pylucene 3.5.0-3

[pylucene.git] / lucene-java-3.5.0 / lucene / contrib / facet / src / java / org / apache / lucene / facet / search / sampling / RandomSampler.java

diff --git a/lucene-java-3.5.0/lucene/contrib/facet/src/java/org/apache/lucene/facet/search/sampling/RandomSampler.java b/lucene-java-3.5.0/lucene/contrib/facet/src/java/org/apache/lucene/facet/search/sampling/RandomSampler.java
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+package org.apache.lucene.facet.search.sampling;
+
+import java.io.IOException;
+import java.util.Random;
+
+import org.apache.lucene.facet.search.ScoredDocIDs;
+import org.apache.lucene.facet.search.ScoredDocIDsIterator;
+import org.apache.lucene.facet.util.ScoredDocIdsUtils;
+
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/**
+ * Simple random sampler
+ */
+public class RandomSampler extends Sampler {
+  
+  private final Random random;
+
+  public RandomSampler() {
+    super();
+    this.random = new Random();
+  }
+
+  public RandomSampler(SamplingParams params, Random random) throws IllegalArgumentException {
+    super(params);
+    this.random = random;
+  }
+
+  @Override
+  protected SampleResult createSample(ScoredDocIDs docids, int actualSize, int sampleSetSize) throws IOException {
+    final int[] sample = new int[sampleSetSize];
+    final int maxStep = (actualSize * 2 ) / sampleSetSize; //floor
+    int remaining = actualSize;
+    ScoredDocIDsIterator it = docids.iterator();
+    int i = 0;
+    // select sample docs with random skipStep, make sure to leave sufficient #docs for selection after last skip
+    while (i<sample.length && remaining>(sampleSetSize-maxStep-i)) {
+      int skipStep = 1 + random.nextInt(maxStep);
+      // Skip over 'skipStep' documents
+      for (int j=0; j<skipStep; j++) {
+        it.next();
+        -- remaining;
+      }
+      sample[i++] = it.getDocID();
+    }
+    // Add leftover documents to the sample set
+    while (i<sample.length) {
+      it.next();
+      sample[i++] = it.getDocID();
+    }
+    ScoredDocIDs sampleRes = ScoredDocIdsUtils.createScoredDocIDsSubset(docids, sample);
+    SampleResult res = new SampleResult(sampleRes, sampleSetSize/(double)actualSize);
+    return res;
+  }
+  
+}