/**
* 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);
}
}