void NBS::initialise (const node_t num_nodes)
{
const Mat2Vec mat2vec (num_nodes);
const size_t num_edges = mat2vec.vec_size();
ProgressBar progress ("Pre-computing statistical correlation matrix...", num_edges);
adjacency.reset (new vector< vector<size_t> > (num_edges, vector<size_t>()));
for (node_t row = 0; row != num_nodes; ++row) {
for (node_t column = row; column != num_nodes; ++column) {
const size_t index = mat2vec (row, column);
vector<size_t>& vector = (*adjacency)[index];
vector.reserve (2 * (num_nodes-1));
// Should be able to expand from this edge to any other edge connected to either row or column
for (node_t r = 0; r != num_nodes; ++r) {
if (r != row)
vector.push_back (mat2vec (r, column));
}
for (node_t c = 0; c != num_nodes; ++c) {
if (c != column)
vector.push_back (mat2vec (row, c));
}
++progress;
}
}
}
void remove_random_edge(uchar *adj) {
uchar j;
uchar r = (uchar) (random_rand() % TOT_NUM_NODES);
uchar found = 0;
for (j = 0; j < TOT_NUM_NODES && !found; j++) {
if (adj[mat2vec(r, j)]) {
found = 1;
adj[mat2vec(r, j)] = 1;
adj[mat2vec(j, r)] = 1;
}
}
}
static void set_adj_matrix(uchar *adj) {
uchar i, j;
for (i = 0; i < TOT_NUM_NODES - 1; i++) {
for (j = 0; j < TOT_NUM_NODES - 1; j++) {
if (temp_adj_matrix[i][j]) {
adj[mat2vec(i, j)] = 1;
}
}
}
}
int independent(int n,int mat[MAXN][MAXN]){
i64 vec[MAXN];
int i;
max=1;
sort(n,mat);
for (i=0;i<n;i++)
mat[i][i]=1;
mat2vec(n,mat,vec);
search(n,vec,n-1,0,(((i64)1)<<n)-1);
return max;
}
uchar choose_random_edge(uchar v1, uchar *adj) {
uchar i, random_value, diff_zero = 0;
uchar aux[TOT_NUM_NODES];
for (i = 0; i < TOT_NUM_NODES; i++) {
if (adj[mat2vec(v1, i)]) {
aux[diff_zero] = i;
diff_zero++;
}
}
if (!diff_zero)
return 0;
else {
random_value = (uchar) (random_rand() % diff_zero);
}
return aux[random_value];
}
int clique(int n,int mat[MAXN][MAXN]){
i64 vec[MAXN];
int tmp[MAXN][MAXN],v[MAXN]={0},node[MAXN],m,i,j,k;
for (max=1,i=0;i<n;i++)
if (!v[i]){
m=0;
flood(i,n,mat,v,m,node);
if (m>max){
for (j=0;j<m;tmp[j][j]=0,j++)
for (k=0;k<m;k++)
tmp[j][k]=mat[node[j]][node[k]];
sort(m,tmp);
mat2vec(m,tmp,vec);
search(m,vec,m-1,0,(((i64)1)<<m)-1);
}
}
return max;
}
/**
* %HENNEBURGGRAPH Randomly generates a rigid graph with Henneburg operations
* @param adj Adjacency matrix
*/
void henneburgGraph(uchar *adj) {
uchar i, op, v1, v2, v3;
//Add first bar between first 2 nodes
adj[mat2vec(0, 1)] = 1;
adj[mat2vec(1, 0)] = 1;
//Perform N-2 random Henneburg operations to generate graph
for (i = 2; i < TOT_NUM_NODES; i++) {
if (i > 2)
op = (uchar) (random_rand() % 2) + 1;
else
op = 1;
// Perform the 2-valent operation
if (op == 1) {
//Choose vertices
v1 = (uchar) (random_rand() % i);
v2 = (uchar) (random_rand() % i);
while (v2 == v1) {
v2 = (uchar) (random_rand() % i);
}
//% Add new edges
adj[mat2vec(i, v1)] = 1;
adj[mat2vec(v1, i)] = 1;
adj[mat2vec(i, v2)] = 1;
adj[mat2vec(v2, i)] = 1;
}
// Perform the 3-valent operation
if (op == 2) {
// Choose an edge
v1 = (uchar) (random_rand() % i);
v2 = choose_random_edge(v1, adj);
// Choose a third vertex
v3 = (uchar) (random_rand() % i);
while (v3 == v1 || v3 == v2) {
v3 = (uchar) (random_rand() % i);
}
//Remove edge (v1,v2) and add edges (v1,i), (v2,i), (v3,i)
adj[mat2vec(v1, v2)] = 0;
adj[mat2vec(v2, v1)] = 0;
adj[mat2vec(v1, i)] = 1;
adj[mat2vec(i, v1)] = 1;
adj[mat2vec(v2, i)] = 1;
adj[mat2vec(i, v2)] = 1;
adj[mat2vec(v3, i)] = 1;
adj[mat2vec(i, v3)] = 1;
}
}
}