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package com.google.refine.clustering.knn;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Properties;
import java.util.Set;
import org.json.JSONException;
import org.json.JSONObject;
import org.json.JSONWriter;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.google.refine.browsing.Engine;
import com.google.refine.browsing.FilteredRows;
import com.google.refine.browsing.RowVisitor;
import com.google.refine.clustering.Clusterer;
import com.google.refine.model.Cell;
import com.google.refine.model.Project;
import com.google.refine.model.Row;
import edu.mit.simile.vicino.clustering.NGramClusterer;
import edu.mit.simile.vicino.clustering.VPTreeClusterer;
import edu.mit.simile.vicino.distances.BZip2Distance;
import edu.mit.simile.vicino.distances.Distance;
import edu.mit.simile.vicino.distances.GZipDistance;
import edu.mit.simile.vicino.distances.JaccardDistance;
import edu.mit.simile.vicino.distances.JaroDistance;
import edu.mit.simile.vicino.distances.JaroWinklerDistance;
import edu.mit.simile.vicino.distances.JaroWinklerTFIDFDistance;
import edu.mit.simile.vicino.distances.LevenshteinDistance;
import edu.mit.simile.vicino.distances.PPMDistance;
public class kNNClusterer extends Clusterer {
private Distance _distance;
static final protected Map<String, Distance> _distances = new HashMap<String, Distance>();
List<Set<Serializable>> _clusters;
Map<Serializable, Integer> _counts = new HashMap<Serializable, Integer>();
final static Logger logger = LoggerFactory.getLogger("kNN_clusterer");
static {
_distances.put("levenshtein", new LevenshteinDistance());
_distances.put("jaccard", new JaccardDistance());
_distances.put("jaro", new JaroDistance());
_distances.put("jaro-winkler", new JaroWinklerDistance());
_distances.put("jaro-winkler-tfidf", new JaroWinklerTFIDFDistance());
_distances.put("gzip", new GZipDistance());
_distances.put("bzip2", new BZip2Distance());
_distances.put("ppm", new PPMDistance());
}
class VPTreeClusteringRowVisitor implements RowVisitor {
Distance _distance;
JSONObject _config;
VPTreeClusterer _clusterer;
double _radius = 1.0f;
public VPTreeClusteringRowVisitor(Distance d, JSONObject o) {
_distance = d;
_config = o;
_clusterer = new VPTreeClusterer(_distance);
try {
JSONObject params = o.getJSONObject("params");
_radius = params.getDouble("radius");
} catch (JSONException e) {
//Refine.warn("No parameters found, using defaults");
}
}
@Override
public void start(Project project) {
// nothing to do
}
@Override
public void end(Project project) {
// nothing to do
}
@Override
public boolean visit(Project project, int rowIndex, Row row) {
Cell cell = row.getCell(_colindex);
if (cell != null && cell.value != null) {
Object v = cell.value;
String s = (v instanceof String) ? ((String) v) : v.toString();
_clusterer.populate(s);
count(s);
}
return false;
}
public List<Set<Serializable>> getClusters() {
return _clusterer.getClusters(_radius);
}
}
class BlockingClusteringRowVisitor implements RowVisitor {
Distance _distance;
JSONObject _config;
double _radius = 1.0d;
int _blockingNgramSize = 6;
HashSet<String> _data;
NGramClusterer _clusterer;
public BlockingClusteringRowVisitor(Distance d, JSONObject o) {
_distance = d;
_config = o;
_data = new HashSet<String>();
try {
JSONObject params = o.getJSONObject("params");
_radius = params.getDouble("radius");
logger.debug("Use radius: {}", _radius);
_blockingNgramSize = params.getInt("blocking-ngram-size");
logger.debug("Use blocking ngram size: {}",_blockingNgramSize);
} catch (JSONException e) {
logger.debug("No parameters found, using defaults");
}
_clusterer = new NGramClusterer(_distance, _blockingNgramSize);
}
@Override
public void start(Project project) {
// nothing to do
}
@Override
public void end(Project project) {
// nothing to do
}
@Override
public boolean visit(Project project, int rowIndex, Row row) {
Cell cell = row.getCell(_colindex);
if (cell != null && cell.value != null) {
Object v = cell.value;
String s = (v instanceof String) ? ((String) v) : v.toString().intern();
_clusterer.populate(s);
count(s);
}
return false;
}
public List<Set<Serializable>> getClusters() {
return _clusterer.getClusters(_radius);
}
}
@Override
public void initializeFromJSON(Project project, JSONObject o) throws Exception {
super.initializeFromJSON(project, o);
_distance = _distances.get(o.getString("function").toLowerCase());
}
@Override
public void computeClusters(Engine engine) {
//VPTreeClusteringRowVisitor visitor = new VPTreeClusteringRowVisitor(_distance,_config);
BlockingClusteringRowVisitor visitor = new BlockingClusteringRowVisitor(_distance,_config);
FilteredRows filteredRows = engine.getAllFilteredRows();
filteredRows.accept(_project, visitor);
_clusters = visitor.getClusters();
}
public static class ValuesComparator implements Comparator<Entry<Serializable,Integer>>, Serializable {
private static final long serialVersionUID = 204469656070583155L;
@Override
public int compare(Entry<Serializable,Integer> o1, Entry<Serializable,Integer> o2) {
return o2.getValue() - o1.getValue();
}
}
@Override
public void write(JSONWriter writer, Properties options) throws JSONException {
writer.array();
for (Set<Serializable> m : _clusters) {
if (m.size() > 1) {
Map<Serializable,Integer> internal_counts = new HashMap<Serializable,Integer>();
for (Serializable s : m) {
internal_counts.put(s,_counts.get(s));
}
List<Entry<Serializable,Integer>> values = new ArrayList<Entry<Serializable,Integer>>(internal_counts.entrySet());
Collections.sort(values, new ValuesComparator());
writer.array();
for (Entry<Serializable,Integer> e : values) {
writer.object();
writer.key("v"); writer.value(e.getKey());
writer.key("c"); writer.value(e.getValue());
writer.endObject();
}
writer.endArray();
}
}
writer.endArray();
}
private void count(Serializable s) {
if (_counts.containsKey(s)) {
_counts.put(s, _counts.get(s) + 1);
} else {
_counts.put(s, 1);
}
}
}