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/*
* 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 org.apache.commons.rng.sampling;
import org.apache.commons.rng.UniformRandomProvider;
/**
* Class for representing combinations
* of a sequence of integers.
*
* A combination is a selection of items from a collection, such that (unlike
* permutations) the order of selection does not matter. This
* sampler can be used to generate a combination in an unspecified order and is
* faster than the corresponding {@link PermutationSampler}.
*
* Note that the sample order is unspecified. For example a sample
* combination of 2 from 4 may return {@code [0,1]} or {@code [1,0]} as the two are
* equivalent, and the order of a given combination may change in subsequent samples.
*
* The sampler can be used to generate indices to select subsets where the
* order of the subset is not important.
*
* Sampling uses {@link UniformRandomProvider#nextInt(int)}.
*
* @see PermutationSampler
*/
public class CombinationSampler {
/** Domain of the combination. */
private final int[] domain;
/** The number of steps of a full shuffle to perform. */
private final int steps;
/**
* The section to copy the domain from after a partial shuffle.
*/
private final boolean upper;
/** RNG. */
private final UniformRandomProvider rng;
/**
* Creates a generator of combinations.
*
* The {@link #sample()} method will generate an integer array of
* length {@code k} whose entries are selected randomly, without
* repetition, from the integers 0, 1, ..., {@code n}-1 (inclusive).
* The returned array represents a combination of {@code n} taken
* {@code k}.
*
*
In contrast to a permutation, the returned array is not
* guaranteed to be in a random order. The {@link #sample()}
* method returns the array in an unspecified order.
*
*
If {@code n <= 0} or {@code k <= 0} or {@code k > n} then no combination
* is required and an exception is raised.
*
* @param rng Generator of uniformly distributed random numbers.
* @param n Domain of the combination.
* @param k Size of the combination.
* @throws IllegalArgumentException if {@code n <= 0} or {@code k <= 0} or
* {@code k > n}.
*/
public CombinationSampler(UniformRandomProvider rng,
int n,
int k) {
SubsetSamplerUtils.checkSubset(n, k);
domain = PermutationSampler.natural(n);
// The sample can be optimised by only performing the first k or (n - k) steps
// from a full Fisher-Yates shuffle from the end of the domain to the start.
// The upper positions will then contain a random sample from the domain. The
// lower half is then by definition also a random sample (just not in a random order).
// The sample is then picked using the upper or lower half depending which
// makes the number of steps smaller.
upper = k <= n / 2;
steps = upper ? k : n - k;
this.rng = rng;
}
/**
* Return a combination of {@code k} whose entries are selected randomly,
* without repetition, from the integers 0, 1, ..., {@code n}-1 (inclusive).
*
*
The order of the returned array is not guaranteed to be in a random order
* as the order of a combination does not matter.
*
* @return a random combination.
*/
public int[] sample() {
return SubsetSamplerUtils.partialSample(domain, steps, rng, upper);
}
}