Java tutorial
/** * 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. */ package net.myrrix.common.collection; import java.util.NoSuchElementException; import com.google.common.base.Preconditions; import org.apache.commons.math3.distribution.IntegerDistribution; import org.apache.commons.math3.distribution.PascalDistribution; import org.apache.commons.math3.random.RandomGenerator; import org.apache.mahout.cf.taste.impl.common.AbstractLongPrimitiveIterator; import org.apache.mahout.cf.taste.impl.common.LongPrimitiveIterator; import net.myrrix.common.random.RandomManager; /** * Wraps a {@link LongPrimitiveIterator} and returns only some subset of the elements that it would, * as determined by a sampling rate parameter. * * Adapted from the same class in Mahout 0.8. * * @author Sean Owen * @author Mahout * @since 1.0 */ public final class SamplingLongPrimitiveIterator extends AbstractLongPrimitiveIterator { private final IntegerDistribution geometricDistribution; private final LongPrimitiveIterator delegate; private long next; private boolean hasNext; public SamplingLongPrimitiveIterator(LongPrimitiveIterator delegate, double samplingRate) { this(RandomManager.getRandom(), delegate, samplingRate); } public SamplingLongPrimitiveIterator(RandomGenerator random, LongPrimitiveIterator delegate, double samplingRate) { Preconditions.checkNotNull(random); Preconditions.checkNotNull(delegate); Preconditions.checkArgument(samplingRate > 0.0 && samplingRate <= 1.0); // Geometric distribution is special case of negative binomial (aka Pascal) with r=1: geometricDistribution = new PascalDistribution(random, 1, samplingRate); this.delegate = delegate; this.hasNext = true; doNext(); } @Override public boolean hasNext() { return hasNext; } @Override public long nextLong() { if (hasNext) { long result = next; doNext(); return result; } throw new NoSuchElementException(); } @Override public long peek() { if (hasNext) { return next; } throw new NoSuchElementException(); } private void doNext() { int toSkip = geometricDistribution.sample(); delegate.skip(toSkip); if (delegate.hasNext()) { next = delegate.next(); } else { hasNext = false; } } /** * @throws UnsupportedOperationException */ @Override public void remove() { throw new UnsupportedOperationException(); } @Override public void skip(int n) { int toSkip = 0; for (int i = 0; i < n; i++) { toSkip += geometricDistribution.sample(); } delegate.skip(toSkip); if (delegate.hasNext()) { next = delegate.next(); } else { hasNext = false; } } public static LongPrimitiveIterator maybeWrapIterator(LongPrimitiveIterator delegate, double samplingRate) { return samplingRate >= 1.0 ? delegate : new SamplingLongPrimitiveIterator(delegate, samplingRate); } }