inline void
CertificateCacheTtl::removeAll()
{
  for(Cache::iterator it = m_cache.begin(); it != m_cache.end(); it++)
    m_scheduler.cancelEvent(it->second.second);

  m_cache.clear();
}
Example #2
0
static void ClearCacheTimer(uv_timer_t *req)
{
    uint64_t now = time(0);
    Cache::iterator itc = _cache.begin();
    while (itc != _cache.end()) {
        if (itc->second.expire  > 0 && itc->second.expire < now) itc->second.clear(0);
        itc++;
    }
}
Example #3
0
/*-------------------------------------------------------------------------*/
void NOMAD::Cache::insert ( Cache & c )
{
    if ( &c == this )
        return;
    
    // check the eval types:
    if ( c._eval_type != _eval_type )
        throw NOMAD::Cache::Cache_Error ( "Cache.cpp" , __LINE__ ,
                                         "NOMAD::Cache:insert(c): c._eval_type != this->_eval_type" );
    
    // insertion:
    NOMAD::Point              bbo_cache , bbo_cur;
    const NOMAD::Eval_Point * cache_x;
    const NOMAD::Eval_Point * cur = c.begin();
    
    while ( cur ) {
        
        cache_x = find ( *cur );
        
        // the current point is already in cache:
        if ( cache_x ) {
            update ( get_modifiable_point ( *cache_x ) , *cur );
            delete cur;
        }
        
        // point not in cache:
        else
            insert ( *cur );
        
        cur = c.next();
    }
    
    c._sizeof = static_cast<float> ( sizeof_init() );
    
    c._cache1.clear();
    c._cache2.clear();
    c._cache3.clear();
    c._extern_pts.clear();
}
Example #4
0
File: main.cpp Project: radi9/svm
vector<double> get_Q(int i)
{
	for(vector<double> rows : tempQ)
	{
		if(rows[0] == i)
		{
			rows.erase(rows.begin());
			return rows;
		}
	}


	vector<double> column;
	column.push_back(i);//id
	if(tempQ.size() < 1000)
	{
		for(int j = 0; j < train_num; j++)
		{
			double temp;
			temp = kernel(trainData[j], trainData[i]);
			column.push_back(temp);
		}
		tempQ.push_back(column);
	}
	else
	{
		tempQ.erase(tempQ.begin());
		for(int j = 0; j < train_num; j++)
		{
			double temp;
			temp = kernel(trainData[j], trainData[i]);
			column.push_back(temp);
		}
		tempQ.push_back(column);
	}

	column.erase(column.begin());
	return column;
}