本文整理汇总了C++中graph_access::set_partition_count方法的典型用法代码示例。如果您正苦于以下问题：C++ graph_access::set_partition_count方法的具体用法？C++ graph_access::set_partition_count怎么用？C++ graph_access::set_partition_count使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类graph_access的用法示例。
在下文中一共展示了graph_access::set_partition_count方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: initial_partition
void greedy_mis::initial_partition(const unsigned int seed, graph_access & G) {
random_functions::setSeed(seed);
NodePermutationMap permutation;
generate_permutation(G, permutation);
bucket_array *buckets = new bucket_array(G.number_of_nodes());
G.set_partition_count(2);
// Initialize the priority queue
forall_nodes (G, n) {
NodeID node = permutation[n];
EdgeWeight node_degree = G.getNodeDegree(node);
buckets->increment(node, node_degree);
G.setPartitionIndex(node, 0);
} endfor示例2: initial_partition
void bipartition::initial_partition( const PartitionConfig & config,
const unsigned int seed,
graph_access & G,
int* partition_map) {
timer t;
t.restart();
unsigned iterations = config.bipartition_tries;
EdgeWeight best_cut = std::numeric_limits<EdgeWeight>::max();
int best_load = std::numeric_limits<int>::max();
for( unsigned i = 0; i < iterations; i++) {
if(config.bipartition_algorithm == BIPARTITION_BFS) {
grow_regions_bfs(config, G);
} else if( config.bipartition_algorithm == BIPARTITION_FM) {
grow_regions_fm(config, G);
}
G.set_partition_count(2);
post_fm(config, G);
quality_metrics qm;
EdgeWeight curcut = qm.edge_cut(G);
int lhs_block_weight = 0;
int rhs_block_weight = 0;
forall_nodes(G, node) {
if(G.getPartitionIndex(node) == 0) {
lhs_block_weight += G.getNodeWeight(node);
} else {
rhs_block_weight += G.getNodeWeight(node);
}
} endfor
int lhs_overload = std::max(lhs_block_weight - config.target_weights[0],0);
int rhs_overload = std::max(rhs_block_weight - config.target_weights[1],0);
if(curcut < best_cut || (curcut == best_cut && lhs_overload + rhs_block_weight < best_load) ) {
//store it
best_cut = curcut;
best_load = lhs_overload + rhs_overload;
forall_nodes(G, n) {
partition_map[n] = G.getPartitionIndex(n);
} endfor
} 示例3: perform_recursive_partitioning_internal
void graph_partitioner::perform_recursive_partitioning_internal(PartitionConfig & config,
graph_access & G,
PartitionID lb,
PartitionID ub) {
G.set_partition_count(2);
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// configuration of bipartitioning
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
PartitionConfig bipart_config = config;
bipart_config.k = 2;
bipart_config.stop_rule = STOP_RULE_MULTIPLE_K;
bipart_config.num_vert_stop_factor = 100;
double epsilon = 0;
bipart_config.rebalance = false;
bipart_config.softrebalance = true;
if(config.k < 64) {
epsilon = m_rnd_bal/100.0;
bipart_config.rebalance = false;
bipart_config.softrebalance = false;
} else {
epsilon = 1/100.0;
}
if(m_global_k == 2) {
epsilon = 3.0/100.0;
}
bipart_config.upper_bound_partition = ceil((1+epsilon)*config.largest_graph_weight/(double)bipart_config.k);
bipart_config.corner_refinement_enabled = false;
bipart_config.quotient_graph_refinement_disabled = false;
bipart_config.refinement_scheduling_algorithm = REFINEMENT_SCHEDULING_ACTIVE_BLOCKS;
bipart_config.kway_adaptive_limits_beta = log(G.number_of_nodes());
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// end configuration
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
NodeID new_ub_lhs = floor((lb+ub)/2);
NodeID new_lb_rhs = floor((lb+ub)/2+1);
NodeID num_blocks_lhs = new_ub_lhs - lb + 1;
NodeID num_blocks_rhs = ub - new_lb_rhs + 1;
if(config.k % 2 != 0) {
//otherwise the block weights have to be
bipart_config.target_weights.clear();
bipart_config.target_weights.push_back((1+epsilon)*num_blocks_lhs/(double)(num_blocks_lhs+num_blocks_rhs)*config.largest_graph_weight);
bipart_config.target_weights.push_back((1+epsilon)*num_blocks_rhs/(double)(num_blocks_lhs+num_blocks_rhs)*config.largest_graph_weight);
bipart_config.initial_bipartitioning = true;
bipart_config.refinement_type = REFINEMENT_TYPE_FM; // flows not supported for odd block weights
} else {
bipart_config.target_weights.clear();
bipart_config.target_weights.push_back(bipart_config.upper_bound_partition);
bipart_config.target_weights.push_back(bipart_config.upper_bound_partition);
bipart_config.initial_bipartitioning = false;
}
bipart_config.grow_target = ceil(num_blocks_lhs/(double)(num_blocks_lhs+num_blocks_rhs)*config.largest_graph_weight);
perform_partitioning(bipart_config, G);
if( config.k > 2 ) {
graph_extractor extractor;
graph_access extracted_block_lhs;
graph_access extracted_block_rhs;
std::vector<NodeID> mapping_extracted_to_G_lhs; // map the new nodes to the nodes in the old graph G
std::vector<NodeID> mapping_extracted_to_G_rhs; // map the new nodes to the nodes in the old graph G
NodeWeight weight_lhs_block = 0;
NodeWeight weight_rhs_block = 0;
extractor.extract_two_blocks(G, extracted_block_lhs,
extracted_block_rhs,
mapping_extracted_to_G_lhs,
mapping_extracted_to_G_rhs,
weight_lhs_block, weight_rhs_block);
PartitionConfig rec_config = config;
if(num_blocks_lhs > 1) {
rec_config.k = num_blocks_lhs;
rec_config.largest_graph_weight = weight_lhs_block;
perform_recursive_partitioning_internal( rec_config, extracted_block_lhs, lb, new_ub_lhs);
//apply partition
forall_nodes(extracted_block_lhs, node) {
G.setPartitionIndex(mapping_extracted_to_G_lhs[node], extracted_block_lhs.getPartitionIndex(node));
} endfor