public void inform(SolrCore core) {
if (initParams != null) {
log.info("Initializing Clustering Engines");
boolean searchHasDefault = false;
boolean documentHasDefault = false;
for (int i = 0; i < initParams.size(); i++) {
if (initParams.getName(i).equals("engine")) {
NamedList engineNL = (NamedList) initParams.getVal(i);
String className = (String) engineNL.get("classname");
if (className == null) {
className = CarrotClusteringEngine.class.getName();
}
SolrResourceLoader loader = core.getResourceLoader();
ClusteringEngine clusterer = (ClusteringEngine) loader.newInstance(className);
if (clusterer != null) {
String name = clusterer.init(engineNL, core);
if (name != null) {
boolean isDefault = name.equals(ClusteringEngine.DEFAULT_ENGINE_NAME);
if (clusterer instanceof SearchClusteringEngine) {
if (isDefault == true && searchHasDefault == false) {
searchHasDefault = true;
} else if (isDefault == true && searchHasDefault == true) {
throw new RuntimeException("More than one engine is missing name: " + engineNL);
}
searchClusteringEngines.put(name, (SearchClusteringEngine) clusterer);
} else if (clusterer instanceof DocumentClusteringEngine) {
if (isDefault == true && documentHasDefault == false) {
searchHasDefault = true;
} else if (isDefault == true && documentHasDefault == true) {
throw new RuntimeException("More than one engine is missing name: " + engineNL);
}
documentClusteringEngines.put(name, (DocumentClusteringEngine) clusterer);
}
} else {
if (clusterer instanceof SearchClusteringEngine && searchHasDefault == false) {
searchClusteringEngines.put(
ClusteringEngine.DEFAULT_ENGINE_NAME, (SearchClusteringEngine) clusterer);
searchHasDefault = true;
} else if (clusterer instanceof DocumentClusteringEngine
&& documentHasDefault == false) {
documentClusteringEngines.put(
ClusteringEngine.DEFAULT_ENGINE_NAME, (DocumentClusteringEngine) clusterer);
documentHasDefault = true;
} else {
throw new RuntimeException("More than one engine is missing name: " + engineNL);
}
}
}
}
}
log.info("Finished Initializing Clustering Engines");
}
}
@SuppressWarnings("unchecked")
@Override
public void inform(SolrCore core) {
if (initParams != null) {
log.info("Initializing Clustering Engines");
// Our target list of engines, split into search-results and document clustering.
SolrResourceLoader loader = core.getResourceLoader();
for (Map.Entry<String, Object> entry : initParams) {
if ("engine".equals(entry.getKey())) {
NamedList<Object> engineInitParams = (NamedList<Object>) entry.getValue();
String engineClassName =
StringUtils.defaultIfBlank(
(String) engineInitParams.get("classname"),
CarrotClusteringEngine.class.getName());
// Instantiate the clustering engine and split to appropriate map.
final ClusteringEngine engine =
loader.newInstance(engineClassName, ClusteringEngine.class);
final String name = StringUtils.defaultIfBlank(engine.init(engineInitParams, core), "");
final ClusteringEngine previousEntry;
if (engine instanceof SearchClusteringEngine) {
previousEntry = searchClusteringEngines.put(name, (SearchClusteringEngine) engine);
} else if (engine instanceof DocumentClusteringEngine) {
previousEntry = documentClusteringEngines.put(name, (DocumentClusteringEngine) engine);
} else {
log.warn("Unknown type of a clustering engine for class: " + engineClassName);
continue;
}
if (previousEntry != null) {
log.warn("Duplicate clustering engine component named '" + name + "'.");
}
}
}
// Set up the default engine key for both types of engines.
setupDefaultEngine("search results clustering", searchClusteringEngines);
setupDefaultEngine("document clustering", documentClusteringEngines);
log.info("Finished Initializing Clustering Engines");
}
}
public static void main(String[] args) throws Exception {
ClusteringEngine<double[]> c = new ClusteringEngine<double[]>();
c.add(new double[] {100, 0, 0});
c.add(new double[] {101, 0, 0});
c.add(new double[] {102, 0, 0});
c.add(new double[] {105, 0, 0});
c.add(new double[] {0, 301, 0});
c.add(new double[] {0, 309, 0});
c.add(new double[] {0, 304, 0});
c.add(new double[] {0, 305, 0});
c.add(new double[] {0, 307, 0});
c.add(new double[] {0, 0, 290});
c.add(new double[] {0, 0, 291});
c.add(new double[] {0, 0, 293});
c.add(new double[] {0, 0, 298});
c.predictWithKmeans(3, 5, ClusterDouble.class);
System.out.println("=================");
for (int k = 0; k < c.size(); k++) {
System.out.println(c.getPoint(k) + " -> " + c.getLabel(k));
}
}
