inline void lru_cache_cab::insert(const bucket* pbuck, const double & time)
{
assert(cache.size() + flow_table.size() <=_capacity);
buffer_check.insert(std::make_pair(pbuck, time)); // insert bucket as rec
cache.insert(container_T::value_type(pbuck, time)); // insert bucket
for (auto iter = pbuck->related_rules.begin(); iter != pbuck->related_rules.end(); iter++)
{
// rule_down_count += 1; // controller does not know which rules are kept in OFswtich
auto ins_rule_result = flow_table.insert(std::make_pair(*iter, 1));
if (!ins_rule_result.second)
++ins_rule_result.first->second;
else
++rule_down_count; // controller knows which rules are kept in OFswitch
}
while(cache.size() + flow_table.size() > _capacity) // kick out
{
const bucket * to_kick_buck = cache.right.begin()->second;
cache.right.erase(cache.right.begin());
buffer_check.erase(to_kick_buck);
for (auto iter = to_kick_buck->related_rules.begin(); iter != to_kick_buck->related_rules.end(); ++iter) // dec flow occupy no.
{
--flow_table[*iter];
if (flow_table[*iter] == 0)
flow_table.erase(*iter);
}
}
}
static double
score2(const boost::unordered_map<int, double> &m0,
const boost::unordered_map<int, double> &m1)
{
int tmp = 0;
auto i0 = m0.begin();
auto i1 = m1.begin();
while (i0 != m0.end() && i1 != m1.end()) {
if (i0->first < i1->first) ++i0;
else if (i0->first > i1->first) ++i1;
else ++tmp, ++i0, ++i1;
}
return m0.size() + m1.size() - tmp;
}
void IfcTreeWidget::slotObjectsSelected( boost::unordered_map<int, shared_ptr<IfcPPEntity> >& map )
{
if( m_block_selection_signals )
{
return;
}
if( map.size() < 1 )
{
return;
}
// take the first object from map and highlight it
shared_ptr<IfcPPEntity> object = (*(map.begin())).second;
int selected_id = object->m_id;
for( int i=0; i<topLevelItemCount(); ++i )
{
QTreeWidgetItem* toplevel_item = topLevelItem( i );
QTreeWidgetItem* selected_item = ViewerUtil::findItemByIfcId( toplevel_item, selected_id );
if( selected_item != 0 )
{
blockSignals(true);
m_block_selection_signals = true;
setCurrentItem( selected_item, 1, QItemSelectionModel::SelectCurrent );
blockSignals(false);
m_block_selection_signals = false;
break;
}
}
}
std::string srv_scrape(const Ctracker_input& ti, t_user* user)
{
if (m_use_sql && m_config.m_log_scrape)
m_scrape_log_buffer += Csql_query(m_database, "(?,?,?),")(ntohl(ti.m_ipa))(user ? user->uid : 0)(srv_time()).read();
if (!m_config.m_anonymous_scrape && !user)
return "d14:failure reason25:unregistered torrent passe";
std::string d;
d += "d5:filesd";
if (ti.m_info_hashes.empty())
{
m_stats.scraped_full++;
d.reserve(90 * m_torrents.size());
for (auto& i : m_torrents)
{
if (i.second.leechers || i.second.seeders)
d += (boost::format("20:%sd8:completei%de10:downloadedi%de10:incompletei%dee") % boost::make_iterator_range(i.first) % i.second.seeders % i.second.completed % i.second.leechers).str();
}
}
else
{
m_stats.scraped_http++;
if (ti.m_info_hashes.size() > 1)
m_stats.scraped_multi++;
for (auto& j : ti.m_info_hashes)
{
if (const t_torrent* i = find_torrent(j))
d += (boost::format("20:%sd8:completei%de10:downloadedi%de10:incompletei%dee") % j % i->seeders % i->completed % i->leechers).str();
}
}
d += "e";
if (m_config.m_scrape_interval)
d += (boost::format("5:flagsd20:min_request_intervali%dee") % m_config.m_scrape_interval).str();
d += "e";
return d;
}
void PropertyExpressionEngine::buildGraph(const ExpressionMap & exprs,
boost::unordered_map<int, ObjectIdentifier> & revNodes, DiGraph & g) const
{
boost::unordered_map<ObjectIdentifier, int> nodes;
std::vector<Edge> edges;
// Build data structure for graph
for (ExpressionMap::const_iterator it = exprs.begin(); it != exprs.end(); ++it)
buildGraphStructures(it->first, it->second.expression, nodes, revNodes, edges);
// Create graph
g = DiGraph(revNodes.size());
// Add edges to graph
for (std::vector<Edge>::const_iterator i = edges.begin(); i != edges.end(); ++i)
add_edge(i->first, i->second, g);
// Check for cycles
bool has_cycle = false;
int src = -1;
cycle_detector vis(has_cycle, src);
depth_first_search(g, visitor(vis));
if (has_cycle) {
std::string s = revNodes[src].toString() + " reference creates a cyclic dependency.";
throw Base::Exception(s.c_str());
}
}
static double
recall(const boost::unordered_map<int, double> &real,
const boost::unordered_map<int, double> &fake,
double thres = 0.0)
{
return 1.0 * hit(real, fake, thres).first / real.size();
}
std::string RippleAddress::humanAccountID () const
{
switch (nVersion)
{
case VER_NONE:
throw std::runtime_error ("unset source - humanAccountID");
case VER_ACCOUNT_ID:
{
boost::mutex::scoped_lock sl (rncLock);
boost::unordered_map< Blob , std::string >::iterator it = rncMap.find (vchData);
if (it != rncMap.end ())
return it->second;
if (rncMap.size () > 10000)
rncMap.clear ();
return rncMap[vchData] = ToString ();
}
case VER_ACCOUNT_PUBLIC:
{
RippleAddress accountID;
(void) accountID.setAccountID (getAccountID ());
return accountID.ToString ();
}
default:
throw std::runtime_error (str (boost::format ("bad source: %d") % int (nVersion)));
}
}
static double
precision(const boost::unordered_map<int, double> &real,
const boost::unordered_map<int, double> &fake,
double thres = 0.0)
{
if (real.size() == 0) return 0.0;
std::pair<int, int> count = hit(real, fake, thres);
return 0 == count.second ? 0.0 : 1.0 * count.first / count.second;
}
inline void operator<< (object::with_zone& o, const boost::unordered_map<K,V>& v)
{
o.type = type::MAP;
if(v.empty()) {
o.via.map.ptr = NULL;
o.via.map.size = 0;
} else {
object_kv* p = (object_kv*)o.zone->malloc(sizeof(object_kv)*v.size());
object_kv* const pend = p + v.size();
o.via.map.ptr = p;
o.via.map.size = v.size();
typename boost::unordered_map<K,V>::const_iterator it(v.begin());
do {
p->key = object(it->first, o.zone);
p->val = object(it->second, o.zone);
++p;
++it;
} while(p < pend);
}
}
static void serialize(storage_type& s, const boost::unordered_map<T1, T2>& o)
{
uint32_t sz = o.size();
s.serialize(sz);
for (typename boost::unordered_map<T1,T2>::const_iterator it = o.begin(), it_end = o.end(); it != it_end; ++it)
{
s.serialize(it->first);
s.serialize(it->second);
}
}
void PropertyExpressionEngine::buildGraphStructures(const ObjectIdentifier & path,
const boost::shared_ptr<Expression> expression,
boost::unordered_map<ObjectIdentifier, int> & nodes,
boost::unordered_map<int, ObjectIdentifier> & revNodes,
std::vector<Edge> & edges) const
{
std::set<ObjectIdentifier> deps;
/* Insert target property into nodes structure */
if (nodes.find(path) == nodes.end()) {
int s = nodes.size();
revNodes[s] = path;
nodes[path] = s;
}
else
revNodes[nodes[path]] = path;
/* Get the dependencies for this expression */
expression->getDeps(deps);
/* Insert dependencies into nodes structure */
std::set<ObjectIdentifier>::const_iterator di = deps.begin();
while (di != deps.end()) {
Property * prop = di->getProperty();
if (prop) {
ObjectIdentifier cPath(di->canonicalPath());
if (nodes.find(cPath) == nodes.end()) {
int s = nodes.size();
nodes[cPath] = s;
}
edges.push_back(std::make_pair(nodes[path], nodes[cPath]));
}
++di;
}
}
void hopscotch_map_sanity_checks() {
ASSERT_TRUE(cm2.begin() == cm2.end());
for (size_t i = 0;i < NINS; ++i) {
cm2[17 * i] = i;
um2[17 * i] = i;
}
for (size_t i = 0;i < NINS; ++i) {
assert(cm2[17 * i] == i);
assert(um2[17 * i] == i);
}
assert(cm2.size() == NINS);
assert(um2.size() == NINS);
for (size_t i = 0;i < NINS; i+=2) {
cm2.erase(17*i);
um2.erase(17*i);
}
for (size_t i = 0;i < NINS; i+=2) {
assert(cm2.count(17*i) == i % 2);
assert(um2.count(17*i) == i % 2);
if (cm2.count(17*i)) {
assert(cm2.find(17*i)->second == i);
}
}
assert(cm2.size() == NINS / 2);
assert(um2.size() == NINS / 2);
typedef graphlab::hopscotch_map<uint32_t, uint32_t>::value_type vpair;
{
size_t cnt = 0;
foreach(vpair &v, cm2) {
ASSERT_EQ(v.second, um2[v.first]);
++cnt;
}
ASSERT_EQ(cnt, NINS / 2);
}
void save(Archive & ar, const boost::unordered_map<T,U> & t, unsigned int version)
{
// write the size
// TODO: should we handle bucket size as well?
typedef typename boost::unordered_map<T, U>::size_type size_type;
typedef typename boost::unordered_map<T,U>::const_iterator const_iterator;
size_type size = t.size();
ar & BOOST_SERIALIZATION_NVP(size);
unsigned int count = 0;
for (const_iterator it = t.begin(); it != t.end(); it++) {
ar & boost::serialization::make_nvp("pair" + count, *it);
count++;
}
}
/// Only used by Cpp Vertex Shader
void stream_assembler::update_register_map( boost::unordered_map<semantic_value, size_t> const& reg_map )
{
register_to_input_element_desc.clear();
register_to_input_element_desc.reserve( reg_map.size() );
typedef pair<semantic_value, size_t> pair_t;
for(auto const& sv_reg_pair: reg_map)
{
input_element_desc const* elem_desc = layout_->find_desc(sv_reg_pair.first);
if(elem_desc == nullptr)
{
register_to_input_element_desc.clear();
return;
}
register_to_input_element_desc.push_back(
make_pair(sv_reg_pair.second, elem_desc)
);
}
}
std::string RippleAddress::humanAccountID () const
{
switch (nVersion)
{
case VER_NONE:
throw std::runtime_error ("unset source - humanAccountID");
case VER_ACCOUNT_ID:
{
StaticScopedLockType sl (s_lock, __FILE__, __LINE__);
boost::unordered_map< Blob , std::string >::iterator it = rncMap.find (vchData);
if (it != rncMap.end ())
return it->second;
// VFALCO NOTE Why do we throw everything out? We could keep two maps
// here, switch back and forth keep one of them full and clear the
// other on a swap - but always check both maps for cache hits.
//
if (rncMap.size () > 250000)
rncMap.clear ();
return rncMap[vchData] = ToString ();
}
case VER_ACCOUNT_PUBLIC:
{
RippleAddress accountID;
(void) accountID.setAccountID (getAccountID ());
return accountID.ToString ();
}
default:
throw std::runtime_error (str (boost::format ("bad source: %d") % int (nVersion)));
}
}
int DeviceCassandraController::updateDevice(
const string &devicename, const string &username,
boost::unordered_map<string, string> ¶ms) {
if (params.size() <= 0)
return 0;
string errorCode = "";
int result;
// Get the current device.
boost::shared_ptr<Device> device = getDevice(devicename, username, errorCode);
if (!errorCode.empty()) {
return boost::lexical_cast<int>(errorCode);
}
// Check if devicename needs to be changed.
if (params.count("new_devicename")) {
// Delete the current device from db.
result = deleteDevice(devicename, username);
if (result != 0) {
return result;
}
}
// Update data in the current device.
if (params.count("new_devicename")) {
device->setDevicename(params["new_devicename"]);
}
if (params.count("type")) {
device->setType(params["type"]);
}
if (params.count("metadata")) {
device->setContentMeta(params["metadata"]);
device->setContentTimestamp(time(NULL));
}
if (params.count("dir_ip")) {
device->setDirIp(params["dir_ip"]);
}
if (params.count("dir_port")) {
unsigned short portValue = -1;
if (!ControllerHelper::isNullOREmptyString(params["dir_port"]))
portValue = boost::lexical_cast<unsigned short>(params["dir_port"]);
device->setDirPort(portValue);
}
if (params.count("ip")) {
device->setIp(params["ip"]);
}
if (params.count("port")) {
unsigned short portValue = -1;
if (!ControllerHelper::isNullOREmptyString(params["port"]))
portValue = boost::lexical_cast<unsigned short>(params["port"]);
device->setPort(portValue);
}
if (params.count("os")) {
device->setOs(params["os"]);
}
if (params.count("description")) {
device->setDescription(params["description"]);
}
if (params.count("public_folder")) {
device->setPublicFolder(params["public_folder"]);
}
if (params.count("private_folder")) {
device->setPrivateFolder(params["private_folder"]);
}
if (params.count("is_indexed")) {
bool is_indexed = false;
if (boost::iequals(params["is_indexed"], "true"))
is_indexed = true;
device->setSearchable(is_indexed);
}
// Update lastseen.
device->setLastSeen(time(NULL));
// Add the new device.
result = addDevice(device);
return result;
}
void Task::featuresOut(const int current_image_idx, const boost::unordered_map<boost::uuids::uuid, StereoFeature> &hash)
{
ExteroFeatures features_samples;
base::samples::Pointcloud features_points;
double const &baseline(cameracalib.extrinsic.tx);
cv::Mat cv_image1;
/** Uncertainty in the images (left and right) planes **/
Eigen::Matrix4d px_var;
px_var << this->pxleftVar, Eigen::Matrix2d::Zero(),
Eigen::Matrix2d::Zero(), this->pxrightVar;
#ifdef DEBUG_PRINTS
std::cout<<"[FEATURES_OUT] Current hash.size(): "<<hash.size()<<"\n";
#endif
/** Parse the hash table of features **/
for (boost::unordered_map<boost::uuids::uuid, StereoFeature>::const_iterator
it = hash.begin(); it != hash.end(); ++it)
{
//std::cout<<"[FEATURES_OUT] img_idx: "<<it->second.img_idx<<" current_idx: "<<current_image_idx<<"\n";
if (it->second.img_idx == current_image_idx)
{
Feature feature;
/** Get the uuid **/
feature.index = it->first;
/** Take the "Stereo" 2d point **/
cv::Point const &left_pt(it->second.keypoint_left.pt);
cv::Point const &right_pt(it->second.keypoint_right.pt);
feature.stereo_point = base::Vector3d(left_pt.x, right_pt.x, left_pt.y);
/** Compute the 3d point **/
double disparity = std::min(right_pt.x - left_pt.x, -1);
base::Vector4d image_point (left_pt.x, left_pt.y, disparity, 1);
base::Vector4d homogeneous_point = Q * image_point;
feature.point_3d = base::Vector3d (homogeneous_point(0)/homogeneous_point(3),
homogeneous_point(1)/homogeneous_point(3),
homogeneous_point(2)/homogeneous_point(3));
#ifdef DEBUG_PRINTS
std::cout<<"[FEATURES_OUT] Image point[left]: "<<left_pt.x<<" "<<left_pt.y<<"\n";
std::cout<<"[FEATURES_OUT] Image point[right]: "<<right_pt.x<<" "<<right_pt.y<<"\n";
std::cout<<"[FEATURES_OUT] 3D point:\n"<<feature.point_3d<<"\n";
#endif
if (_output_debug.value())
{
/** 3D point coordinates in base point cloud structure **/
features_points.points.push_back(base::Vector3d (
homogeneous_point(0)/homogeneous_point(3),
homogeneous_point(1)/homogeneous_point(3),
homogeneous_point(2)/homogeneous_point(3)));
/** Color **/
cv_image1 = frame_helper::FrameHelper::convertToCvMat(this->left_color_frame);
cv::Vec3b color = cv_image1.at<cv::Vec3b>(left_pt.y, left_pt.x);
base::Vector4d color4d;
color4d[0] = color[0]/255.0;//R
color4d[1] = color[1]/255.0;//G
color4d[2] = color[2]/255.0;//B
color4d[3] = 1.0;//Alpha
features_points.colors.push_back(color4d);
}
/** Compute the covariance **/
Eigen::Matrix<double, 3, 4> noise_jacobian; /** Jacobian Matrix for the triangulation noise model */
double disparity_power = pow(disparity,2);
noise_jacobian << -(baseline*right_pt.x)/disparity_power, 0.00, (baseline*left_pt.x)/disparity_power, 0.00,
-(baseline*left_pt.y)/disparity_power, baseline/disparity, (baseline*left_pt.y)/disparity_power, 0.00,
-(baseline*cameracalib.camLeft.fx)/disparity_power, 0.00, (baseline*cameracalib.camLeft.fx)/disparity_power, 0.00;
feature.cov_3d = noise_jacobian * px_var * noise_jacobian.transpose();
/** Store the feature in the vector **/
features_samples.features.push_back(feature);
}
}
#ifdef DEBUG_PRINTS
std::cout<<"[FEATURES_OUT] Sent "<<features_samples.features.size()<<" vector of uuids\n";
#endif
features_samples.time = this->frame_pair.time;
features_samples.img_idx = current_image_idx;
_features_samples_out.write(features_samples);
if (_output_debug.value())
{
features_points.time = this->frame_pair.time;
_features_point_samples_out.write(features_points);
}
return;
}
int main(int ac, char* av[])
{
//read and parse command line inputs (using boose::program_options)
po::options_description desc("Allowed options");
desc.add_options()
("help,h", "produce help message")
//scenario parameters
("lambda,l", po::value<double>(&lambda_mean)->default_value(10), "mean demand (E[lambda])")
("beta,b", po::value<double>(&beta0)->default_value(1), "beta")
("cost,c", po::value<double>(&cost)->default_value(1), "unit cost")
//file names input
("path,p", po::value<string>(&path), "path for temporary archive files")
("outfile,o", po::value<string>(&resultFile), "file to save result")
;
po::variables_map vm;
po::store(po::parse_command_line(ac, av, desc), vm);
po::notify(vm);
if (vm.count("help")) {
cout << "Usage: options_description [options]\n";
cout << desc;
return 0;
}
//initialize the file names by taking all parameters
modelName = "NVLearning_Full";
if (resultFile == "") resultFile = modelName + ".result.txt";
//Open output file
file.open(resultFile, fstream::app|fstream::out);
if (! file)
{
//if fail to open the file
cerr << "can't open output file NVLearning_Full_result.txt!" << endl;
exit(EXIT_FAILURE);
}
file << setprecision(10);
cout << setprecision(10);
//omp_set_num_threads(omp_get_num_procs());
//cout << "Num of Procs: " << omp_get_num_procs() << endl;
//cout << "Max Num of Threads: " << omp_get_max_threads() << endl;
cout << "Num of periods (N): " << N << endl;
cout << "r\tc\talpha\tbeta\tQ_F\tPi_F\tTime_F\tCPUTime_F\tComp_F" << endl;
//file << "Num of Procs: " << omp_get_num_procs() << endl;
//file << "Max Num of Threads: " << omp_get_max_threads() << endl;
//file << "Num of periods (N): " << N << endl;
file << "r\tc\talpha\tbeta\tQ_F\tPi_F\tTime_F\tCPUTime_F\tComp_F" << endl;
//initialize cost parameters
price = 2;
//lambda_mean = 10;
//cost = 1;
//beta0 = 1;
for (lambda_mean=10; lambda_mean<=50; lambda_mean+=10)
for (beta0=2; beta0>=0.05; beta0/=2)
{
alpha0 = beta0*lambda_mean;
for (cost=1.8; cost>=0.15; cost-=0.1)
{
v_map.clear();
cout << price << "\t" << cost << "\t" << alpha0 << "\t" << beta0 << "\t";
file << price << "\t" << cost << "\t" << alpha0 << "\t" << beta0 << "\t";
auto startTime = chrono::system_clock::now();
clock_t cpu_start = clock();
V_F(1, 0, 0);
clock_t cpu_end = clock();
auto endTime = chrono::system_clock::now();
cout << chrono::duration_cast<chrono::milliseconds> (endTime-startTime).count() << "\t" << 1000.0*(cpu_end-cpu_start)/CLOCKS_PER_SEC << "\t";
file << chrono::duration_cast<chrono::milliseconds> (endTime-startTime).count() << "\t" << 1000.0*(cpu_end-cpu_start)/CLOCKS_PER_SEC << "\t";
scenarioName = ".l" + dbl_to_str(lambda_mean) +".b" + dbl_to_str(beta0) + ".c" + dbl_to_str(cost);
archiveFile = path + modelName + scenarioName + ".oarchive.txt";
archiveVMap(v_map, archiveFile);
auto mapSize = v_map.size();
cout << mapSize+1 << endl;
file << mapSize+1 << endl;
}
}
file.close();
return 0;
}
