public IndexHashTable(int size, com.epl.geometry.IndexHashTable.HashFunction hashFunction)
{
//this is aimed to speedup the find
//operation and allows to have less buckets.
// Create hash table. size is the bin count in the table. The hashFunction
// is the function to use.
m_hashBuckets = new com.epl.geometry.AttributeStreamOfInt32(size, NullNode());
m_lists = new com.epl.geometry.IndexMultiList();
m_hash = hashFunction;
m_bit_filter = new int[(size * 10 + 31) >> 5];
}
internal bool ClusterNonReciprocal_()
{
int point_count = m_shape.GetTotalPointCount();
com.epl.geometry.Envelope2D env = m_shape.GetEnvelope2D();
m_origin = env.GetLowerLeft();
double dim = System.Math.Max(env.GetHeight(), env.GetWidth());
double mincell = dim / (com.epl.geometry.NumberUtils.IntMax() - 1);
if (m_cell_size < mincell)
{
m_cell_size = mincell;
m_inv_cell_size = 1.0 / m_cell_size;
}
// This holds clusters.
m_clusters = new com.epl.geometry.IndexMultiList();
m_clusters.ReserveLists(m_shape.GetTotalPointCount() / 3 + 1);
m_clusters.ReserveNodes(m_shape.GetTotalPointCount() / 3 + 1);
m_hash_values = m_shape.CreateUserIndex();
m_new_clusters = m_shape.CreateUserIndex();
// Make the hash table. It serves a purpose of fine grain grid.
// Make it 25% larger than the 4 times point count to reduce the chance
// of collision.
// The 4 times comes from the fact that we check four neighbouring cells
// in the grid for each point.
m_hash_function = new com.epl.geometry.Clusterer.ClusterHashFunction(this, m_shape, m_origin, m_sqr_tolerance, m_inv_cell_size, m_hash_values);
m_hash_table = new com.epl.geometry.IndexHashTable(4 * point_count / 3, m_hash_function);
m_hash_table.ReserveElements(m_shape.GetTotalPointCount());
bool b_clustered = false;
// Go through all vertices stored in the m_shape and put the handles of
// the vertices into the clusters and the hash table.
for (int geometry = m_shape.GetFirstGeometry(); geometry != -1; geometry = m_shape.GetNextGeometry(geometry))
{
for (int path = m_shape.GetFirstPath(geometry); path != -1; path = m_shape.GetNextPath(path))
{
int vertex = m_shape.GetFirstVertex(path);
for (int index = 0, nindex = m_shape.GetPathSize(path); index < nindex; index++)
{
System.Diagnostics.Debug.Assert((vertex != -1));
int hash = m_hash_function.Calculate_hash_from_vertex(vertex);
m_shape.SetUserIndex(vertex, m_hash_values, hash);
m_hash_table.AddElement(vertex, hash);
// add cluster to the
// hash table
System.Diagnostics.Debug.Assert((m_shape.GetUserIndex(vertex, m_new_clusters) == -1));
vertex = m_shape.GetNextVertex(vertex);
}
}
}
{
// m_hash_table->dbg_print_bucket_histogram_();
// scope for candidates array
com.epl.geometry.AttributeStreamOfInt32 candidates = new com.epl.geometry.AttributeStreamOfInt32(0);
candidates.Reserve(10);
for (int geometry_1 = m_shape.GetFirstGeometry(); geometry_1 != -1; geometry_1 = m_shape.GetNextGeometry(geometry_1))
{
for (int path = m_shape.GetFirstPath(geometry_1); path != -1; path = m_shape.GetNextPath(path))
{
int vertex = m_shape.GetFirstVertex(path);
for (int index = 0, nindex = m_shape.GetPathSize(path); index < nindex; index++)
{
if (m_shape.GetUserIndex(vertex, m_new_clusters) == com.epl.geometry.StridedIndexTypeCollection.ImpossibleIndex2())
{
vertex = m_shape.GetNextVertex(vertex);
continue;
}
// this vertex was merged with another
// cluster. It also was removed from the
// hash table.
int hash = m_shape.GetUserIndex(vertex, m_hash_values);
m_hash_table.DeleteElement(vertex, hash);
while (true)
{
CollectClusterCandidates_(vertex, candidates);
if (candidates.Size() == 0)
{
// no candidate for
// clustering has
// been found for
// the cluster_1.
break;
}
bool clustered = false;
for (int candidate_index = 0, ncandidates = candidates.Size(); candidate_index < ncandidates; candidate_index++)
{
int cluster_node = candidates.Get(candidate_index);
int other_vertex = m_hash_table.GetElement(cluster_node);
m_hash_table.DeleteNode(cluster_node);
clustered |= MergeClusters_(vertex, other_vertex, candidate_index + 1 == ncandidates);
}
b_clustered |= clustered;
candidates.Clear(false);
// repeat search for the cluster candidates for
// cluster_1
if (!clustered)
{
break;
}
}
// positions did not change
// m_shape->set_user_index(vertex, m_new_clusters,
// Strided_index_type_collection::impossible_index_2());
vertex = m_shape.GetNextVertex(vertex);
}
}
}
}
if (b_clustered)
{
ApplyClusterPositions_();
}
m_hash_table = null;
m_hash_function = null;
m_shape.RemoveUserIndex(m_hash_values);
m_shape.RemoveUserIndex(m_new_clusters);
// output_debug_printf("total: %d\n",m_shape->get_total_point_count());
// output_debug_printf("clustered: %d\n",m_dbg_candidate_check_count);
return(b_clustered);
}
