org.jheaps.monotone.BigIntegerRadixHeap Maven / Gradle / Ivy
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/*
* (C) Copyright 2014-2016, by Dimitrios Michail
*
* JHeaps Library
*
* Licensed 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.jheaps.monotone;
import java.lang.reflect.Array;
import java.math.BigInteger;
import java.util.ArrayList;
import java.util.List;
/**
* A radix heap for {@link BigInteger} keys. The heap stores {@link BigInteger}
* keys sorted according to the {@linkplain Comparable natural ordering} of its
* keys. A radix heap is a monotone heap, especially designed for algorithms
* (such as Dijkstra) which scan elements in order of nondecreasing keys.
*
*
* The implementation uses arrays in order to store the elements. Operations
* {@code insert} and {@code findMin} are worst-case constant time. The cost of
* operation {@code deleteMin} is amortized O(logC) assuming the radix-heap
* contains keys in the range {@literal [0, C]} or equivalently
* {@literal [a,a+C]}.
*
*
* Note that this implementation is not synchronized. If
* multiple threads access a heap concurrently, and at least one of the threads
* modifies the heap structurally, it must be synchronized externally.
* (A structural modification is any operation that adds or deletes one or more
* elements or changing the key of some element.) This is typically accomplished
* by synchronizing on some object that naturally encapsulates the heap.
*
* @author Dimitrios Michail
*/
public class BigIntegerRadixHeap extends AbstractRadixHeap {
private final static long serialVersionUID = 1;
/**
* Constructs a new heap which can store values between a minimum and a
* maximum key value (inclusive).
*
* It is important to use the smallest key range as the heap uses O(logC)
* where C=maxKey-minKey+1 buckets to store elements. Moreover, the
* operation {@code deleteMin} requires amortized O(logC) time.
*
* @param minKey
* the non-negative minimum key that this heap supports
* (inclusive)
* @param maxKey
* the maximum key that this heap supports (inclusive)
* @throws IllegalArgumentException
* if the minimum key is negative
* @throws IllegalArgumentException
* if the maximum key is less than the minimum key
*/
@SuppressWarnings("unchecked")
public BigIntegerRadixHeap(BigInteger minKey, BigInteger maxKey) {
super();
if (minKey == null) {
throw new IllegalArgumentException("Minimum key cannot be null");
}
if (minKey.compareTo(BigInteger.ZERO) < 0) {
throw new IllegalArgumentException("Minimum key must be non-negative");
}
this.minKey = minKey;
this.lastDeletedKey = minKey;
if (maxKey == null) {
throw new IllegalArgumentException("Maximum key cannot be null");
}
if (maxKey.compareTo(minKey) < 0) {
throw new IllegalArgumentException("Maximum key cannot be less than the minimum");
}
this.maxKey = maxKey;
// compute number of buckets
BigInteger diff = maxKey.subtract(minKey);
int numBuckets = 2 + 1 + diff.bitLength();
// construct representation
this.buckets = (List[]) Array.newInstance(List.class, numBuckets);
for (int i = 0; i < this.buckets.length; i++) {
buckets[i] = new ArrayList();
}
this.size = 0;
this.currentMin = null;
}
/**
* {@inheritDoc}
*/
@Override
protected int compare(BigInteger o1, BigInteger o2) {
return o1.compareTo(o2);
}
/**
* {@inheritDoc}
*/
@Override
protected int msd(BigInteger a, BigInteger b) {
if (a.equals(b)) {
return -1;
}
/*
* return floor(log_2(a xor b)).
*/
return a.xor(b).bitLength() - 1;
}
}