int check_ev(const igraph_matrix_t *A, const igraph_vector_t *values,
const igraph_matrix_t *vectors) {
int i, n=igraph_matrix_nrow(A);
int ne=igraph_matrix_ncol(vectors);
igraph_vector_t v, lhs, rhs;
if (ne != igraph_vector_size(values)) {
printf("'values' and 'vectors' sizes do not match\n");
exit(1);
}
igraph_vector_init(&lhs, n);
igraph_vector_init(&rhs, n);
for (i=0; i<ne; i++) {
igraph_vector_view(&v, &MATRIX(*vectors, 0, i), n);
igraph_blas_dgemv(/*transpose=*/ 0, /*alpha=*/ 1, A, &v,
/*beta=*/ 0, &lhs);
igraph_vector_update(&rhs, &v);
igraph_vector_scale(&rhs, VECTOR(*values)[i]);
if (igraph_vector_maxdifference(&lhs, &rhs) > 1e-10) {
printf("LHS: "); igraph_vector_print(&lhs);
printf("RHS: "); igraph_vector_print(&rhs);
exit(2);
}
}
igraph_vector_destroy(&rhs);
igraph_vector_destroy(&lhs);
return 0;
}
igraph_bool_t check_ev(const igraph_matrix_t *A,
const igraph_vector_t *values_real,
const igraph_vector_t *values_imag,
const igraph_matrix_t *vectors_left,
const igraph_matrix_t *vectors_right,
igraph_real_t tol) {
int n=igraph_matrix_nrow(A);
igraph_vector_t v_real, v_imag;
igraph_vector_t AV_real, AV_imag, lv_real, lv_imag;
igraph_vector_t null;
int i;
if (igraph_matrix_ncol(A) != n) { return 1; }
if (igraph_vector_size(values_real) != n) { return 1; }
if (igraph_vector_size(values_imag) != n) { return 1; }
if (igraph_matrix_nrow(vectors_left) != n) { return 1; }
if (igraph_matrix_ncol(vectors_left) != n) { return 1; }
if (igraph_matrix_nrow(vectors_right) != n) { return 1; }
if (igraph_matrix_ncol(vectors_right) != n) { return 1; }
igraph_vector_init(&AV_real, n);
igraph_vector_init(&AV_imag, n);
igraph_vector_init(&lv_real, n);
igraph_vector_init(&lv_imag, n);
igraph_vector_init(&null, n);
igraph_vector_null(&null);
for (i=0; i<n; i++) {
if (VECTOR(*values_imag)[i]==0.0) {
igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i), n);
igraph_vector_view(&v_imag, VECTOR(null), n);
} else if (VECTOR(*values_imag)[i] > 0.0) {
igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i), n);
igraph_vector_view(&v_imag, &MATRIX(*vectors_right, 0, i+1), n);
} else if (VECTOR(*values_imag)[i] < 0.0) {
igraph_vector_view(&v_real, &MATRIX(*vectors_right, 0, i-1), n);
igraph_vector_view(&v_imag, &MATRIX(*vectors_right, 0, i), n);
igraph_vector_scale(&v_imag, -1.0);
}
real_cplx_mult(A, &v_real, &v_imag, &AV_real, &AV_imag);
sc_cplx_cplx_mult(VECTOR(*values_real)[i], VECTOR(*values_imag)[i],
&v_real, &v_imag, &lv_real, &lv_imag);
if (igraph_vector_maxdifference(&AV_real, &lv_real) > tol ||
igraph_vector_maxdifference(&AV_imag, &lv_imag) > tol) {
igraph_vector_print(&AV_real); igraph_vector_print(&AV_imag);
igraph_vector_print(&lv_real); igraph_vector_print(&lv_imag);
return 1;
}
}
igraph_vector_destroy(&null);
igraph_vector_destroy(&AV_imag);
igraph_vector_destroy(&AV_real);
igraph_vector_destroy(&lv_imag);
igraph_vector_destroy(&lv_real);
return 0;
}
/*__________________________________________________________________________ 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);
}
/**
* \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_i_kleinberg(const igraph_t *graph, igraph_vector_t *vector,
igraph_real_t *value, igraph_bool_t scale,
igraph_arpack_options_t *options, int inout) {
igraph_adjlist_t myinadjlist, myoutadjlist;
igraph_adjlist_t *inadjlist, *outadjlist;
igraph_vector_t tmp;
igraph_vector_t values;
igraph_matrix_t vectors;
igraph_i_kleinberg_data_t extra;
long int i;
options->n=igraph_vcount(graph);
options->start=1;
IGRAPH_VECTOR_INIT_FINALLY(&values, 0);
IGRAPH_MATRIX_INIT_FINALLY(&vectors, options->n, 1);
IGRAPH_VECTOR_INIT_FINALLY(&tmp, options->n);
if (inout==0) {
inadjlist=&myinadjlist;
outadjlist=&myoutadjlist;
} else if (inout==1) {
inadjlist=&myoutadjlist;
outadjlist=&myinadjlist;
} else {
/* This should not happen */
IGRAPH_ERROR("Invalid 'inout' argument, plese do not call "
"this funtion directly", IGRAPH_FAILURE);
}
IGRAPH_CHECK(igraph_adjlist_init(graph, &myinadjlist, IGRAPH_IN));
IGRAPH_FINALLY(igraph_adjlist_destroy, &myinadjlist);
IGRAPH_CHECK(igraph_adjlist_init(graph, &myoutadjlist, IGRAPH_OUT));
IGRAPH_FINALLY(igraph_adjlist_destroy, &myoutadjlist);
IGRAPH_CHECK(igraph_degree(graph, &tmp, igraph_vss_all(), IGRAPH_ALL, 0));
for (i=0; i<options->n; i++) {
if (VECTOR(tmp)[i] != 0) {
MATRIX(vectors, i, 0) = VECTOR(tmp)[i];
} else {
MATRIX(vectors, i, 0) = 1.0;
}
}
extra.in=inadjlist; extra.out=outadjlist; extra.tmp=&tmp;
options->n = igraph_vcount(graph);
options->nev = 1;
options->ncv = 3;
options->which[0]='L'; options->which[1]='M';
options->start=1; /* no random start vector */
IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_kleinberg2, &extra,
options, 0, &values, &vectors));
igraph_adjlist_destroy(&myoutadjlist);
igraph_adjlist_destroy(&myinadjlist);
igraph_vector_destroy(&tmp);
IGRAPH_FINALLY_CLEAN(3);
if (value) {
*value = VECTOR(values)[0];
}
if (vector) {
igraph_real_t amax=0;
long int which=0;
long int i;
IGRAPH_CHECK(igraph_vector_resize(vector, options->n));
for (i=0; i<options->n; i++) {
igraph_real_t tmp;
VECTOR(*vector)[i] = MATRIX(vectors, i, 0);
tmp=fabs(VECTOR(*vector)[i]);
if (tmp>amax) { amax=tmp; which=i; }
}
if (scale && amax!=0) { igraph_vector_scale(vector, 1/VECTOR(*vector)[which]); }
}
if (options->info) {
IGRAPH_WARNING("Non-zero return code from ARPACK routine!");
}
igraph_matrix_destroy(&vectors);
igraph_vector_destroy(&values);
IGRAPH_FINALLY_CLEAN(2);
return 0;
}
int igraph_eigenvector_centrality(const igraph_t *graph, igraph_vector_t *vector,
igraph_real_t *value, igraph_bool_t scale,
const igraph_vector_t *weights,
igraph_arpack_options_t *options) {
igraph_vector_t values;
igraph_matrix_t vectors;
igraph_vector_t degree;
long int i;
options->n=igraph_vcount(graph);
options->start=1; /* no random start vector */
if (weights && igraph_vector_size(weights) != igraph_ecount(graph)) {
IGRAPH_ERROR("Invalid length of weights vector when calculating "
"eigenvector centrality", IGRAPH_EINVAL);
}
if (weights && igraph_is_directed(graph)) {
IGRAPH_WARNING("Weighted directed graph in eigenvector centrality");
}
IGRAPH_VECTOR_INIT_FINALLY(&values, 0);
IGRAPH_MATRIX_INIT_FINALLY(&vectors, options->n, 1);
IGRAPH_VECTOR_INIT_FINALLY(°ree, options->n);
IGRAPH_CHECK(igraph_degree(graph, °ree, igraph_vss_all(),
IGRAPH_ALL, /*loops=*/ 0));
for (i=0; i<options->n; i++) {
if (VECTOR(degree)[i]) {
MATRIX(vectors, i, 0) = VECTOR(degree)[i];
} else {
MATRIX(vectors, i, 0) = 1.0;
}
}
igraph_vector_destroy(°ree);
IGRAPH_FINALLY_CLEAN(1);
options->n = igraph_vcount(graph);
options->nev = 1;
options->ncv = 3;
options->which[0]='L'; options->which[1]='A';
options->start=1; /* no random start vector */
if (!weights) {
igraph_adjlist_t adjlist;
IGRAPH_CHECK(igraph_adjlist_init(graph, &adjlist, IGRAPH_ALL));
IGRAPH_FINALLY(igraph_adjlist_destroy, &adjlist);
IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_eigenvector_centrality,
&adjlist, options, 0, &values, &vectors));
igraph_adjlist_destroy(&adjlist);
IGRAPH_FINALLY_CLEAN(1);
} else {
igraph_adjedgelist_t adjedgelist;
igraph_i_eigenvector_centrality_t data = { graph, &adjedgelist, weights };
IGRAPH_CHECK(igraph_adjedgelist_init(graph, &adjedgelist, IGRAPH_ALL));
IGRAPH_FINALLY(igraph_adjedgelist_destroy, &adjedgelist);
IGRAPH_CHECK(igraph_arpack_rssolve(igraph_i_eigenvector_centrality2,
&data, options, 0, &values, &vectors));
igraph_adjedgelist_destroy(&adjedgelist);
IGRAPH_FINALLY_CLEAN(1);
}
if (value) {
*value=VECTOR(values)[0];
}
if (vector) {
igraph_real_t amax=0;
long int which=0;
long int i;
IGRAPH_CHECK(igraph_vector_resize(vector, options->n));
for (i=0; i<options->n; i++) {
igraph_real_t tmp;
VECTOR(*vector)[i] = MATRIX(vectors, i, 0);
tmp=fabs(VECTOR(*vector)[i]);
if (tmp>amax) { amax=tmp; which=i; }
}
if (scale && amax!=0) { igraph_vector_scale(vector, 1/VECTOR(*vector)[which]); }
}
if (options->info) {
IGRAPH_WARNING("Non-zero return code from ARPACK routine!");
}
igraph_matrix_destroy(&vectors);
igraph_vector_destroy(&values);
IGRAPH_FINALLY_CLEAN(2);
return 0;
}
