VALUE cIGraph_modularity(VALUE self, VALUE groups){
igraph_t *graph;
igraph_real_t value;
igraph_vector_t membership;
VALUE group;
int i,j;
Data_Get_Struct(self, igraph_t, graph);
igraph_vector_init(&membership,igraph_vcount(graph));
for(i=0;i<RARRAY_LEN(groups);i++){
group = RARRAY_PTR(groups)[i];
for(j=0;j<RARRAY_LEN(group);j++){
igraph_vector_set(&membership,
cIGraph_get_vertex_id(self,RARRAY_PTR(group)[j]),i);
}
}
igraph_modularity(graph,&membership,&value,NULL);
igraph_vector_destroy(&membership);
return rb_float_new(value);
}
/**
* \ingroup communities
* \function igraph_i_community_multilevel_step
* \brief Performs a single step of the multi-level modularity optimization method
*
* This function implements a single step of the multi-level modularity optimization
* algorithm for finding community structure, see VD Blondel, J-L Guillaume,
* R Lambiotte and E Lefebvre: Fast unfolding of community hierarchies in large
* networks, http://arxiv.org/abs/0803.0476 for the details.
*
* This function was contributed by Tom Gregorovic.
*
* \param graph The input graph. It must be an undirected graph.
* \param weights Numeric vector containing edge weights. If \c NULL, every edge
* has equal weight. The weights are expected to be non-negative.
* \param membership The membership vector, the result is returned here.
* For each vertex it gives the ID of its community.
* \param modularity The modularity of the partition is returned here.
* \c NULL means that the modularity is not needed.
* \return Error code.
*
* Time complexity: in average near linear on sparse graphs.
*/
int igraph_i_community_multilevel_step(igraph_t *graph,
igraph_vector_t *weights, igraph_vector_t *membership,
igraph_real_t *modularity) {
long int i, j;
long int vcount = igraph_vcount(graph);
long int ecount = igraph_ecount(graph);
igraph_integer_t ffrom, fto;
igraph_real_t q, pass_q;
int pass;
igraph_bool_t changed = 0;
igraph_vector_t links_community;
igraph_vector_t links_weight;
igraph_vector_t edges;
igraph_vector_t temp_membership;
igraph_i_multilevel_community_list communities;
/* Initial sanity checks on the input parameters */
if (igraph_is_directed(graph)) {
IGRAPH_ERROR("multi-level community detection works for undirected graphs only",
IGRAPH_UNIMPLEMENTED);
}
if (igraph_vector_size(weights) < igraph_ecount(graph))
IGRAPH_ERROR("multi-level community detection: weight vector too short", IGRAPH_EINVAL);
if (igraph_vector_any_smaller(weights, 0))
IGRAPH_ERROR("weights must be positive", IGRAPH_EINVAL);
/* Initialize data structures */
IGRAPH_VECTOR_INIT_FINALLY(&links_community, 0);
IGRAPH_VECTOR_INIT_FINALLY(&links_weight, 0);
IGRAPH_VECTOR_INIT_FINALLY(&edges, 0);
IGRAPH_VECTOR_INIT_FINALLY(&temp_membership, vcount);
IGRAPH_CHECK(igraph_vector_resize(membership, vcount));
/* Initialize list of communities from graph vertices */
communities.vertices_no = vcount;
communities.communities_no = vcount;
communities.weights = weights;
communities.weight_sum = 2 * igraph_vector_sum(weights);
communities.membership = membership;
communities.item = igraph_Calloc(vcount, igraph_i_multilevel_community);
if (communities.item == 0) {
IGRAPH_ERROR("multi-level community structure detection failed", IGRAPH_ENOMEM);
}
IGRAPH_FINALLY(igraph_free, communities.item);
/* Still initializing the communities data structure */
for (i=0; i < vcount; i++) {
VECTOR(*communities.membership)[i] = i;
communities.item[i].size = 1;
communities.item[i].weight_inside = 0;
communities.item[i].weight_all = 0;
}
/* Some more initialization :) */
for (i = 0; i < ecount; i++) {
igraph_real_t weight = 1;
igraph_edge(graph, (igraph_integer_t) i, &ffrom, &fto);
weight = VECTOR(*weights)[i];
communities.item[(long int) ffrom].weight_all += weight;
communities.item[(long int) fto].weight_all += weight;
if (ffrom == fto)
communities.item[(long int) ffrom].weight_inside += 2*weight;
}
q = igraph_i_multilevel_community_modularity(&communities);
pass = 1;
do { /* Pass begin */
long int temp_communities_no = communities.communities_no;
pass_q = q;
changed = 0;
/* Save the current membership, it will be restored in case of worse result */
IGRAPH_CHECK(igraph_vector_update(&temp_membership, communities.membership));
for (i = 0; i < vcount; i++) {
/* Exclude vertex from its current community */
igraph_real_t weight_all = 0;
igraph_real_t weight_inside = 0;
igraph_real_t weight_loop = 0;
igraph_real_t max_q_gain = 0;
igraph_real_t max_weight;
long int old_id, new_id, n;
igraph_i_multilevel_community_links(graph, &communities,
(igraph_integer_t) i, &edges,
&weight_all, &weight_inside,
&weight_loop, &links_community,
&links_weight);
old_id = (long int)VECTOR(*(communities.membership))[i];
new_id = old_id;
/* Update old community */
igraph_vector_set(communities.membership, i, -1);
communities.item[old_id].size--;
if (communities.item[old_id].size == 0) {communities.communities_no--;}
communities.item[old_id].weight_all -= weight_all;
communities.item[old_id].weight_inside -= 2*weight_inside + weight_loop;
/* debug("Remove %ld all: %lf Inside: %lf\n", i, -weight_all, -2*weight_inside + weight_loop); */
/* Find new community to join with the best modification gain */
max_q_gain = 0;
max_weight = weight_inside;
n = igraph_vector_size(&links_community);
igraph_vector_sort(&links_community);
for (j = 0; j < n; j++) {
long int c = (long int) VECTOR(links_community)[j];
igraph_real_t w = VECTOR(links_weight)[j];
igraph_real_t q_gain =
igraph_i_multilevel_community_modularity_gain(&communities,
(igraph_integer_t) c,
(igraph_integer_t) i,
weight_all, w);
/* debug("Link %ld -> %ld weight: %lf gain: %lf\n", i, c, (double) w, (double) q_gain); */
if (q_gain > max_q_gain) {
new_id = c;
max_q_gain = q_gain;
max_weight = w;
}
}
/* debug("Added vertex %ld to community %ld (gain %lf).\n", i, new_id, (double) max_q_gain); */
/* Add vertex to "new" community and update it */
igraph_vector_set(communities.membership, i, new_id);
if (communities.item[new_id].size == 0) {communities.communities_no++;}
communities.item[new_id].size++;
communities.item[new_id].weight_all += weight_all;
communities.item[new_id].weight_inside += 2*max_weight + weight_loop;
if (new_id != old_id) {
changed++;
}
}
q = igraph_i_multilevel_community_modularity(&communities);
if (changed && (q > pass_q)) {
/* debug("Pass %d (changed: %d) Communities: %ld Modularity from %lf to %lf\n",
pass, changed, communities.communities_no, (double) pass_q, (double) q); */
pass++;
} else {
/* No changes or the modularity became worse, restore last membership */
IGRAPH_CHECK(igraph_vector_update(communities.membership, &temp_membership));
communities.communities_no = temp_communities_no;
break;
}
IGRAPH_ALLOW_INTERRUPTION();
} while (changed && (q > pass_q)); /* Pass end */
if (modularity) {
*modularity = q;
}
/* debug("Result Communities: %ld Modularity: %lf\n",
communities.communities_no, (double) q); */
IGRAPH_CHECK(igraph_reindex_membership(membership, 0));
/* Shrink the nodes of the graph according to the present community structure
* and simplify the resulting graph */
/* TODO: check if we really need to copy temp_membership */
IGRAPH_CHECK(igraph_vector_update(&temp_membership, membership));
IGRAPH_CHECK(igraph_i_multilevel_shrink(graph, &temp_membership));
igraph_vector_destroy(&temp_membership);
IGRAPH_FINALLY_CLEAN(1);
/* Update edge weights after shrinking and simplification */
/* Here we reuse the edges vector as we don't need the previous contents anymore */
/* TODO: can we use igraph_simplify here? */
IGRAPH_CHECK(igraph_i_multilevel_simplify_multiple(graph, &edges));
/* We reuse the links_weight vector to store the old edge weights */
IGRAPH_CHECK(igraph_vector_update(&links_weight, weights));
igraph_vector_fill(weights, 0);
for (i = 0; i < ecount; i++) {
VECTOR(*weights)[(long int)VECTOR(edges)[i]] += VECTOR(links_weight)[i];
}
igraph_free(communities.item);
igraph_vector_destroy(&links_community);
igraph_vector_destroy(&links_weight);
igraph_vector_destroy(&edges);
IGRAPH_FINALLY_CLEAN(4);
return 0;
}
