dendrogram to a membership vector.
*
* Time complexity: O(|E||V|log|V|) in the worst case,
* O(|E|+|V|log^2|V|) typically, |V| is the number of vertices, |E| is
* the number of edges.
*/
int igraph_community_fastgreedy(const igraph_t *graph,
const igraph_vector_t *weights,
igraph_matrix_t *merges, igraph_vector_t *modularity) {
long int no_of_edges, no_of_nodes, no_of_joins, total_joins;
long int i, j, k, n, m, from, to, dummy;
igraph_integer_t ffrom, fto;
igraph_eit_t edgeit;
igraph_i_fastgreedy_commpair *pairs, *p1, *p2;
igraph_i_fastgreedy_community_list communities;
igraph_vector_t a;
igraph_real_t q, maxq, *dq, weight_sum;
igraph_bool_t simple;
/*long int join_order[] = { 16,5, 5,6, 6,0, 4,0, 10,0, 26,29, 29,33, 23,33, 27,33, 25,24, 24,31, 12,3, 21,1, 30,8, 8,32, 9,2, 17,1, 11,0, 7,3, 3,2, 13,2, 1,2, 28,31, 31,33, 22,32, 18,32, 20,32, 32,33, 15,33, 14,33, 0,19, 19,2, -1,-1 };*/
/*long int join_order[] = { 43,42, 42,41, 44,41, 41,36, 35,36, 37,36, 36,29, 38,29, 34,29, 39,29, 33,29, 40,29, 32,29, 14,29, 30,29, 31,29, 6,18, 18,4, 23,4, 21,4, 19,4, 27,4, 20,4, 22,4, 26,4, 25,4, 24,4, 17,4, 0,13, 13,2, 1,2, 11,2, 8,2, 5,2, 3,2, 10,2, 9,2, 7,2, 2,28, 28,15, 12,15, 29,16, 4,15, -1,-1 };*/
no_of_nodes = igraph_vcount(graph);
no_of_edges = igraph_ecount(graph);
if (igraph_is_directed(graph)) {
IGRAPH_ERROR("fast greedy community detection works for undirected graphs only", IGRAPH_UNIMPLEMENTED);
}
total_joins=no_of_nodes-1;
if (weights != 0) {
if (igraph_vector_size(weights) < igraph_ecount(graph))
IGRAPH_ERROR("fast greedy community detection: weight vector too short", IGRAPH_EINVAL);
if (igraph_vector_any_smaller(weights, 0))
IGRAPH_ERROR("weights must be positive", IGRAPH_EINVAL);
weight_sum = igraph_vector_sum(weights);
} else weight_sum = no_of_edges;
IGRAPH_CHECK(igraph_is_simple(graph, &simple));
if (!simple) {
IGRAPH_ERROR("fast-greedy community finding works only on simple graphs", IGRAPH_EINVAL);
}
if (merges != 0) {
IGRAPH_CHECK(igraph_matrix_resize(merges, total_joins, 2));
igraph_matrix_null(merges);
}
if (modularity != 0) {
IGRAPH_CHECK(igraph_vector_resize(modularity, total_joins+1));
}
/* Create degree vector */
IGRAPH_VECTOR_INIT_FINALLY(&a, no_of_nodes);
if (weights) {
debug("Calculating weighted degrees\n");
for (i=0; i < no_of_edges; i++) {
VECTOR(a)[(long int)IGRAPH_FROM(graph, i)] += VECTOR(*weights)[i];
VECTOR(a)[(long int)IGRAPH_TO(graph, i)] += VECTOR(*weights)[i];
}
} else {
debug("Calculating degrees\n");
IGRAPH_CHECK(igraph_degree(graph, &a, igraph_vss_all(), IGRAPH_ALL, 0));
}
/* Create list of communities */
debug("Creating community list\n");
communities.n = no_of_nodes;
communities.no_of_communities = no_of_nodes;
communities.e = (igraph_i_fastgreedy_community*)calloc(no_of_nodes, sizeof(igraph_i_fastgreedy_community));
if (communities.e == 0) {
IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(free, communities.e);
communities.heap = (igraph_i_fastgreedy_community**)calloc(no_of_nodes, sizeof(igraph_i_fastgreedy_community*));
if (communities.heap == 0) {
IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(free, communities.heap);
communities.heapindex = (igraph_integer_t*)calloc(no_of_nodes, sizeof(igraph_integer_t));
if (communities.heapindex == 0) {
IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY_CLEAN(2);
IGRAPH_FINALLY(igraph_i_fastgreedy_community_list_destroy, &communities);
for (i=0; i<no_of_nodes; i++) {
igraph_vector_ptr_init(&communities.e[i].neis, 0);
communities.e[i].id = i;
communities.e[i].size = 1;
}
/* Create list of community pairs from edges */
debug("Allocating dq vector\n");
dq = (igraph_real_t*)calloc(no_of_edges, sizeof(igraph_real_t));
if (dq == 0) {
IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(free, dq);
debug("Creating community pair list\n");
IGRAPH_CHECK(igraph_eit_create(graph, igraph_ess_all(0), &edgeit));
IGRAPH_FINALLY(igraph_eit_destroy, &edgeit);
pairs = (igraph_i_fastgreedy_commpair*)calloc(2*no_of_edges, sizeof(igraph_i_fastgreedy_commpair));
if (pairs == 0) {
IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(free, pairs);
i=j=0;
while (!IGRAPH_EIT_END(edgeit)) {
long int eidx = IGRAPH_EIT_GET(edgeit);
igraph_edge(graph, eidx, &ffrom, &fto);
/* Create the pairs themselves */
from = (long int)ffrom; to = (long int)fto;
if (from == to) {
IGRAPH_ERROR("loop edge detected, simplify the graph before starting community detection", IGRAPH_EINVAL);
}
if (from>to) {
dummy=from; from=to; to=dummy;
}
if (weights) {
dq[j]=2*(VECTOR(*weights)[eidx]/(weight_sum*2.0) - VECTOR(a)[from]*VECTOR(a)[to]/(4.0*weight_sum*weight_sum));
} else {
dq[j]=2*(1.0/(no_of_edges*2.0) - VECTOR(a)[from]*VECTOR(a)[to]/(4.0*no_of_edges*no_of_edges));
}
pairs[i].first = from;
pairs[i].second = to;
pairs[i].dq = &dq[j];
pairs[i].opposite = &pairs[i+1];
pairs[i+1].first = to;
pairs[i+1].second = from;
pairs[i+1].dq = pairs[i].dq;
pairs[i+1].opposite = &pairs[i];
/* Link the pair to the communities */
igraph_vector_ptr_push_back(&communities.e[from].neis, &pairs[i]);
igraph_vector_ptr_push_back(&communities.e[to].neis, &pairs[i+1]);
/* Update maximums */
if (communities.e[from].maxdq==0 || *communities.e[from].maxdq->dq < *pairs[i].dq)
communities.e[from].maxdq = &pairs[i];
if (communities.e[to].maxdq==0 || *communities.e[to].maxdq->dq < *pairs[i+1].dq)
communities.e[to].maxdq = &pairs[i+1];
/* Iterate */
i+=2; j++;
IGRAPH_EIT_NEXT(edgeit);
}
igraph_eit_destroy(&edgeit);
IGRAPH_FINALLY_CLEAN(1);
/* Sorting community neighbor lists by community IDs */
debug("Sorting community neighbor lists\n");
for (i=0, j=0; i<no_of_nodes; i++) {
igraph_vector_ptr_sort(&communities.e[i].neis, igraph_i_fastgreedy_commpair_cmp);
/* Isolated vertices won't be stored in the heap (to avoid maxdq == 0) */
if (VECTOR(a)[i] > 0) {
communities.heap[j] = &communities.e[i];
communities.heapindex[i] = j;
j++;
} else {
communities.heapindex[i] = -1;
}
}
communities.no_of_communities = j;
/* Calculate proper vector a (see paper) and initial modularity */
q=0;
igraph_vector_scale(&a, 1.0/(2.0 * (weights ? weight_sum : no_of_edges)));
for (i=0; i<no_of_nodes; i++)
q -= VECTOR(a)[i]*VECTOR(a)[i];
maxq=q;
/* Initializing community heap */
debug("Initializing community heap\n");
igraph_i_fastgreedy_community_list_build_heap(&communities);
debug("Initial modularity: %.4f\n", q);
/* Let's rock ;) */
no_of_joins=0;
while (no_of_joins<total_joins) {
IGRAPH_ALLOW_INTERRUPTION();
IGRAPH_PROGRESS("fast greedy community detection", no_of_joins*100.0/total_joins, 0);
/* Store the modularity */
if (modularity) VECTOR(*modularity)[no_of_joins] = q;
/* Some debug info if needed */
/* igraph_i_fastgreedy_community_list_check_heap(&communities); */
#ifdef DEBUG
debug("===========================================\n");
for (i=0; i<communities.n; i++) {
if (communities.e[i].maxdq == 0) {
debug("Community #%ld: PASSIVE\n", i);
continue;
}
debug("Community #%ld\n ", i);
for (j=0; j<igraph_vector_ptr_size(&communities.e[i].neis); j++) {
p1=(igraph_i_fastgreedy_commpair*)VECTOR(communities.e[i].neis)[j];
debug(" (%ld,%ld,%.4f)", p1->first, p1->second, *p1->dq);
}
p1=communities.e[i].maxdq;
debug("\n Maxdq: (%ld,%ld,%.4f)\n", p1->first, p1->second, *p1->dq);
}
debug("Global maxdq is: (%ld,%ld,%.4f)\n", communities.heap[0]->maxdq->first,
communities.heap[0]->maxdq->second, *communities.heap[0]->maxdq->dq);
for (i=0; i<communities.no_of_communities; i++)
debug("(%ld,%ld,%.4f) ", communities.heap[i]->maxdq->first, communities.heap[i]->maxdq->second, *communities.heap[0]->maxdq->dq);
debug("\n");
#endif
if (communities.heap[0] == 0) break; /* no more communities */
if (communities.heap[0]->maxdq == 0) break; /* there are only isolated comms */
to=communities.heap[0]->maxdq->second;
from=communities.heap[0]->maxdq->first;
debug("Q[%ld] = %.7f\tdQ = %.7f\t |H| = %ld\n",
no_of_joins, q, *communities.heap[0]->maxdq->dq, no_of_nodes-no_of_joins-1);
/* DEBUG */
/* from=join_order[no_of_joins*2]; to=join_order[no_of_joins*2+1];
if (to == -1) break;
for (i=0; i<igraph_vector_ptr_size(&communities.e[to].neis); i++) {
p1=(igraph_i_fastgreedy_commpair*)VECTOR(communities.e[to].neis)[i];
if (p1->second == from) communities.maxdq = p1;
} */
n = igraph_vector_ptr_size(&communities.e[to].neis);
m = igraph_vector_ptr_size(&communities.e[from].neis);
/*if (n>m) {
dummy=n; n=m; m=dummy;
dummy=to; to=from; from=dummy;
}*/
debug(" joining: %ld <- %ld\n", to, from);
q += *communities.heap[0]->maxdq->dq;
/* Merge the second community into the first */
i = j = 0;
while (i<n && j<m) {
p1 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[to].neis)[i];
p2 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[from].neis)[j];
debug("Pairs: %ld-%ld and %ld-%ld\n", p1->first, p1->second,
p2->first, p2->second);
if (p1->second < p2->second) {
/* Considering p1 from now on */
debug(" Considering: %ld-%ld\n", p1->first, p1->second);
if (p1->second == from) {
debug(" WILL REMOVE: %ld-%ld\n", to, from);
} else {
/* chain, case 1 */
debug(" CHAIN(1): %ld-%ld %ld, now=%.7f, adding=%.7f, newdq(%ld,%ld)=%.7f\n",
to, p1->second, from, *p1->dq, -2*VECTOR(a)[from]*VECTOR(a)[p1->second], p1->first, p1->second, *p1->dq-2*VECTOR(a)[from]*VECTOR(a)[p1->second]);
igraph_i_fastgreedy_community_update_dq(&communities, p1, *p1->dq - 2*VECTOR(a)[from]*VECTOR(a)[p1->second]);
}
i++;
} else if (p1->second == p2->second) {
/* p1->first, p1->second and p2->first form a triangle */
debug(" Considering: %ld-%ld and %ld-%ld\n", p1->first, p1->second,
p2->first, p2->second);
/* Update dq value */
debug(" TRIANGLE: %ld-%ld-%ld, now=%.7f, adding=%.7f, newdq(%ld,%ld)=%.7f\n",
to, p1->second, from, *p1->dq, *p2->dq, p1->first, p1->second, *p1->dq+*p2->dq);
igraph_i_fastgreedy_community_update_dq(&communities, p1, *p1->dq + *p2->dq);
igraph_i_fastgreedy_community_remove_nei(&communities, p1->second, from);
i++;
j++;
} else {
debug(" Considering: %ld-%ld\n", p2->first, p2->second);
if (p2->second == to) {
debug(" WILL REMOVE: %ld-%ld\n", p2->second, p2->first);
} else {
/* chain, case 2 */
debug(" CHAIN(2): %ld %ld-%ld, newdq(%ld,%ld)=%.7f\n",
to, p2->second, from, to, p2->second, *p2->dq-2*VECTOR(a)[to]*VECTOR(a)[p2->second]);
p2->opposite->second=to;
/* need to re-sort community nei list `p2->second` */
/* TODO: quicksort is O(n*logn), although we could do a deletion and
* insertion which can be done in O(logn) if deletion is O(1) */
debug(" Re-sorting community %ld\n", p2->second);
igraph_vector_ptr_sort(&communities.e[p2->second].neis, igraph_i_fastgreedy_commpair_cmp);
/* link from.neis[j] to the current place in to.neis if
* from.neis[j] != to */
p2->first=to;
IGRAPH_CHECK(igraph_vector_ptr_insert(&communities.e[to].neis,i,p2));
n++; i++;
if (*p2->dq > *communities.e[to].maxdq->dq) {
communities.e[to].maxdq = p2;
k=igraph_i_fastgreedy_community_list_find_in_heap(&communities, to);
igraph_i_fastgreedy_community_list_sift_up(&communities, k);
}
igraph_i_fastgreedy_community_update_dq(&communities, p2, *p2->dq - 2*VECTOR(a)[to]*VECTOR(a)[p2->second]);
}
j++;
}
}
while (i<n) {
p1 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[to].neis)[i];
if (p1->second == from) {
debug(" WILL REMOVE: %ld-%ld\n", p1->first, from);
} else {
/* chain, case 1 */
debug(" CHAIN(1): %ld-%ld %ld, now=%.7f, adding=%.7f, newdq(%ld,%ld)=%.7f\n",
to, p1->second, from, *p1->dq, -2*VECTOR(a)[from]*VECTOR(a)[p1->second], p1->first, p1->second, *p1->dq-2*VECTOR(a)[from]*VECTOR(a)[p1->second]);
igraph_i_fastgreedy_community_update_dq(&communities, p1, *p1->dq - 2*VECTOR(a)[from]*VECTOR(a)[p1->second]);
}
i++;
}
while (j<m) {
p2 = (igraph_i_fastgreedy_commpair*)VECTOR(communities.e[from].neis)[j];
if (to == p2->second) { j++; continue; }
/* chain, case 2 */
debug(" CHAIN(2): %ld %ld-%ld, newdq(%ld,%ld)=%.7f\n",
to, p2->second, from, p1->first, p2->second, *p2->dq-2*VECTOR(a)[to]*VECTOR(a)[p2->second]);
p2->opposite->second=to;
/* need to re-sort community nei list `p2->second` */
/* TODO: quicksort is O(n*logn), although we could do a deletion and
* insertion which can be done in O(logn) if deletion is O(1) */
debug(" Re-sorting community %ld\n", p2->second);
igraph_vector_ptr_sort(&communities.e[p2->second].neis, igraph_i_fastgreedy_commpair_cmp);
/* link from.neis[j] to the current place in to.neis if
* from.neis[j] != to */
p2->first=to;
IGRAPH_CHECK(igraph_vector_ptr_push_back(&communities.e[to].neis,p2));
if (*p2->dq > *communities.e[to].maxdq->dq) {
communities.e[to].maxdq = p2;
k=igraph_i_fastgreedy_community_list_find_in_heap(&communities, to);
igraph_i_fastgreedy_community_list_sift_up(&communities, k);
}
igraph_i_fastgreedy_community_update_dq(&communities, p2, *p2->dq-2*VECTOR(a)[to]*VECTOR(a)[p2->second]);
j++;
}
/* Now, remove community `from` from the neighbors of community `to` */
if (communities.no_of_communities > 2) {
debug(" REMOVING: %ld-%ld\n", to, from);
igraph_i_fastgreedy_community_remove_nei(&communities, to, from);
i=igraph_i_fastgreedy_community_list_find_in_heap(&communities, from);
igraph_i_fastgreedy_community_list_remove(&communities, i);
}
communities.e[from].maxdq=0;
/* Update community sizes */
communities.e[to].size += communities.e[from].size;
communities.e[from].size = 0;
/* record what has been merged */
/* igraph_vector_ptr_clear is not enough here as it won't free
* the memory consumed by communities.e[from].neis. Thanks
* to Tom Gregorovic for pointing that out. */
igraph_vector_ptr_destroy(&communities.e[from].neis);
if (merges) {
MATRIX(*merges, no_of_joins, 0) = communities.e[to].id;
MATRIX(*merges, no_of_joins, 1) = communities.e[from].id;
communities.e[to].id = no_of_nodes+no_of_joins;
}
/* Update vector a */
VECTOR(a)[to] += VECTOR(a)[from];
VECTOR(a)[from] = 0.0;
no_of_joins++;
}
/* TODO: continue merging when some isolated communities remained. Always
* joining the communities with the least number of nodes results in the
* smallest decrease in modularity every step. Now we're simply deleting
* the excess rows from the merge matrix */
if (no_of_joins < total_joins) {
long int *ivec;
ivec=igraph_Calloc(igraph_matrix_nrow(merges), long int);
if (ivec == 0)
IGRAPH_ERROR("can't run fast greedy community detection", IGRAPH_ENOMEM);
IGRAPH_FINALLY(free, ivec);
for (i=0; i<no_of_joins; i++) ivec[i] = i+1;
igraph_matrix_permdelete_rows(merges, ivec, total_joins-no_of_joins);
free(ivec);
IGRAPH_FINALLY_CLEAN(1);
}
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;
}
/**
* \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;
}
