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Algorithms that build k-nearest neighbors graph (k-nn graph): Brute-force, NN-Descent,...
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/*
* The MIT License
*
* Copyright 2015 Thibault Debatty.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
package info.debatty.java.graphs.build;
import info.debatty.java.spamsum.ESSum;
import java.util.ArrayList;
import java.util.List;
/**
* Builds the k-nn graph by partitioning the graph using Context Triggered
* Piecewize Hashing. This graph builder is meant for string node values.
*
* @author Thibault Debatty
* @param type of nodes
*/
public class NNCTPH extends PartitioningGraphBuilder {
@Override
protected final List[] partition(
final List nodes) {
ESSum ess = new ESSum(getOversampling(), getNPartitions(), 1);
ArrayList[] buckets = new ArrayList[getNPartitions()];
for (T node : nodes) {
int[] hash = ess.HashString(node.toString());
for (int stage = 0; stage < getOversampling(); stage++) {
int partition = hash[stage];
if (buckets[partition] == null) {
buckets[partition] = new ArrayList();
}
// !! this is not efficient !!!!
if (!buckets[partition].contains(node)) {
buckets[partition].add(node);
}
}
}
return buckets;
}
}