int init_resources()
{
simpleVS= new Shader(NETWORK_VISUALIZER_RESSOURCE_PATH "shader/simple.vs.c",GL_VERTEX_SHADER);
simpleFS= new Shader(NETWORK_VISUALIZER_RESSOURCE_PATH "shader/simple.fs.c",GL_FRAGMENT_SHADER);
simpleProgram = new SProgram(*simpleVS,*simpleFS);
uniform_proj=uniform_init("proj",*simpleProgram);
uniform_pos=uniform_init("obj_pos",*simpleProgram);
uniform_col=uniform_init("color",*simpleProgram);
uniform_scale=uniform_init("scale",*simpleProgram);
print_log(simpleProgram->getProgram());
initNetworkEntity();
init_MovingCubes();
sniffer_start();
return 1;
}
double darts(long n)
{
long k = 0;
int i = 0;
double x = 0, y = 0;
uniform_init();
for(i = 0;i < n;i++)
{
x = uniform_double(0, 1);
/*y = uniform_double(0, 1);*/
y = x;
/*printf("%f %f\n", x, y);*/
if(x*x + y*y <= 1)
k++;
}
uniform_close();
/*printf("%ld\n", k);*/
return 4.0*k/n;
}
void RunKMedoids(const leveldb::Slice& begin,
const leveldb::Slice& end,
int K, leveldb::DB* db,
leveldb::DB* work_db, int concurrency,
std::ostream& ivar_out, std::ostream& cent_out) {
auto very_start = std::chrono::system_clock::now();
auto key_centroids = uniform_init(begin, end, K);
std::vector<GDELTMini> val_centroids(K);
{
auto it = iter(db);
for (int i = 0; i < K; ++i) {
it->Seek(key_centroids[i]);
CHECK(it->Valid());
read(it->value(), val_centroids[i]);
}
}
std::cout << "Divying up range among threads... " << std::flush;
auto parvec = get_par_ranges(uniform_init(begin, end, concurrency), db, end);
std::cout << "DONE" << std::endl;
int i = 0;
bool centers_changed = true;
vuad totals(K);
vuai cluster_sizes(K);
for (int i = 0; i < K; ++i) {
cluster_sizes[i].reset(new std::atomic<int>);
totals[i].reset(new std::atomic<double>);
}
while (centers_changed) {
auto start = std::chrono::system_clock::now();
assign_closest(parvec, totals, K, work_db, val_centroids, concurrency,
cluster_sizes);
auto tot = std::accumulate(totals.begin(), totals.end(), 0.0,
[](double sum, typename vuad::value_type& d) {
return sum + d->load();
});
auto end = std::chrono::system_clock::now();
std::cout << "Iteration " << ++i << " total intravariance " << tot;
std::cout << "\n Assigning medoids took " << secs(start, end)
<< "s" << std::endl;
start = std::chrono::system_clock::now();
for (auto& d : totals) {
ivar_out << d->load() << " ";
}
ivar_out << std::endl;
cent_out << key_centroids << std::endl;
end = std::chrono::system_clock::now();
std::cout << " Saving medoids took " << secs(start, end)
<< " s" << std::endl;
start = std::chrono::system_clock::now();
centers_changed = update_medoids(concurrency, K, db, work_db,
val_centroids, key_centroids,
totals, cluster_sizes);
end = std::chrono::system_clock::now();
std::cout << " Medoid update took " << secs(start, end)
<< " s" << std::endl;
start = end;
}
auto very_end = std::chrono::system_clock::now();
std::cout << "K-medoid clustering COMPLETE in "
<< secs(very_start, very_end) << " s" << std::endl;
}
