static int igraph_i_realize_directed_degree_sequence(
igraph_t *graph,
const igraph_vector_t *outdeg,
const igraph_vector_t *indeg,
igraph_realize_degseq_t method)
{
long node_count = igraph_vector_size(outdeg);
long edge_count = long(igraph_vector_sum(outdeg));
if (igraph_vector_size(indeg) != node_count)
IGRAPH_ERROR("In- and out-degree sequences must have the same length", IGRAPH_EINVAL);
if (igraph_vector_sum(indeg) != edge_count)
IGRAPH_ERROR("In- and out-degree sequences do not sum to the same value", IGRAPH_EINVAL);
igraph_vector_t edges;
IGRAPH_CHECK(igraph_vector_init(&edges, 2*edge_count));
IGRAPH_FINALLY(igraph_vector_destroy, &edges);
switch (method) {
case IGRAPH_REALIZE_DEGSEQ_SMALLEST:
IGRAPH_CHECK(igraph_i_kleitman_wang(outdeg, indeg, &edges, true));
break;
case IGRAPH_REALIZE_DEGSEQ_LARGEST:
IGRAPH_CHECK(igraph_i_kleitman_wang(outdeg, indeg, &edges, false));
break;
case IGRAPH_REALIZE_DEGSEQ_INDEX:
IGRAPH_CHECK(igraph_i_kleitman_wang_index(outdeg, indeg, &edges));
break;
default:
IGRAPH_ERROR("Invalid bi-degree sequence realization method", IGRAPH_EINVAL);
}
igraph_create(graph, &edges, igraph_integer_t(node_count), true);
igraph_vector_destroy(&edges);
IGRAPH_FINALLY_CLEAN(1);
return IGRAPH_SUCCESS;
}
static int igraph_i_realize_undirected_degree_sequence(
igraph_t *graph,
const igraph_vector_t *deg,
igraph_realize_degseq_t method)
{
long node_count = igraph_vector_size(deg);
long deg_sum = long(igraph_vector_sum(deg));
if (deg_sum % 2 != 0)
IGRAPH_ERROR("The sum of degrees must be even for an undirected graph", IGRAPH_EINVAL);
igraph_vector_t edges;
IGRAPH_CHECK(igraph_vector_init(&edges, deg_sum));
IGRAPH_FINALLY(igraph_vector_destroy, &edges);
switch (method) {
case IGRAPH_REALIZE_DEGSEQ_SMALLEST:
IGRAPH_CHECK(igraph_i_havel_hakimi(deg, &edges, false));
break;
case IGRAPH_REALIZE_DEGSEQ_LARGEST:
IGRAPH_CHECK(igraph_i_havel_hakimi(deg, &edges, true));
break;
case IGRAPH_REALIZE_DEGSEQ_INDEX:
IGRAPH_CHECK(igraph_i_havel_hakimi_index(deg, &edges));
break;
default:
IGRAPH_ERROR("Invalid degree sequence realization method", IGRAPH_EINVAL);
}
igraph_create(graph, &edges, igraph_integer_t(node_count), false);
igraph_vector_destroy(&edges);
IGRAPH_FINALLY_CLEAN(1);
return IGRAPH_SUCCESS;
}
/*__________________________________________________________________________ MAIN CYCLE (FLTK CYCLE) ____*/
void mainidle_cb(void*){ //this routine updates the program.
//thus, it computes the EVOLUTION
double shooted;
double dens, err;
double totdens, toterr, totimerr;
char s[100];
// ---- running controls AND PRINTING
if(
(amstepping==0 && runningcontrol==1 && graphisloaded==1 && ticks<=maxtime ) ||
(amstepping==1 && runningcontrol==1 && graphisloaded==1 && ticks<=maxtime && tickstep<=step-1)
)
{
Evolution(deltat);
//PRINTS
if((int)printdatabutton->value()==1){
//if have steady state
if(usesteady==1){
igraph_matrix_t activation;
igraph_matrix_init(&activation,nodesnumber,totrun);
igraph_matrix_null(&activation);
igraph_vector_t correlation;
igraph_vector_init(&correlation,(nodesnumber*nodesnumber)); igraph_vector_null(&correlation);
fprintf(output1,"%i ", ticks);
fprintf(output2,"%i ", ticks);
fprintf(output5,"%i ", ticks);
fprintf(output6,"%i ", ticks);
totdens=0; toterr=0;
for(int i=0;i<nodesnumber;++i){
shooted=0;
dens=0;
err=0;
for(int j=0; j<totrun; ++j){
dens=dens+MATRIX(density,i,j);
err=err+((VECTOR(statstate)[i]-MATRIX(density,i,j))*(VECTOR(statstate)[i]-MATRIX(density,i,j)));
shooted=shooted+MATRIX(loss,i,j);
if(MATRIX(loss,i,j)!=0){++MATRIX(activation,i,j);}
}
dens=dens/totrun;
err=sqrt(err)/totrun;
shooted=shooted/totrun;
totdens=totdens+dens;
toterr=toterr+err;
fprintf(output1,"%f ",dens);
fprintf(output2,"%f ",err);
fprintf(output5,"%f ",shooted);
}
totdens=totdens/nodesnumber;
toterr=toterr/nodesnumber;
fprintf(output1,"%f ",totdens);
fprintf(output2,"%f ",toterr);
// printf("\n\n ACTIVATION MATRIX \n \n"); print_matrix_ur(&activation,stdout); printf("\n\n");
// ---- CORRELATION ---
igraph_vector_t meanactivation;
igraph_vector_init(&meanactivation,nodesnumber);
igraph_vector_null(&meanactivation);
//calculate mean activation
for (int j=0; j<totrun; ++j) {
for (int i=0; i<nodesnumber; ++i) {
VECTOR(meanactivation)[i]=VECTOR(meanactivation)[i]+MATRIX(activation,i,j);
}
}
igraph_vector_scale(&meanactivation,1./totrun);
//calculate actual correlation
for (int x=0; x<nodesnumber ; ++x) {
for(int y=0; y<nodesnumber; ++y){
double prod=0;
for (int j=0; j<totrun; ++j) {
prod=prod+ ( MATRIX(activation,x,j)*MATRIX(activation,y,j) );
}
prod=prod/totrun;
VECTOR(correlation)[(x*nodesnumber+y)] = prod - (VECTOR(meanactivation)[x]*VECTOR(meanactivation)[y]);
}
}
igraph_vector_destroy(&meanactivation);
for (int i=0; i<(nodesnumber*nodesnumber); ++i) {
fprintf(output6,"%f ",VECTOR(correlation)[i]);
}
//calculate error on run
igraph_matrix_t distl1; igraph_matrix_t distimel1;
igraph_matrix_init(&distl1,nodesnumber,totrun); igraph_matrix_init(&distimel1,nodesnumber,totrun);
igraph_matrix_null(&distl1); igraph_matrix_null(&distimel1);
igraph_vector_t rundistl1; igraph_vector_t rundistimel1;
igraph_vector_init(&rundistl1,totrun); igraph_vector_init(&rundistimel1,totrun);
igraph_vector_null(&rundistl1); igraph_vector_null(&rundistimel1);
toterr=0; totimerr=0;
//for every run
for(int j=0;j<totrun;++j){
//i evaluate the distance between the state and the stationary state (toterr) and the distance between old and new density (totimerr)
for(int i=0; i<nodesnumber; ++i)
{
//L1 DISTANCE WRT STATSTATE & DENSITY
MATRIX(distl1,i,j)=fabs(VECTOR(statstate)[i]-MATRIX(density,i,j));
//L1 DISTANCE WRT OLD DENSITY & DENSITY
MATRIX(distimel1,i,j)=fabs(MATRIX(densityold,i,j)-MATRIX(density,i,j));
}
}
igraph_matrix_rowsum(&distl1,&rundistl1); igraph_matrix_rowsum(&distimel1,&rundistimel1);
igraph_vector_scale(&rundistl1,(1./nodesnumber)); igraph_vector_scale(&rundistimel1,(1./nodesnumber));
toterr= (double)( igraph_vector_sum(&rundistl1) ) / (double)totrun ;
totimerr= (double)( igraph_vector_sum(&rundistimel1)) / (double)totrun;
igraph_vector_destroy(&rundistl1); igraph_vector_destroy(&rundistimel1);
igraph_matrix_destroy(&distl1); igraph_matrix_destroy(&distimel1);
fprintf(output2,"%f %f",toterr, totimerr);
fprintf(output1,"\n");
fprintf(output2,"\n");
fprintf(output5,"\n");
fprintf(output6,"\n");
//if i have BRIDGES ("clustered" graph), I print the traffic on the BRIDGES, using "output3" file
if(isclustered==1){
//for each bridge
fprintf(output3,"%i ",ticks);
for(int nbri=0; nbri<igraph_matrix_ncol(&bridgeslinks); ++nbri){
for(int i=0; i<igraph_matrix_nrow(&bridgeslinks);++i){
double tfl=0;
for(int j=0; j<totrun; ++j){
int beid;
beid=(int)MATRIX(bridgeslinks,i,nbri);
tfl=tfl+MATRIX(flux,beid,j);
}
fprintf(output3,"%f ",tfl);
}
}
fprintf(output3,"\n");
}
igraph_matrix_destroy(&activation);
igraph_vector_destroy(&correlation);
}
//if i HAVENT STEADY STATE
else {
fprintf(output1,"%i ", ticks);
fprintf(output5,"%i ", ticks);
for(int i=0;i<nodesnumber;++i){
shooted=0;
dens=0;
for(int j=0; j<totrun; ++j){
dens=dens+MATRIX(density,i,j);
shooted=shooted+MATRIX(loss,i,j);
}
dens=dens/totrun;
shooted=shooted/totrun;
fprintf(output1,"%f " ,dens);
fprintf(output5,"%f " ,shooted);
}
fprintf(output1,"\n");
fprintf(output5,"\n");
}
}
}
if((ticks==maxtime || tickstep==step) && runningcontrol==1){
run();
}
// ---- no graph loaded
if(graphisloaded==0 && rewrite==1) {
runbutton->deactivate();
sprintf(s,"No\nnetwork\nloaded");
databuff->text(s);
}
// ---- graph loaded
else {
runbutton->activate();
if(islattice==1 && rewrite==1){
if(istoro==1){
sprintf(s,"Nodes=%i\nToroidal\nLattice\n%iD Side=%i",nodesnumber, latticedim, latticeside);
}
else{
sprintf(s,"Nodes=%i\nLattice\n%iD Side=%i",nodesnumber, latticedim, latticeside);
}
databuff->text(s);
}
else if(rewrite==1){
sprintf(s,"Nodes=%i",nodesnumber);
databuff->text(s);
}
}
//have path
if(havepath==1 && rewrite==1){pathbuff->text(path); }
else if(havepath==0 && rewrite==1){pathbuff->text("No Path");}
if(error==1 && rewrite==1){
sprintf(s,errorstring);
databuff->text(s);
}
if (ticks<=maxtime){
scene->redraw();
datascene->redraw();
}
rewrite=0;
//Fl::repeat_timeout(1.0, mainidle_cb);
}
int main() {
igraph_t g;
igraph_vector_t v, v2;
int i, ret;
igraph_barabasi_game(&g, 10, 2, 0, 0, 1);
if (igraph_ecount(&g) != 18) {
return 1;
}
if (igraph_vcount(&g) != 10) {
return 2;
}
if (!igraph_is_directed(&g)) {
return 3;
}
igraph_vector_init(&v, 0);
igraph_get_edgelist(&g, &v, 0);
for (i=0; i<igraph_ecount(&g); i++) {
if (VECTOR(v)[2*i] <= VECTOR(v)[2*i+1]) {
return 4;
}
}
igraph_destroy(&g);
/* out degree sequence */
igraph_vector_resize(&v, 10);
VECTOR(v)[0]=0;
VECTOR(v)[1]=1;
VECTOR(v)[2]=3;
VECTOR(v)[3]=3;
VECTOR(v)[4]=4;
VECTOR(v)[5]=5;
VECTOR(v)[6]=6;
VECTOR(v)[7]=7;
VECTOR(v)[8]=8;
VECTOR(v)[9]=9;
igraph_barabasi_game(&g, 10, 0, &v, 0, 1);
if (igraph_ecount(&g) != igraph_vector_sum(&v)) {
return 5;
}
igraph_vector_init(&v2, 0);
igraph_degree(&g, &v2, igraph_vss_all(), IGRAPH_OUT, 1);
for (i=0; i<igraph_vcount(&g); i++) {
if (VECTOR(v)[i] != VECTOR(v2)[i]) {
return 6;
}
}
igraph_vector_destroy(&v);
igraph_vector_destroy(&v2);
igraph_destroy(&g);
/* outpref, we cannot really test this quantitatively,
would need to set random seed */
igraph_barabasi_game(&g, 10, 2, 0, 1, 1);
igraph_vector_init(&v, 0);
igraph_get_edgelist(&g, &v, 0);
for (i=0; i<igraph_ecount(&g); i++) {
if (VECTOR(v)[2*i] <= VECTOR(v)[2*i+1]) {
return 7;
}
}
if (!igraph_is_directed(&g)) {
return 8;
}
igraph_vector_destroy(&v);
igraph_destroy(&g);
/* Error tests */
igraph_set_error_handler(igraph_error_handler_ignore);
ret=igraph_barabasi_game(&g, -10, 1, 0, 0, 0);
if (ret != IGRAPH_EINVAL) {
return 9;
}
ret=igraph_barabasi_game(&g, 10, -2, 0, 0, 0);
if (ret != IGRAPH_EINVAL) {
return 10;
}
igraph_vector_init(&v, 9);
ret=igraph_barabasi_game(&g, 10, 0, &v, 0, 0);
if (ret != IGRAPH_EINVAL) {
return 11;
}
igraph_vector_destroy(&v);
return 0;
}
/**
* \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;
}
/**
* \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);
}
