void CDLib::generate_clique_graph(graph& g, id_type size) {
init_empty_graph(g, size);
for (id_type i = 0; i < g.get_num_nodes(); i++)
for (id_type j = 0; j < i; j++)
if (i != j) g.add_edge(i, j, 1);
g.set_graph_name("clique_" + T2str<id_type > (size));
}
void CDLib::generate_barabasi_albert_model(graph& g, size_t num_nodes, size_t min_degree_of_node) {
init_empty_graph(g, num_nodes);
vector<id_type> vertices_with_edges;
UniformRandomGeneratorAkash<id_type> randint;
UniformRandomGeneratorAkash<double> randdouble;
for (id_type k = 1; k <= min_degree_of_node; k++) {
g.add_edge(0, k, 1);
vertices_with_edges.push_back(k);
}
for (id_type i = 1; i < num_nodes; i++) {
while (g.get_node_in_degree(i) < min_degree_of_node) {
double R1 = randdouble.next(1);
if (R1 < 0.5) {
id_type R2 = randint.next(vertices_with_edges.size());
g.add_edge(i, vertices_with_edges[R2], 1);
vertices_with_edges.push_back(vertices_with_edges[R2]);
} else {
id_type R3 = randint.next(i);
g.add_edge(i, R3, 1);
vertices_with_edges.push_back(R3);
}
}
}
g.set_graph_name("ba_" + T2str<size_t > (num_nodes) + "_" + T2str<size_t > (min_degree_of_node));
}
bool CDLib::read_edgelist(graph& g, const string& filepath) {
g.clear();
ifstream ifs;
ifs.open(filepath.c_str());
if (ifs.is_open()) {
vector<string> units;
double weight;
while (!ifs.eof()) {
weight = 1;
string line;
getline(ifs, line);
if ((line.size() > 0) && (line[0] != '#')) {
split(line, units);
if (units.size() != 0) {
if ((units.size() < 2) || (units.size() > 3)) return false;
if (units.size() == 3) weight = str2T<double>(units[2]);
g.add_node(units[0]);
g.add_node(units[1]);
g.add_edge(units[0], units[1], weight);
}
}
}
g.set_graph_name(filename(filepath));
return true;
}
return false;
}
void CDLib::generate_LEET_chord_graph(graph& g, id_type num_nodes) {
// init_empty_graph(g,num_nodes);
// id_type cluster_size = log2(g.get_num_nodes());
// for (id_type i=0; i<g.get_num_nodes(); i++)
// {
// g.add_edge(i,(i-1) % g.get_num_nodes(),1);
// g.add_edge(i,(i+1) % g.get_num_nodes(),1);
// id_type id_in_cluster = g.get_num_nodes() % static_cast<id_type>(cluster_size);
// g.add_edge(i,id_in_cluster*(1+static_cast<id_type>(cluster_size)),1);
// }
init_empty_graph(g, num_nodes);
id_type num_clusters = num_nodes / log2(num_nodes);
id_type num_nodes_per_cluster = static_cast<id_type> (log2(num_nodes));
for (id_type i = 0; i < num_clusters; i++) {
id_type start_id = i*num_nodes_per_cluster;
//Adding the individual Clusters
for (id_type j = 0; j < num_nodes_per_cluster; j++) {
g.add_edge(start_id + j, start_id + ((j - 1) % num_nodes_per_cluster), 1);
for (id_type k = 1; k <= num_nodes_per_cluster / 2; k *= 2)
g.add_edge(start_id + j, start_id + ((j + k) % num_nodes_per_cluster), 1);
}
//Adding the long range links
for (id_type j = log2(num_clusters) - 1, k = 0; j > 0; j--, k++) {
id_type next_cluster_id = ((i + j) % num_clusters) * num_nodes_per_cluster;
g.add_edge(start_id + (k % num_nodes_per_cluster), next_cluster_id + (j % num_nodes_per_cluster), 1);
}
}
g.set_graph_name("leet_chord_" + T2str<id_type > (num_nodes));
g.remove_isolates();
}
void CDLib::generate_kademlia_graph(graph& g, id_type num_nodes) {
init_empty_graph(g, num_nodes);
unsigned int num_bits = log2(num_nodes);
for (unsigned int i = 0; i < num_nodes; i++)
for (unsigned int j = 0; j < num_bits; j++)
g.add_edge(i, (i ^ ((1 << j))) % num_nodes, 1);
g.set_graph_name("kademlia_" + T2str<id_type > (num_nodes));
}
void CDLib::generate_chord_graph(graph& g, id_type num_nodes) {
init_empty_graph(g, num_nodes);
for (id_type i = 0; i < g.get_num_nodes(); i++) {
g.add_edge(i, (i - 1) % g.get_num_nodes(), 1);
for (id_type j = 1; j <= g.get_num_nodes() / 2; j *= 2)
g.add_edge(i, (i + j) % g.get_num_nodes(), 1);
}
g.set_graph_name("chord_" + T2str<id_type > (num_nodes));
}
void CDLib::generate_spoke_graph(graph& g, id_type size) {
generate_star_graph(g, size);
id_type last_id = g.get_num_nodes() - 1;
if (last_id > 1) {
for (id_type i = 1; i < last_id; i++)
g.add_edge(i, (i + 1), 1);
g.add_edge(last_id, 1, 1);
}
g.set_graph_name("spoke_" + T2str<id_type > (size));
}
void CDLib::generate_erdos_renyi_graph(graph& g, id_type num_nodes, double p) {
if (p >= 0 && p <= 1) {
init_empty_graph(g, num_nodes);
RandomGenerator<double> p_gen(0, 1, 1);
for (id_type i = 0; i < num_nodes; i++)
for (id_type j = 0; j < num_nodes; j++)
if ((!g.is_directed() && i < j) && p_gen.next() <= p) g.add_edge(i, j, 1);
g.set_graph_name("er_" + T2str<id_type > (num_nodes) + "_" + T2str<double>(p));
}
}
void CDLib::generate_de_bruijn_graph(graph& g, id_type num_symbols, id_type sequence_length) {
if (num_symbols && sequence_length) {
id_type size = (unsigned long) pow((double) num_symbols, (double) sequence_length);
init_empty_graph(g, size);
for (id_type i = 0; i < g.get_num_nodes(); i++) {
id_type basis = (i * num_symbols) % g.get_num_nodes();
for (id_type j = 0; j < num_symbols; j++) g.add_edge(i, basis + j, 1);
}
g.set_graph_name("db_" + T2str<id_type > (num_symbols) + "_" + T2str<id_type > (sequence_length));
}
}
void CDLib::generate_scale_free_graph(graph& g, id_type num_nodes, id_type num_edges, double alpha, double beta) {
init_empty_graph(g, num_nodes);
RandomGenerator<id_type> x_gen(0, num_nodes), from_gen(0, num_nodes), to_gen(0, num_nodes);
vector<id_type> outdegrees(num_nodes, 0.0);
for (id_type i = 0; i < num_nodes; i++)
outdegrees[i] = (id_type) x_gen.exp_next(alpha, beta);
for (id_type i = 0; i < num_edges; i++) {
id_type from_id = from_gen.next(), to_id = to_gen.next();
if (outdegrees[from_id] && outdegrees[to_id] && from_id != to_id && !g.get_edge_weight(from_id, to_id))
g.add_edge(from_id, to_id, 1);
}
g.set_graph_name("sf_" + T2str<id_type > (num_nodes) + "_" + T2str<id_type > (num_edges) + "_" + T2str<double>(alpha) + "_" + T2str<double>(beta));
}
/*degree distribution of this model follows power law distribution.
* this is a most suitable synthetic model to real-world network like peer to peer networks and citation networks.*/
bool CDLib::generate_vertex_copying_model(graph& g, size_t num_nodes, size_t num_of_out_degree, size_t num_of_vertices_at_initial, double probability_to_copy_from_existing_vertex) {
if (num_of_vertices_at_initial > num_of_out_degree && probability_to_copy_from_existing_vertex >= 0 && probability_to_copy_from_existing_vertex <= 1) {
UniformRandomGeneratorAkash<wt_t> randdouble;
UniformRandomGeneratorAkash<id_type> randint;
init_empty_graph(g, num_nodes);
for (id_type i = 0; i < num_of_vertices_at_initial; i++) {
while (g.get_node_out_degree(i) < num_of_out_degree) {
back:
id_type R1 = randint.next(num_of_vertices_at_initial);
if (R1 == i)
goto back;
else {
g.add_edge(i, R1, 1);
}
}
}
for (id_type i = num_of_vertices_at_initial; i < num_nodes; i++) {
id_type R2 = randint.next(i);
vector<id_type> vertices_pointed_by_R2;
for (adjacent_edges_iterator aeit = g.out_edges_begin(R2); aeit != g.out_edges_end(R2); aeit++) {
vertices_pointed_by_R2.push_back(aeit->first);
}
while (g.get_node_out_degree(i) < num_of_out_degree) {
wt_t R3 = randdouble.next(1);
if (R3 < probability_to_copy_from_existing_vertex) {
g.add_edge(i, vertices_pointed_by_R2[g.get_node_out_degree(i)], 1);
} else {
A:
id_type R4 = randint.next(num_nodes);
if (R4 != i) {
g.add_edge(i, R4, 1);
} else
goto A;
}
}
}
g.set_graph_name("vc_" + T2str<size_t > (num_nodes) + "_" + T2str<size_t > (num_of_out_degree) + "_" + T2str<size_t > (num_of_vertices_at_initial) + "_" + T2str<double>(probability_to_copy_from_existing_vertex));
return 1;
} else {
// cout<<"\nnum_of_vertices_at_initial should greater than num_of_out_degree\n";
return 0;
}
}
bool CDLib::read_adjacencylist(graph& g, const string& filepath) {
g.clear();
ifstream ifs;
ifs.open(filepath.c_str());
if (ifs.is_open()) {
int type = 0;
id_type nid = 0, estart = 0;
string line;
getline(ifs, line);
vector<id_type> units;
split(line, units);
if ((units.size() > 2) && (units[0] == 0) && (units[1] == units.size() - 2)) {
type = 0;
estart = 2;
} else if ((units.size() > 1) && (units[0] == 0)) {
type = 1;
estart = 1;
} else {
type = 2;
estart = 0;
}
g.add_node(to_string(nid));
for (id_type i = estart; i < units.size(); i++) {
g.add_node(to_string(units[i]));
g.add_edge(to_string(nid), to_string(units[i]), 1);
}
while (!ifs.eof()) {
string line;
getline(ifs, line);
vector<id_type> units;
split(line, units);
if (units.size() > 0) {
if ((type == 0) || (type == 1)) nid = units[0];
else nid++;
g.add_node(to_string(nid));
for (id_type i = estart; i < units.size(); i++) {
g.add_node(to_string(units[i]));
g.add_edge(to_string(nid), to_string(units[i]), 1);
}
}
}
g.set_graph_name(filename(filepath));
return true;
}
return false;
}
bool CDLib::read_matlab_sp(graph& g, const string& filepath) {
g.clear();
ifstream ifs;
ifs.open(filepath.c_str());
if (ifs.is_open()) {
id_type from, to;
double weight = 1;
while (!ifs.eof()) {
ifs >> from >> to >> weight;
while (max(from, to) > g.get_num_nodes()) {
g.add_node();
}
g.add_edge(from - 1, to - 1, weight);
}
g.set_graph_name(filename(filepath));
return true;
}
void CDLib::generate_planted_partition_graph(graph& g, id_type num_comms, id_type comm_size, double pin, double pout, vector< node_set>& communities) {
if (pin >= 0 && pout >= 0 && pin <= 1 && pout <= 1) {
id_type num_nodes = comm_size*num_comms;
init_empty_graph(g, num_nodes);
communities.assign(num_comms, node_set());
Uniform01RandomGeneratorMT p_gen;
for (id_type i = 0; i < num_nodes; i++)
if (i % comm_size) communities[i / comm_size].insert(i);
for (id_type i = 0; i < g.get_num_nodes(); i++) {
id_type comm_id_i = i / comm_size;
for (id_type j = 0; j < g.get_num_nodes(); j++) {
id_type comm_id_j = j / comm_size;
double p = p_gen.next();
if (comm_id_i == comm_id_j && p > pin) g.add_edge(i, j, 1);
else if (p > pout) g.add_edge(i, j, 1);
}
}
g.set_graph_name("pp_" + T2str<id_type > (num_comms) + "_" + T2str<id_type > (comm_size) + "_" + T2str<double>(pin) + "_" + T2str<double>(pout));
}
}
void CDLib::generate_configuration_model(graph& g, vector<id_type>& degree_sequence) {
if (degree_sequence.size() > 0) {
init_empty_graph(g, degree_sequence.size());
vector<id_type> nodes_with_non_0_degree;
for (id_type i = 0; i < degree_sequence.size(); i++) {
if (degree_sequence[i] != 0) {
nodes_with_non_0_degree.push_back(i);
}
}
UniformRandomGeneratorAkash<id_type> rand;
for (id_type i = 0; i < degree_sequence.size(); i++) {
id_type remaining_degree = degree_sequence[i];
for (id_type j = 0; j < remaining_degree; j++) {
back:
id_type R = rand.next(nodes_with_non_0_degree.size());
if (degree_sequence[i] == 1 && i == nodes_with_non_0_degree[R])
goto back;
g.add_edge(i, nodes_with_non_0_degree[R], 1);
degree_sequence[i]--;
degree_sequence[nodes_with_non_0_degree[R]]--;
if (degree_sequence[nodes_with_non_0_degree[R]] == 0) {
if (nodes_with_non_0_degree[R] == i)
break;
nodes_with_non_0_degree.erase(nodes_with_non_0_degree.begin() + R);
}
if (degree_sequence[i] == 0)
break;
}
if (remaining_degree != 0) {
nodes_with_non_0_degree.erase(nodes_with_non_0_degree.begin());
}
}
g.set_graph_name("configuration_model");
}
}
void CDLib::generate_prices_model(graph& g, size_t num_nodes, size_t num_of_out_degree, size_t in_degree_constant) {
init_empty_graph(g, num_nodes);
vector<id_type> vertices_pointed_by_edges;
UniformRandomGeneratorAkash<id_type> randint;
UniformRandomGeneratorAkash<double> randdouble;
double probability = num_of_out_degree / (num_of_out_degree + in_degree_constant);
for (id_type i = 0; i < num_nodes; i++) {
while (g.get_node_out_degree(i) < num_of_out_degree) {
double R1 = randdouble.next(1);
if (R1 < probability) {
id_type R2 = randint.next(vertices_pointed_by_edges.size());
g.add_edge(i, vertices_pointed_by_edges[R2], 1);
vertices_pointed_by_edges.push_back(vertices_pointed_by_edges[R2]);
} else {
id_type R3 = randint.next(num_nodes);
g.add_edge(i, R3, 1);
vertices_pointed_by_edges.push_back(R3);
}
}
}
g.set_graph_name("price_" + T2str<size_t > (num_nodes) + "_" + T2str<size_t > (num_of_out_degree) + "_" + T2str<size_t > (in_degree_constant));
}
/*this model is used to generate graph with high clustering coefficient.
this model matches sports network like american football league.*/
bool CDLib::generate_small_world_model(graph& g, size_t num_nodes, size_t degree_of_each_vertex, double probability_to_replace_edge) {
if (probability_to_replace_edge >= 0 && probability_to_replace_edge <= 1) {
UniformRandomGeneratorAkash<id_type> randint;
UniformRandomGeneratorAkash<double> randdouble;
init_empty_graph(g, num_nodes);
for (id_type i = 0; i < num_nodes; i++) {
for (id_type j = 0; j < degree_of_each_vertex / 2; j++) {
g.add_edge(i, (i + j + 1) % num_nodes, 1);
}
if (degree_of_each_vertex % 2 == 1) {
g.add_edge(i, (i + (degree_of_each_vertex / 2) + 1) % num_nodes, 1);
}
}
for (id_type i = 0; i < num_nodes; i++) {
for (id_type j = 0; j < degree_of_each_vertex; j++) {
double R1 = randdouble.next(1);
if (R1 < probability_to_replace_edge) {
back:
id_type R2 = randint.next(num_nodes);
if (R2 == i)
goto back;
else {
g.add_edge(i, R2, 1);
}
}
}
}
g.set_graph_name("sw_" + T2str<size_t > (num_nodes) + "_" + T2str<size_t > (degree_of_each_vertex) + "_" + T2str<double>(probability_to_replace_edge));
return 1;
} else {
// cout<<"\nprobability value might be wrong";
return 0;
}
}
void CDLib::generate_erdos_renyi_graph(graph& g, id_type num_nodes, id_type num_edges) {
double p = (double) num_edges / (num_nodes * (num_nodes - 1));
generate_erdos_renyi_graph(g, num_nodes, p);
g.set_graph_name("er_" + T2str<id_type > (num_nodes) + "_" + T2str<id_type > (num_edges));
}
void CDLib::generate_star_graph(graph& g, id_type size) {
init_empty_graph(g, size);
for (id_type i = 1; i < g.get_num_nodes(); i++)
g.add_edge(0, i, 1);
g.set_graph_name("star_" + T2str<id_type > (size));
}
void CDLib::generate_ring_graph(graph& g, id_type size) {
init_empty_graph(g, size);
for (id_type i = 0; i < g.get_num_nodes(); i++)
g.add_edge(i, (i + 1) % size, 1);
g.set_graph_name("ring_" + T2str<id_type > (size));
}
